Ahead of 2019, DW requested predictions from organisation working in the IT industry. We received over 150 of these, some of which you will have read in December, some of which you’ll read in this issue of DW, and the rest of which will appear in February. They make for fascinating reading. However, not one of them sought to make any social or moral judgement as to whether or not the technologies discussed are a force for good, for bad or for neutral.

For example, the rise of the digital personal assistant seems to get everyone very excited but, in the UK at least, obesity is a growing issue (if you’ll excuse the pun) and any technology that allows people to spend even more time sat on their couch is not necessarily a good thing. Indeed, thanks to the rise of technology, it’s more than possible to live one’s life entirely without leaving one’s home. We can work from home, all the sustenance we need can be delivered to home and all our leisure hours can be spent at home. Of course, we can exercise at home as well.

And there’s the crux of the issue. Technology itself is definitely neutral, it’s how we choose to use it (or not) that gives it a good or bad association. Many cases are clear cut – technology used by cybercriminals to mess up individuals, companies and even governments is not a good idea; technology used to save people’s lives is.

Ah, but is it that simple? We live on a planet with finite resources and, the more people we keep alive for longer and longer, the more pressure that will be put on these resources. So, is keeping alive people until they are, say, 120, just so they can sit in their armchairs and watch television and sleep all day, a good thing? Especially when the resources required to do this could be better used to help individuals at the other end of the life cycle?

There are no easy answers, but there seems to be an urgent need for governments across the globe to come to grips with the digital world and what it means for their citizens moving forward. For example, there is growing unease that some of the tech giants appear to be able to play fast and loose with the tax rules as they currently exist in most, if not all, countries. So, how does one redress the balance, so that what most would deem a fair share of tax is paid by these organisations?

At a time when the UK seems hell-bent on withdrawing from an organisation whose primary aim (whatever else has followed) is to ensure cooperation between many European countries, it seems that more and more of such cooperation is required, rather than less. A pipe dream maybe, but imagine if countries across the planet had unified policies in many areas of life – not least technology. Right now, it’s all too easy for any organisation or individual to justify a policy or an action along the lines of: “Well, if we don’t do it then someone else, somewhere else will take advantage of the opportunity (ie selling arms to various nations!). Imagine if there was a global policy for everything?!!

And in case anyone thinks that the DW editor has completely lost the plot, I would ask this question: “Why is so much time and effort being spent on developing autonomous vehicles, and, apparently, so little effort being spent on developing some kind of Robocop, when crime and anti-social behaviour levels seem to be rising on a daily basis?”

Governments have a chance to shape the digital future. Right now, they appear to be passengers.

Research from the Cloud Industry Forum and BT finds over half of enterprises expect their business models to be disrupted within two years.

New research, launched by the Cloud Industry Forum (CIF) and BT, has revealed that while large enterprise organisations are investing in new technologies in pursuit of digital transformation, skills shortages, and migration and integration challenges, are inhibiting the pace of change.

The research, which was conducted by Vanson Bourne and commissioned by CIF in association with BT, sought to understand how the technology decisions being made by large enterprises, with more than 1,000 employees, in the face of heightening levels of digital disruption. It found that 52% of enterprises expect their business models to be moderately or significantly disrupted by 2020 and that 74% either have a digital transformation strategy in place or are in the process of implementing one.

However, just 14% believe that they are significantly ahead of their competitors in terms of the adoption of next generation technologies, indicating that many are struggling to adapt to the digital revolution. The research suggests that skills shortages sit at the heart of this issue, with enterprises significantly more likely to report facing skills shortages than their smaller counterparts. 59% stated that they lack staff with integration and migration skills (compared to just 28% of SMEs), 64% needed more security expertise, and 54% require more strategic digital transformation skills.

Commenting on the findings, David Simpkins, General Manager, Managed Services and Public Cloud at BT, said: “The research confirms that most enterprises have well developed strategies aimed at minimising digital disruption and enhancing competitiveness. Cloud is clearly an enabler, but many organisations are finding challenges in achieving the agility and flexibility they seek. Unlike small organisations, who can easily be more agile and nimbler in the face of market conditions, change within large enterprises, whose IT estates are infinitely more complex, is much more difficult to achieve.

“Increasingly we’re seeing enterprises managing a wide range of workloads, combining public and private cloud deployments with data centre infrastructure, while at the same time addressing a range of new security threats. This is changing the skillsets that enterprise IT departments need, and it is clear that many will need greater support to safely transition to the digital age,” he continued.

Alex Hilton, CEO of CIF added: “Of all the parts of our economy, it is large, enterprises that are the most vulnerable to digital disruption and that is clearly something that our respondents recognise. Many have invested heavily in their company assets and carry with them a significant amount of tech debt, often making change difficult, slow and expensive. This makes the customer and IT supplier relationship critical, and enterprise organisations must consider their choice of partner carefully to help them navigate this complexity and integrate existing legacy investments with newer cloud-based technologies. Those that do not, will find themselves at a digital disadvantage.”

The internet is made up of thousands of public and private networks around the world. And since it came to life in 1984, more than 4.7 zettabytes of IP traffic have flowed across it. That’s the same as all the movies ever made crossing global IP networks in less than a minute.Yet the new Visual Networking Index (VNI) by Cisco predicts that is just the beginning.

By 2022, more IP traffic will cross global networks than in all prior ‘internet years’ combined up to the end of 2016. In other words, more traffic will be created in 2022 than in the 32 years since the internet started. Where will that traffic come from? All of us, our machines and the way we use the internet. By 2022, 60 percent of the global population will be internet users. More than 28 billion devices and connections will be online. And video will make up 82 percent of all IP traffic.

“The size and complexity of the internet continues to grow in ways that many could not have imagined. Since we first started the VNI Forecast in 2005, traffic has increased 56-fold, amassing a 36 percent CAGR with more people, devices and applications accessing IP networks,” said Jonathan Davidson, senior vice president and general manager, Service Provider Business, Cisco. “Global service providers are focused on transforming their networks to better manage and route traffic, while delivering premium experiences. Our ongoing research helps us gain and share valuable insights into technology and architectural transitions our customers must make to succeed.”

Key predictions for 2022

Cisco’s VNI looks at the impact that users, devices and other trends will have on global IP networks over a five-year period. From 2017 to 2022, Cisco predicts:

1. Global IP traffic will more than triple

• Global IP traffic is expected to reach 396 exabytes per month by 2022, up from 122 exabytes per month in 2017. That’s 4.8 zettabytes of traffic per year by 2022.
• By 2022, the busiest hour of internet traffic will be six times more active than the average. Busy hour internet traffic will grow by nearly five times (37 percent CAGR) from 2017 to 2022, reaching 7.2 petabytes[1] per second by 2022. In comparison, average internet traffic will grow by nearly four times (30 percent CAGR) over the same period to reach 1 petabyte by 2022.

2. Global internet users will make up 60 percent of the world’s population

• There will be 4.8 billion internet users by 2022. That’s up from 3.4 billion in 2017 or 45 percent of the world’s population.
  

3. Global networked devices and connections will reach 28.5 billion

• By 2022, there will be 28.5 billion fixed and mobile personal devices and connections, up from 18 billion in 2017—or 3.6 networked devices/connections per person, from 2.4 per person.
• More than half of all devices and connections will be machine-to-machine by 2022, up from 34 percent in 2017. That’s 14.6 billion connections from smart speakers, fixtures, devices and everything else, up from 6.1 billion.

4. Global broadband, Wi-Fi and mobile speeds will double or more

• Average global fixed broadband speeds will nearly double from 39.0 Mbps to 75.4 Mbps.
• Average global Wi-Fi connection speeds will more than double from 24.4 Mbps to 54.0 Mbps.
• Average global mobile connection speeds will more than triple from 8.7 Mbps to 28.5 Mbps.

5. Video, gaming and multimedia will make up more than 85 percent of all traffic

• IP video traffic will quadruple by 2022. As a result, it will make up an even larger percentage of total IP traffic than before—up to 82 percent from 75 percent.
• Gaming traffic is expected to grow nine-fold from 2017 to 2022. It will represent four percent of overall IP traffic in 2022.
• Virtual and augmented reality traffic will skyrocket as more consumers and businesses use the technologies. By 2022, virtual and augmented reality traffic will reach 4.02 exabytes/month, up from 0.33 exabytes/month in 2017.

Regional IP traffic growth details (2017 – 2022)

• APAC: 173 exabytes/month by 2022, 32 percent CAGR, four-times growth
• North America: 108 exabytes/month by 2022, 21 percent CAGR, three-times growth
• Western Europe: 50 exabytes/month 2022, 22 percent CAGR, three-times growth
• Central & Eastern Europe: 25 exabytes/month by 2022, 26 percent CAGR, three-times growth
• Middle East and Africa: 21 exabytes/month by 2022, 41 percent CAGR, six-times growth
• Latin America: 19 exabytes/month by 2022, 21 percent CAGR, three-times growth 

More than 87 per cent of organisations are classified as having low business intelligence (BI) and analytics maturity, according to a survey by Gartner, Inc. This creates a big obstacle for organisations wanting to increase the value of their data assets and exploit emerging analytics technologies such as machine learning.

Organisations with low maturity fall into “basic” or “opportunistic” levels on Gartner’s IT Score for Data and Analytics. Organisations at the basic level have BI capabilities that are largely spreadsheet-based analyses and personal data extracts. Those at the opportunistic level find that individual business units pursue their own data and analytics initiatives as stand-alone projects, lacking leadership and central guidance.

“Low BI maturity severely constrains analytics leaders who are attempting to modernize BI,” said Melody Chien, senior director analyst at Gartner. “It also negatively affects every part of the analytics workflow. As a result, analytics leaders can struggle to accelerate and expand the use of modern BI capabilities and new technologies.”

According to Ms Chien, organisations with low maturity exhibit specific characteristics that slow down the spread of BI capabilities. These include primitive or aging IT infrastructure; limited collaboration between IT and business users; data rarely linked to a clearly improved business outcome; BI functionality mainly based on reporting; and bottlenecks caused by the central IT team handling content authoring and data model preparation.

“Low maturity organisations can learn from the success of more mature organisations,” said Ms Chien. “Without reinventing the wheel and making the same mistakes, analytics leaders in low BI maturity organisations can make the most of their current resources to speed up modern BI deployment and start the journey toward higher maturity.”

Gartner said there are four steps that data and analytics leaders can follow in the areas of strategy, people, governance and technology, to evolve their organisations’ capabilities for greater business impact.

1. Develop holistic data and analytics strategies with a clear vision

Organisations with low BI maturity often exhibit a lack of enterprisewide data and analytics strategies with clear vision. Business units undertake data or analytics projects individually, which results in data silos and inconsistent processes.

Data and analytics leaders should coordinate with IT and business leaders to develop a holistic BI strategy. They should also view the strategy as a continuous and dynamic process, so that any future business or environmental changes can be taken into account.

2. Create a flexible organisational structure, exploit analytics resources and implement ongoing analytics training

Enterprises must have people, skills and key structures in place to foster and secure skills and develop capabilities. They must anticipate upcoming needs and ensure the proper skills, roles and organisations exist, are developed, or can be sourced to support the work identified in the data and analytics strategy.

With limited analytics capabilities in-house, data and analytics leaders should strive for a flexible working model by building “virtual BI teams” that include business unit leaders and users.

3. Implement a data governance programme

Most organisations with low BI maturity do not have a formal data governance programme in place. They may have thought about it and understand the importance of it, but do not know where to start.

Analytics leaders can consider governance as the “rules of the game.” Those rules can support business objectives and also enable the organisation to balance out the opportunities and risks in the digital environment. Governance is also a framework that describes the decision rights and authority models that must be imposed on data and analytics.

4. Create integrated analytics platforms that can support a broad range of uses

Low-maturity organisations often have primitive IT infrastructures. Their BI platforms are more traditional and reporting-centric, embedded in enterprise resource planning systems, or simple disparate reporting tools that support limited uses.

To improve their analytics maturity, data and analytics leaders should consider integrated analytics platforms that extend their current infrastructure to include modern analytics technologies.

Sumo Logic has released new research at DockerCon Europe in Barcelona that reveals 63 percent of European organisations use machine data analytics for security, but lag in broader implementation across the business. The report, titled ‘Using Machine Data Analytics to Gain Advantage in the Analytics Economy,’ takes a comparative look at the adoption and usage of machine data across Europe and the U.S., further finding that only 40 percent of European companies had a “software-centric mindset” compared to 64 percent of US organisations.

The research, conducted by 451 Research and commissioned by Sumo Logic, surveyed 250 executives across the UK, Sweden, the Netherlands and Germany. This was also compared with data based on a previous survey of US respondents that were asked the same questions. The results show that companies in the U.S. are currently more likely to use and understand the value of machine data analytics than their European counterparts.

Key findings include:

• 64 percent of U.S. respondents said that machine data is extremely important to their company’s ability to meet its goals, while only 54 percent of European respondents said the same.
• When asked if machine data tools are deployed on-premises, only 48 percent of European correspondents responded affirmatively, compared to 74 percent of U.S. respondents.
• However, Europe leads the way in recognising the benefit of machine data analytics in security use cases, with 63 percent of European companies, ahead of the U.S. Other top use cases cited for machine data in Europe were monitoring (55 percent), business insight (48 percent), and troubleshooting (48 percent).

Docker adoption continues to expand rapidly in AWS

Looking at its own research, which is derived from active and anonymised data from more than 1,600 customers and 50,000 users, Sumo Logic found in its 2018 “State of Modern Applications and DevSecOps in the Cloud” report that Docker adoption has grown rapidly for companies deploying on AWS. In the past year, the number of companies running Docker containers on AWS has grown from 24 percent of respondents to 28 percent, according to the findings. This represents a year on year growth in companies running Docker containers on AWS of 16 percent. Both Docker Engine, which provides a standardized packaging format for diverse applications,and Docker Enterprise, an enterprise-ready container platform for managing and securing applications, are available on the AWS Marketplace. Additionally, the Sumo Logic Logging Plugin for Docker Enterprise is available for download on the Docker Store.

“The move to microservices and container-based architectures from Docker Enterprise makes it easier to deploy at scale, but it can also make it harder to effectively monitor activities over time without the right approach to logs and metrics in place,” said Colin Fernandes, director of EMEA product marketing, Sumo Logic “Conversely, getting effective oversight across systems and users with machine data makes delivering better services easier alongside improving security and operations. It’s gratifying to see that European organisations already understand the value in using machine data analytics for security purposes.”

International gaming and casino operations company Paf has deployed its critical applications infrastructure on AWS as part of a move to modernise its IT. The deployment included using Sumo Logic to get detailed machine data analytics and insight into performance levels.

"We chose Sumo Logic to provide us with insight into our new application deployments, which are far more complex than our previous applications, and to support our move to container based deployments," said Lars-Goran Hakamo, Security Architect at Paf. “Sumo Logic gives us the ability to identify and resolve issues faster and keep those applications performing at scale. The rich visibility and data insights we are able to glean from Sumo Logic from across our container estate, across our applications and our AWS infrastructure is simply unbelievable.”

Business barriers to data deployments

The 451 Research report also provided insight into the barriers preventing wider usage of machine data analytics:

• Real-time access to data was most commonly cited (37 percent), while the management of analytics tools also prevented broader usage of machine data.
• 47 percent of respondents said that the adoption of modern technologies does make it harder to get the data they need for speedy decision-making.
• Fewer respondents in Europe felt their organisations had a software-centric mindset compared to the US audience. This described how much the organisations viewed their use and management of software as critical to their success.

“Europe is adopting modern tools and technologies at a slower rate than their U.S. counterparts, and fewer companies currently have that ‘software-led’ mindset in place. However, the desire for more continuous insights derived from machine data is there. What the data shows is that once European organisations start using machine data analytics to gain visibility into their security operations, they begin to see the value for other use cases across operations, development and the business,” said Fernandes. “It’s our goal to democratise machine data and make it easier to deploy this as part of modern application deployments running on on the Docker Enterprise container platform.”

Findings demonstrate pressing need to build the right foundation for consolidating and managing cloud deployments.

New research commissioned by SoftwareONE, a global leader in software and cloud portfolio management, has revealed that more than six in ten organisations (62 per cent) believe that the actual costs of maintaining cloud technologies are higher than they expected. This indicates that, despite the evident benefits that the cloud brings to an organisation’s digital transformation efforts, businesses can run into difficulties if they do not have the technology, licensing agreements and ongoing monitoring procedures in place to effectively manage and optimise cloud-based software and applications within their wider IT estate.

The survey, conducted by market research firm Vanson Bourne, also found that 36 per cent of businesses feel that cloud-based “as-a-service” offerings – such as SaaS, PaaS or IaaS – have increased in complexity over the past two years, with an additional 33 per cent believing that the level of complexity has remained unchanged in this time. When viewed alongside the unexpected management costs associated with the cloud, it becomes clear that cloud deployments are fraught with challenges if businesses do not have the means to administer the various elements of their implementations effectively.

Zak Virdi, UK Managing Director at SoftwareONE said: “The cloud has been instrumental in helping to bring greater agility and efficiency to IT, but it’s also important to recognise that making it a success takes time, as well as a commitment to proper, long-term integration and management. This means selecting the right technology, meeting the right licensing agreements, and putting frameworks are in place to consistently and closely monitor the entire implementation.

“From our research, it’s clear that the rapid growth in cloud services and options – while providing an exceptional level of choice to businesses – is also leading to organisations struggling to fully maximise cloud investments while keeping expenditure as low as possible,” continued Virdi.

To illustrate this point further, the research also found that more than four in ten (44 per cent) of respondents claimed that budget restraints often push their organisation towards choosing second or third-choice technology options, rather than the option that they felt was ideal for them. Moreover, 38 per cent said that the management of licences and subscriptions for both cloud deployments and on-premise software pose a significant degree of complexity.

For Virdi, this provides additional evidence of a need for technology that can ease the management of so many different software-based requirements, whether they are based in the cloud or on-premise.

He added: “With so many plates to keep spinning and so many different responsibilities to fulfil – on-premise and cloud deployments, licensing requirements, keeping costs down and so on – it’s absolutely vital that businesses are able to cut out or automate much of the administrative burden, enabling companies to maximise ROI and make their digital transformation efforts a resounding success.”

Virdi concluded: “Amid the urge to adopt cloud, it’s about being able to step back and take stock of what needs to be done from a management perspective. If organisations embrace a platform that allows them to manage their entire software estate and cloud portfolio from a single location, they will be in a much better position to monitor, analyse and optimise the resources at their disposal.”

Businesses across the world still struggle to understand, optimise, and protect their rapidly expanding application environments, according to new research from F5 Labs.

The 2018 Application Protect Report reveals that as many as 38% of respondents have “no confidence” they have an awareness of all their organisation’s applications in use.

Based on regional analysis conducted for the report by the Ponemon Institute, UK businesses know the least about their application situation – only 32% are “confident” or “very confident” that they have full oversight –whereas Germans are the most confident, with 45% claiming to know the full story.

The Application Protection Report, which is the most extensive study of its kind yet, also identified grossly inadequate web application security practices, with 60% of businesses stating they don’t test for web application vulnerabilities, have no pre-set schedule for tests, are unsure if tests happen, or only test annually.

Furthermore, 46% of surveyed respondents disagreed or strongly disagreed that their organisation had adequate resources to detect application vulnerabilities. 49% said the same about their remediation capabilities.

“Many businesses fail to keep pace with technological developments and make unwitting and dangerous security compromises as they have a worrying lack of insight into their application environments. This is a big problem. The pressure has never been higher to deliver applications with unprecedented speed, adaptive functionality, and robust security — particularly against the backdrop of increasing European data protection legislation,” said David Warburton, Senior EMEA Threat Research Evangelist, F5 Networks.

Counting the cost

According to thePonemon Institute’s regional review, the global average for web app frameworks and environments in use is 9,77. The US has the most (12,09), with both the UK (9,72) and Germany (10,37) claiming to be above average.

On average, global businesses consider 33,85% all apps to be “mission critical”. In EMEA, the percentage is 35% and 33% for the UK and Germany, respectively. All regions identified the same top three critical apps: document management and collaboration; communication apps (such as email and texting); and Microsoft Office suites.

Global respondents were also unanimous that the three most devastating threats facing businesses today are credential theft, DDoS attacks, and web fraud.

In EMEA, 76% of German respondents are most concerned about credential theft, which is second only to Canada (81%). DDoS attacks (64%) and web fraud (49%) are German business’ next biggest concerns.

Interestingly, the UK is more threatened by web fraud than anyone else (57% of respondents). Nevertheless, its biggest worries are credentials theft (69%) and DDoS attacks (59%).

Unsurprisingly, web app attacks are a major operational blight in all countries. 90% of respondents in the US and Germany said it would be “very painful” if an attack resulted in the denial of access to data or apps. The UK is the next most potentially vulnerable country with 87% concurring.

The global average incident cost for app denial of service is $6,86m. The US endures the costliest range of attacks with losses of $10,64m on average, closely followed by Germany’s $9,17 million. The UK is slightly below the global average with an average of $6,57m per incident.

Regional differences are also apparent when estimating the incident cost of confidential or sensitive information leaks, such as intellectual property or trade secrets. Globally, the average cost stands at $8,63m. The US pays out the most, having to foot an average bill $16,91m. Germany is second with typical losses of $11,30m. The UK fares better with average losses of $8,10m, which is almost half the US estimate.

Meanwhile, the global average estimated incident cost for leakage of personally identifiable information (customer, consumers or employees) stands at $6,29m. The US is once again hardest hit at an average of $9,37m, ahead of Germany ($8,48m), India ($6,63m), and the UK ($5,63m).

Tools and tactics

According to surveyed businesses, the three main tools for keeping apps safe are Web Application Firewalls (WAF), application scanning, and penetration testing

WAF takes the top spot in the US (30%), Brazil (30%), UK (29%), Germany (29%), Canada (26%) and India (26%). Penetration testing is most prominent in India (24%), followed China (20%), Brazil (19%), Germany (20%), Canada (20%), the UK (18%) and the US (18%). India is again in the lead for app scanning (24%), trailed by China (22%), Brazil (21%), Canada (19%), the US (18%), Germany (16%), and the UK (13%).

The business community’s growing appetite for WAF is further echoed in F5’s 2018 State of Application Delivery report³, which revealed that 61% of surveyed global businesses currently use WAFs to protect applications – a trend largely driven by soaring multi-cloud usage.

The Ponemon Institute also reported that DDoS mitigation and backup technologies are the most widely used technologies to achieve high web application availability. German and Brazilian respondents were the strongest DDoS mitigation advocates (both 64%), edging out the US (62%), the UK (60%) and China (60%). Backup technologies are most popular in Canada (76%), the UK (74%), and Germany (73%).

Storage encryption is also seen as a critical defensive tool. Germany leads the way in this respect, with 50% of businesses using the technology “most of the time”, ahead of Canada (44%), the US (40%) and the UK (39%).

Safeguarding the future

“A company’s reputation depends on a comprehensive security architecture. Firms across the globe can no longer rely on traditional IT infrastructures. Technologies such as bot protection, application-layer encryption, API security, and behavior analytics, as we see in advanced WAFs, are now essential to defend against attacks. Thanks to automated tools with enhanced machine learning, businesses can start to detect and mitigate cybercrime with the highest level of accuracy yet,” said Warburton.

TIBCO Software Inc. has released the initial results of the 2018 TIBCO CXO Innovation Survey examining the leading trends in innovation strategy within the enterprise.

The research provides a deep dive into how and why companies are innovating, as well as the tactics and technologies needed to drive initiatives. The research results also examine the role of digital transformation in innovation across industries, which teams within an organisation are driving innovation the most aggressively, and the obstacles they are facing.

The 2018 TIBCO CXO Innovation Survey polled more than 600 respondents around the world including CXOs, senior vice presidents, vice presidents, senior directors, and directors from business and IT functional areas. Respondents represented industries that include retail/wholesale, manufacturing, financial services, healthcare, transportation, aerospace, energy, oil and gas, professional services, technology and software, and more.

Key findings include:

• Digital transformation is a work in progress. Approximately 65% of respondents identified that they have yet to reach “expert” status in their digital transformation maturity.
• Obstacles to success for innovation-based projects are directly linked to technology, culture, and people. Approximately 24% of respondents listed that limited time, resources, and budget associated with company culture priorities are top obstacles.
• Respondents are adopting cloud, BI/analytics, and integration solutions as an early part of their innovation strategy. AI/ML, open source, blockchain, and IoT align with more sophisticated strategies. For example, of the respondents that consider their organisations to be experts in their digital transformation maturity, 41% have adopted blockchain technologies.

“Unlocking innovation potential is key for organisations that want to be at the cutting edge of their markets,” said Thomas Been, chief marketing officer, TIBCO. “People, data, and technology form the nucleus of innovation and executives across all industries need all three working together for success. This survey dives deep on these relationships and shows how more digitally mature companies are innovating faster and more often. We’re excited to bring forward compelling insights on the factors critical to innovation. These elements are what every executive should consider when determining strategies to stay competitive.” 

Large organizations are running an average of 29 different pre-deployment initiatives to digitize the supply chain, but 86% have failed to scale any of them.

A new study from the Capgemini Research Institute “The digital supply chain’s missing link: focus”, has identified a clear gap between expectations of what supply chain digitization can deliver, and the reality of what companies are currently achieving. While exactly half of the organizations surveyed consider supply chain digitization to be one of their top three corporate priorities, most are still struggling to get projects beyond the testing stage (86%).

Cost savings and new revenue opportunities are the top goals for supply chain digitization

Over three quarters (77%) of companies said their supply chain investments were driven by the desire for cost savings, with increasing revenues (56%) and supporting new business models (53%) also frequently cited. Organizations, especially in the UK (58%), Italy (56%), The Netherlands (54%) and Germany (53%) have supply chain digitization as one of their top priorities.

The broad enthusiasm for focusing on digital supply chain initiatives may be explained by the prospect of the return on investment (ROI) that they offer. The research finds that ROI on automation in supply chain and procurement averaged 18%, compared to 15% for initiatives in Human Resources, 14% in Information Technology, 13% in Customer Service and 12% in Finance and Accounting, and also R&D. According to the report, the average pay back period for supply chain automation is just twelve months.

Most organizations have spread their investments too thinly and are struggling to scale pilot initiatives

The organizations surveyed have an average of 29 digital supply chain projects at the ideation, proof-of-concept or pilot stage. Just 14% have succeeded in scaling even one of their initiatives to multi-site or full-scale deployment. However, for those that have achieved scale, 94% report that these efforts have led directly to an uplift in revenue.

The evidence from those who have moved to implementation suggests that companies are taking on too much, and not focusing enough on strategic priorities. The organizations who successfully scaled initiatives had an average of 6 projects at proof-of-concept stage while those who failed to scale averaged 11 projects.

There was also a clear gap in procedure and methodology between organizations that had and had not implemented digital supply chain initiatives at scale. The vast majority of companies to have successfully scaled said they had a clear procedure in place to evaluate the success of pilot projects (87% vs. 24%) and had clear guidelines for prioritizing those projects that needed investment (75% vs. 36%).

Dharmendra Patwardhan, Head of the Digital Supply Chain Practice for Business Services at Capgemini, added: “While most large organizations clearly grasp the importance of supply chain digitization, few appear to have implemented the necessary mechanisms and procedures to turn it into a reality. Companies are typically running too many projects, without enough infrastructure in place, and lack the kind of focused, long-term approach that has delivered success for market leaders in this area. Digitization of the supply chain will only be achieved by rationalizing current investments, progressing on those that can be shown to drive returns, and involving suppliers and distributors in the process of change.”

Steps to unlock the value in supply chain transformation

As well as learning from organizations that have successfully scaled supply chain initiatives, the report recommends that companies looking to make progress should focus on three key areas:

·Advocate and Align: Ensure transformation efforts are driven by C-suite leadership and senior management. Supply chain digitization is a complex process that spans planning, procurement, IT and HR and as such it cannot be led by any one business unit and must be driven from the top to succeed. Leadership needs to advocate for this transformation, and to provide strategic focus on objectives and what to prioritize. Supply chain digitization is integral to achieving business objectives and must also be aligned with wider efforts – for example to increase transparency and improve customer satisfaction – so it is not considered solely as a cost-cutting exercise.

·Build: For supply chain digitization to be successful, both upstream and downstream partners (suppliers and distributors/logistics providers) need to be onboarded and made part of the digitization efforts. Breaking the silos among the various supply chain functions as well as the technology teams is also critical to the success of supply chain initiatives.

·Enable: While the above help in starting the digitization, in order to sustain it, organizations also need to invest in key areas of building a customer-centric mindset and developing a talent base. They need to devise approaches to attract, retain and upskill their employees.

Commenting on this approach, Rob Burnett, CIO of Global Supply Chain & Engineering at GE Transportation said: “Management buy-in is a huge part of identifying and investing in the digital supply chain projects that can really drive improvement. Rather than a cost center, the supply chain can be a source of innovation and efficiency for the whole organization, but it’s important to maintain a sharp focus on priority projects to get the ball rolling. There should be a wider appreciation that less is more.”

Robotic Process Automation (RPA) and Internet of Things (IOT) represent several viable use cases

In terms of specific use cases, Capgemini’s report reviews the 25 most popular use cases for supply chain digitization today, analyzing each in terms of how easy it is to implement, and benefits realized, to produce the top recommended use cases that can become strategic wins. Of these, RPA and IOT feature more often, in use cases like order processing, smart sensors to monitor product conditions, and to update and maintain connected products. Based on working examples from across today’s supply chain, these use cases have been shown to save time and money on supply chain processes. 

The DCS Awards categories provide a comprehensive range of options for organisations involved in the IT industry to participate, so you are encouraged to get your nominations made as soon as possible for the categories where you think you have achieved something outstanding or where you have a product that stands out from the rest, to be in with a chance to win one of the coveted crystal trophies.

The editorial staff at Angel Business Communications will validate entries and announce the final short list to be forwarded for voting by the readership of the Digitalisation World stable of publications during April. The winners will be announced at a gala evening on 16^th May at London’s Grange St Paul’s Hotel.

The 2019 DCS Awards feature 26 categories across four groups. The Project Awards categories are open to end use implementations and services that have been available before 31^st December 2018.  The Innovation Awards categories are open to products and solutions that have been available and shipping in EMEA between 1st January and 31st December 2018. The Company nominees must have been present in the EMEA market prior to 1^st June 2018.  Individuals must have been employed in the EMEA region prior to 31^st December 2018. 

Nomination is free of charge and all entries can submit up to four supporting documents to enhance the submission.  The deadline for entries is : 1^st March 2019.

Please visit : www.dcsawards.com  for rules and entry criteria for each of the following categories:

DCS PROJECT AWARDS

Data Centre Energy Efficiency Project of the Year

New Design/Build Data Centre Project of the Year

Data Centre Consolidation/Upgrade/Refresh Project of the Year

Cloud Project of the Year

Managed Services Project of the Year

GDPR compliance Project of the Year

DCS INNOVATION AWARDS

Data Centre Facilities Innovation Awards

Data Centre Power Innovation of the Year

Data Centre PDU Innovation of the Year

Data Centre Cooling Innovation of the Year

Data Centre Intelligent Automation and Management Innovation of the Year

Data Centre Safety, Security & Fire Suppression Innovation of the Year

Data Centre Physical Connectivity Innovation of the Year

Data Centre ICT Innovation Awards

Data Centre ICT Storage Product of the Year

Data Centre ICT Security Product of the Year

Data Centre ICT Management Product of the Year

Data Centre ICT Networking Product of the Year

Data Centre ICT Automation Innovation of the Year

Open Source Innovation of the Year

Data Centre Managed Services Innovation of the Year

DCS Company Awards

Data Centre Hosting/co-location Supplier of the Year

Data Centre Cloud Vendor of the Year

Data Centre Facilities Vendor of the Year

Data Centre ICT Systems Vendor of the Year

Excellence in Data Centre Services Award

DCS Individual Awards

Data Centre Manager of the Year

Data Centre Engineer of the Year

Nomination Deadline : 1^st March 2019

www.dcsawards.com    

Yet, if anything the pressures are rising for customers; just as in a rising market, many stay profitable enough not to have to think about changing infrastructure, while IT mistakes and wrong decisions matter less, a year of great change may eventually find out those poor deals and false savings. Hence the hesitant IT customer confidence, especially in areas which have less history behind them such as AI and IoT. The thinking is that it is better to hold on to existing technologies which are at least better understood through use.

At the same time, however, the pressure from senior management and those with a strategic view is asking IT to do more with less; squeezed resources will not deliver change, and IT departments themselves may have become more siloed in the last year.

Working with scarce resources should be something that the managed services providers well understand; their industry is all about scale and efficient delivery; they should be able to talk to senior management in customers about the inherent effectiveness of their IT model and how this can be shared with the customer and the customer’s customer.

Yet the promise of technological delivery of riches has not always lived up to the expectations, and research has shown that a half-hearted or lightweight approach to innovation does not yield such good results. The recent Capgemini Research Institute’s “Upskilling your people for the age of the machine” study found that automation has not improved productivity because it has not been a part of the full digital transformation of business processes.

Companies do need to do their homework in terms of change management, in many cases. The need to adopt technology that links to and supports the implementation of a strategy should be a no-brainer. But this is not about new technology, it’s about the basics of change management and communication from leaders, which have been discussed for decades.

The managed services industry may need to encourage new thinking along these lines even more in 2019. It should be pushing at an open door: Equinix research shows that almost three quarters (71%) of organisations are likely to move more of their business functions to the cloud in coming years, they may still need answers that address their security fears, however. And they need help managing that change process in their businesses.

It will be those managed services companies with expertise in particular vertical markets or with a particularly strong customer relationship who do best in this. They are able to talk in meaningful ways about real solutions and engage with realistic customer expectations. They will also hopefully not be afraid to say when a transformation is not going far enough and what real gains could be made by further moves.

For this to work properly they need a clear understanding of the nature of change management in customer organisations, coupled with the required changes in working practices that deliver a safe and secure environment.

The agenda for the 2019 European Managed Services and Hosting Summit, in Amsterdam on 23 May, aims to reflect these new pressures and build the skills of the managed services industry in addressing the wider issues of engagement with customers at a strategic level. Experts from all parts of the industry, plus thought leaders with ideas from other businesses and organisations will share experiences and help identify the trends in a rapidly-changing market.  

A round-up of the latest Gartner research, covering IT infrastructure and 5G.

As more organizations embrace digital business, infrastructure and operations (I&O) leaders will need to evolve their strategies and skills to provide an agile infrastructure for their business. In fact, Gartner, Inc. said that 75 percent of I&O leaders are not prepared with the skills, behaviors or cultural presence needed over the next two to three years. These leaders will need to embrace emerging trends in edge computing, artificial intelligence (AI) and the ever-changing cloud marketplace, which will enable global reach, solve business issues and ensure the flexibility to enter new markets quickly, anywhere, anytime.

IT departments no longer just keep the lights on, but are also strategic deliverers of services, whether sourced internally or external to the organization. They must position specific workloads based on business, regulatory and geopolitical impacts. As organizations’ customers and suppliers grow to span the globe, I&O leaders must deliver on the idea that “infrastructure is everywhere” and consider the following four factors:

Agility Thrives on Diversity

Bob Gill, vice president at Gartner, said the days of IT controlling everything are over. As options in technologies, partners and solutions rise, I&O leaders lose visibility, surety and control over their operations. “The cyclical, dictated factory approach in traditional IT cannot provide the agility required by today’s business,” Mr. Gill said. “The need for agility evolved faster than our ability to deliver.”

Despite agility placing among their top 3 priorities for 2019, I&O leaders are faced with conundrum as a diverse range of products is available to them. “The ideal situation for I&O leaders would be to coordinate the unmanageable collection of options we face today — colocation, multicloud, platform as a service (PaaS) — and get ahead of the business needs tomorrow. We must reach into our digital toolbox of possibilities and apply it to customer intimacy, product leadership and operational excellence to establish guardrails around managing the diversity of options in the long term,” Mr. Gill said.

The need for agility will only increase, so the two key tasks of I&O leaders will be to manage the sprawl of diversity in the short term and become the product manager of services needed to build business driven, agile solutions in the long term. “I&O has the governance, security and experience to lead this new charge for the business,” Mr. Gill said.

Applications Enable Change

Infrastructure can save money and enable applications, but by itself it does not drive direct business value — applications do. Dennis Smith, vice president at Gartner, said that there is no better time to be an application developer. “Application development offers an opportunity to jump on the express train of change to satisfy customer needs and build solutions composed of a tapestry of software components enabled through APIs,” Mr. Smith said.

Gartner research found that by 2025, 70 percent of organizations not adopting a service/product orientation will be unable to support their business, so I&O engineers must engage with consumers and software developers; integrate people, processes and technology; and deliver services and products all to support a solid infrastructure on which applications reside.

Boundaries Are Shifting

Digital business blurs the lines between the physical and the digital, leveraging new interactions and more real-time business moments. As more things become connected, the data center will no longer be the center of data. “Digital business, IoT and immersive experiences will push more and more processing to the edge,” said Tom Bittman, distinguished vice president at Gartner.

By 2022, more than half of enterprises-generated data will be created and processed outside of data centers, and outside of cloud. Immersive technologies will help to light a fire of cultural and generational shift. People will expect more of their interactions to be immersive and real time, with fewer artificial boundaries between people and the digital world.

The need for low latency, the cost of bandwidth, privacy and regulatory changes as data becomes more intimate, and the requirement for autonomy when the internet connection goes down, are factors that will expand the boundary of enterprise infrastructures all the way to the edge.

People Are the Cornerstone

I&O leaders are struggling to deliver value faster in a complex, evolving environment, hindering the ability of organizations to learn quickly and share knowledge.

“The new I&O worker profile will embrace versatile skills and experiences rather than reward a narrow focus on one technical specialty,” said Kris van Riper, managing vice president at Gartner. “Leading companies are changing the way that they reward and develop employees to move away from rigid siloed career ladders toward more dynamic career diamonds. These new career paths may involve experiences and rotations across multiple technology domains and business units over time. Acquiring a broader understanding of the IT portfolio and business context will bring collective intelligence and thought diversity to prepare teams for the demands of digital business.”

Ultimately, preparing for I&O in the digital age comes down to encouraging different behaviors. Building competencies such as adaptability, business acumen, fusion collaboration and stakeholder partnership will allow I&O teams to better prepare for upcoming change and disruption.

The Top 10 trends impacting infrastructure and operations for 2019

Gartner, Inc. has highlighted the key technologies and trends that infrastructure and operations (I&O) leaders must start preparing for to support digital infrastructure in 2019.

 “More than ever, I&O is becoming increasingly involved in unprecedented areas of the modern day enterprise. The focus of I&O leaders is no longer to solely deliver engineering and operations, but instead deliver products and services that support and enable an organization’s business strategy,” said Ross Winser, senior research director at Gartner. “The question is already becoming ‘How can we use capabilities like artificial intelligence (AI), network automation or edge computing to support rapidly growing infrastructures and accomplish business needs?”

During his presentation, Mr. Winser encouraged I&O leaders to prepare for the impacts of 10 key technologies and trends to support digital infrastructure in 2019. They are:

Serverless Computing

Serverless computing is an emerging software architecture pattern that promises to eliminate the need for infrastructure provisioning and management. I&O leaders need to adopt an application-centric approach to serverless computing, managing APIs and SLAs, rather than physical infrastructures. “The phrase ‘serverless’ is somewhat of a misnomer,” noted Mr. Winser. “The truth is that servers still exist, but the service provider is responsible for all the underlying resources involved in provisioning and scaling a runtime environment, resulting in appealing agility.”

Serverless does not replace containers or virtual machines, so it’s critical to learn how best and where to use the technology. “Developing support and management capabilities within I&O teams must be a focus as more than 20 percent of global enterprises will have deployed serverless computing technologies by 2020, which is an increase from less than 5 percent today,” added Mr. Winser.

AI Impacts

AI is climbing up the ranks in terms of the value it will serve I&O leaders who need to manage growing infrastructures without being able to grow their staff. AI has the potential to be organizationally transformational and is at the core of digital business, the impacts of which are already being felt within organizations. According to Gartner, global AI-derived business value will reach nearly $3.9 trillion by 2022.

Network Agility (or Lack of?)

The network underpins everything IT does — cloud services, Internet of Things (IoT), edge services — and will continue to do so moving forward.

“Teams have been under pressure to ensure network availability is high and as such the team culture is often to limit change, yet all around the network team the demands for agility have increased,” said Mr. Winser. The focus for 2019 and beyond must move to how I&O leaders can help their teams increase the pace of network operations to meet demand. “Part of the answer is building network agility that relies on automation and analytics, and addressing the real skills shift needed to succeed,” said Mr. Winser.

The demands on the network are set to grow with the advent of 5G, increasing cloud maturity, and the explosion in numbers of IoT devices. “These are just a few of the pressures leaders should anticipate — so the critical time frame to deal with this challenge is now,” said Mr. Winser.

Death of the Data Center

Gartner predicts that by 2025, 80 percent of enterprises will migrate entirely away from on-premises data centers with the current trend of moving workloads to colocation, hosting and the cloud leading them to shut down their traditional data center.

“I&O leaders must prepare to place workloads based on business needs, not constrained by physical location. From colocation through to public cloud — plenty of alternatives to on-premises data centers exist. Leaders must identify whether there are truly strategic reasons to persist with on-premises needs, especially when they consider the significant amount of investment involved is often amortized over many years,” said Mr. Winser. Preparations must begin now, as the critical time frame for this is 2021 to 2025.

Edge Computing

IoT and immersive technologies will drive more information processing to the edge, redefining and reshaping what I&O leaders will need to deploy and manage. The edge is the physical location where things and people connect with the networked digital world, and infrastructure will increasingly reach out to the edge. Edge computing is a part of a distributed computing topology where information processing is located close to the edge, which is where things and people produce or consume that information. It touches on the laws of physics, economy and land, all of which are contributing factors to how and when to use edge.

“This is another trend that does not replace the cloud, but augments it,” said Mr. Winser. “The critical time frame for organizations to adopt this trend is between 2020 and 2023.”

Digital Diversity Management

Digital diversity management is not about people, but rather about the discovery and maintenance of assets that are “out there” in any given modern digital enterprise. “There has been huge growth in the range and quantity of “things” that I&O is expected to know about, be supporting and be managing,” said Mr. Winser. “Traditional asset management is still important, but we’re moving into the realms of involvement with new assets that might have direct effects on the finances, health and welfare of the organization’s customers.” Preparing I&O is vital now before the critical time frame of 2020 to 2025.

New Roles Within I&O

I&O leaders find that staffing justifications require resolving complex relationships between costs, activities and customer quality expectations. Explaining I&O staffing requirements to IT and business leaders in terms of business value by connecting staffing levels to business performance and strategic objectives is a must in today’s modern digital enterprise.

“For instance, IT is increasingly taking on the role of supporting cloud services in terms of aggregation, customization, integration and governance. A big challenge with cloud services is keeping costs under control, and the business expects I&O to be doing just that. Rather than focusing solely on engineering and operations, I&O must develop the capabilities needed to broker services; these will require different roles to the I&O of old,” said Mr. Winser. The critical time frame for this trend starts immediately in 2019.

Software as a Service (SaaS) Denial

SaaS is software that is owned, delivered and managed remotely by one or more providers. The provider delivers software based on one set of common code and data definitions that is consumed in a one-to-many model by all contracted customers at any time on a pay-for-use basis or as a subscription based on use metrics.

In 2019 and beyond, SaaS will have a big impact on how organizations look at infrastructure delivery strategies moving forward. However, most I&O leaders are still focused on infrastructure as a service (IaaS) and platform as a service (PaaS) solutions. “SaaS itself is becoming a level of complexity that IT shops aren’t yet coping with as they should. The shift to SaaS must be accompanied with I&O support, all the way from ensuring visibility is maintained of what is in use, through to supporting compliance requirements and enterprise integration needs. Leaders must start this now as the pressure will be on through 2021 and beyond,” said Mr. Winser.

Talent Management Becomes Critical

Historically, IT staff have been vertically organized based around the technology stack they managed. As infrastructures go digital, there becomes a need for people to work horizontally across stacks in order to identify and remediate technology work stoppages in their business. Expanding I&O skill sets, practices and procedures to accommodate hybrid operations is of the utmost importance in 2019 and beyond. “In short, talent is the critical ingredient for a modern, high-performing technology organization, and great talent is in high demand. People that show versatility and adaptability are quickly becoming must-haves, particularly in hybrid environments,” said Mr. Winser.

Global Infrastructure Enablement

Despite few infrastructures being truly “global” in nature, organizations must still prepare for the notion of “infrastructure everywhere.” While doing so, I&O leaders must work within the constraints of tight budgets and cost pressures.

One way to tackle this challenge is to wisely choose the network of partners needed for global success. “I&O leaders must look hard at their existing partners and raise the bar of expectation. Can they clearly identify the value the partner will bring to them in the context of global infrastructure? Are they unlocking all the value from recent investments their partners have been making?” said Mr. Winser. “There will be no time for ‘B-team’ partners in 2019 and beyond — I&O leaders must be on top of this trend between 2020 and 2023.”

Two-thirds of organisations intend to deploy 5G by 2020

Sixty-six percent of organizations have plans to deploy 5G by 2020, according to a new 5G use case and adoption survey by Gartner, Inc. Organizations expect 5G networks to be mainly used for Internet of Things (IoT) communications and video, with operational efficiency being the key driver.

“In terms of 5G adoption, end-user organizations have clear demands and expectations for 5G use cases,” said Sylvain Fabre, senior research director at Gartner. “However, one major issue that 5G users face is the lack of readiness of communications service providers (CSPs). Their 5G networks are not available or capable enough for the needs of organizations.”

To fully exploit 5G, a new network topology is required, including new network elements such as edge computing, core network slicing and radio network densification. “In the short to medium term, organizations wanting to leverage 5G for use cases such as IoT communications, video, control and automation, fixed wireless access and high-performance edge analytics cannot fully rely on 5G public infrastructure for delivery,” added Mr. Fabre.

Top Use Cases for 5G

IoT communications remains the most popular target use case for 5G, with 59 percent of the organizations surveyed expecting 5G-capable networks to be widely used for this purpose. The next most popular use case is video, which was chosen by 53 percent of the respondents.

“The figure for IoT communications is surprising, given that other proven and cost-effective alternatives, such as Narrowband IoT over 4G and low-power wide-area solutions, already exist for wireless IoT connectivity,” said Mr. Fabre. “However, 5G is uniquely positioned to deliver a high density of connected endpoints — up to 1 million sensors per square kilometer.”

“Additionally, 5G will potentially suit other subcategories of IoT that require very low latency. With regard to video, the use cases will be varied. From video analytics to collaboration, 5G’s speed and low latency will be well suited to supporting 4K and 8K HD video content,” added Mr. Fabre.

Status of 5G Deployment

Gartner predicts that, by 2022, half of the CSPs that have completed commercial 5G deployments will fail to monetize their back-end technology infrastructure investments, due to systems not fully meeting 5G use case requirements. “Most CSPs will only achieve a complete end-to-end 5G infrastructure on their public networks during the 2025-to-2030 time frame — as they focus on 5G radio first, then core slicing and edge computing,” said Mr. Fabre.

Mr. Fabre added that this is because CSPs’ 5G public networks plans vary significantly in timing and scope. CSPs will initially focus on consumer broadband services, which may delay investments in edge computing and core slicing, which are much more relevant and valuable to 5G projects.

Gartner advises that, to meet the demands of businesses, technology product managers planning 5G infrastructure solutions should focus on 5G networks that offer not only 5G radio but also core slicing and edge computing infrastructure and services for private networks. CSPs alone may not fully satisfy the short-to-midterm demands of organizations that are keen to deploy 5G quickly.

“Private networks for enterprises will be the most direct option for businesses that want to benefit from 5G capabilities early on,” said Mr. Fabre. “These networks may be offered not only by CSPs but also directly by infrastructure vendors — and not just by the traditional large vendors of infrastructure, but also by suppliers with cloud and software backgrounds.”

The latest research news from analyst firm, IDC, covering, digitalisation, robotics, AR and VR, servers, storage and Cloud.

European spending on technologies and services that enable the digital transformation (DX) of business practices, products, and organizations is forecast to reach $378.2 billion in 2022, according to the latest Worldwide Semiannual Digital Transformation Spending Guide published by International Data Corporation (IDC). DX spending is expected to steadily expand throughout the 2017-2022 forecast period, achieving a five-year compound annual growth rate (CAGR) of 15.1%.

Europe is the third largest geography for DX spending, after the United States and China. Four industries will be responsible for nearly 44% of the $256 billion in European DX spending in 2019: discrete manufacturing ($39 billion), process manufacturing ($25 billion), retail ($26 billion), and utilities ($23 billion). For European manufacturers, the top DX spending priority is smart manufacturing. IDC expects the industry to invest more than $27.6 billion in smart manufacturing next year along with significant investments in digital innovation ($8.8 billion) and digital supply chain optimization ($5.5 billion). In the retail space, the leading strategic priority is omni-channel commerce, which translates to nearly $5.0 billion in spending for related platforms and order orchestration and fulfillment. Meanwhile, the top priority for the utility industry is digital grid, which will drive investments of more than $13.6 billion in intelligent and predictive grid management and digital grid simulation.

IDC predicts the largest investments in DX use cases across all industries in 2019 will be freight management ($11 billion), autonomic operations ($7 billion), robotic manufacturing ($8 billion), and intelligent and predictive grid management ($12 billion).

"European manufacturing companies are increasingly adopting innovation accelerator technologies," says Neli Vacheva, senior analyst with IDC's Customer Insights and Analysis Group. "The sector is introducing innovation-enabled production processes, advanced asset and inventory management, and new sales models based on IoT, robotization, artificial intelligence, machine learning, and 3D printing. IoT data utilization efforts has repositioned manufacturers in the value creation chain and transformed entire industrial ecosystems."

"European retailers are also running fast in the DX race, with the aim of gaining a competitive advantage, while the non-DX players are confined to a shrinking addressable market," says Angela Vacca, senior research manager with IDC's Customer Insights and Analysis Group. "European retailers will increasingly leverage technology to renovate their business models, deliver innovative services, and enhance customer experience (CX)."

From a technology perspective, hardware and services will account for more than 78% of all DX spending in 2019. Services spending will be led by IT services ($43 billion) and connectivity services ($25 billion), while business services will post the highest growth (19.8% CAGR) over the five-year forecast period. Hardware spending will be spread across several categories, including enterprise hardware, personal devices, and IaaS infrastructure. DX-related software spending will total $55 billion in 2019 and will be the fastest-growing technology category with a CAGR of 18.1%.

The Worldwide Semiannual Digital Transformation Spending Guide quantifies enterprise spending for 181 DX use cases and 12 technology categories across 19 industries and nine geographies. The guide provides spending data for 31 DX strategic priorities and 68 programs, as well as technology spending by delivery type (cloud, non-cloud, and other). Unlike any other research in the industry, the DX Spending Guide was designed to help business and IT decision makers to better understand the scope and direction of investments in digital transformation over the next five years. 

Whether the result of previous mergers, a failure to keep up with technological advances or a reluctance to budget for development, legacy platforms are certainly not uncommon. Yet, while most businesses recognise the need to update their data management systems, the cost of change and perceived difficulties of integrating their systems with new solutions can act as a deterrent. However, continued use of legacy platforms holds businesses back from reaching their true potential and can severely impact business operations. With this in mind, we look at the true costs businesses are likely to face if they fail to bring their data management capabilities in line with 21^st century requirements.

Why failing to update will be costly

Despite the difficulties associated with implementing and integrating new data management platforms, businesses are more likely to be negatively impacted by inertia than by taking action and updating their data management solutions. According to our research, more than a third of financial institutions saying that legacy data platforms are the biggest obstacles to improving their data management and analytics capabilities. For financial institutions this is a worrying statistic as they are heavily reliant on easy access to quality data and analytics to perform their role effectively.

However, this is just one of the issues preventing businesses from taking action with a further 31% of financial institutions citing the cost of change is holding them back from updating their legacy systems. For these organisations, there is a mistaken idea that it is cheaper and therefore more cost-effective to stick with legacy systems than to update them. Yet, this doesn’t take into account the indirect costs of legacy platforms and the effects these have on a business which can be felt across a number of other areas, including information security and lack of business user enablement and productivity.

It is crucial that organisations consider how much their current data management systems are holding them back operationally as they typically take longer to carry out processes, delaying data delivery to end-user applications and reports, and lowering productivity. Legacy systems can slow down organisations as they are costly to maintain, miss audit or lineage information, often cannot scale to new volume requirements, and do not quickly and easily provide business users with the data they require. Especially with frequent new regulatory requirements on data quality and due process, the cost of change can be formidable.

Data discrepancies because a business lacks a clear and comprehensive view of its sourcing and validation process can be another costly by-product of legacy platforms. Similarly, they are a higher security risk as they tend to no longer be supported or patched. This leaves data businesses vulnerable which can be costly in several ways, including potentially breaching GDPR or other data regulations.

Moving to insight driven data management

With investment in the right tools, it is possible for businesses to overcome the challenges posed by legacy platforms. Although the initial cost of implementing a new solution may be daunting, continuing to use outdated solutions is likely to be the riskier move and result in a growing number of indirect costs.

While replacing systems may be met with some reluctance, our research shows that many businesses have a good understanding of what they require from new data management solutions. According to our recent study, when considering new data management and analytics capabilities, firms remain focused on the fundamentals with more than a third citing ease of use and flexible deployment as their top business consideration, while 41% consider ROI to be the biggest factor. Therefore, organisations must deploy data management platforms that deliver this and can be easily integrated with other systems within their business.

Undoubtedly, changing data management strategy and tactics can be a difficult task as it is not only expensive to start again in terms of systems spend, but also with regards to time and resources to undo a solution which is typically deeply embedded. However, complacency is likely to involve much higher risks and costs, with a potentially devastating impact on business continuity, security and reliability. We are finding ourselves in an ever more data intensive environment and this data is under more scrutiny than ever before. Businesses, therefore, must ensure they have the most efficient and effective solutions in place to avoid discrepancies and non-compliance and optimally support the business. 

Please can you give us a brief refresher on the company’s origins and progress to date?

Zoho Corporation was established in 1996 and is comprised of three operating divisions: ManageEngine, which offers Enterprise IT management products; WebNMS, which provides an Internet of Things (IoT) framework and solutions. The last division, Zoho.com offers over 40+ cloud business applications serving more than 40 million users worldwide. These cloud applications cover the entire spectrum of business software, ranging from sales and marketing software to HR, Finance, IT office, communication and a collaboration suite. We are bootstrapped and profitable with over 6,500 employees in 8 office locations worldwide. Our business model does not rely on monetising our customer’s data and we take users’ data privacy very seriously.

1.     And who are the key personnel?

Zoho is privately held and was founded by Sridhar Vembu, Shailesh Kumar, Tony Thomas and Kumar Vembu. The founders are still active within the organisation. This is supported by a senior management team that has been with the company for close to two decades and which is instrumental in setting up a scalable organisation.

2.     Can you summarise Zoho’s SaaS/technology vision/philosophy?

Zoho’s philosophy is to offer compelling solutions with rich functionality, that can increase productivity for businesses. This is achieved by using superior technology in a very easy-to-use way and by providing software that supports rich integrations, out-of-the-box. This provides tremendous value to businesses who were traditionally used to software components cobbled together, that were either not interoperable or complex or expensive to integrate.

3.     In more detail, can you tell us something about the recent upgrade to Zoho Desk, with the addition of AI and process automation?

Zoho Desk was the industry’s first contextually aware customer support application. Recently, we added a process automation feature, called Blueprint. With Blueprint, customer success managers can easily create workflows with drag and drop and connect various important processes. Zoho’s AI-powered engine, Zia (Zoho’s Intelligent Assistant) is now available within multiple products including Zoho Desk. Zia in Desk is all about increasing the productivity of teams to make them better partners in customer’s success. Zia can now undertake sentiment analysis of incoming tickets and crunches data to detect anomalies in trends. These, along with other features around AI makes Zoho Desk one of the most advanced customer support products for businesses.

4.     And you’ve added ‘deeper’ analytics and AI to your CRM Plus product?

Yes, CRM plus makes a perfect platform to analyse data as it creates a massive set of data across three main front-facing departments of any organisation: sales, marketing and customer support. Zoho Analytics is a module within CRM Plus that’s also available as a separate product. The analytics module helps blend data across sales, marketing and support functions in a way that enables leaders to get visibility into customer journeys across these departmental contexts. This is visually available via dashboards for better decision making.

5.     Zoho Analytics – a new departure for the company?

Not exactly. Zoho Analytics is for the new face of Zoho Reports. This product has been around for over a decade and was one of the first self-service SaaS BI software on the market. Over the last couple of years, we have made significant improvements to the product that deepen the product’s focus on analytical capabilities, hence the change in name. This is our biggest release in the last several years for the product. In this release, we have worked on the following:

a.     Introduced machine learning and Natural Language Processing (NLP). A business user can now just ask queries via the ‘Ask Zia’ module such as “Show me the top 5 selling product in the UK” and get a visual chart as a response that can be drilled-down for analysis. This makes it easier for the non-technical user who does not have to write complex database queries to create the reports

b.     For enterprises, we have also released an on-premise version for the Business Intelligence software that can be deployed in private data-centres of mid to large sized enterprises.

6.     And what does it offer end users?

Previously I mentioned the main features that were added in the new release. We worked on those features for end users with below framework in mind:

• Make analysis for all that shouldn’t be restricted to people who know about querying databases
• Ability to blend and correlate data from across departments and applications to derive meaningful insights. This includes supporting third party application vendors such asSalesforce, Xero, Quickbooks, Facebook, Google, etc.

7.     Zoho Social- richer analytics?

Social media is vast and the data flow is unstructured in most parts. As a business with a keen interest on tapping the potential of social media, it’s imperative to have a tool that connects the dots and helps businesses to make quick decisions. The analytics on Zoho social helps you understand your audience better and also have a clear visibility into every single post that your team has made on the popular social media platforms. Zoho Social helps firms manage Facebook, Twitter, LinkedIn, Google Plus and Instagram. Apart from this, we have made the life of marketers easier by integrating Zoho Social with Facebook lead ads and Zoho CRM. Social media teams can now run Facebook ads on Zoho social and push the leads directly to Zoho CRM with just click of a button.

8.     Analytics seem to be a big focus for Zoho right now – why is that?

Analytics was always there in individual products, but as our suite becomes more mature and connects more data points, the relevance of analytics is getting stronger and we are able to find information that was once hidden in the siloed application. Also, this is in response to a growing need from businesses, which have an abundance of information residing in different systems. They need analytics to make decisions. We are just making sure they have a simple and smarter way to get things done.

9.     And do you think end users are wary of analytics as, thus far, the promise/hype has somewhat exceeded the reality?

Analytics was previously accessible to only a few select power users in companies and in some cases only to companies or teams that could afford it. Our aim with Zoho Analytics or any analytics module available in our products was to break down the entry barrier by keeping it simple so that anyone can build dashboard and connect data and keep the prices reasonable.

Building dashboards that blend data from custom applications and legacy systems is not easy. It’s a complex technical use case to solve. As every application is built on different platforms and has different database schemas, it’s perhaps this complexity that requires vendors to stay in this field for long to understand and develop platforms that help businesses.

10.  Can you give us a bit of background on the rest of the Zoho portfolio?

We have briefly touched upon Zoho’s Sales, Analytics and a bit on Marketing suite of products. Although these are five more products that are part of marketing, which include automation, live chat, event management, website optimisation and a website builder. Apart from these front office tools, Zoho has an entire range of products to manage the back office. The finance suite has the accounting, invoicing, subscriptions, checkout and expenses solutions and we have an HCM suite- Zoho People for HR operations. Zoho also has a Low Code developer platform called Zoho Creator that has been around for 12 years. Over 2 million business are hosted on the Zoho Creator platform and there are more than 100,000 developers across the world who are building apps on Zoho Creator using Zoho’s own scripting language called Deluge. Overall there are over 40 applications that Zoho has on cloud with 40 active million users worldwide.

11.  More generally, how do you see the SaaS market right now – buoyant. Steady, slow?

We see the SaaS marketing evolving and growing at a rapid pace as more and more business feel that it is the right business model to deploy and use. This has been demonstrated by the inflow of venture capital in the SaaS business and the emergence and growth of SaaS companies.

12.  And what will it take for SaaS to gain major traction – or is it more a question of a steady evolution?

While most small and mid-sized companies readily embrace SaaS, larger companies or those that operate in heavily regulated industries are still not ‘fully SaaS’. For these companies, it is a matter of time as they are gradually moving products to either SaaS software or to deploy their in-house applications on publicly or privately available web-scale architectures.

13.  How does Zoho compete and/or work alongside the hyperscalers who seem to want to do and own everything it-related?

Zoho’s focus is primarily on providing business applications or development platforms on which developers can build applications on, whereas the hyperscalers are focussed on the infrastructure layer.

14.  Presumably, customer service is an area of potential major differentiation – the speed and agility with which customers are helped?

Customer support is one area that Zoho takes pride in. We offer a very high quality of technical support through various channels – email, phone, chat, social, in-app, web, etc. Our online forum and communities with educational content keeps customers engaged with latest development on product and our vision of the direction.

15.  Any other thoughts on the SaaS market?

The SaaS market may also witness consolidation in some over-crowded market categories that contains many players. This may result in some larger players acquiring smaller niche ones, but here, integrating the products may be a challenge and not work well for the customer. Zoho is ideally positioned as we offer a very diverse and broad portfolio of products that are well integrated not only between themselves but also with other third party software.

16.  Before finishing – can you give us some background on the company’s footprint to date – Channel and/or direct sales?

Zoho operates in a dual mode with both direct sales and channel-driven sales. As we are a privately held company, we are not in a position to disclose financial figures.

17.  And how do you see this developing over time?

We are actively recruiting and nurturing our network of channel partners who resell our software, offer services to customise or build on top of it.

18.  Finally, what can we expect from Zoho during 2019?

A lot more focus on AI, automation and analytics, which can increase productivity for businesses.

The most powerful examples revolve around the ability of machines to spot patterns and trends within huge volumes of data. CIO Magazine spotted the trend towards better data signals last year, saying: “Many BI tools are bringing in more, and better, data signals to produce more accurate, insightful reports that blur the distinctions that traditionally separated BI from more advanced analytics. As such, BI vendors will need to advance, or risk losing out in the market.”

If you visit any event in the BI space, every leading vendor is talking about their approach to AI and ML. At Yellowfin, we’ve made it possible to cut through the deluge of data by using well-understood algorithms along with newer machine learning elements to surface insights and deliver practical benefits. Whatever tool you look at, you need to consider how users across areas such as sales, marketing, and human resources can maximise their BI to uncover valuable business information without the need for deep analytical skills.

Dashboard limits

For many organisations, the dashboard is what most people associate with their Business Intelligence tool. Charts and graphics alongside a traditional ‘traffic light’ approach offer a variety of methods for visualising your data specifically for monitoring a known set of metrics over time. However, business users increasingly need to discover new insights, rather than just monitor existing ones, and this is where dashboards tend to fail.

Dashboards were originally designed as a monitoring tool and not as a tool for data discovery. And with the increasing amount of data that sits in silos within every business, and the ever increasing number of applications available now, it is almost impossible to condense it all on to one page. As a result, the data is aggregated. For the business user, the dashboard offers essential top line numbers but gives little visibility into what's happening in the underlying business. In order to get into the detail, users need to feel confident at using filters and drill-down. So dashboards put the onus of discovery back onto the user by making them slice and dice the data themselves to find insights. However, this gives rise to several problems.

The discovery of insights become less predictable and requires the user to master the skill of manually drilling down into data and having the time to do so.  As the data may not change every day, the user has to repeat the process of data discovery to check for changes. Not only is this a waste of time, but it can lead to ‘analysis fatigue’ with the result that users may miss a change when something significant actually happens.

Workbook workaround

To counter this, businesses often start to use workbook solutions where users load data onto the platform, and then automation helps them build a better dashboard. Often the data is loaded manually so it’s not live and if a business user doesn’t have access or knowledge of the backend, then they must rely on data analysts to keep the underlying information updated. Once the data is loaded, the platform then runs basic algorithms that make layout suggestions based on the data. However, the platform only looks at the data at that particular point in time which means that analysts must constantly refresh the data.

More advanced solutions have started to allow users to ask a question and the application then analyses the data and tries to find an answer. However, this assumes that the user knows what questions to ask the platform – if a user has seen an outlier or a spike it may trigger them to question it. The platform doesn’t do the heavy lifting of finding outliers for the user. Instead, the platform just automates the existing data discovery process, but the onus of understanding what questions to ask still sits with the user. That’s why this approach is used mostly by data analysts rather than business users.

Automate to innovate

Yellowfin takes automated analytics much further. Yellowfin Signals applies machine learning along with more advanced algorithms to discover critical variances in business data. It runs continually in the background and surfaces statistically significant changes, alerting people of the changes relevant to their role. When it finds something, it analyses other data sources to find correlated information, then sends an alert highlighting the pattern so all recipients can determine if the data is actionable.

Signals runs on live data, so analysts don’t have to manually load data into a workbook before analysis can be performed. The underlying algorithms also tailor the notifications of changes to users’ roles, using information from each user’s interactions, and the interactions of those who hold similar roles, with previous signals. Something that may be insignificant to the CEO could be very important to someone further down the organisation. This level of nuance is effectively a learning process that gets more powerful as the system runs within an organisation. As it’s automated, it can never suffer from analysis fatigue or human bias, which are common issues within traditional dashboard uses.

Skilled analysis

Automation technology is not just making it easier for users to gain more insights, faster; it is ultimately helping to alleviate the skills shortage in the industry. Data analysts and scientists command premium salaries and there simply aren’t enough people to fill demand. 

The adoption of new technologies like Signals is at the start of the curve but growing rapidly. For organisations that have reached the limits of the usefulness of dashboards or that are struggling with hiring and retaining a growing army of data analysts, a change is coming.

Making devices smaller and more compact will be the number one design priority for electronics engineers in 2019. That’s according to a recent poll by thermal simulation software provider Future Facilities, conducted at this year’s Engineering Design Show.

 The research, which surveyed over 100 electronics professionals and engineers, found that 33% believe that shrinking device sizes will have more of an impact on the electronics industry than new technology developments such as 5G, artificial intelligence (AI) and the internet of things (IoT).

 Future Facilities’ research identified the top trends defining electronic design in 2019 as:

1. Making devices smaller / more compact
2. The internet of things
3. The need to add AI capabilities
4. Extending battery life
5. Incorporating edge computing into designs 

 Other trends, such as the addition of 5G capabilities and making devices more computationally powerful didn’t rank highly on the survey. Making devices greener and more sustainable ranked lowest in the poll, with a mere 2% agreeing it was their top priority for 2019.

As devices get smaller and new functions are added, Future Facilities predicts a host of new thermal challenges for design engineers.

As Tom Gregory, Product Manager at 6SigmaET explains: “Across all five of the top trends shaping electronic design in 2019, thermal management represents a major challenge. As devices become smaller and components are pushed together, the potential for thermal complications and the requirement for innovative grows significantly. At the same time, new technologies such as AI and the IoT are also bringing their own unique challenges and a host of new hardware requirements.

“Despite these concerns, previous research shows that many designers still aren’t taking thermal considerations seriously enough, often failing to run simulations and not identifying thermal complications until after a design is complete. If engineers are going to successfully develop the complex designs needed and fully capitalise on the new technology trends, this approach needs to change.”

Observing the evolution of global networks over the course of my career has always been fascinating. Our fast-paced, innovative industry has transformed the world, ushering in the age of mass communication that touches every part of our lives. Most people don’t give a second thought to how we keep networks in operation and evolve them to meet new demands, and that’s exactly how it should be. But for those of us at the coalface, the coming year is looking very exciting for the industry. Here’s my take on the key topics we’ll see ruling the agenda for 2019.

5G reality strikes

No surprise here that high consumer expectations and voracious demand for new services will drive the rollout of 5G throughout 2019. This is the shape of the future and we’ll see all stakeholders in the industry sharing roadmaps and innovations that will whet our appetites for things to come. The pilot projects that A10 Networks has been closely involved in have shed light on some of the new challenges that this major advance in infrastructure is going to create for service providers. We’ve learned that 5G demands are inherently different to 4G, with smaller packet sizes, more throughput, and higher concurrent session counts observed. That means service providers will need the facility to scale to multi-billion concurrent sessions with high throughput capacity.

As might be expected, core infrastructure security for 5G is a whole new and much bigger ballgame. The approach will need to be more advanced, automated and scalable to guarantee uptime and meet new requirements for control plane and user plane security. Alongside innovations in firewall and DNS protection, we’ll see a new generation of AI and machine learning-based security solutions brought into play to mitigate the increasing DDoS risk created by the proliferation of IoT devices and the resulting expanded attack surface.

Low latency, low TCO and high reliability will all be crucial factors for 5G success. Competition in this market will be fierce, so there’ll be focused investment in technology that delivers robust, secure and cost-effective networks.

Historical investment protection

With all the buzz around 5G we shouldn’t forget that it won’t happen overnight. Network evolution takes time and service providers still have a considerable investment in legacy infrastructure that needs to be maintained, and boosted, to cope with growing demand through the transition period. We’ve been seeing this over several years, as demand has skyrocketed and new entrants have started running advanced services over existing networks. Full network upgrades are cost-prohibitive, so service providers are having to invest in products that can make what they’ve already got work more effectively.

Take IP addresses as a case in point. The pool of IPv4 addresses is being exhausted by the explosion in volumes of IoT devices. The expectation was that everyone would move to IPv6 to solve the problem, but that’s effectively an upgrade and we haven’t seen service providers going full throttle down that route. Instead they’re adopting technology like our Carrier Grade Networking (CGN) solutions that helps them preserve their investment, and get the best out of the technology they have today by extending the lifecycle of IPv4, and carefully managing an effective and affordable transition to IPv6 over the longer term to underpin business continuity.

Overall, I expect to see a measured migration and network evolution. Rip and replace is simply too costly an option and service providers need to think carefully about how best to beachhead into profitable 5G services while maintaining existing infrastructure.

Security gets smarter and more pragmatic

Cybersecurity will continue to be a defining challenge as we move into 2019. There’s a noticeable shift, though, as defence techniques and philosophies mature. We’re moving away from the fortress mentality of building a wall and defending it at all costs, to acceptance that the battle for the network perimeter has pretty much been lost and a more pragmatic approach is necessary. Cybercrime is big business and we know that resourceful adversaries are succeeding in penetrating our networks, so now the focus is on building resilient networks that are capable of rapidly identifying and eliminating malicious activity when it occurs. 

The threat of DDoS attacks is still ever-present, and attacks are now so easy and cheap to launch that they will undoubtedly continue to intensify. Protecting against DDoS is now simply a cost of doing business, so organisations want to ensure that they’re getting the best protection for their investment. This means looking for protection that is automated, intelligent and scalable, but which also achieves this at a low TCO.

A shift in the business model for network investment

As service providers maintain existing networks and build out new capabilities, I believe we’ll see a reversing of the trend for deferring capital expenditure in preference for operational expenditure that has dominated in recent years. Organisations used to be keen to reduce CapEx and accept higher OpEx but, when you know you’re in a major upgrade cycle, that approach ties you into existing technology and simply pushes problems further out into the future, building up a technology debt that will eventually need to be repaid. With the speed of innovation in today’s market, that’s a risk that many service providers are starting to question.

Service providers are now thinking further ahead, aiming to futureproof their networks by spending a bit more upfront in a bid to reduce that long tail of operational expenditure further down the line. Solution providers who can offer licensing and contract flexibility should reap the benefits of this change in approach.

The coming year promises to be incredibly exciting for all of us involved in the network industry. Overall, I predict that it will be a balancing act between looking forward to 5G and all the opportunities it offers, while handling the challenges of supporting existing networks and developing security strategies to defend against increasing threats. One thing’s for sure, it won’t be boring!

Staying one step ahead of cybercriminals is crucial when it comes to protecting company and customer data. But this is only possible if you have a good hold on short and long-term cybersecurity trends.

So, what does 2019 have in store? Smarter bots, complex clouds, IoT risks and data regulations will all dominate boardroom conversations. Here’s a summary of the trends that I think will make the year ahead as turbulent as the one just passed:

1. Cyber-attacks will grow - and go slow

Organisations will see an increase in cyberattacks but these will be “low and slow”, rather than “noisy” incidents such as DDoS attacks. Launched by botnets, “low and slow” attacks aim to remain under the radar for as long as possible, to steal as much data as they can. Often these take the form of credential stuffing attacks, where stolen credentials are used to access associated accounts and steal further personal data such as addresses and payment details. To protect themselves, businesses will need to adopt bot management solutions, which identify, categorise and respond to different bot types. The technology uses behaviour-based bot detection and continuous threat analysis to distinguish people from bots.

2. Bots will overtake human web traffic

As bots become more sophisticated, more than 50% of web traffic will come from bots. Already, Akamai has found that 43% of all login attempts come from malicious botnets – and this is set to increase as credential stuffing and “low and slow” attacks grow in popularity. More sophisticated bots will become capable of accurately mimicking human behaviour online – making it harder for bot solutions to detect and block their activities. Effective bot management tools are crucial for addressing this threat. They are able to use contextual information, such as IP addresses and past user behaviour data (neuromuscular interaction), to determine whether a visitor is a bot or human and respond accordingly.  

Cyber-attacks will grow - and go slow

Organisations will see an increase in cyberattacks but these will be “low and slow”, rather than “noisy” incidents such as DDoS attacks. Launched by botnets, “low and slow” attacks aim to remain under the radar for as long as possible, to steal as much data as they can. Often these take the form of credential stuffing attacks, where stolen credentials are used to access associated accounts and steal further personal data such as addresses and payment details. To protect themselves, businesses will need to adopt bot management solutions, which identify, categorise and respond to different bot types. The technology uses behaviour-based bot detection and continuous threat analysis to distinguish people from bots.

2. Bots will overtake human web traffic

As bots become more sophisticated, more than 50% of web traffic will come from bots. Already, Akamai has found that

Businesses adopting multi-cloud strategies will face increasingly complex challenges to ensure that security is consistently, and effectively, deployed across them all. With Gartner predicting that multi-cloud will be the most common cloud strategy next year, organisations that have successfully secured one cloud will need to replicate this across all their cloud portfolio to ensure that vulnerabilities are patched and nothing slips through the cracks. With many businesses already experiencing ‘leaks’ or breaches of their single-vendor solutions, we expect companies to seek out cloud-agnostic security solutions to simplify deployment and management across the enterprise.

4. Consumers will continue to put convenience ahead of security

1)    Major public cloud providers will differentiate

In some ways 2019 will be business as usual for the major public cloud providers. Their IaaS model is well-entrenched, and any new technology which drives CPU and RAM consumption on their platforms will be more than welcome.

However, with multi-cloud becoming the norm, the major players will have to prove their worth more than ever before in an enterprise’s IT strategy. Price wars between the leaders have proven to result in a race to the bottom, so instead they’re looking to differentiate. Expect to see Google focus on its AI credentials, Microsoft on its workload migration capabilities, and Amazon to continue pushing AWS hard in the public sector space.

This differentiation will be important for the incumbents as it could be the year they come under increasing pressure from other public cloud players. IBM’s acquisition of Red Hat is a signal of potential competition, while eastern players such as Alibaba and Tencent continue to improve their capabilities locally, undoubtedly with an eye on international expansion.

2)    Kubernetes will be used as the industry standard to manager containers at scale

The value of containerisation has been almost universally realised, and adoption of Kubernetes has almost hit a peak rate, making it essentially an industry standard. The challenge in 2019 will be to progress beyond the early adoption of containers towards using them to manage deployments at larger scales.

The ubiquity of Kubernetes will likely drive consolidation within the container market. While open source development is beneficial overall, the sheer number of Kubernetes distributions currently on the market will be hard to sustain. As larger vendors look to improve and differentiate their own distributions with specific capabilities, expect smaller niche players to be snapped up for their expertise.

In general, we are likely to see a continued break down of computing into smaller bits to add to the competitive landscape between cloud providers. Technologies such as serverless computing will likely play an increasingly important role over the next twelve months. We expect to see the beginnings of open source serverless solutions start to compete for broad acceptance in the developer community, which will shape the future of that technology ecosystem for years to come.

3)    The continued importance of open source

Challenges still remain for businesses when attempting to deploy cloud computing effectively, especially as complexity increases due to demands for multi-cloud strategies. It seems likely that the trend of creating Lego-like building blocks to help standardise and bring more order to cloud stacks (such as Kubernetes, OpenStack etc.) will continue and even increase.

This is true as businesses realise the benefits of the CI/CD (continuous integration/continuous delivery) approach which the current fast-moving pace of cloud innovation demands. Using open source technology means less disruption with each new implementation, and allows dev teams to fine tune new software more effectively. The commercial benefits of this approach are also clear, as it allows teams to more readily pinpoint changes in productivity as a result of software implementations.

However, creating these applications to improve our lives and businesses is no mean feat. In fact, AI-enabled applications are extremely hard to build. Large AI programs are difficult to design and write as they involve many types of data. Porting them from one platform to another tends to be troublesome. 

What’s more, several steps are required at each stage to begin building even the most rudimentary AI application, each requiring different skills. Feature extraction, data collection verification and analysis, and machine resource management make up the majority of the codebase necessary to support a comparatively small subset of actual ML code.

Keeping it contained 

There’s a lot of work to do to get to the starting line, as well as a large amount of ongoing effort required to keep the applications current. Fortunately, Kubernetes -- the open-source platform that automates the deployment and management of containerised applications, including complicated workloads like AI and machine learning -- can be a facilitator.

Containers provide a compact environment for processes to run. They’re easy to scale, they’re portable across a range of environments – from development to test to production – and they therefore enable large, monolithic applications to be broken into targeted, easier-to-maintain microservices.

Kubernetes has had a meteoric rise as a container orchestration platform. The vast majority of respondents to a Cloud Native Computing Foundation survey say they are increasing their use of Kubernetes across a variety of development stages. Forrester stated recently that “Kubernetes has won the war for container orchestration dominance and should be at the heart of your microservices plans.”

The go-to for AI

Kubernetes and AI represent converging trends. Most companies are running (or plan to move to) Kubernetes as a platform for their workloads, and AI is an increasingly important workload.

Kubernetes is ideal for the job because AI algorithms must be able to scale to be optimally effective. Some deep learning algorithms and data sets require a large amount of compute. Kubernetes helps because it is all about scaling based on demand. It also provides a way to deploy AI-enabled workloads over multiple commodity servers across the software pipeline while abstracting away the management overhead. Once the models are trained, serving them in various deployment scenarios, from edge compute to central datacenters, poses challenges to non-containerised forms of applications. Again, Kubernetes can provide the necessary flexibility for a distributed rollout of inference agents on a variety of substrates.

Shifting attention

As organisations increasingly shift their attention to AI to decrease operating costs, improve decision-making and serve customers in new ways, Kubernetes-based containers are becoming the go-to technology to help enterprises adopt AI and machine learning. In December of last year, the Kubernetes project introduced Kubeflow, “dedicated to making deployments of machine learning workflows on Kubernetes simple, portable and scalable.” While Kubernetes started with just stateless services, the project said, “customers have begun to move complex workloads to the platform, taking advantage of rich APIs, reliability and performance provided by Kubernetes. One of the fastest growing use cases is to use Kubernetes as the deployment platform of choice for machine learning.”

At the beginning of 2017, among the three major public cloud vendors, only the Google Cloud Platform supported Kubernetes, with its Google Kubernetes Engine. By the end of the year, they were all on board, after Microsoft added Kubernetes support to the Azure Container Service and Amazon debuted the Amazon Elastic Container Service for Kubernetes. Now, the uses for Kubernetes and ways it’s being deployed by companies is seemingly limitless.

That’s a lot of activity in a relatively short time span, and it shows the extent to which tech vendors and their customers are rallying around the notion that containers offer huge benefits in developing and managing AI components of applications.

The rise of AI is helping fuel the growing interest in containers as an excellent way to bring repeatability, fault tolerance and repeatability to these complex workloads. And Kubernetes is becoming a de facto standard to manage these containerised AI applications. It’s a wonderful match that should dramatically benefit enterprises for some time to come.

In a bid to simplify such progress-impeding complexity, convergence - in the form of Hyperconverged Infrastructure (HCI) and Converged Infrastructure (CI) -- brings assets, such as storage, networking, processing and other functional appliances together, to be managed under one unified system.

When bringing in any new technology, it is vital to consider its impact on the revenue-related, mission-critical systems upon which the business relies. So how does the convergence solution impact mission-critical application availability, scalability and performance? To better understand this challenge, it is helpful to delve deeper into the basis for HCI - what it addresses, where, and having been tried and tested, whether it may be falling short of its promise. From there, it will be possible to pinpoint exactly what can be done about it.

Challenges and drivers for HCI

As mentioned, the pain points of the disparate IT environment today are a result of how the IT infrastructure has evolved; and the persistent behaviours surrounding it. Typically, there is no long-term plan for deployments. Installations tend to be fragmentary, adding more layers to the infrastructure, initiated as a direct result of individual departments or business units’ unique requirements. Each layer commonly has its own data management, storage, processing and compute resources incorporated, utilising networking at different tiers within the data centre. In this way, silo functions - for example, for support, development and application execution -came about.

When procurements are made, or whenever any hardware, system, software, network, storage, or development tool is upgraded, it comes with a raft of side effect issues that are notoriously difficult to detect, while diagnosis and repair would require greater expertise in each specific area. For example, the resources used by applications may reside within many different computing tiers, and if there is an issue, locating them can be akin to finding a white glove in a snowstorm.

Some systems will suffer from overutilisation of workloads, while others will be relatively underutilised -- which is extremely inefficient and wasteful considering capacity cost. And because of the inflexibility of the silo design, there is no easy way to migrate workloads between systems to ensure they are more evenly balanced.

In the struggle to overcome these challenges and increase performance, IT managers are facing on-going pressure to embrace new trends and more efficient technologies such as flash and the cloud, adding yet more layers of complexity, while being expected to do more with fewer resources.

For organisations still relying on this silo design -- and there are many -- getting IT functions aligned with the business is a major priority. Which is precisely why HCI is so compelling, though even this option is not free of limitations, as the decision of whether workloads should be migrated to a platform such as HCI will entirely depend on the workloads themselves.

HCI scaling restrictions

The drawback to HCI usually becomes apparent some time after deployment, when the IT team realises that the organisation needs more resources to manage its workloads, and therefore want to ‘scale out’. Scaling out can be described as the addition of extra nodes to a cluster (increasing the node count, or quantity), as opposed to the replacement of nodes with more powerful ones (thereby increasing size/capacity, processing power), as is the case with ‘scaling up’. To allow for growth, enterprises really need to be able to carry out both types: scale out and scale up, as workloads require.

Bolt-on systems for HCI that service a particular workload are generally not an issue, however each organisation’s workloads requirement will be unique, and issues can arise where scale-out of a single resource is needed, as is often the case. For example, there may be adequate network bandwidth, but not enough storage. In this instance organisations would have to pay for a full range of features including those which are unnecessary -- which is uneconomical in terms of cost, space and power consumption.

Innovation: the advantages of ‘self-protecting HCI’

This challenge is tackled with the next generation of HCI; which is based on creating two distinct tiers for processing: a performance tier and a protection tier, as opposed to traditional HCI’s single tier.

As the organisation grows, self-protecting HCI is conducive to applications scaling easily, with high levels of performance, low latency with high-level security, and full resiliency during any system failures.

High levels of performance are achieved through the utilisation of flash, with the convergence of VM (virtual machine) or container and IO processing into industry standard x86-based servers. Self-proecting HCI intelligently harnesses existing flash storage, as well as processing nodes or servers within the data centre, mitigating the relinquishment of other existing hardware and software resources, as has previously been the case.

The protection tier converges data processing, primary storage, backup and archive into data nodes which have been optimised for long-term resiliency, efficiency, and security. Storage can be based on spinning disk or flash, as per requirements. As the data resides locally in this tier, the delays, so characteristic of traditional backup environments, are avoided.

Scale up or scale out

Previously, when it came to scaling, organisations would have had to trade off one approach for the other. The good news is that with this new generation of HCI, comes the innovative capability to implement both scale up and scale out types of growth, while also enabling application availability and performance with HCI, utilising the organisation’s existing legacy server hardware.

This is made possible through the creation of a tier 1 application platform. So, depending on which particular constraint the workload is facing within a given architecture, enterprises can now scale up or out as needed. If more storage is needed, more servers can be added to accommodate increasing workload requirements. And if an application requires more processing power, units with greater processing capability can be easily added. Systems designed to enable ‘scale up’, allow increases in storage processing power, networking capability and more, growing to support petabyte-scale workloads, with the ability to maintain low latency at that scale, at impressive uptime rates.

Scaling performance

With the effective use of commodity server-based flash storage, performance can scale linearly in a way that is fast and cost-effective, even supporting converged data backup both on-prem and in the cloud. Flash stores all of the active data required by a particular application on the server executing it. So subject to workload requirements, flash can be configured granularly and used as a server-side cache to reduce data access latency, and within the storage nodes for improved overall data centre efficiency. With flash’s provision of microsecond latency, enterprise scale tasks and tier-1 applications can be supported with ease.

So in answer to the question of whether hyperconverged systems can handle critical enterprise applications, yes, they can. Through the innovative partitioning of workload components into individual performance and protection tiers, supported by fast-performing server-based flash and resilient scale-out storage. Enterprises can now confidently embrace all the benefits of next-generation convergence with the flexibility of scaling they require, bringing organisational growth, agility and, most importantly, the assurance of mission-critical workload performance.

The essential requirements of a UPS are that it is reliable, easy to maintain, efficient to operate or control and unobtrusive—one wants to know that it is there, but one would prefer that it never be needed.

Increasingly, given the high levels of automation and remote management in today’s data centres, UPS systems must have IoT enabled capabilities to ensure their status can be monitored, and where possible their operation be controlled, from outside the white space. Furthermore, any maintenance that is necessary must be performed as quickly and easily as possible, with an absolute minimum of downtime.

Schneider Electric’s Easy UPS 3S series is designed to meet all these requirements for small and medium businesses. Available in power configurations ranging from 10 kVA to 40kVA, the three-phase UPS is designed with simplicity in mind, ensuring such aspects as installation, startup, maintenance, monitoring, management and scalability are made simple.

It is intended for use in applications including small and medium data centres, on-premise computer rooms, manufacturing facilities, telecommunications, commercial buildings or healthcare.

Installation and startup

Easy 3S UPS models are available in a range of sizes and can be configured with internal or external batteries, depending on size constraints and computer-room layout. Mounted on wheeled enclosures they can be rolled into place easily and an Easy Loop Test allows the performance to be verified in advance of connecting the load so that any obvious faults may be detected and rectified in a timely manner.

To simplify installation, input output and bypass breakers are included as is an Emergency Power Off switch all of which speed up deployment.

Maintenance

The UPSs enclosures are easily accessible from the front to simplify servicing and maintenance. For example, the dust filters are placed right behind the magnetic front panel so they can be easily removed and replaced which can be a frequent occurrence, especially in harsh or ruggedised environments. 

Expansion and resilience

The Easy UPS 3S series can be deployed with up to four models arranged in a parallel design to provide increased capacity or improve redundancy in situations where downtime is critical.

For high availability systems the UPS can be deployed in a variety of parallel or distributed redundant designs so that the failure of any one UPS can be accommodated, without risk to loss of power by other units in the configuration.

Efficiency

Easy UPS 3S series also offer an advanced economy mode of operation which reduces operating costs while offering very high levels of protection. They utilise Li-Ion battery technologies, which provide smaller footprint in terms of size and a better total cost ownership, compared with traditional valve-regulated lead-acid battery (VRLA) batteries.

Depending on the level of availability that is required the systems can be deployed in fully online mode, where the battery and power inverters are permanently connected to the power path from utility to load. Another option is to deploy it in economy mode, where a modicum of reliability is traded off for greater energy efficiency.

Double-conversion online UPS topologies are most commonly found within large data centres, where mains power is rectified to DC before charging the backup battery. Afterward it passes through an inverter to be converted back to AC, hence double conversion.

When in double-conversion mode, power output from the UPS will always pass through the inverter, providing a regular conditioned supply to the load. There is no loss of power in the event of a mains outage or blackout because the load is always connected to the inverter and battery backup. Operating in this mode however, means there is constant wear on the power components, with attendant reduction in Mean Time Between Failure (MTBF) and a knock-on effect on reliability. 

In economy mode, or ECO Mode, a manual bypass switch overrides the double conversion path and connects the load directly to the mains input. This can help to save energy, but power protection is reduced as the IT load is exposed to raw utility mains power - without the conditioning normally provided by the double-conversion, online UPS.  The UPS must therefore continuously monitor the mains power and quickly switch to the inverter when a problem is detected and before it can affect the critical load. 

Overall, the Easy UPS 3S series can deliver 96% efficiency in double conversion mode and up to 99% efficiency in ECO Mode. It can also accept a wide input voltage window from 280 to 415V which also helps save battery power.

Data Driven Monitoring and Management

An intuitive graphical user interface (GUI) on the front panel allows simple system configuration. For more in-depth system monitoring and management from a central location, there is the option to include an SNMP (Simple Network Management Protocol) which allows the UPS to be managed via a Web interface or through Data Centre Infrastructure Management (DCIM) software application such as Schneider Electric’s EcoStruxure IT.

Use of the network-card allows status updates or alerts regarding the UPS performance to be sent to a Smart phone application or to a central management console. As issues arise they can be addressed by remote management from the console or Smart device or, depending on severity, a service professional can be dispatched to deal with the problem in person.

EcoStruxure IT monitoring and management software is available in several variants to accompany. EcoStruxure’s Asset Advisor software is a cloud-based application particularly suited for customers who prefer to outsource their data-centre management services to third parties. This software provides round the clock monitoring of hardware assets, including UPS and other critical IT assets, delivering updates directly to a customer’s mobile phone. In addition it provides analytics services that deliver detailed insights into how well a data centre is performing and offers recommendations based on realtime information.

EcoStruxure IT’s on-premise management suite, namely StruxureWare for Data Centers, is an integrated suite of applications typically enabling businesses to manage their data centres across multiple domains. It allows customers to make decisions regarding how to balance their equipment for an optimal mix of high availability and peak efficiency throughout the entire data centre life cycle.

Both software suites provide customers with the intelligence to proactively perform maintenance and replace batteries in a timely manner, ensuring that power security is never impaired. The Easy UPS 3S series makes use of Lithium Ion battery technology, which provides a longer lifetime operation and a higher volume of charge and discharge energy cycles, when compared to traditional lead-acid batteries. In addition, as well as taking up less space.

Given its range of advanced technological options, IoT enabled connectivity and compatibility with leading infrastructure management software systems, Schneider Electric’s Easy UPS 3S range makes business continuity a reliable, simple and easy to deploy option for today’s always-on businesses. 

The world’s CCTV and police cameras are one upgrade cycle away from capturing higher-definition imagery, which will help facial-recognition algorithms work better

Silicon Valley’s approach to facial recognition, using powerful computers and large datasets of faces to train highly accurate software, is only beginning to percolate into the security market. That will speed up in 2019

The combination of web-tracking and physical biometrics will mean that spaces in which human beings are not tracked will shrink in 2019.

In America, for example, Major League Baseball will start allowing fans to validate their tickets and enter stadiums via a scan of their face, rather than a paper stub. Singapore’s newest megamall will use the technology to track shoppers and recommend deals to them. Tokyo will spend the year installing facial-recognition systems in preparation for the Olympics in 2020, when it will use the technology to make sure that only authorised persons enter secure areas. Research by SITA, a technology vendor, suggests that three quarters of all Airports and Airlines are investing in the technology or carrying out research in the area.

It is worth worrying about facial recognition for the principles it offends and the damage it threatens. Human beings need spaces where there movements are not tracked. A world with ubiquitous facial recognition means one in which no coffee morning, no midnight walk, no trip to the shop can occur without being assigned to a specific face and identity. Strong laws that protect individual rights are the best hope for limiting such tracking.

While in reality integration of AI into HR solutions will be a slow process, there’s no doubting the technology’s potential to take on elements of the HR function, delivering substantial time and cost efficiencies for professionals and improving the employee experience.

But will there ever be a time when technology makes HR professionals obsolete? Or are there other elements of the function which can simply not be engineered?

The state of play now

HR departments are often criticised for lagging behind when it comes to innovation and technology adoption, but evidence suggests that this is no longer the case. According to our Global Employee Benefits Watch 2018/19 research, 70% of global employers now use benefits management software. This has the capability to automate many manual processes; from scheme enrolment through to administration, deduction and taxation. Historically these were time-exhaustive error prone tasks for HR and benefits teams.

However, while automation is streamlining some HR processes, there is still potential for technology to remove a far greater proportion of the administrative burden from teams – before even touching the strategic or consultative elements of the role.

If we take administrating private medical insurance (PMI) as an example. While benefits software has expedited and improved the employee experience of selecting PMI cover, insurers often lack the technology needed to automatically receive selections and immediately kick-off schemes from date of election. Instead, employees’ selections are often stuck in a holding pattern, waiting for insurers to enrol them. This is often only processed on a monthly, rather than real-time, basis.

Enterprises need to consider this experience in contrast to that offered to consumers. If you or I needed travel insurance for example, we could log onto a platform and likely receive cover that day. If the HR supply chain were able to automate the end-to-end PMI enrolment process, the same speed and seamless experience could be achieved, while further reducing the administrative burden on HR teams.

The HR departments of tomorrow

If we imagine for a moment that we have overcome technology integration as a hurdle, we can then look forward to a future where technology plays a greater role in HR – going beyond administration to defining to strategy.

If we return to PMI as an example. In future, we may see AI-enabled solutions able to evaluate reams of demographic and lifestyle data on a global employee population and determine a list of PMI providers best suited to the employee’s needs. This could take into account the best price point and product offering specific to the employee’s need and likelihood of claim. It could then project cost and product comparisons between schemes and with the click of a button enrol the employee instantly into the most cost-effective and relevant scheme for them. Such choice, comparison and hyper-personalisation not only delivers a consumer grade experience, but also has the promise to disintermediate the employer from the benefit arrangement; yielding further savings and efficiencies while delivering a market-leading benefit offering.

On a grander scale, we could see machine learning and data modelling used to predict the impact of one decision on another. For example, an HR professional may be able to ask, “what might my medical costs be next year in China if I increase my headcount by 10%?” with software able to instantly calculate an answer, considering trends in benefits take-up, salary and insurance premium hikes. In this scenario, technology has the potential to influence where an organisation places head-count, directly impacting HR and business strategy.

The advantages of such solutions, in terms of their ability to reduce administration, optimise the employee experience, reduce organisational costs are limitless – but is this enough to eliminate the need for people in HR?

A place for people

The answer is of course “no”. Developments in automation, data analytics and eventually AI will drive and necessitate the evolution of HR. However, I cannot imagine a near, or mid-term, future where technology is able to replicate the emotional intelligence (EQ) integral to the function, and therefore take on the consultative element of HR’s role. 

Human Resources departments fundamentally deal with people, and these people will continue to crave some form of human interaction, particularly when seeking help on a sensitive matter or one linked to their personal health and happiness. Computers are not yet able to emulate empathy which is ultimately what makes us human. When it comes to benefits for example, our research found that almost half of global employees (46%) still highly value face-to-face communications. Handing every engagement opportunity over to a machine could therefore alienate a large proportion of the workforce.

Next steps for businesses

Further automation and eventually AI integration into HR is inevitable. This will continue to improve the employee experience, remove the administrative burden from HR teams and even inform business strategy. However, this future will only be realised if HR teams are able to take full advantage of the tools at their disposal. It’s imperative that organisations equip their HR and benefits professionals with the skills and understanding they need to take advantage of the benefits offered by technology and shift into their increasingly consultative role.

Technology will not and should not replace people in HR. As long as people have a role in the workplace, there will always be a need for human interaction and management. A future where human empathy, sympathy and discretion are not needed in the function is a long way off.

Additionally, with the sheer amount of API communications showing explosive growth, analysing data trends and predicting events requires that API security becomes more intelligent. With such significant advances in Artificial Intelligence (AI) in recent years, the next logical step is using AI to enhance the interpretation of API data.

Why APIs?

Firstly, let’s be clear about the role that APIs play in your network today. APIs are the synapses that connect applications together and enable them to share data. They literally underpin almost everything we do, from banking to shopping to controlling our heating. Without APIs, we would not have seen the exponential growth of cloud computing, the Internet of Things, and even social media. Even our favourite devices – smartphones, tablets, smart watches, fitness trackers etc. all require connections to cloud services to function.  In other words, they all use APIs.

With the profound growth and adoption of APIs, API vulnerabilities have become the sleeping giant of our API-led technology world. The vulnerabilities posed by exposed APIs and insecure API Gateways are significant, yet they remain one of the most overlooked threats to information security today. This is largely because API vulnerabilities are not always easy to spot, and require specialized technology for detection and prevention. This is notable with the OWASP Top 10 (the highly respected, peer-reviewed list of the top vulnerabilities facing organisations today) which now reference APIs in 9 of the top 10 vulnerabilities.

Is AI ready to help?

So, is AI ready? The consensus within the IT industry is a firm yes. With the convergence of a number of factors such as the availability of low cost cloud computing resources, well established AI algorithms, and in-depth knowledge of API bi-directional information properties, the time is right for AI to extend beyond chess-games and be applied toward real-world API deployments.

How does AI help APIs?

First and foremost, we see AI as providing an additional layer of analytics and context to the API architecture. AI is not a replacement of an API security gateway, or an alternative approach to securing APIs.  The only guaranteed way to secure the traffic that travels through your APIs is to deploy API security gateways that are secure by design. Secure by design means – an operating system that is locked down (no root access, no ability to add 3rd party software, integrity checks at both startup and while running), product architecture that follows strict security architecture principles (e.g. administration, policy storage, sensitive security artefacts such as PKI keys, passwords, etc. must be encrypted locally and during transit), and product components built with mission-critical stability in order to maintain performance during high volume transactions and penetration attacks.

With a fundamental API security gateway architecture in place, you can then add Artificial Intelligence to further enhance the protection, visibility, and predictive analysis that properly designed API AI models can offer.

By leveraging recent advances in artificial intelligence and machine learning, API Security Gateways can begin to predict and protect against attack behaviour in real-time. They are uniquely positioned to make use of AI for a number of reasons:

1.     Centralised data gathering

API security gateways represent the information gateway or the conduit of data going in and out of the network. This puts them in the perfect position to capture and analyse this data from a central position. What’s more, by pooling together and analysing threat behaviour across all of your API communications, AI can be used to leverage API analysis far more easily that trying to aggregate logs from disparate services and components across your enterprise.

2.     Deep content awareness

The API security gateway already has access to the bi-directional API data on your network, so it has a unique advantage over other technologies. Using deep content-parsing and awareness of the data in the network and the activity on it, the API Security Gateway can intelligently feed AI algorithms for advanced predictive analysis.

3.     Granular feature engineering

Feature engineering is one of the most important aspects of AI.  With API Security

Gateways, the API communication is contextualized into granular features which are

then isolated to build predictive models such as anomaly detection, capacity

planning, response profiles, etc. As each set of business APIs are distinctly different, automated and granular feature engineering are required to ensure the AI models are properly and accurately predicting outcomes.

There is no substitute for good API security design

In conclusion, by using AI and machine learning to analyse the data that passes through it, the AI-enhanced API Security Gateway will be able to predict the behaviour of API attacks in real-time.

AI is perfectly positioned to enhance the security capabilities of API Security Gateways, but should not be mistaken as a replacement for good security design. Rather, AI has the capacity to enhance and augment the protection and visibility gained by deploying API Security Gateways. 

AI is no longer science fiction and has already begun to transform many industries. However, an AI model is only as good as the data you feed it. This is why the combination of AI with API Security Gateways represents the next frontier in advanced analytics.

Gartner’s infrastructure team managing vice president and chief of research, David J. Cappuccio, recently stated that his planning assumption is that by 2025, 80% of enterprises will have shut down their traditional data centre, versus 10% today. This prediction may or may not come true, but data centre staff are now finding that they don’t have the cloud knowledge or skills demanded of them to ensure a smooth transition from on-premise to cloud-based applications.

Cloud 2.0 or Infrastructure as a Service (IaaS), as it is frequently referred to, needs a lot more planning as it is dealing with application performance, rather than just availability. There are two distinct approaches a) ‘Lift and shift’ where you move your existing application to a new infrastructure with minimal change, or b) ‘Cloud Native’ whereby you either re-write the application for the cloud or use the cloud service provider resources to do so. Most business-critical applications are made up of code dating back many years and so will not be an easy task to re-write. These applications also have dependencies on accessing other applications and resources, so it is critical to have a full understanding of your on-premise hosted applications before migration is considered. For this discussion we will concentrate on ‘Lift and shift’.

Primary drivers for moving to the cloud are to reduce infrastructure spending, personnel costs and while enabling business agility and scalability. Physical infrastructure such as hardware, floor space, cooling, security can be owned and managed by a third party and their shared hosting approach should mean a cost reduction – so why is this not always the case? The primary reason is lack of planning. If you simply decide to replicate your on-premise environment at a hosted site then the costs will be similar to where they are today. The planning process should include the question ‘How much will it cost to run my application in the cloud?’ This potentially opens a huge can of worms because to know what service you expect from the cloud provider you need to start with knowing how your applications are performing now – this is a very different question to ‘how are my servers/fabric/storage/ performing now?’ which is how you have always managed the infrastructure.

The other fundamental is ‘Which Cloud Service Provider is the best choice for my application.  Very few cloud providers even come close to offering a Service Level Agreement (SLA) for the performance of your application in their environment – yet this is vital to your decision process. If the application is going to run slower than it does currently this migration decision could potentially affect your organisation’s business. If you have to add more capacity/power/resource to host it then the cost goes up.

The starting point, therefore, is to analyse the workload behaviour and performance characteristics of your applications you plan to migrate. You need to know how they are performing and what provisions are they using before the cloud service provider selection process begins. Each application has an individual workload profile that will perform differently in different environments. When you look at the application workload you can see the peaks and troughs of resource requirements, and you need to gather this information over time – 8:00am on Monday can need different resources compared to 2:00pm on Thursday. Seasonality also needs to be factored in – do you have more throughput at different times of the year/month/week/day? 

In addition to the application’s performance you need to understand its dependencies. If the application is accessing other resources that are not going to be hosted in the cloud, or is managed by a different provider, this can affect performance and cost.

Each cloud provider has strengths and weaknesses when it comes to hosting your application. You need to approach each potential supplier with your eyes wide open. You are putting your business at risk if you get the service wrong, so you should not trust their performance claims. Each application workload needs to be tested against the new environment to ensure you are getting an equal or better service than you currently have.  Many organisations have migrated an application then moved it back in-house because of disappointing performance or escalating cost – in the main this repatriation is caused by lack of or poor planning prior to migration.

Most organisations have a cloud initiative and the analysts and advisors are pushing the business to reap the benefits of an IaaS environment. A cloud hosted infrastructure, if well planned, can bring good financial and performance rewards. Don’t rush to the cloud without answering these three questions:

• Will my application perform as expected in the public cloud?
• How much will it cost to run the application in the public cloud?
• Which cloud service provider is best fit for my application?

To take these in turn:

Will my application perform as expected in the public cloud? – How do you know which application workloads to migrate and which to retain in an on-premise data centre? How are the applications performing now? Have you assessed your seasonal application workload behavior? If you can either run your application workload in the cloud test and dev environment to ensure performance or synthesise the application workload and run a simulation of it in a live environment, you should get a good idea of what will happen.

How much will it cost to run the application in the public cloud? – How do I simplify and reduce time to migrate a large number of diverse workloads? How do I select the optimal CPU, memory, network, and storage configuration? Be specific with the host. You should be negotiating cost based on a known application workload and a known environment – at no point should you sign up to a service that doesn’t offer you better performance for your applications at lower cost than running it yourself – after all, these are key reasons why you are going down this route.

Which cloud service provider is best fit for my application? -  How do I test cloud workload performance before migrating? Does the cloud host have the capability to run your application workload prior to migration so they can prove to you how it will perform? The infinite different host configurations are not guaranteed to perform the same way for your application. Test several hosts back to back to ensure you will get what you expect.

Finally, with all questions are answered, and you are happy with the SLA the cloud provider is offering, you can move ahead with the migration. This is usually managed by the cloud provider in conjunction with you. But how do you know the new hosted application is adhering to the agreed SLA once you go live? This is where a performance monitoring solution comes in - again don’t trust the cloud provider to deliver this, make sure you know. Monitor your application workloads post migration to identify any unforeseen performance or capacity issues and for peace of mind that all is well.

As online shopping becomes more popular, are machines, then, the future of customer service?

Yes and no. Technology certainly has the ability to improve customer experiences. Three out of four consumers believe that’s already the case today. Yet, the same study uncovered that consumers want to know that human assistance is on hand if required. One in three consumers felt that live human assistance should be offered as part of the initial online experience, with most consumers feeling it should be reserved for special cases, such as during complex transactions.

The future of customer service isn’t man vs. machine, but rather man and machine working together. This can be seen easily in the case of contact centres. As the point of entry for many customer queries or issues, contact centres represent the front line for many businesses’ customer service engine, with the potential to significantly impact the organisation’s reputation among customers. By automating many of the more generic responses, human customer service experts are left with more time to deal with more complex queries and issues – reducing frustration caused by call waiting times. Our research found that many businesses may be missing crucial areas for improvement in this area, by simply assuming the effectiveness of their customer service.  Fewer than half of respondents believe the technology needed to deliver the perfect online buying experience is available. This stands in stark contrast to findings of a previous Mitel survey in which 90% of IT decision-makers optimistically reported progress in improving customer experience through the use of technology.

Why the disconnect?

Most businesses have a multichannel relationship with customers – meaning they have a number of customer touchpoints including online, in stores, through social media and over the phone. For a consumer, these engagements are all part of broader experience, but some businesses tend to still view these engagements in isolation. As a result, customers often find themselves repeatedly prompted for the same information as they pass through different channels. Most consumers we asked (58%) believe that the technology currently deployed by brands has room for improvement when it comes to delivering the perfect online experience.

Bringing Artificial Intelligence (AI) into the customer experience can have a transformative effect on the customer’s relationship with a brand. More than aligning customer data with the right customer, AI can be used to help customer handlers to personalise and improve human-based interactions by “learning” what leads to better outcomes. As an example, an AI-enabled contact centre might intuit which kind of consumers are more likely to prefer a callback rather than waiting for an available attendant, and offer the callback option early in the process. At another level, AI contact centres could prioritise calls based on recent events (e.g., a returned product, an overcharge) to ensure that potentially dissatisfied customers receive top priority and are routed to more experienced agents.

While technology is a fantastic tool to boost the customer experience, the role of the human is far from dead. Businesses need to take customers’ individual preferences into account and find a way to blend these experiences without losing the benefits of online and offline, whether it’s convenience, selection or service. Those that are able to empower machine to human interactions by tying together communications and collaboration capabilities with technologies such as IoT, AI will be best placed to strike the balance. In a hypercompetitive world where customer experience has become just as important as the product or service delivered, corporations that build this approach into their strategies will see a direct impact on their customer retention and ultimately business growth.

So why aren’t companies already leveraging the wealth of potential available to them, and instead choosing to leave it abandoned and untapped?

Voice data is much harder to secure, deliver and analyse than ‘traditional data’. And it is harder to gather clean and representative data to build usable models from it. But companies should not be deterred; those that overcome the challenges will reap the rewards from this new frontier.

Here, there and everywhere: enterprise voice data surrounds us

In today’s connected age, the chatbot may have passed its sell-by date, but conversational artificial intelligence (interacting with computers via speech) is visibly on the rise. It is now the case that 20 percentage of Google searches are made via voice control and Alexa now has over 10,000 skills in its set. Furthermore, as the number of Internet of Things (IoT)-enabled platforms grows, so does the number of speech interfaces which can interact with them, such as smartphones and cars.

This goes beyond just speaking with machines – human-to-human interaction can also make up part of this revolution, such as customer service calls or interactions with healthcare providers. Some organisations, such as Pindrop, are already using this form of AI technology to detect fraudulent claims. This, however, is only scratching the surface of the potential of voice data. One day we may be able to mine call centre data to try and predict which customers are most likely to buy what product and even deliver real-time customer satisfaction metrics.

The road may be bumpy, but that shouldn’t stop your travels

There are a variety of challenges which come from attempting to analyse and understand voice data.

The principle issue facing those who want to get the most from the wealth of voice data their company sits upon, is ensuring access to quality data. It has been estimated that data scientists can take up to 80% of their time just acquiring and cleaning up their data.

But even once the data has been cleansed and organised, this does not necessarily mean the data is sufficiently diverse, potentially resulting in data bias. Voice data brings about a whole new spectrum of data bias. For instance, an algorithm trained with male voices from Manchester will likely have difficulty understanding a female voice from Glasgow.

Challenges like this often result in the proliferation of ‘data capitalism’, providing an advantage to already-established data companies. Apple, Google, and Facebook often have a monopoly over this complex form of data, whilst smaller organisations scramble around to find sufficient data. There is a silver lining in this evolving technology space however, as large conglomerates develop open-source software libraries. Google’s TensorFlow, and AudioSet, (which is an ontology of over 2 million individual audio files), and YouTube’s YouTube-8M (which offers 450,000 hours of video that have been classified and labelled) allow smaller players to build upon these foundations.

Regulatory roadblocks

The quality of the data we use isn’t the only challenge. Regulation can also prove to be a roadblock to accessing this precious information. Data redaction will have to meet necessary compliance regulations and ensure the secure delivery of data across the enterprise.

GDPR has now been in effect for 6 months, and whilst organisations are familiar with the requirements and impact of not being compliant, many are still in the midst of understanding and putting in place processes and policies. Increasing pressure on companies to protect personal identifiable data, with the threat of heavy fines for non-compliance, has resulted in companies focusing on Production Data management and protection. However, all organisations have a wealth of non-production data that is not as securely managed or protected as their Production Data.

One of the reasons for over-looking a company’s non-production data is that the comprehensive security measures, such as masking data in the many test, reporting and analytics systems of a large company, can come at a high price and prove very complex to implement company-wide, especially when dealing with such a complex form of data. However, working with modern masking solutions that have inbuilt data profiling capabilities that can sift through large amounts of data to detect sensitive information, will help businesses manage their data privacy processes more efficiently. High-end masking solutions will take this one step further and recommend masking algorithms in order to streamline and accelerate the process of securing data.

Extending this to voice data simply becomes the next step in any organisation’s data strategy. Organisations hoping to tap into the potential of voice data must carefully consider the ways in which they will provide secure access to this information across their business.

Start now to reap the benefits of voice data

Emerging technologies such as voice-activated devices, artificial intelligence, and machine-learning are constantly opening up new opportunities for organisations to innovate and be competitive in their industries. Early adopters will gain the advantage today if they are able to set the right foundations and framework in place to manage and secure the data fuelling these emerging technologies.

Now is the time to be building on the basics, with the right data platform and tools, to establish where data is stored company-wide, and ensuring that those who need the data have fast and easy access to it.

Leveraging voice data can provide extraordinary advantages to businesses. In order to reap the benefits, businesses must invest time and effort to ensure the right practices and procedures are in place. By building out a framework to manage and secure data using both processes and tools to do so, businesses can build a strategy today to ensure they are ready for tomorrow. 

1. A cyberattack on an automobile will kill someone.
   We’ve already seen hackers remotely kill a Jeep on the highway, disable safety features like air bags and antilock brakes, and hack into a car’s Bluetooth and OnStar features. As cars become more connected and driverless cars evolve, hackers will have more opportunities of doing real harm.
   
   
2. Bio-identifiers will outpace traditional passwords.
   Authentication using biometrics — especially facial recognition — continues to grow in popularity, and we don’t see this slowing down any time soon. Case in point: Apple has made passcodes completely optional starting with 2017’s iPhone X release, and it stuck to its decision with this year’s XS and XS Max releases. As ease of use remains a top priority for users, we’ll see traditional passwords decline in popularity.
   
   
3. Cloud-based ransomware will compromise a major corporation’s infrastructure.
   Ransomware continues to grow in sophistication. In 2019, we believe we will see it successfully compromise a major corporation’s cloud infrastructure. The results will be devastating, impacting thousands of customers and resulting in a heavy loss of profits due to missed SLAs and fines.
   
   
4. China will use cyberespionage to manipulate the market.
   China isn’t new to cyberespionage, with reports revealing their efforts cost the United States upwards of $300 billion annually. The United States reacted earlier this year by imposing a $50 billion tariff on Chinese imports. Given the economic impact of these tariffs, we expect China to leverage its cyber-spies to give itself an advantage in the growing trade wars.
   
   
5. Trump’s cell phone will be hacked.
   Yes, we’ve said this one before, but with the President using an unencrypted phone to communicate with leaders of nations, this has to be a hot target. Just imagine what the potential impact will be — not to mention what we’ll see on Twitter.
   
   
6. We’ll see a move to hold CEOs accountable for breaches.
   There are already regulations to hold people accountable (notably CISOs) for breaches. But as the pace and damage of breaches continues to quicken, we believe we’ll see these regulations begin to expand accountability to the CEO role.

Outages wreak havoc on a suffering company’s critical services, and at a time when customer expectations are skyrocketing, cause significant reputational damage which can take years to repair. In an age governed by information and the ability to access it, unfortunate incidents like those suffered by Telstra and TSB are a pertinent reminder of why businesses can ill afford their lights to go out. The ability to remain ‘always on’ is crucial.

But it’s a challenge that’s far from simple to solve. Given the widespread use of third party cloud providers, guaranteeing availability is not just a case of a company having their own resilient backup and recovery options in place. They have to be able to trust that their third party providers are following suit. After all, what would be the point of keeping everything in working order if your staff or customers still can’t access the services they need? Thousands of companies have little or no IT staff to depend on, and are almost entirely reliant on external service providers to deliver what they need to meet their agility goal.

Black clouds

However, despite pressure to maintain this level of high-speed functionality on behalf of their customers, major cloud providers too continue to struggle with regular periods of downtime and disruption when trying to maintain service for customers. These are choppy waters. The knock-on effect of such incidents can be extremely costly; our 2017 research showed the average cost of downtime globally for mission-critical applications can rise as high as £60,000 per hour. The average annual cost of downtime sits at more than £16m, which isn’t something that many companies can easily shoulder.

How can businesses mitigate against such a costly risk? The best way to ensure survival, as is true with most things in life, is through preparation. Whether a business needs to watch its own back or has responsibility to the ongoing success of others, having a plan in place to follow if an outage occurs (that can help recover and get back online quickly) is key. IDC estimates that 80% of businesses that don’t have what’s defined as a ‘disaster recovery plan’ in place will simply fail when an outage strikes, not to mention suffer an almost incalculable drop in revenue due to falling customer trust.

Planning for the worst

So what does a disaster recovery plan look like? Businesses can start their preparations by first ensuring they understand where disaster recovery sits within the context of their overarching business strategy. This comes from carrying out an impact assessment. Businesses need to take the time to identify which apps and businesses processes are critical to operating all day, every day. They need to calculate the maximum amount of downtime they can stand for each of these before they fail. Considering factors like these make it possible to calculate the ideal recovery targets for these apps and processes and appropriately identify what measures are needed to realise them.

The choice of partner to help implement what’s required for an effective disaster recovery plan is also a big decision. Factors such as the partner’s experience and the nature of the service level agreement (SLA) that they can offer are critical to bear in mind. Elements like uptime guarantees, turnaround time on service requests and enquiries, as well as fees and compensation should all be part of even the most bare-bones SLA. With the continued push on businesses to be always-on, these will only become more important considerations. Compliance is also a factor that should not be taken lightly, and any service provider worth taking seriously will be fully compliant with the legal requirements of the territories where they operate.

Location, location, location

Location too is important as part of planning. Choosing on-premises or an offsite location for data storage can make a real difference to any given company’s ability to react, with each having their own strengths and weaknesses. A 3-2-1 strategy is one of the most popular choices we see businesses make, which involves keeping three copies of data on two different types of media, with one offsite.

Offsite data centres can be often more convenient and reliable, as optimal conditions for your servers and equipment are always maintained, and tech support and security are always on hand. If future plans include significant expansion using the cloud, having access to offsite capability that can be quickly scaled up may also be important. However, having critical data physically separated in this way suddenly places greater priority on strong network access, so extra or more reliable bandwidth might be needed. We also return back to the issue of whether the offsite provider can be trusted, as we need to remember they too have their own challenges to maintain service and foster their own business agility.

Fiercer than ever

Planning for the worst by taking these factors into consideration can make a colossal difference when it comes to mitigating the threat of outages and downtime. However, it should also be noted that a disaster recovery plan alone is still not enough. Businesses also need to be regularly testing the viability and quality of their backups to be certain they are completely recoverable and dependable. The worst time to learn that the backup procedure has not been working properly is when they are the only option.

Economic and political climates remain uncertain, but what is crystal clear is that industry competition has become fiercer than ever. Agility has therefore never been more important, and that’s why it has become such a powerful competitive differentiator. But this ability to act quickly can disappear equally as fast, offering catastrophic consequences. Businesses therefore face huge pressure now to ensure their services never falter and remain highly responsive. They cannot afford to grind to a halt. Planning for the worst is imperative, recovery is key. This is how businesses achieve and maintain their need for speed.

With new technologies like Internet of Things (IoT) and data analytics, the manufacturing sector is shifting into the era of fully-networked factories where the entire production process from design, supply chain, production and quality control to distribution are all integrated and powered by Artificial Intelligence solutions that can provide real-time actionable insights 24/7. AI and advanced automation will provide a “level of accuracy and productivity beyond human ability”, according to the World Economic Forum.

Transform to thrive

There’s a lot at stake here. The main reason many firms are forced into taking action and looking for improvements is because of the tough market conditions in which they’re operating. Both mature, industrialized and emerging counterparts have experienced weak manufacturing production growth in recent years, according to the International Yearbook of Industrial Statistics 2017 produced by the United Nations Industrial Development Organization (UNIDO).

2016 saw the growth of manufacturing value added (MVA) in the world’s industrialized economies fall to under 1 percent. Significantly, even the MVA growth of China, the world’s biggest manufacturing nation, fell to 6.7 percent in 2016, down from 7.1 percent the previous year. Industry 4.0 can help by increasing digitization and interconnection of products, value chains and business models. This in turn enables business decisions, supply chains and ultimately products to be informed by real-time insights generated by data collected throughout the manufacturing process. This can bring about slicker, more efficient operations, reductions in downtime, and savings in costs.

Smart manufacturing needs new skills

This level of innovation needs context and a solid business case for manufacturers to adjust their current processes and thrive. The problem with manufacturing at present is that the industry is faced with an entirely new way of operating. Most businesses still haven’t reached industry 4.0 full potential. One of the main causes identified is the lack of skills in digital and the culture of change.
Moreover, the robot versus humans conflict is making harmony difficult to find.

Advanced automation powered by artificial intelligence is able to solve and complete complex tasks in real time. That’s all great, but the real value in all of this is people who will lead the charge in managing and interpreting the data that comes from an industry 4.0 environment.

Mastering the data chaos to deliver tangible business value

These technologies are not really “off the shelves” and require the necessary expertise to deliver the value that everyone is dreaming of. Creating data is not very difficult; companies have been doing it for years! But how do you generate real business value from this data? How do you manage the growing amount of data piling up in the various Information Technologies (IT) and Operation Technologies (OT) systems and on paper? How do you analyse data from various sources to achieve a given business outcome? And in which technology should you invest?

You can start initiatives here and there at various levels of the production line, but you will soon realise that you need to rely on a partner, or an ecosystem of partners, to guide you through your data journey. Business consultants will help you to draw the big picture and identify where the opportunities are. Focussing on business impacts, they craft the vision: what good looks like and start to pull together the various building blocks.

IoT experts and data scientists will then advise on where to find the right data and how to collect it, store it and manage it, according to the business strategy. With that in hand, it becomes easy to spot what kind of sensor to put where to collect the missing data. These experts are able to create or configure algorithms to generate real time dashboards or insights, as well as automation through artificial intelligence and machine learning.

For example, we did some work for a European car manufacturer because they were losing items in their process. The company had a complex supply chain which included tens of thousands of boxes which contained materials for production. Each of these boxes had a value of 400 euros and all in all, the company was haemorrhaging tens of millions of euros due to the boxes that got lost within the supply chain. And that was just one aspect of a much wider supply chain with other concerns they had to manage.

We came up with a solution to track one box out of ten with a sensor powered by a battery that updated the location twice a day. It provided enough information to catch the odd stray box that went missing along the way. More importantly, they were also able to triangulate the precise location of one box and in doing so, they found an entire stash of boxes that had been misdirected. As a result, they were able to reduce the number of boxes that went missing and also address the huge costs associated with it. Granted, not all problems that a business has will be so finite. Having a comprehensive vision of the full process in the time provides valuable insights and is the first step to full automation.

Strong foundations required

Many companies are trying to build cathedrals on the sand. There are business units leading construction of the buildings without engaging the IT in the initial phases of the project.

Connectivity is an essential enabler of Industry 4.0. Without reliable and secured connectivity, there’s no data. Today, there are lots of solutions available, from wireless low power consumption to very high speed wired connectivity. Tomorrow, 5G will be a standard for wireless connectivity. The right connectivity delivering the most quality bandwidth for the money is key to performance and cost effectiveness of collecting data. One technical solution might not be enough. Network integration is key.

Team effort

Orange recently partnered with Siemens to support their transformation to a next generation network (SDN NFV) to support their IoT strategy. The two companies will collaborate to provide a range of solutions around asset tracking and asset monitoring to optimize the supply chain and improve efficiencies. They will also develop digitally enhanced products which offer the opportunity to drive new business models. Underlying all of this, and indeed what should be at the heart of any successful industry 4.0 implementation are deep, actionable insights. By connecting machines and physical infrastructure to the digital world, businesses can translate the wealth of data they produce into business results.

Conclusion

Advanced analytics and digital services will help manufacturing companies increase productivity and efficiency across their business.  Installing the technology isn’t a goal in and of itself and so it will need conversations with your technology provider beforehand to define the business value, agree objectives, metrics and approaches. But just as important are the champions within the business to verify success and continually use the data to inform and improve processes.  

The network layer of the data centre has so far resisted the tide of digitisation; expect this to change in 2019 and beyond. Businesses today are travelling to where their customers are, rather than waiting for customers to come to their location. Retail establishments, restaurants, banking companies and many others are beginning to offer their customers with options such as pop-up locations at concert venues or offices inside of larger stores. To do this, they need to bring a robust network with them – something that’s only possible with wireless.

SDN implementations have already begun to transform networks from static, overprovisioned and inflexible to efficient, agile and programmable, and they’re expected to evolve and accelerate as wireless technologies such as Gigabit LTW and 5G develop. Wireless enables businesses to stay connected while retaining all the requirements of a wired network, including reliability, security, quality of service, and application continuity. By being able to open with one or two wireless connections, organisations still get reliable connectivity with day-1 deployments and they can venture out further than where only a network connection exists.

Changes in the European Channel

Over the past year, channel has become a more technical sell. With OEMs having locked down their technology, reselling hardware now delivers minimal margins for resellers. This is leading to a more innovative channel culture, with more and more partners having to really innovate with the services and solutions that they offer in order to remain competitive.

As this is coming to a head, large global channel partners are playing a more diluted role in the wider ecosystem, and this is beginning to frustrate manufacturers and customers alike. In 2019, we will see the channel continue to shift from simple value-added reselling to providing stronger front-end management consulting to help customers get more from their technology. The channel will take on a broader role, acting as more than just a point of product procurement, likely leading to significant M&A activity in the coming year.

Driverless Cars and the Maintenance Industry

With a ‘digital highway code’ already being considered for driverless cars in the UK, there’s no doubt that autonomous vehicles have the potential to revolutionise the TPM industry. As we move into 2019, we can expect driverless cars to create a more cost-efficient way of transporting hardware and automating data centre maintenance.

However, the task for all service organisations in the wave of automation is ensuring that customer relationships are managed effectively without losing the human touch completely. It’s likely we will see an increase in organisations looking to add value by diversifying their service offering and to encourage face-to-face interaction with clients outside of traditional touchpoints such as delivery and collection.

IT in the UK Public Sector 

Following the announcement of the UK’s Autumn Budget, the Institute for Fiscal Studies warned that many public services will continue to feel squeezed for some time to come. Yet IT spending in certain parts of the public sector could see a substantial increase. 

Indeed, the health sector is one area where there is a significant amount of work to be done. A recent report for the regulator NHS Improvement found that a slow uptake of technology was a key factor in hampering the ability of the NHS to answer 999 calls quickly. Digital technology to access patient records is still in its infancy, as well as a lack of auto-dispatch technology to speed up responses to cardiac arrests.

With the government’s announcement to provide £20 billion worth of extra funding for the NHS, we should start to see real change in the coming year. Following the report’s recommendations, this should be in the form of vital improvements to the NHS’s wider infrastructure, which will help staff work as efficiently and effectively as possible.