Career Path

Five ways to jump the skills gap in IoT

Written by Noah Bethilda

Despite Gartner branding Internet of Things as the stand-out among digital transformation technologies, the research group also found just 21% of large firms had a fully-deployed IoT-based solution in 2017. IoT connectivity forms the bedrock of a range of emerging technologies, including machine learning, robotics, 3D printing, AI, VR/AR and automation. Yet the immaturity of the IoT industry is holding back adoption, leaving enterprises unsure of how to make use of its potential benefits. A major factor is the shortage of relevant skills.

Inmarsat found 77% of IT decision-makers from large organisations felt their companies lacked the required skills for IoT deployment in 2017. Just 7% of respondents believed they had the requisite IoT skills force at management level. Almost half (47%) of IT leaders said their firm had no IoT skills whatsoever. Major research corroborates this sense of pessimism.

Studies from The Economist and others have shown the growth in IoT adoption and value creation in the past 4 years is not happening as quickly as IT leaders expected, whereas Gartner has identified a persistent skills shortage for the past five years at least.

When it comes to the IoT skills bottleneck, companies are still erring on the side of watching and waiting rather than adopting. Data management, network security, and deployment management capability are three of the biggest concerns. Respondents to Inmarsat’s research cited data security, data science and technical support as IoT skills felt to be particularly lacking.

In the face of a stagnant IoT skills market, strategies other than waiting for change are a necessity.


Accept the state of play and identify specific skills needed

Even the largest organisations are forced to recognise that the newness of IoT technology is a significant factor in the paucity of senior management and deployment capabilities among the workforce. Yet it is important to pin down the precise skills needed in order to maximise ROI on IoT spending.

Canonical research points out the advantages of a broader perspective on professionals’ technological proficiency to uncover trainable raw talent. One expertise pool to search in is the cloud computing market; IoT deployment strategies may be a recent industry development, but cloud computing is a much more established field. Gartner advises “Seeing top talent as a customer, and employment by the IT team as a brand promise fulfilled” meaning business leaders best keep an open mind when recruiting IoT staff.

All the same, budgets for IoT employment need not hit the roof. Golnar Poya, MD of Accenture Technology and Media Strategy advises a studied approach to skill selection, bearing in mind the core Internet of Things principles of connect, compute and communicate. Skills in analytics of ML/AI, design (for instance Autocad), data integration and cleansing may be all a company needs for a viable network strategy and its maintenance. Poya said: “Allocating the hard-to-find Data Scientists to become responsible for the whole data value chain is an overkill.”

Canonical research found that 75% of IT leaders considered data analytics to be the most essential skill for an IoT expert, with 71% saying software engineering is absolutely crucial. Cloud software development, embedded electronics and IT security are also beneficial skills in IoT occupations – and much easier to come by than IoT proper.


Automate where possible and bolster cyber security resources

A major cause of hesitation over IoT deployment surrounds the network vulnerability of variously insecure devices connected to sensitive data stores. McAfee’s Chief Scientist Raj Samani has warned companies to learn the lessons of malware from 2017, particularly the rapid infections of WannaCry and NotPetya. IoT

With security breaches having increased by 27% since 2016 (Accenture) and the emergence of ransomware-as-a-service, companies must ensure their security hygiene strategy is up to date before taking on IoT connectivity. Already, the average annual spend on cybersecurity is $11.7m, an increase of 23% compared with last year, according to a 2017 study by Accenture on and Ponemon Institute.

A useful strategy for amping up cyber defences is to analyse whether current business strategy is in line with the ‘simplicity’ principle of the Agile Manifesto, namely, “the essential art of maximizing the amount of work not done”. Are IT technicians spending excessive time on troubleshooting when automation is a possibility? A few strategic investments in modern cybersecurity technologies based on machine learning could streamline IT problem detection and resolution much better than a human brain.


Invest in AI

Parit Patel, Head of Solution Architecture UK at IPsoft, sums up general feeling in saying: “With the help of AI, businesses can bridge the IoT skills gap and resources required to make sense of the data collected from IoT devices and act immediately on the insights that are uncovered.” Patel has also highlighted the critical role machine cognition can play in IoT for customer facing processes, emphasising the need for improved chatbot algorithms to simulate natural conversation in B2C and within organisations themselves.

Gartner research also points to deep learning as the “most promising” AI tech to cope with the network vulnerability, meaning it could well quell cyber security fears among potential IoT adopters.


With its ability to prioritize security alerts, artificial intelligence for IT operations (AIOps) is becoming increasingly better appreciated as the lynchpin of efficient IT infrastructure.

“AIOps takes IT operations analytics (ITOA) to the next level by automatically applying insights to ensure high performing IT environments are proactively making decisions that ultimately improve the health of the business,” said Rick Fitz, senior vice president of Splunk. Enterprises could stand to gain from AIOps’ ability to detect patterns and baseline normal operations by dynamically adapting thresholds.

In addition to naming AI as a “critical” technology for IoT security, Peter Sondergaard, EVP of Gartner, has warned that the wider job market will not spontaneously produce IoT-skilled candidates. Instead, it will be down to IT business leaders to make smart investment decisions. “Prioritize your investment in AI beginning at the top with AI capable leaders,” Sondergaard told delegates at Gartner Symposium/ITxpo 2017 in Orlando.


Lobby the government for better investment in education and infrastructure to feed the talent pool

If politics is of no interest, investment and profitability certainly will be. With companies increasingly aware of the need for GDPR compliance and the tech allowance ring-fenced in the Autumn Budget, CIOs could do well to keep their ears to the walls of Westminster and beyond.

Businesses need to be aware of the financial implications of regulations from Parliament, including proposed drone regulation to be published in spring 2019. In order to plan spending to meet the demands of IoT proliferation, firms must bear in mind the changing government stance on these issues.IoT

While AI is set to receive a cash injection of £75m as outlined in the Autumn Budget, cyber security was granted no such subsidy. Philip Hammond also announced the programme of T-levels to be introduced into skills, with the aim of equipping future workers with technological abilities. Moreover, better policy and infrastructure will become a necessity over the next decade as AI automation begins to replace one in five British workers by 2030.

With Brexit still on the drawing board, the time is ripe for targeted and consistent lobbying of any and all government channels for more urgent measures.


Develop your own talent pool, be it via social networks, educational institutes, staff training

While the HR department is supposed to manage talent acquisition so the CIO doesn’t have to, it is the IT leaders who understand the needs of their department better than any others. With that in mind, a view to tapping academic talent pools by building relationships with educational institutions can bear fruit for years to come.

With competitive salaries offered in the US and Asia, CIO’s need a proactive rather than reactive approach to talent. In order to remain competitive in a global market and convince candidates skilled in IoT to choose your workplace over San Francisco or New York, which means it’s as important to glean insights from external workforce data as well as analysing internal workforce information.IoT

Could your company run an insight programme, workshops or a hackathon? Gartner recommends doubling the volume of communication made with universities and increase in-person participation in academic events and seminars significantly, year on year. In light of a slight drop in outsourced talent since the Brexit referendum, British tech professionals are in demand on an unprecedented scale. Share your company’s innovation, processes and insights through guest speaking, offering micro credentials and apprenticeships where possible.

Inmarsat research of energy companies found 88% expect to deploy IoT technologies by 2019, yet 43% believed their organisation lacked the skills for its delivery and half reported a deficit in technical support. When it comes to upskilling on board staff, Poya, MD at Accenture advises creation of mandatory organization-wide training on business intelligence and analytics. “Training should not be focused on IT and technical staff, rather on users that ultimately will be using the insights to make real-time decisions and take action,” she said.

If resources are limited, a thorough briefing of key HR figures could at least ensure that job adverts on LinkedIn or other hiring platforms contain the correct keywords so the talent can find you.

The post Five ways to jump the skills gap in IoT appeared first on Computer Business Review.

Source link