Slicing and dicing Internet of Things skills predictions

SUMMARY:

The Internet of Things has provoked a frenzy of job skills posts. I combed through them for common themes – and maybe even a useful insight.

master-skill-experienceSmart people have suggested the Internet of Things is about to take a plunge through the trough of disillusionment. If that’s true, don’t tell the IoT skills prognosticators. A rainy London morning is the perfect time to scour through reams of IoT skills pieces, and see if there is meat on this particular career bone.

Most IoT skills pieces take the vantage point of a hands-on practitioner – usually a developer. With that caveat in mind, here’s what I learned.

Citing data from Wanted Analytics, CBRonline published the five most in-demand IoT skills. But first – which jobs are on the IoT most wanted list? As per Wanted Analytics, those are:

  • systems software developers (215% growth in the past year)
  • information security analysts (113% growth), and
  • computer systems engineers (110% growth)

That translates into these top five skills:

  • Computer programming – a no brainer given that software is the main driver of IoT devices. Developers can follow several IoT pursuits: application development, database development, and web development.
  • User interface design (UI) – not an easy skill set when you consider the proliferation of IoT devices and wearables. Job titles could include: interaction designer (XD), UI designer, user experience (UX) designer, visual designer, product designer and digital product designer.
  • Business Intelligence – IoT data streams will push technical BI folks to have a wide range of know-how including Hadoop, NoSQL, and, my add: Apache Spark and real-time analytics.
  • Hardware engineering – specifically focused on connectivity/communications tools such as Wi-Fi, Bluetooh, and Near Field Communications (NFC).
  • Artificial Intelligence expertise – many of these IoT systems will need to run by themselves, or with limited human intervention.

This piece on Six Skills Needed for the Internet of Things starts by quoting one of those useless growth stats, projecting a needed increase from the 300,000 developers working with IoT today to the supposed 4.5 million needed by 2020. This list completely drops artificial intelligence skills (whoops), but adds in the number one slot security and data analytics. Mobile/remote development and networking standards (as in wireless, RFID, etc) are also added.

Mobile development makes sense given how many IoT apps will be powered or controlled by our smart phones. security and data analytics skills are spelled out as:

vulnerability assessment, public key infrastructure (PKI) security, ethical hacking, wireless network security, knowledge of data ethics and privacy policy, securely managing data, and cybersecurity analysis.

This list on Hot IT Skills in the Internet of Things reads like a merge of the prior two, with BI, security, and UI/UX winning the top spots. 4 IoT Skills IT Pros Need takes a different tack, extrapolating key skills from research in IoT by Accenture, which has coined the wanky phrase “Living Services” to describe the need for IoT services that adapt based on new inputs. With that in mind, the four skills are:

  • We’re all data scientists – Why? “If we’re designing for data first, it means that whether you are a software engineer designing an interface for a new IoT product, a network engineer designing how a product will interact with your system, or a UX engineer trying to help a human interact, at heart you are a data scientist. Your job is to help your customers interact as seamlessly as possible with the data driving the product.”
  • Developing AI is the next hard-to-find talent – The Yes, early IoT products were mostly rules-driven. As the author notes, it doesn’t take special AI to turn down the air conditioning if no one is home. But for more complex use cases, AI skills will be needed. But IFTTT is only going to get us so far. For more complicated decisions in IoT, AI will be needed. For now, AI has been seen as the special province of research on supercomputers like Watson, or something we use in gaming. But if it enters the retail space, AI experts will suddenly be in wide demand.
  • UX is king – Another big Accenture finding, and it makes sense. The days of consumers being willing to pore over a 100 page VCR manual are gone forever.
  • Programming gesture technology – consumers will expect to operate their devices with voice and movements. That’s not part of most developers’ skill sets now.

Meanwhile, Ready for the Internet of Things – Five Skills You’ll Need took a less technical view of IoT skills. A key point of emphasis: “softer” collaborative skills that are fundamental to so-called innovators. Five key innovation mega-skills are cited, pulled from a two year study from the National Science Foundation (NSF). The NSF identified twenty essential innovation skills, five of which encompass the entire “innovation process”:

  • Associative Thinker – Joins or connects ideas and facts from different experiences. Transposes observations across unrelated domains.
  • Collaborator – Brings together people with a diversity of knowledge to solve complex problems. Actively integrates knowledge or strategies of others though they may differ from their own.
  • Communicator – Explains ideas or concepts effectively through multiple means including writing, speaking, gestures, pictures, diagrams or stories.
  • Knowledgeable – Possesses expertise that is both broad and deep. Is skilled in independent learning.
  • Persistent – Continues to do something although it is hard, and other people want your actions to stop. Continues beyond the usual or expected effort.

A good list – though hardly IoT-specific. Author Sarah Miller Caldicott then applies this to an IoT skills transition. She recommends:

Get comfortable seeking and recognizing patterns – “Pattern recognition represents a core part of the ‘associative thinking’ competency the NSF identified.” Encouraging factoid for disgruntled liberal arts graduates: Dhiraj Rajaram, CEO and founder of Mu Sigma, a big data services firm, aggressively hires liberal arts grads due to their pattern-seeking ability: “His company values people who are ‘insanely curious’ about why things operate as they do.

Add new stackable credentials to your resume – I almost choked on the phrase “stackable credentials,” but Caldicott is simply advocating continuing education, such as this Internet of Things course from Cloudera.

Learn a coding language or an analytics platform – A proponent of coding literacy, Caldicott points to the many programs that have trained millions of users via online or open sources communities: “If Michael Bloomberg – the former mayor of New York City – can learn to code, you can too.”

Create experiential learning centers in your organization – “The innovation-forward skills the NSF has identified means that training employees must be melded into your daily work environment in a hands-on way. GE is already revamping its leadership training programs at Crotonville as it looks to the digital industrial revolution, making learning more experience-based and less classroom-focused.

My take

None of these articles are what I’d call brilliant – perhaps you’ve seen a better one I missed – but together they form a composite of how tech/biz professionals should approach IoT. Security is clearly a given – along with an expanded definition of UI to include a range of wearables and devices yet to emerge. UX is a big key to market adoption; if you’re interested in how data science and UX intersect, you may want to see my report on my day with Infor’s data science team at MIT.

The “we are all data scientists” mantra runs the risk of diminishing the need for deep experts in statistical analysis and industry process automation. I don’t believe commercial tools can make such “masters” of predictive techniques and industry nuances irrelevant. That said, I do like the notion we all have another bar of data competency to reach for, if we want to generate business results from data – or at least useful decisions.

AI skills stand out. This pushes us beyond analytics into how machines can learn and act autonomously – as terrifying and ethically problematic as some of those use cases might become.

I’m not sure you can make a living as an IoT ethics expert, but those willing to research privacy and security tradeoffs will be valuable to companies – and not just in avoiding Volkswagen-type epic fails. Adoption won’t just about UX/ease of use; it will also be about the IoT machines that win our trust as we invite them into our homes or put them on our mission-critical shop floors.

Completely automated systems sound great until they lock you out of your car or leave you unable to interrupt a broken process. The best IoT designers will know how to incorporate the right human elements and fail safes into these products/services. There’s more to say, but this lays a foundation. Let’s hear your thoughts.

Disclosure: Infor is a diginomica premier partner as of this writing

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