Home » Big Data » Challenges Still Face Full Internet of Things Implementation

Challenges Still Face Full Internet of Things Implementation

June 10, 2016

supplu-chain

Amid all the hype about the Internet of Things (IoT) one fact is beginning to come clear — there are still a lot of challenges to be overcome before its full implementation can be realized. “Amid huge amounts of noise and hype,” explains John Leonard (@_JohnLeonard), “many IT professionals believe that much of the technology constituting the IoT is too immature for them to dive in just yet or they cannot see any compelling case for it, although few doubt that the time will come.”[1] Leonard may be bit too pessimistic when it comes to the emergence of the IoT. Dan Zhang reports, “Smart factories are on the rise. Consulting company McKinsey and Company estimates that factories and manufacturers could be the largest benefactors of the Internet of Things, with economic impact from $1.2 to $3.7 trillion per year. These businesses stand to gain from productivity improvements, energy savings, labor efficiencies, as well as inventory optimization, equipment health, and worker health and safety improvements. It’s no wonder then that this industry sector has been one of the earliest adopters of the IoT.”[2] Nevertheless, Leonard has point when he insists challenges remain for IoT implementation.

 

Anne Aussems (@AnneAussems), Growth Initiative Lead for Alliances at Capgemini, explains, “The need for Manufacturers to transform and embrace technology disruptions brought by Industry 4.0 (a.k.a. Digital Manufacturing) is in essence multi-disciplinary. It spans across Strategy (business priorities definition), Management (evolution of talents, organization and processes), IT (big data and predictive analytics, link with legacy) and Engineering (connecting and securing shop floor machines).”[3] Aussems (and some of her colleagues) describe challenges currently facing full implementation of the Internet of Things. They are:

 

  • Where to start? The IoT can affect nearly every aspect of a business and deciding where to start can be so overwhelming it can result in analysis paralysis. Aussems explains, “The myriad ways in which IoT can support [business] sectors can be categorized into three areas: operational improvements (production line, logistics, etc.), product improvements (for improved user experience, engineering insights, etc.), and new business models (pay per use models, lease vs. sell models, etc.). … There is no straightforward answer as to which of these areas will yield the most short or mid-term benefits and should take priority.”
  • Talent. Aussem’s colleague, Jochen Bechtold (@jobec), asserts that IoT implementation and the transformation into an Industry 4.0 company requires a reassessment of employee work skills. “An IoT transformation, or more generally speaking an Industry 4.0 strategy,” he writes, “does not only imply disruptive changes regarding production and information processing, but revolutionizes daily work for employees at the same time. The five ‘people dimensions’ — leadership, new skills and talent, organization, work environment and collaboration — provides a good framework to assess impacts and identify areas which need to receive particular attention when shaping an. In a nutshell: the human dimension of ‘digital’ is at least as challenging as the technological one.”
  • Organization. Bechtold also believes that Industry 4.0 will drive companies to rethink their business models. “In order to successfully drive value,” he explains, “a disruptive approach is needed and must be mirrored in the operating model. Pioneering companies are … masters of exploration, fostering through the very design of their operating model innovativeness and agility.”
  • Data. Another of Aussems’ colleagues, Avinash Vaidya, suggests the IoT will generate so much data that term “big data” will inadequately describe it. “[The] number [is] so huge,” he writes, “that it will require careful thinking and strategizing to optimize. In my view, one of the key factors determining business success for any IoT implementation will be data strategy, as it will be a key part of any IoT related business case.”
  • Insight. Laurent Perea, another Capgemini analyst, explains, because so much data will need to be analyzed, selecting the right analytics package will be critical. “This is one of the most critical part of your project,” he writes, “running the right analytics to predict and prevent failure, spare part needs, launch relevant alerts, self-correct machine parameters, etc. The main challenge (and success factor) will be to navigate the market place and find the right vendor for your company.” For some analytic challenges, analytics bases solely on statistics will be inadequate. That’s why Enterra Solutions® has partnered with Massive Dynamics™, a computational intelligence firm, to ensure analytics performed by the Enterra Enterprise Cognitive System™ (ECS) — a system that can Sense, Think, Act, and Learn® — always leverages the right type of analysis for the problem at hand.
  • Scope. Capgemini’s Mike Dennis writes, “The balance of speed to benefits within a broader company IT architecture remains one of the biggest challenges to successful IoT implementations. Too much focus on speed, and the company comes away with islands of automation. Too much structure, and innovation suffers. The leaders adopting these capabilities set the guidelines for the innovation: focus on business benefits, alignment on architecture, teams driven to specific outcomes, willingness to cannibalize the existing business. This is where the agile approach is most useful. First setting the context for the initiative: How do I adjust my production to meet rapidly changing demand? How do I keep my people safe and connected in real time? How do I manage a complex supply chain to meet my changing business? Then establishing small, nimble teams to drive outcomes in their areas in weeks, not years.” At Enterra®, we normally recommend that clients start with pilot project to ensure that objectives are being met and to permit changes to be made before scaling the project up.

Standardization, interoperability, privacy, and security are all concerns that have yet to adequately addressed. Leonard explains:

“Interoperability [is] a common problem. It can be difficult to get everything working together in the way it should. … But top of the list [is] concerns over security. … It is characteristic of a technology market in its infancy that businesses rush to get something out there and that security tends to be an afterthought rather than an intrinsic part of the development process — mobile applications being a prime example. With something as all-encompassing as the IoT this would be a very serious mistake. Privacy is another issue of concern. The IoT is all about making technology invisible. Rather than having to type instructions on a keyboard, the idea is that technology will respond to our needs naturally, without us really noticing. This sounds fantastic, but essentially it makes us all passive rather than active participants in the generation and dissemination of data. Concern about internet privacy is rising, but at least we know when we’re on the internet; we will not necessarily know when we’re on the IoT. We will not know what the information will ultimately be used for — and should bear in mind that smart does not necessarily mean benevolent.”

Time and again security (and its close sibling — privacy) rise to the top of concerns about IoT implementation. Ronnie Garrett (@GarrettncRonnie) explains, “IoT has four major building blocks, according a white paper titled ‘IoT Platforms: The Central Backbone for the Internet of Things.’ These include: Hardware (physical devices with IoT installed); communication (where the data are transported); the software backend (where data are managed); and applications (where data are turned into value). ‘Security is a must-have element for all of these building blocks,’ states the white paper sponsored by IoT Analytics, a Hamburg, Germany-based provider of market insights for the IoT.” All of these problems are being addressed, but work remains to be done. Fortunately, I don’t believe getting it right will prove to be a Sisyphean task.

 

Footnotes
[1] John Leonard, “Research: The Internet of Things – hope, hype or hazard?Computing, 12 May 2016.
[2] Dan Zhang, “Internet of Things 2016 Trends: Leveraging Actionable Insights,” Dataversity, 28 January 2016.
[3] Anne Aussems, “The 9 Challenges of an Industrial IoT Implementation (Part 1),” “(Part 2),” Information Management, 16 March and 25 April 2016.
[4] Ronnie Garrett, “Insecurity in IoT,” Supply & Demand Chain Executive, 26 May 2016.

Related Posts: