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Opinion The 9 Challenges of an Industrial IoT Implementation (Part 1)

  • Anne Aussems
  • March 16 2016, 6:30am EDT

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).

In this series, experts across the Capgemini group go over the key challenges in those different areas and make actionable recommendations.

1.Where to start? (by Anne Aussems, Growth Initiative Lead, Alliances)

The myriad ways in which IoT can support the 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).

While industry reports provide some guidance, there is no straightforward answer as to which of these areas will yield the most short or mid-term benefits and should take priority. To name just a couple, Consultancy McKinsey, in its 2015 Report, Unlocking the potential of the Internet of Things, suggests that manufacturers stand to gain the most in making industrial processes more efficient. On the other hand, research firm Forrester, in its August 2015 paper The Internet of Things Has the Potential to Connect and Transform Businesses, counsels companies not to focus too heavily on potential efficiency gains from IoT, lest they “miss out on the potential of IoT to transform business models”.

While there is no one size fits all, the answer to the question of where to start can be found by each company through a diligent and coordinated approach. The first step is to align all stakeholders in the organization around a data-driven process to prioritize opportunities. Then identify all opportunities—whether they apply to operations, supply chain, product enhancements, engineering, etc.—, make a short list and perform a high-level financial evaluation of each opportunity. Coming up with realistic, data-supported hypotheses to use in those evaluations will be the main challenge. Some considerations to keep in mind in this process can be found here.

2.Talent (by Jochen Bechtold, Industry 4.0 Consulting Services, Germany)

An IoT transformation, or more generally speaking an Industry 4.0 strategy, 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.

On an employee level, Industry 4.0 implies that new skills and talent are acquired and developed. In some areas, the definition of entirely new job profiles is required. Hence recruiting, enabling and retaining new talents is one of the top priorities on the agenda of HR departments in an Industry 4.0 world. For example, the “Industrial data engineer” is a new role. He analyzes heterogeneous data sources while creating value-added algorithms driven by the business context. Alongside recruitment of new talents, a training strategy is also required to re-train or up-skill other employees. The “age gap” must be bridged by creating interdisciplinary competency teams to avoid competency and know-how loss in the company.

At the same time, Leaders 4.0 will become the game changers of tomorrow as they navigate the organization through the Fourth Industrial Revolution by embracing these disruptive changes and encouraging talent to do the same. They are more than just digital leaders as they combine entrepreneurial, agile, strategic and visionary roles. They are actively contributing to an organization that provides the right platforms for their leadership style and talents to flourish.

Find more insight from our German Industry 4.0 experts here.

3.Organization (by Jochen Bechtold, Industry 4.0 Consulting Services, Germany)

A firm’s operating model can be defined as the comprehensive model for how it creates (or acquires) and aligns the capabilities needed to deliver upon its strategic objectives. In that sense, today’s organizations are doing mostly one thing: improving upon the existing. Organizational design, processes, performance management mechanisms, information systems – all are focused on squeezing a maximum of efficiency out of the business, to master exploitation. However, in order to successfully drive value, a disruptive approach is needed and must be mirrored in the operating model. Pioneering companies are thus equally masters of exploration, fostering through the very design of their operating model innovativeness and agility.

So what does such an agile operating model look like? As always, there is no one-size-fits-all solution. The general paradigm that we may apply here is clearly the “startup” one, as in the words of Eric Ries “a startup is a human institution designed to create a new product or service under conditions of extreme uncertainty” – which is definitely what companies face today when it comes to the uncharted possibilities and challenges of the Digital Transformation.

In part 2 of this bog, our experts will go over challenges around project scoping, data strategy and how to turn data into insights.

In part 3, they will dive into security and IoT standards challenges.

(About the author: Anne Aussems is Growth Initiative Lead, Alliances, at Capgemini. This post originally appeared on her Capgemini blog, which can be viewed here).

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