Industrial IoT: A Solution Looking For A Problem

Lionel Grealou Digital Manufacturing 3 minutes

It does not matter what technology is used in the background, whether it is called machine to machine (M2M), Internet of Things (IoT), mobility, cloud, big data, or whatever other technical jargon. The IoT is about sensors (which capture data) and devices (which collate, aggregate, interpret, report, share data).

The Industrial IoT (IIoT) is the use of IoT technologies in manufacturing (…)

M2M is about connecting devices… while IoT is about generating data and performing specific functions with that data, managing series of events, leveraging modern IT tools, languages, platforms, standards, etc.

It’s all about the data. Really, it’s all about the end customer.

While they definitely overlap, IoT and IIoT have different applications and implications: in brief, IoT relates to products, consumer goods, user experience, new user services, new consuming behaviours – while IIoT relates to value chain, operational efficiency, manufacturing productivity, economies of scale and scope, new business models, new commercial services, new skills and jobs, new organisational culture, etc.

  • Value chain: increasing value to customers and consumers, new capabilities and solutions to improve people’s jobs and life, creating new markets to complement existing ones or disrupt them with better ones – to create new competitive advantage.
  • Productivity: doing more with the same or with less – to improve profitability and the ability to deliver against demand.
  • Efficiency: reduce unit cost of products and services to increase margins or reduce price to customers – to make a return on investment and maintain competitive advantage.
  • Economies of scale: share parts, components and services to become leaner, improve quality, reduce risk, etc.
  • Economies of scope: reuse and learn across functions, industries, etc. to become more agile, flexible, as well as more integrated.
  • New business models: sell complementary products or services, enter or create new markets, new commercial models, etc.
  • New commercial services: focus more on the customers, and the consumers (e.g. the customers of an organisation’s customers, leveraging new customer touch points and experiences, shifting from conventional models to disruptive products and services, bridging old and old economies).
  • New skills and jobs: focus on value added activities, learn and develop new technology solutions, electronics and embedded system solutions, big data scientist to leverage new products and services.

Often, IoT experts focus on enabling technologies, trying to find requirements or problems for “IT solutions” to fix… while actually, they should remove from their vocabulary this generic jargon which contributes to blur the discussions.

Problem resolution, improved or optimised solutions, innovative products and services are what needs to be discussed.

The technology or data used does not really matter, as soon as new ‘intelligence‘ is derived or created from it, and then new solutions, products or services. Sensors are (or will be soon) everywhere.

Data is the new oil.

Data flows from these sensors and can be used for new purposes and applications. The data collected might be available in large quantity and used for interpretation of existing or new requirements and solutions, derived from existing or new business models. The foundations for IIoT exist or can be set from existing IoT sensors, devices and platforms. Similar questions will emerge from IIoT solutions, compared to IoT, such as:

  • Who owns the data from the industry or business functions?
  • What will be done with the data in terms of business innovation in the industry?
  • What will be the infrastructure and who will pay for it?
  • How much openness will be required or allowed, and what will differ from one industry to another in terms of data security?
  • Where are the ‘value pockets‘ within the industrial eco-system, and how are these ‘moving‘ in time? What is driving this?

IoT connects the digital world with the physical world. What matters is that it adds value in terms of product, technology innovation and business model innovation (incl. service innovation). 

Software eats the world today, what will be next?

What are your thoughts?

This post was originally published on LinkedIn on 26 March 2016.

About the Author

Lionel Grealou


Lionel Grealou, a.k.a. Lio, helps original equipment manufacturers transform, develop, and implement their digital transformation strategies—driving organizational change, data continuity and process improvement, managing the lifecycle of things across enterprise platforms, from PDM to PLM, ERP, MES, PIM, CRM, or BIM. Beyond consulting roles, Lio held leadership positions across industries, with both established OEMs and start-ups, covering the extended innovation lifecycle scope, from research and development, to engineering, discrete and process manufacturing, procurement, finance, supply chain, operations, program management, quality, compliance, marketing, etc.

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