The "Digital DNA" of IIoT: a systematic approach to create value and efficiency
When it comes to IIoT, it has a completely different DNA, compared with what we all have experienced with the IoT associated with our daily life as a consumer, sometimes an excessive consumer. The core of consumer-driven IoT is the volume of traffic and human greediness. Just to think how easily and how often we can be lured to buy stuff we probably never use, just out of impulsiveness and thanks to the convenience of buying.
The DNA for IIoT, however, focuses on value creation and efficiency improvement. The part of Siemens business that I passionately work for is known as "Siemens Advanta" in the market. What we do is to help industrial customers orchestrate and implement digital transformation.?
In order to do so, we have a concept called "Digital DNA". For a manufacturing company, there're 3 stages to embody such Digital DNA. As foundation, a manufacturing company must have its own industry know-how, be it a manufacturing process or a product's technical design. To be efficient in what you produce, you should have lean manufacturing and lean management in place.
Stage 2 features the convergence of IT and OT. The pyramid structure of IT doesn’t give you much flexibility, how to modularize and upgrade on top of your legacy infrastructure is a more feasible and economically viable. The real power of IIoT is to be compounded with your operation techstack, and this is how you create impactful use cases. Take the example of Digital Twin: the combination of models in the physical world and data in the virtual world. The real difficulty here is how to combine both worlds and how to do cross-references between simulations and AI in a meaningful way. The convergence of IT and OT creates and sustains such knowledge, which can be accessible and automized to create value and efficiency.
To make the IO and OT converge, we need the convergence of innovation capabilities and management capabilities. On an individual level, this implies a competency model in the shape of pi constant. The ideal workforce should be skillful in both business domains (e.g. a particular functional knowledge or business process know-how) and digital techniques (e.g. programming skills or data modelling), and both sets of skills are converged with an overarching layer of leadership skills and growth mindset. A client once told me about his company's struggle of finding a CDO, Chief Digital Officer, instead of a CIO, and the difference is that CDO must know the business. Joking aside, this reality shows the demand for talent who knows both how to innovate in the tech domain and how to manage a business.
Stage 3 is exactly the theme, which I discussed as a panelist during this year's Academy of Management Annual Conference "The Impact of IIoT on Ecosystems" together with Prof. Erkko Autio, Prof. Jannis Kallinikos, Prof. Frank Piller, Peter Shearman, Massimo Russo, Dimitri Petrik and Selina Cao. To build up a strong ecosystem, all partners should be orientated on one set of core principles and working methodologies, and advocate their joint beliefs. We should strive for sustainable growth with clear environmental, social and governance responsibilities.
We call it DNA, as this is a living mechanism and continuous evolving progress. This concept has been developed and validated through not only Siemens's own digital transformation journey as a practitioner, but also the proven record of Siemens customers in various industries. ?
So how does this concept work in reality? We need a systematic approach to orchestrate. Let me introduce our framework for digital transformation strategy.
领英推荐
As all strategic frameworks, the starting point is to create sustainable core competitiveness, and in this case, for digital transformation. There are two directional levers: one is towards internal, i.e. to harness internal capabilities to improve efficiency, and the other one is towards the external market to grow business. Such competitive advantages should be extended and plugged into an ecosystem to drive further growth.
"Strategy in digital age" differentiates from "strategy in industrial age" in both scope and approach:
The core of this strategy framework is to break down the silos among the 3 value chains centered on production, which is the core activity of all manufacturing companies. The 3 value chains, - product lifecycle, asset operations and customer value fulfillment, imply not only the flow of physical goods but also data flow. How to connect the dots among these value chains? In some companies, such communication is done by people calling each other, whereas more advanced companies have automized data flow between humans and machines or connected devices.
If we reflect further, among these 3 value chains there is the most valuable asset for a company's operation: people's knowledge. How supply chain management data correlate to product design data depends on human's knowledge. That's why industry know-how is the foundation of Digital DNA.
How to "copy" such human knowledge to machines? How to create more values with faster communications made by machines to machines? And how to create new insights with machine learning so that machines can generate more learning themselves, and execute the tasks on behalf of humans? That's why we need the convergence of IT and OT in Stage 2 of Digital DNA. With the convergence of innovation and management capabilities, you can address external market, for example, with intelligent products (market entry), generating new revenue streams and creating new business models with data, and leveraging digital marketing for optimal coverage.
As a focused technology company, Siemens has a comprehensive offering such as data analytics and AI, connectivity and edge, and cybersecurity. With the Digital DNA and a systematic approach for digital transformation, we aim to create value and efficiency for a better world. ?