You support your customers in creating competitive advantages based on data. How did you come to this? What interests you about it?
I am interested in the use of data as a driver of innovation. I believe that smart data - the clever use of data for commercial purposes - is one of the most effective ways of our time to drive innovation. In my opinion, this makes smart data a clear competitive advantage. In recent years, we have seen a lot of hype surrounding terms such as artificial intelligence, machine learning and deep learning. Before that, it was the hype surrounding Big Data.
However, I believe that, beyond the exaggerated expectations, these technologies will lead to differentiation from the competition if companies know how to use them appropriately. And the smart use and commercialization of data plays a very important - decisive and incisive - role in this.
"The time for the use of AI has definitely come."
You just spoke of hype in connection with AI, deep learning and the like. How does this fit in with your diagnosis that these technologies are the new drivers of differentiation and growth?
What I mean is the so-called hype curve. Typically, enthusiasm for a new technology goes through various phases of a cycle - sometimes with periods of great euphoria and exaggerated expectations - until you actually get to value-adding solutions that establish themselves on the market.
When it comes to AI, interest and attention have steadily increased over the last ten years and have been particularly pronounced recently. Think, for example, of the discussion surrounding the ever-growing GPT language models.
So, in your estimation, we are now at the point where the use of AI can actually be a competitive advantage?
Yes, we are now at that point. The time for the use of AI has definitely come. We should just quickly get over the exaggerated expectations of the current hype and move swiftly on to practical, commercial applications.
Why is now the time to use AI?
In the more than 70-year history of AI development, there have always been phases in which commercial exploitation and even AI research came to a virtual standstill - the so-called AI winters.
However, the last 25 years have not only seen the successful development of new mathematical methods for AI. In the meantime, technologies associated with the use of AI have also become widely available, for example in networked products. Just think of the ubiquitous smartphone.
You mean the proliferation of the web and the ability to collect and analyze large amounts of data?
Exactly. The harsh consequence of this is that these information technologies are currently transforming competition between companies in a very fundamental and radical way.
"This sets a creative dynamic in motion that leads to new ideas."
You spoke earlier about data-based innovations. What do you have in mind here?
When I talk about data-based innovations, I think of smart data innovations. What I mean by this is, first of all, the smart use of data for business benefit - generating insights from data and turning them into marketable added value. In addition, it is the special combination of data, advanced analytics and intelligence that generates a unique customer advantage.
This means the automated or semi-automated evaluation of data - to a far greater extent than has previously been the case in business intelligence. This allows a company to gain completely new insights into its business and the use of its products, but also to create forecasts or generate recommendations.
This enables companies to gain long-term competitive advantages. The way in which organizations harness and use data is increasingly becoming a decisive factor in their future viability. I don't think this has really been fully understood by companies yet.
What do you mean by that?
Yes. In my opinion, the insights that can be generated from the evaluation of data can be transformed into marketable added value in two areas in particular.
Firstly, in product development: existing products can be enriched with additional functionality using the automated evaluation of data. This further development means that products - also known as smart products - can be aligned more closely with customer needs than comparable offerings to date. This is a clear competitive advantage.
On the other hand, in the development of business models: Smart data makes completely new, innovative business models possible in the first place. Think of the big tech companies Alphabet (Google) and Meta (Facebook), for example. Their business models are largely based on extraordinarily advanced analyses of data.
In these two areas, product development and the development of new business models - including digital business models - I see the great potential of smart data for long-term competitive advantages. But it also poses a threat to existing competitive advantages.
You mean that nothing is stopping competitors from using data to their advantage? That would quickly eliminate my competitive advantage.
Yes, exactly. But that doesn't necessarily have to happen if you choose the right path and see your existing products as the starting point for your smart data strategy.
So you see the potential of smart data primarily in the further development of the existing product portfolio.
Yes, I would certainly start here. When expanding a product with smart data, new business ideas usually emerge quite quickly - at least that's my experience - because you think more about your own positioning when you take the path of smart data innovations.
The use of smart data sets a dynamic in business field development in motion, so to speak.
Yes, if the approach is pursued consistently. The company enters into a process in which it thinks intensively about its value creation: it examines its entire value creation process and changes and adapts it with regard to the use of data for business success. This sets a creative dynamic in motion that leads to new ideas and developments.
"The company was able to establish its technological leadership with the help of smart data."
And such a dynamic is particularly productive if you choose the right product: one that I can develop further on the basis of smart data and that is central to my value creation.
Yes, exactly.
Could you explain that?
Take industrial 3D printing as an example, the technology of which I helped to create. As you know, 3D printing is a transformation technology that is now used in a large number of industrial segments. It is an essential part of the fourth industrial revolution.
I worked for one of the first manufacturers of 3D printing machines in the pioneering phase. By using data and advanced analytics, I was able to gain valuable insights into the underlying 3D printing process. This then enabled me to control this core process much more precisely and detect any errors at an early stage.
In concrete terms, I developed software that implements what is known as "closed-loop process management" for the first time - in other words, process management with an integrated feedback mechanism. This software monitors the 3D printing process and controls it adaptively and based on data using an analytics engine.
This was an important innovation at the time. It enabled us to significantly improve the key performance indicators of our machines: Process stability, build speed, defect rate and quality of the printed parts. This in turn resulted in greater cost efficiency - so obviously all improvements with clear added value for our customers.
Smart Data was the innovation driver here, the key factor that took our technology to the next level. We can even say that Smart Data was a decisive factor in the breakthrough of our elementary 3D printing process and helped to establish the company's technological leadership.
And this example can be transferred to other industrial companies.
For sure. This can be realized at a wide variety of mechanical engineering companies and in manufacturing companies. Wherever the use of sensor technology is possible and data can be collected from technical processes, for example. Also where networkable machines or products are used by customers. The same applies to general business processes, which today can be recorded more and more via process data. It makes sense to think about smart data applications everywhere in order to generate added value for the customer.
"In order to monetize data, it is necessary to build an ecosystem for data-based innovations."
What advice would you give to a company that wants to use smart data?
So, my clear recommendation is: build an ecosystem for smart data innovations step by step. Companies often already have an idea of the role artificial intelligence could play in the value creation process. Initial use cases may already exist or there may be areas that are already using data-based applications, for example via external services.
It is then important to quickly move on from such initial attempts and gain a foothold with relevant, commercial applications - with the declared aim of systematically using data for innovation and value creation.
How would you proceed with the development of such an application?
In my experience, the following aspects need to be taken into account during development:
Firstly, when it comes to innovations, focus strictly on the value for your customers. So start where you expect the greatest impact for the customer - where by "value" I mean a relevant benefit for the customer that is aligned with your own business goals.
Secondly, it is more important to gain effective insights from the data than to first collect a huge amount of data, compile it and try to master it. It's more about quickly building up the necessary domain expertise.
Thirdly, the quality of the data forms the foundation for your relevant, commercial application. So build an acquisition pipeline for high-quality data.
Fourthly, create transparency about the application and performance limits of your application. To build positive momentum for success, it is advisable to also communicate the limits: where your innovation can and cannot be used.
Fifthly, time-to-value is essential for the success of your innovation. Speed is crucial. On the one hand, the speed with which you update your insights. On the other hand, the speed with which you make the necessary course corrections during innovation development in order to generate real customer benefits and generate value for your company.
But as I said, in my experience, this is best implemented within the framework of an appropriate ecosystem. In order to monetize data, it is necessary to build an ecosystem for data-based innovations - in other words, to create favourable conditions for smart data applications within the company. This is the only way for innovative applications to grow and flourish.
Unfortunately, we only have a short time left. Can you say anything more about building such an ecosystem? What is important here?
An effective ecosystem should have three characteristics:
Firstly, agility. Agile working methods are extremely advantageous in the development, but also in the provision and operation of a smart data solution, because it is typically necessary - throughout the entire lifecycle of a smart data innovation - to adapt it again and again, for example to new customer requirements.
An ecosystem should also offer a reliable technology platform for data - a platform for collecting, cleansing and analyzing data, which usually comes from very different sources. Building such a platform can mean a profound change in the company: We talked about this earlier - about the changes you initiate when you think about realigning your value chain.
And the third feature?
The third feature of an effective ecosystem is conducive data governance. This goes hand in hand with a corresponding culture of cooperation within the company. In order to leverage the potential of data, new forms of collaboration are generally required - both within the company and beyond its borders.
They are beginning to build digital supply networks in addition to the existing supply chains. And these are no longer supply chains, but networks. And to do this really successfully, you need an advanced culture of cooperation: in the direct handling of data, but also within your organizations as a whole. This should definitely be part of an overarching strategy to unleash the potential of data.
This may sound like a challenging, perhaps even risky transformation. But all of this is undoubtedly feasible. And it's worth it. If you tackle these challenges consistently, you will create a conducive environment for successful smart data innovations: You generate real, sustainable competitive advantages based on data.
A nice closing statement, thank you for talking to us!
You're very welcome!
