Digital Transformation - Big Picture (english version)

In this course, I explain the success factors of digital transformation that have emerged in the strategic initiatives and projects of the past ten years. This incorporates the latest findings from science and industry.

You will learn which digital technologies are essential, which management methods the professionals use today and how significant the competitive advantages of the digital pioneers have become in the meantime. We will talk intensively about digital business models, especially platforms and data- and AI-driven models.

 But digitization has long been a topic with a major external impact: How is digitization changing competition? And which effects can be expected on the growth and productivity of the economies? How is digitization changing work, and how can it help achieve climate protection goals?

In the end, I will explain how companies determine their digital maturity level and how they develop into a successful digital company in 6 steps.

 

Let's first look at the decade of the digital economy, in which the balance of power in the global economy has shifted drastically. 2012, only four companies from the digital world were among the top ten most valuable companies globally. Oil companies dominated the top ten. Today, the world looks very different, with 8 of the ten most valuable companies coming from the digital sector. Five of them operate on a platform model.

 

The impact of this shift from linear business models to platforms can be seen in the annual reports:  The revenues of the top ten platforms have increased massively in the past ten years, and the increase has accelerated again. This dynamic can be seen even more clearly in profits: Together, the ten most valuable platforms earned around $370 billion last year.

 

This development of the digital economy has had a massive impact on the stock markets. The share of the United States has risen to 60%, and the percentage of Europe has fallen accordingly to only 15%. On China has gained significantly, the rest has remained about the same. The rise of the United States is not coincidentally related to the introduction of the iPhone. That was the beginning of the triumphant advance of the platform economy.

 

What are the digital pros doing better?

This epochal change is no coincidence but the result of massive investments in research & development, the right management methods, and a superior business model.   

 

First: Investments in research and development

 The Superstar companies have massively increased their investment in research and development of new products in recent years - and have continued to increase the pace during the pandemic. In contrast, many traditional companies have cut back on spending.

 

This rapid increase is even evident at the national economy level. Superstars are more productive, so a shift toward them results in higher overall productivity. Industries with higher growth of superstars show higher innovation and productivity. Superstars also appear to generate positive productivity spillovers, partly through technology transfer. We have found that trading in superstars can increase the productivity of a small firm by 8-10%.

 

As a result, Digital pioneers such as the United States, South Korea, and Israel have vigorously widened the gap to Europe over the past 20 years due to investments in their digitalization.

China has also caught up strongly, as a look at its world-class patents for digitization shows. The United States and China have pulled ahead of the rest of the world over the past decade.

 

Second: Success Factors of digital transformation

Success in digitization is not luck. In the meantime, we know from the past decade’s experience which factors lead to success. If we look at the connection between digitization status and revenue growth, we can see clear links, and we can also see the recipes for success. Above all, it is automation in sales, data-driven decisions, and new digital products and business models.

 

If you look at the connection between digitization and margin growth, you also see a relationship and clear criteria that determine success. The most important success criteria are process automation, cloud technology to reduce costs, and a more favorable cost structure of digital business models.

 

Third: Digital Business Models

If we look at the typology of digital business models, we can distinguish three types in principle: Platforms, data / AI-driven models, or digital extensions of analog models. Platform models can be differentiated into transactional platforms and data/IoT platforms. While transaction platforms such as Amazon Marketplace encompass the management of data-based interactions between external suppliers and demanders, data/IoT platforms provide the infrastructure for sharing and analyzing data across companies to develop data-driven business models. Examples include Siemens Mindsphere.

 

Data/AI-driven business models can be divided into three forms: As-a-Service models, data products, and data-driven manufacturing. As-a-service models transform products into intelligent IoT services, as tire manufacturer Michelin has deployed its "tire as a service." Data products monetize a product or product feature based on usage data. Examples include Tesla Fleet Learning and Google Maps. Data-based manufacturing derives a product from customer behavior. An example of this business model is Alibaba's smart factory Xunxi, which manufactures only those products that Alibaba derives from the behavior of its one billion customers.

Companies often begin their digital transformation by adding digital components to their analog models. Possibilities include the automated provision of a product or service or digital sales.

 

In the course, in addition to business-to-consumer markets such as mobility or retail, we will, of course, also look at business-to-business. This includes transaction and IoT platforms, which play an essential role for Europe.

 

Many incumbents have now established themselves in the platform economy. In machinery and equipment, 35 percent of the leading platforms come from the top 20 incumbents in the sector. In agriculture and agrochemicals, 30 percent of market leaders come from the industry; in healthcare and life sciences, 15 percent.

 

Let's look at the IoT/data platforms first. Consolidation is currently taking place in this market. Almost all the major digital players such as Microsoft, Amazon, Google, SAP, Oracle, or IBM are meeting industry champions such as Siemens, General Electric, Bosch, or DMG Mori from Germany. PTC Thingworx and Schneider Electric are also among the providers in this category. Other industries such as agriculture or healthcare are also represented by well-known names from John Deere, Siemens Healthineers, or General Electric Healthcare.

 

After a long period of gold-rush sentiment on the market for IoT platforms, the market situation is now consolidating. The share of the top 10 providers is rising steadily, and the first providers are exiting the market again. The share of the large US Hyperscalers Amazon, Microsoft, and Google increased from 5 to 30 percent in five years.

 

The development path from the physical product to the "Equipment as a Service" model can contain various intermediate stages. The first step is to add additional services such as spare parts supply, which may be billed in a subscription model but are not yet a digital model. In a further step, additional digital services can be developed, for example, remote monitoring or predictive maintenance. The additional services are billed separately but already allow data to flow back to gain insights from the use of the machine or system. The third step makes the transition to "equipment as a service" possible. The machine is no longer sold but made available to the customer and billed depending on usage or output. The advantages are a significantly lower barrier to entry for demanders and an increase in demand. However, the supplier shares the risk of machine downtime with the customer.

 

Digitization is increasing competitive pressure, and now in almost all industries. If you ask companies representative of Germany, 51% now say that competitors in their sector who digitized early are ahead of them today. And as many as 70% of companies believe that competitors from the digital industry are pushing into their market.

 

Investment in digitization is also rising steadily. The companies' investments have experienced another acceleration with Corona, and venture capitalists' investments in digital startups are increasing very strongly.

 

How is the course structured? We start with digital technologies as enablers and discuss on the second level the relevant aspects in management and processes, i.e., leadership, operations, and digital work. Then we look at the digital business models, which usually determine success or failure. That is the internal view.

 

Then we add the external effects. What about competitiveness? How does digitization affect growth, welfare, and work, and how is digital policy influencing this process? We talk about the status quo and the investments going into digitization at the very beginning.

 

In the end, we explain how to determine a company's digital maturity level and what steps are required to become a digital company.

 

In addition to the course, once a month, I explain the latest developments in digital transformation in a live session and am available to answer questions from course participants. There is also a 14-day newsletter on digital transformation, and you can see more information on my website www.netzoekonom.de


Dr. Holger Schmidt

Holger Schmidt lehrt Digitale Transformation an der TU Darmstadt und Plattformökonomie an der Executive School der Universität St. Gallen. Daneben ist er als Keynote-Speaker tätig. Seine Kernthemen sind digitale Geschäftsmodelle, Plattformökonomie und Künstliche Intelligenz. Er ist Berater des "The Original Platform Fund", der auf dem von ihm erfundenen Plattform-Index basiert. Sein Faible für Klimaschutz stammt aus einer Zeit, als das Thema noch nicht en vogue war: 1997 wurde er mit einer Arbeit über die internationalen Verteilungswirkungen des Klimaschutzes promoviert. Er ist Autor mehrerer Bücher über Digitale Transformation und Künstliche Intelligenz sowie als Podcaster für die FAZ tätig.