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Fraunhofer IESE combines software engineering and research to optimally implement the digital transformation in your company.
In digital business, exceptional customer experiences are created through digital transformation. Digital business models replace the traditional core business by adapting or realigning it. An ideal combination of physical and digital resources opens up completely new opportunities for companies. Innovation in Digital Business is therefore reflected in products and processes.
Digital transformation is a continuous process of change that is permanently transforming the economy and society. Innovations, new technologies and techniques are already reshaping diverse industries and sectors today.
When we talk about Digital Business, we usually do so in connection with digital transformation or digitalization. However, these terms are not synonyms, as there are different approaches, goals, and implications. Using the music industry as an example, we clearly delineate the terms in the following:
As a starting point, let’s think back to the 1950s to 1980s, when the music industry made its living from the sale of vinyl records. The purchasing process started in a dedicated store where people would listen to records to sample them and eventually buy them.
Digitization
In the mid-1980s, the CD was about to be launched on the market, paving the way for digitization. Technology transformed media and data into digital products – from the analog vinyl to the digital CD. Thus, music was still tied to a physical medium, but it was stored and read digitally. The purchasing process did not change.
Digitalization
In the early 2000s, the music industry underwent the next change: digitalization. From this point on, the purchasing process also changed. The basis for this was the MP3 format developed by the Fraunhofer-Gesellschaft. The digitalized music could now be read on CDs and played on the computer or on portable MP3-capable devices. At about the same time, the Internet became established, making the purchasing process purely digital.
Digital Transformation
In the 2010s, the latest digital change in the music industry to date, the digital transformation, started happening.
The digital transformation is changing the economy and society. Technologies and digital business models are replacing the previous purchasing process. From the user perspective, a completely new added value emerged that changed an entire industry, as impressively demonstrated by the European solution Spotify. For a fixed monthly fee, users buy the right to listen to music for which there normally is a charge. This means that owning the music is no longer necessary. Other added values, such as analyzing the listening behavior to enable customized music suggestions, are included.
One often gets the feeling that digital transformation is a fairly new trend. As if our economy and industry has only recently had to face up to the challenges. Yet software has been developed professionally since the 1950s already. The digitalization of the economy has been in full swing ever since then. Software also serves to improve an existing business or to newly create a more efficient business.
Digital business models can achieve an increase in growth and revenue that is impossible to achieve with traditional models. This is due, in particular, to a typical characteristic of software products: scalability. Software code can be duplicated as often as desired without exploding costs. The fact that changes are easy to make enables true modularity and extensibility. Because of this, and with the right combination of innovation engineering and software engineering, digital transformation of industries is not uncommon, as Spotify impressively demonstrated in the music industry.
The challenge of becoming more resilient as a company should not be overlooked. Here, too, digital transformation can play a role. New, software-based value streams can make companies more resilient to crises.
Another central focus for companies is their competitive advantage. This results from an ideal combination of physical and digital resources. Last but not least, digital transformation is also about European technology sovereignty. Because using innovative products or services to keep the competition at bay or even transform an industry is the order of the day. The potential and the multitude of possibilities for implementation are enormous.
Companies are faced with the challenge of developing meaningful foundations for strategic decision-making. Which technology solves relevant problems? Which trends are just hot air? What does digital transformation mean for employees and the organization? As a research institute, we have developed a wide variety of proven solutions that take our customers to the next level in their competitiveness.
Read more on the topic of “Innovation Engineering”:
As soon as you delve into the topic of digital and data-driven business models, you will encounter the term “Digital Ecosystems”. The chance to shape one and be the initiator provides access to completely new possibilities – digital transformation not only of one’s own company but possibly of an entire industry. As an initiator, for example, you can analyze the activities in the Digital Ecosystem, whereupon improved and new services can emerge. Further information can be found in our current study [in German] on the possibilities and best practices of Digital Ecosystems.
Due to the success and popularity of large Digital Ecosystems, companies also want to establish one of their own as quickly as possible – usually as a starting point for their digital transformation. However, the complexity in terms of requirements management, (system) architecture, business model, and competence development of one’s own workforce is usually greatly underestimated. Unfortunately, this often results in expensive and half-baked solutions without real added value for the customer. Digital Ecosystems like Netflix, Airbnb, Booking.com, Uber, or Amazon Marketplace have had a disruptive influence on their respective industries. Currently, however, the majority of very successful Digital Ecosystems do not come from Germany, but rather from Silicon Valley and increasingly also from China, and are mostly aimed directly at end customers (B2C). Nevertheless, there is still a lot of potential for new Digital Ecosystems, especially in business-to-business (B2B). It is precisely in this area that the strength of the German economy traditionally lies.
The topic of Digital Ecosystems has been an integral part of our institute for many years. We have supported our customers in numerous projects already – from strategic positioning to technical implementation. In this context, the TED method we developed ourselves in the area of Innovation Engineering has proven to be an extremely effective and efficient solution for the evaluation of Digital Ecosystems. In addition, we are working with companies that already have a Digital Ecosystem in place and are in the scaling phase – which can trigger network effects.
Find out more about our focus topic “Digital Ecosystems”:
Just about every company has to deal with modernizing its legacy systems at some point. The reasons for system modernization or software modernization are diverse and multi-layered. A discontinued core technology, maintenance and security problems, or Software as a Service (SaaS) as the goal for a new business model are just a few examples. It is therefore advisable to see modernization not just as an annoying chore, but also as an opportunity to make the legacy system and the whole company fit for the future. So this is how the basis for digital transformation is created. New technological developments, e.g., in the sense of ever more comprehensive networking, Machine Learning processes, and innovative business models open up numerous new possibilities. In particular, modernization offers the opportunity to rethink fundamental assumptions and throw unnecessary ballast overboard.
A central characteristic of legacy modernization is that it goes beyond purely functional further development of the system and that the focus is on other aspects, such as restructuring or paradigm shifts. This is often accompanied by increased technical and organizational complexity, which makes modernization a challenging undertaking. Nevertheless, such an investment in the modernization of a legacy system is well worth the effort in many cases because it creates a solid foundation for the sustained and sustainable success of a company’s core systems through Digital Business.
Fraunhofer IESE advises and supports companies of all kinds, from SMEs to large corporations, in their projects to modernize their legacy systems. In doing so, we contribute expert knowledge from all areas of software and systems engineering in order to develop tailor-made approaches and solution concepts. Since technology never exists in isolation, we always consider related areas as well, such as user experience, business model, as well as the organization of the teams and the company. Only a holistic approach leads to sustainable success and ultimately to a successful digital transformation.
Further information on modernizing software and systems:
Data-driven business models bring with them promising prospects. First, however, it is important to create a foundation by collecting data in a meaningful way. Only then, with continuity, is there a basis for Big Data and a prospect for using Artificial Intelligence (AI).
AI is already found in many systems today: from voice assistants to intelligent algorithms that evaluate our behavior when shopping online or on social media. In the future, we will encounter AI systems much more frequently due to the digital transformation. Here, the quality of the collected data, in particular, plays a decisive role in providing safety assurance against failures of AI systems. In Germany, there is a strong focus on industrial AI applications, for example in the areas of mobility, logistics, Industrie 4.0, or medical technology. Especially in these industries, it is essential that AI systems are safe, dependable, and trustworthy. Assuring these qualities and making the risk of an AI system transparent and manageable is the subject of current research.
Fraunhofer IESE is working intensively on designing dependable AI systems. In this context, we offer our customers various entry scenarios for the meaningful use of Big Data and AI in companies. For several years, Fraunhofer IESE has successfully covered continuing education measures as well as the implementation of projects related to Data Science and Artificial Intelligence. This has resulted in numerous methods such as the Big Data Potential Analysis and software tools for dynamic risk management and uncertainty management.
Learn more about our service portfolio in the area of “Dependable AI”:
Digital business relies on the use of data-based services. In companies, the options are unmanageably diverse when it comes to what should be done with the company’s own data. On the one hand, data must be protected against external threats and for reasons of data protection. On the other hand, new business potential can be developed if further processing of the data takes place, e.g., on the basis of Artificial Intelligence.
Trading with data as a business model is the backbone of many digital champions. This is also relevant for digital transformation. No wonder, because once data has been collected, it opens up the possibility of analyzing the user experience (UX), uncovering system vulnerabilities, and many other perspectives. However, data is usually shared either completely or not at all. This means that many companies consider it risky to release data into the data trade in an uncontrolled manner as part of their digital transformation. The desire for control – in line with the European idea of data protection – is a fundamental need and a current obstacle for a large number of companies when it comes to actively engaging in data trade. But not exchanging data reduces a company’s competitiveness. Opening up in an uncontrolled manner, on the other hand, entails risks. An implementation of informational self-determination that does justice to both aspects was developed at Fraunhofer IESE out of a research project and bears the name MYDATA Control Technologies. With the help of MYDATA Control Technologies, data usage control (=an extension of access control) can be enforced in companies. For this purpose, data can be filtered or masked before being shared in accordance with legal requirements and company regulations. At the core of MYDATA Control Technologies is the vision of “Share data, retain control”. Where data release had to be handled conservatively in the past, with data usage control data can now be released easily – compliance with usage authorization guaranteed. And in case of doubt, the usage authorization can still be changed or revoked.
Read more about our topic area “Data Sovereignty”:
Attacks on corporate IT are an everyday occurrence nowadays – regardless of whether the target is a start-up, a small or medium-sized enterprise, or a large corporation. That is why protection against data thieves is an essential part of the digital transformation.
It is often the case that many companies only realize the importance of cyber security when attackers have already gained access to data. As soon as there are ransom demands or industrial espionage becomes a possibility, the result is ultimately blind actionism. Management demands cyber security according to the motto “whatever the cost”.
In order to protect companies from unnecessary bad investments, several teams of experts at Fraunhofer IESE are intensively addressing challenges such as a predictive IT hardening strategy and systematic penetration tests.
In this context, we not only form the Red Team at the Fraunhofer Security Operations Center, but are also carrying out research at the interface between security, privacy, and usability of IT systems. Unfortunately, the “low hanging fruits” of IT security in many SMEs are still particularly alarming.
At our institute, cyber security is inextricably linked with Digital Business. This is the only way to ensure sustainable business success through digital transformation with secure systems.
Find out more about our topic area “Cyber Security”:
Due to our interdisciplinary collaboration, new products are constantly emerging, such as an SaaS solution for Crowd-based Requirements Engineering (CrowdRE). CrowdRE combines requirements engineering and data science so that requirements-relevant information about a company’s products can be collected and analyzed semi-automatically from heterogeneous user groups (the crowd) and other data sets. This creates the basis for implementing the digital transformation.
For example, it is possible to use customer reviews on Internet portals to understand which functions and qualities of a company’s systems users like, like less, or still miss. In addition, behavioral patterns can also be identified to learn more about the use of the systems. The insights gained from the software through semi-automatic collection can then be fed back into the requirements of the R&D department and product development.
CrowdRE is a digital transformation tool that provides companies in the B2C or B2B sector with valuable insights into the experiences of their users.
Read more about our topic area “Crowd-based Requirements Engineering”:
As an institute of the Fraunhofer-Gesellschaft, our greatest concern is to generate direct benefits for companies from application-oriented research. With our pragmatic and scientifically based approach, we are committed to neutrality and therefore always answer our partners’ questions with a customized solution – free from technological bias.
Fraunhofer IESE is the competence center for software-, systems-, and innovation engineering. This holistic expertise in software-intensive systems allows us to lead very challenging projects to success in a goal-oriented manner. In this way, we offer our partners comprehensive support throughout the entire project.
Fraunhofer Institute for Experimental Software Engineering IESE