In this Episode, I talked with Prof. Dr. Christian Janiesch, Junior Professor for Information Management at the University of Würzburg about the impact of digitization on society and business, the challenges and opportunities for organizations and about his key research topics: business process management and business intelligence. Moreover, we talked about the importance of seed projects and the long tail of digitization projects.
How will the future look like in 2050? Prof. Janiesch was asked this question in a recent radio interview. And of course, nobody can profoundly answer this question. But taking into consideration current developments in business and research progress, one can try to give a brief answer. The short answer was, “we will probably digitize everything that we physically don’t need”. Taking this one step further, it implies several questions: Do I need to own everything, or do we go over to share more objects and services? Moreover, there will be a lot more digital assistants that we won’t even notice, in the car and other parts of our social and business life. These trends can of course be transferred to the future business and work life, where we will see a lot more automation, connected machines equipped with sensors and data-driven processes. For instance, already today we see predictive maintenance in industrial production processes and the future leads to more smart objects and services – in an Internet of Things huge amounts of data are gathered, analyzed and put into action to support a faster and better decision-making.
Business Intelligence and Business Process Management
A core challenge in the context of digitization and digital transformation is the management of underlying processes. Business Process Management (BPM) is the methodology that deals with discovering, modeling, analyzing, optimizing and in the end automating processes of a business organization. This is very basic and highly important for organizations, as small adjustments can already lead to considerable cost savings. Every business is a collection of its business processes. It is the goal of BPM to screen all processes and to figure out if a process adds value to the company or not or if there could be more value by adjusting or replacing certain processes. Business intelligence or business analytics are the techniques to produce reports, to do online analytical processing, data mining, benchmarking, text mining or predictive analytics.
How does a practical example look like? Let’s take for instance a very small process like travel planning in a business organization. Very often, the process generates costs because people need to deal with their receipts, they need to calculate, they need to report their travel expenses for reimbursement, this needs to be pre-approved, approved and so on. There is basic technology to improve this. It starts with technology for operational management, for the day-to-day business which is about automation and monitoring and reaches of course to strategic topics.
Prof. Janiesch and his team focuses on research that is combining both, BPM and BI – thereby he is collaborating with other chairs and firms (https://bit.ly/2GXKToN ). Moreover, the chair is doing research in the field of complex event planning: the technology is similar to database technologies for storing data and complex event processing technologies for processing event data in real time. Event data is data about things that happened, for example a status change in a process from “receipt submitted” to “receipt paid”. This event becomes a digital time stamp and is integrated in communication processes. Where is the value of this information? Let’s take a complex process, for example in the field of logistics. The firms participating in this process will have separate business process management systems. This technology uses data from other systems and harmonizes processes in real time – this increases transparency, speed and efficiency.
Prof. Janiesch and his team are participating on several cooperation projects with firms bringing in his expertise and knowledge on BPM and BI. Industrial partners are for instance Möhringer Anlagenbau GmbH from Wiesentheid, Bavaria/Germany and APE Engineering GmbH from Aschaffenburg, Bavaria/Germany.
Möhringer is a manufacturing/engineering company with its focus on cutting and saw technology. APE is a service company that supports the automation of the machinery. Prof. Janiesch and his team are supporting the integration of monitoring the machines in both companies. This brings opportunities, as for instance service technicians are having more information. The main idea behind the project and the role of the chair is to analyze data from different systems that provide monitoring data and make use of business intelligence techniques (data reporting, observation of trends etc.).
The involved small-medium-sized firms are open-minded for technological progress and digital transformation. The German industry structure is characterized by 99% small and medium-sized companies. One of the main challenges for these companies concerns digital transformation in process transformation and data handling. But it starts even more basic. One of the first questions for most small and medium-sized companies with the topic of digitalization is „What can we actually do to be more digital?“ This sounds simple, but it is of course much more than just buying expansive computers and software solutions or using cloud computing capacity.
In the first step, it is important to develop a new mindset. Therefore, digital transformation is an opportunity to improve processes and getting rid of actions that bring no value to the organization. A simple but efficient approach can be described as: drop, simplify, automate. What does that mean? It means, either you need to remove the function that nobody needs, you need to simplify it so that it becomes easy to use and execute and in the next step to automate it. Because, automating something that is not needed, brings no value. That’s the reason why it’s called digital transformation and not digital automation.
Seed projects and the long-run
At the end of the session, we discussed the advantages of digital seed-projects. Generally, it is not effective to roll-out digital processes at once in the whole organization. Oftentimes, there is a chance to pick small seed projects, to start there, learn from the errors, make first (good) experience and accumulate knowledge. The long tail of business processes can be connected to this idea of optimization in smaller projects.
Due to high complexity and lack of resources, companies cannot roll out digital processes in every part of the organization, so typically they prioritize by dysfunctionality, feasibility and importance. Based on that, they pick a few processes and try to optimize them. But everything that’s not directly linked to these processes is left aside. If you take a deeper look under the surface of organizations, there are a lot of small processes that are highly inefficient and annoy everyone, but they are not important enough to be fixed first, because they are not losing money – for instance again the travel reimbursement process. The idea is to figure out how something like collaborative production models, that we know from Wikipedia, can improve processes. The solution can be seen in very small improvements which can make a difference in the long run.
Although this procedure is not “simplifying and dropping” parts of larger processes and by far not a complex case of digital transformation, it improves overall efficiency. Further, it is better than waiting for years until digital transformation projects are started or finalized.