Data as a success factor for project management and sustainability

The network forum brings together project management with relevant topics such as data science, AI and digitalization, as event initiator Prof. Dr. Holger Timinger explained when welcoming the 40 or so participants. The aim was to provide food for thought, exchange experiences and strengthen the network. He was particularly pleased that the current event was being held for the first time in cooperation with the VDI Landshut district group. Its head, Dr. Helmut Straßer, emphasized that the cooperation with the university was to be strengthened again.

Prof. Dr. Timinger presented the "

In three presentations, the academic staff demonstrated the importance of data in various areas: Alexander Wallis and Christoph Glück kicked things off with their presentation on data as the basis for optimized processes. The prerequisite is available and reliable digital information that can be used to adapt processes. The central question today is how to deal with the large amount of data. Around 80 percent of the data is unstructured. However, clustering algorithms, forecasting techniques, data analysis, etc. only make sense if you work with good structured data. In order to generate added value, data quality is crucial, Wallis emphasized.

When collecting data, it is important to keep the intended purpose in mind from the very beginning, Glück added. The more structure that is already present when the data is collected, the better it can be used. For mapping process performance, one would have to consider in advance, based on defined key performance indicators or KPIs, which data is available and needed. A specific goal also requires specific data, as the speaker emphasized. Only when this data is available can the next step be the monitoring and analysis of process data and its visualization, which makes trends recognizable and thus serves as a basis for decision-making. Defining the purpose in advance and then using high-quality data is just as important for optimization as it is, for example, for the automation of selected processes. The quality of the data is crucial for making the right decisions.

A structured approach is also necessary when it comes to CSR and sustainability management, as Martina Hörmann emphasized in the subsequent presentation. Corporate Social Responsibility CSR is about the social impact and responsibility of companies, and social and environmental concerns are integrated into corporate activities. The topic of sustainability was anchored at the latest with the adoption of 17 Sustainable Development Goals (SDGs) by the UN. The goals relate to the economic system, the social community and the biosphere.

A sustainability report will become mandatory for listed companies from 2024 and for companies with 250 or more employees from 2026. An indirect compulsion may already arise if manufacturers oblige their suppliers to do so or if banks or insurance companies also demand such a report. Four fields of action are relevant for companies: in the social area, the community and the employees, in addition to the economy (e.g. products, services, supply chains, procurement, logistics...) and ecology (climate protection, energy efficiency, etc.).

But how does one approach such a report in one's own company? First, you have to take stock of the situation. Next, a strategy with key topics must be defined. For example, how transportation can be reduced, energy and water consumption lowered, or packaging made more environmentally friendly. Other topics include product disposal, energy efficiency, workplace safety, product safety or fair conditions for suppliers. This is followed by a materiality analysis, which defines what is important and relevant. And data also plays a fundamental role in the preparation of a sustainability report and the monitoring of its success (measurement, evaluation, official reporting). It is necessary to consider at an early stage what information can be drawn on and what additional information is needed. One of the first steps must be well-structured data collection.

The importance of data was also emphasized by Anna Schidek in her presentation "Modern project management - data as the key to successful tailoring". She said that the question often arises as to what successful project management should look like in a company or even for specific tasks, and what role data plays here. Many influencing factors and framework conditions are important here, company-specific aspects as well as project-specific ones. A standard procedure would cover many projects, but since every project is different, tailoring to the specific framework conditions is necessary.  

An important question is what role data plays in this project adaptation. The strengths of data-based project management include objectivity, measurability, automation and standardization. Weaknesses, on the other hand, are that data can be deceptive, and experience and knowledge or best practices, as well as social factors, are left out. And here, too, the quality of the data is crucial. In principle, measurement should also not move in the direction of employee control.

A survey of the participants showed that the majority of them consider their own experience and data to be the most important factors for tailoring project management - most of them have not yet adopted a data-based approach. This result provided a good basis for the subsequent discussion, in which many of the experts advocated the use of data - which, however, would have to be of good quality - as an aid to decision-making and as a basis for argumentation.

How to generate comparable data and how to use it to optimize processes and projects. The IDP at Landshut University of Applied Sciences provides a wide range of assistance in this regard. Currently, the two research projects (