Podcast Episode 17: Data Analytics in Project Management - From Guesswork to Data-Driven Decisions

Data Analytics in Project Management: A Key to Success

In the latest episode of Snacksize Project Management, we dive into a topic that is crucial for organizations of all sizes: Data Analytics. Sebastian speaks with Martin Riedl, Managing Director of dab: Daten – Analysen & Beratung GmbH, about the role of data in project management and a range of practical applications.

Martin Riedl shares his path into the world of data analytics – a journey that began with a later dive into studying business informatics. What started as a university project on extracting data from SAP systems turned into dab: Daten – Analysen & Beratung GmbH, a company that now helps businesses around the world standardize and automate their data analysis.

His love for data comes from a clear conviction: “Data doesn’t lie.” With the right analytical approach, powerful insights can be uncovered – whether it’s spotting fraud or fine-tuning internal processes.

During the conversation, Martin highlights the importance of making decisions based on data – especially when compared to relying on instinct or experience alone. He puts it simply: "when you're driving a car, your gut might tell you you're going fast, but only the speedometer shows how fast you're actually going. Data gives you the facts you need to make smart, informed decisions."

Martin highlights three major trends shaping data analytics for mid-sized companies:

• the automation and standardization of analyses,
  
  
• breaking down data silos,
  
  
• and the rise of so-called "data citizens" – employees who are empowered to run their own reports and analyses

These developments underscore how data analytics is becoming not only more important, but also more accessible across different roles within an organization.

A key part of the conversation is how data analytics and project management go hand in hand.

With the right data, project managers can identify risks early on and make more informed decisions. Martin emphasizes that fact-based analysis lays the groundwork for effective project management – helping teams communicate project status clearly, accurately, and with confidence.

Another important topic is the challenges related to data quality.

Martin recommends focusing on the six dimensions of data quality:

1. Completeness
2. Accuracy
3. Consistency
4. Timeliness
5. Uniqueness
6. Accessibility

Proper data preparation is crucial to ensure that the data used is both high-quality and representative.

The Role of AI in Data Analysis

Finally, the topic of Artificial Intelligence (AI) is also discussed. Martin views AI as a valuable complement that opens up new possibilities in data analysis. However, he emphasizes that AI cannot replace human expertise, and the context of the analysis remains crucial.

Conclusion

This episode highlights the importance of solid data analysis for the success of projects. Companies should recognize the value of data and develop strategies to use it effectively. By implementing professional data platforms and fostering a data-driven culture, project success can be significantly enhanced.

For anyone looking to better understand the world of data analysis and leverage it for their project success, this episode is a must-listen!