Insight Driven Decision Making
from the series „Trends for the Next Decade“ (#1)
Do you know which of your innovative projects actually promise success?
Many innovative business models are very effectively extended or even made possible in the first place by the intelligent use of data and algorithms. Be it to achieve digital added value or to make processes more efficient; companies are increasingly pushing AI and analytics projects. However, it often turns out that it is unclear which projects can be implemented quickly and how costs and benefits can be compared.
Our recommended actions
- #1 Anchor and combine key competencies from Data Science, Data Engineering and the respective departments
- #2 Realistically assess the possibilities and limitations of data-driven decision making
- #3 Build up skills (methodological knowledge, etc.) and infrastructure to make successful decisions
- #4 Organize best practices for data capture and collection, data preparation, data analysis and model-based data classification
- #5 Use agile process models to iteratively approach an optimal solution together with representatives of different disciplines. Let user feedback flow consistently into the project
- #6 Develop the organizational framework for your digitization projects
- #7 Assemble the modern algorithms exactly according to your needs to maximize the added value to be achieved
- #8 Communicate the added value gained in order to create lasting acceptance and further development potential at all levels