Case Study ratioform
“Next Level Product Management
with MACHINE LEARNING”
You know this as a product manager, …
… you are managing an overwhelming number of products, where it is difficult to monitor performance manually.
… there are performance fluctuations in your products, which you can only manage after they have already occurred.
… you are facing the challenge of being able to assess the performance of your portfolio since a KPI-based classification regarding the positioning in the product life cycle is not possible with simple models due to the heterogeneity of the products.
INITIAL SITUATION AT KAISERKRAFT (FORMERLY RATIOFORM)
The product managers of our customer kaiserkraft (formerly ratioform) have always faced similar challenges.
Obtaining meaningful information about products was a complex task, which distracted the focus from the value-adding activities of a product manager. To change this, it was necessary to analyze and evaluate all data from every system in the company.
Our diverse product portfolio has presented us with the great challenge of efficiently and purposefully supporting and managing all the products it contains. What we lacked was an automated, technology-based approach to evaluate the large number of products in the different phases of their lifecycles. The ML-based solution implemented by our partner Striped Giraffe was able to overcome this challenge. It allows us to organize our daily work more efficiently and gives us the opportunity to continuously optimize our portfolio with reliable data.
Daniela Senkbeil, Vice President Category Management Industrial & Packaging (a Division of TAKKT AG)
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