Optimized product management with machine learning

ratioform, the German market leader in the field of packaging, optimizes their product management with future-oriented product lifecycle advisor.

Product managers often have to monitor a large number of products simultaneously, react quickly to performance fluctuations and assess the efficiency of their portfolio. Obtaining meaningful information about products is a complex task that distracts the focus from a product manager’s value-adding activities. To change this, the entire data from all the company’s systems would have to be analyzed and evaluated. The product managers at ratioform were also faced with this challenge.

Daniela Senkbeil, Director Category Management, Solution & Pricing at ratioform described the situation as follows: „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.”

“This automated process could be realized with a machine learning (ML) solution. Together with the service provider Striped Giraffe, who has been supporting us for many years in the areas of data management and business intelligence (BI), we decided on this approach. Our new machine learning solution enables product managers to identify correlations between different items and initiatives or, for example, to examine different scenarios in advance for their later effectiveness on the market. This enables the product managers to act preventively instead of just reacting as before,” explains Marcus Eichler, Director Marketing, Digital & Technology at ratioform.

Since analyses of the product data inventory and categorization into different product lifecycles were not sufficient to provide product managers with adequate insights into their product portfolio, we developed with our partner Kentivo a Product Lifecycle Advisor based on the machine learning platform “Genie”. The solution provides our customer ratioform with the ability to predict the performance and development of a product throughout its entire lifecycle.

By predicting the future development of products, product managers can take action in advance to efficiently manage their products. For example, the product manager can see whether a marketing or bundle initiative could prevent an item from drifting into the next stage of the product lifecycle.

Thanks to the possibility of weighting individual KPIs, ratioform was enabled to focus specifically on products with high turnover or margins and thus achieve even better forecast results.

“With the implementation of the ML-based solution by our partner Striped Giraffe, we were 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,” confirms Daniela Senkbeil.

To develop this solution, the data management experts analyzed more than 15,000 product data records, 10 million transactions, and 8 years of ratioform’s data history. The entire project was completed within 4 months.

We summarized all the details of the project in a case study that can be downloaded from www.striped-giraffe.com/en/case-study-ratioform/.