B2B Online Retailer of Industrial Goods_
Executive Summary
DATA-Driven PLANNING IN SALES AND CATEGORY MANAGEMENT
A leading industrial and workshop equipment supplier needed to align its purchasing and category management decisions more closely with sales.
TalentFormation developed a prototype data-based planning system that supports automated decisions. The aim was to integrate the sales perspective into the purchasing process to optimize the product range and minimize excess stock. The team of experts analyzed exemplary product and customer behavior data, identified relevant attributes and developed a product scoring model.
TalentFormation thus created the basis for an operational prototype that can lead to more precise, customer-oriented purchasing decisions and improved sales planning.
The Initial Situation
Searching for significant data For Better Sales Planning
The company's target group is customers from industry, retail, crafts and logistics, who benefit from professional advice and a wide range of own and third-party brands.
The company was dissatisfied with its decision-making processes in purchasing and category management. The lack of a solid database led to inefficient and sometimes subjective decision-making processes. Performance targets were largely defined top-down. A realistic, data-based assessment by category management was not possible.
This led to plans whose realism and feasibility were difficult to assess and which resulted in missed business targets and dissatisfaction on both sides.
The Goal
DEVELOPMENT OF A DATA-BASED PLANNING SYSTEM FOR OPTIMIZED PURCHASING DECISIONS
The aim was to investigate the possibilities for data-based decisions in purchasing and category management, as well as in sales planning.
Existing data sets were to be analyzed as prototypes and new data sources were identified. The long-term goal is to integrate the sales perspective into the purchasing process to offer a more customer-oriented range and avoid overstocking and the resulting discounts.
The aim of the project was the conceptual development of a prototype for an automated bottom-up planning system for data-based support of category management and purchasing in assortment and purchasing decisions.
Peter Cabelström
Product Manager, TalentFormation Network
The Power Of Data-Based Decision_
Our Approach
LEAN & FAST: RAPID VALIDATION OF HYPOTHESES
With a highly efficient team of experts consisting of a product manager, category management specialist and data scientist/engineer, TalentFormation quickly analyzed how data-supported decision-making processes can be designed.
Our approach:
1. Start-up mentality with prototype development parallel to day-to-day business
2. Validation of the strategic top-down planning objectives with a data-driven, customer-centered bottom-up planning tool at EAN/SKU level
3. Analysis of existing data, in particular product and customer behaviour data
4. Cleansing the transaction data records of all external influences and distortions
5. Definition of critical, defining attributes for a specific product category
6. Calculation of individual product scores based on a specific set of attributes and their strength => sales per product detail page view, which also serve as a basis for marketing decisions.
7. Regression analysis and machine learning for data processing and hypothesis testing
8. Determination of the minimum score and the ideal size of the product category (number of SKUs)
Our Impact
DATA-BASED SCORING FOR BETTER ASSORTMENT DECISIONS
In a very short time, TalentFormation has developed a model for data-driven product scoring that enables customer-oriented product range decisions.
The prototype analyzes the influence of various product attributes on the sales figures of an item.
It was found that certain attributes have a positive impact on sales. With this approach, findings about product-specific attributes can be incorporated directly into purchasing decisions, product-range design and sales planning.
The prerequisite for determining a minimum score and the ideal size of a product category (number of SKUs) was created. The data analysis model can now be used for further development into an operational prototype.
The TalentFormation Factor
TalentFormation uses its network of top talents to form highly specialized, well-coordinated teams that can implement complex projects to a very high standard in the shortest possible time.
This enabled the team, which had already worked together successfully on other data projects, to achieve a result very effectively and quickly, which would have cost many times more project days in a different constellation. Close cooperation and coordination between the team members and stakeholders on the client side ensured that the limited budget was used optimally.
The further development of the model into a prototype that can be used in operational business can be easily realized by expanding the team with appropriate experts at short notice.