Achieving Merchandising Excellence -
Driving Retail Innovation with Analytics, AI, and Automation
Sweden's second largest food retailer
Axfood was founded in 1999 and is based in Stockholm
The principal owner is Axel Johnson AB
With a market share of 20%, Axfood has approximately 300 Group-owned stores, e-commerce
and collaborates with approximately 900 additional stores in SwedenThe company operates brands such as Willys, Hemköp, Tempo, Axfood Snabbgross, Mat.se and Middagsfrid
Axfood has over 13,000 employees and net sales of over SEK 80 bn
Further information: www.axfood.com
Success Story
Axfood: Achieving Merchandising Excellence - Driving Retail Innovation with Analytics, AI, and Automation
Challenge
To become customer-centric, retailers need to go beyond generic assortments for stores and channels to tailor unique offerings for individual locations based on their consumers. This requires modern, advanced assortment planning solutions that are driven by customer data science, utilize predictive analytics and AI, and achieve a high degree of automation for greater efficiency and collaboration across the organization.
SAP Assortment Planning
Benefits & Opportunities for Business Improvement
To better serve customers, store assortments must be tailored for the local clientele. Therefore Axfood embarked on a project to enhance assortment planning across all banners and channels. The retailer aimed to become more data-driven, automated, efficient, and customer-centric while maintaining profit margins.
Business Benefits
1. Enhanced Customer Satisfaction:
- Tailored store assortments to better serve local clientele.
- Data-driven decisions allowed for more unique assortments without increasing labor.
- Increased assortment per product group to better meet customer needs.
- Transparency in the assortment revision process.
- Shared relevant information across the organization.
2. Improved Efficiency and Profit Margins:
- Automated recommendations based on business rules, weighted ranking keys, customer data science, and AI.
- Optimized assortments within the constraints of available shelf space.
- Improved profit margins while driving growth.
3. Streamlined Decision Making:
- Infused decisions with customer data and insights.
- Enabled planning of many assortments simultaneously.
- Evaluated assortments based on the roles each category fulfills.
4. Increased Collaboration and Flexibility:
- Category managers had control over the level of data-driven decisions and automation applied per category.
- Continuous support and dialogue with users ensured enhancements and new capabilities.
- Functionality requested by planners rather than forced decisions increased acceptance and usage.
5. Business Alignment and Stakeholder Involvement:
- Early and continuous involvement of business users in the design process.
- Formalized support and continuous improvements post-implementation.
Opportunities for Business Improvement
1. Data-Driven Decision Making:
- Leveraging customer data science, predictive analytics, and AI to drive smarter assortment planning.
- Using a Consumer Decision Tree and metrics like demand transference, substitutability, and incrementality for better assortment decisions.
2. Advanced Automation and Efficiency:
- High degree of automation to handle the workload of planning and managing assortments.
- Use of AI to complete store clustering and provide automatic recommendations.
3. Enhanced Customer Engagement:
- Personalizing assortments to meet the unique needs of customers at each location.
- Ensuring that each part of a store assortment plays a role in customer perception and satisfaction.
4. Continuous Improvement and Adaptation:
- Implementing an iterative approach to leverage AI and predictive technologies for continuous learning and adaptation.
- Formalized support for continuous enhancements and new capabilities in assortment planning.
Project Review
Merchandising Excellence
See the recording of a LIVE discussion for more information