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The planogram data is beyond crucial to the Consumer Products sector. It makes the planogram come alive, and it shows exactly where products are performing and how improvements can be made.
Now that data represents one of the key assets, organizations that do not use it to automate planning and optimize proper product assortment miss out on key benefits such as:
1.) Shelf Performance Analysis
To understand how a category is performing, you need to be able to analyze performance in relation to space allocations, which would be impossible without data.
2.) Shelf Replenishment Analysis
Understanding the Days of Supply (DOS) is crucial as all your products on the shelf need to decrease roughly simultaneously. At the same time, you can increase your profits by putting high-profit margin products at eye-level, which is the most lucrative product positioning. Without data, you won’t know which products are most in demand, so you won’t know which should be placed in the best locations in your stores.
3.) Proper Stock Management
Considering that space planners have to regularly update planograms with new sales data, which will result in changes to product space allocation, by replenishing your stock, you can optimize your product and store performance. Additionally, preventing out of stocks will also help to increase sales.
4.) A Data-driven Planogram
When it comes to explaining why a planogram should be generated in a particular way, data will play a key role in backing up any debate that a space planner might have with the plan. Data is going to empower a supplier to influence where products are placed in their retailers, and prevent planograms from being built just because they are visually appealing.
Now that you understand the benefits of using data and analytics to optimize space and assortment, what should you do next to get started?
You need to find a Business Analyst who has in-depth knowledge of data and analytics tools, your business and sector, and who can bring innovative approaches to understanding your data. Finding a person who fits this profile can be difficult, but they are critical to your data and analytics strategy.
