Optimising Inventory for an online Retailer
Replenishment recommendations for thousands of SKU's every week.Customer
A Danish cosmetics and organic beauty products retailer.
Challenge
A fast growing online retailer with hundreds of suppliers and thousands of products, trying to figure out what to order and when.
Solution
Shelf Planner’s Automated Replenishment for WooCommerce
Scope
Generate Order Proposals and automate replenishment for hundreds of products in the midst of Covid19.
A Danish retailer, specialized in organic beauty products, that was already experiencing rapid growth found it accentuated by the COVID-19 pandemic of 2020.
They believed advanced demand forecasting would be of great benefit to their operations and solve two core problems: Lengthy lead times and volatile demand. This combination had proved to be a challenge for traditional forecasting methods, leading to a large number of products that were overstocked with more than 26 weeks of supply.
Before implementing the Shelf Planner extension, the company did not have proper forecasting in place, the order book was the significant driver of decision-making.
Any outlooks and decisions on what to produce and what to buy were done in extensive Excel sheets.
The solution
Starting with a small sample of SKUs to prove the technology, the Shelf Planner team worked to include covariate data such as COVID-19 cases, mobility data, government actions such as shelter-in-place orders, and online traffic.
Simplified, this meant we had to create a digital copy of the store for the period it was closed for business due to covid.
Based on these assumptions, the Shelf Planner engine was able to create a new baseline for the future sales, as if Covid had never happened.
Shelf Planner was engaged to connect the client’s data into the forecasting engine in the Shelf Planner AI platform, with the goal of forecasting sales up to 6 months in advance. Starting with a small sample of SKUs to prove the technology, the Shelf Planner team worked to include covariate data such as COVID-19 cases, mobility data, government actions such as shelter-in-place orders, and online traffic.
Once we became familiar with the client’s product range, it became clear we needed to split products into 2 buckets: those with short lead times and those with longer lead times, as different forecasting approaches and data streams were relevant for each bucket.
Sales Forecasting is a particularly powerful tool for ecommerce businesses because the space allows for access to a plethora of data and data streams – fantastic for some of the data hungry algorithms in the Shelf Planner AI Forecasting Engine.
In the case of this client, a combination of quality data, powerful technology, and a strong project team produced the accuracy results that the client needed to succeed.
Value delivery
Customer benefits
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KPI's impacted
- Faster response to market opportunities
- Reduction of lost sales
- Reduction of cost through better capacity utilization and planning
Sustainability impact
Better stock projection and phase-in of newer products, phase-out of older products more efficiently.
Systems replaced
Thrive, Excel
