The selections of discounted items or discounts are based on experience. Which method and tool enable an optimal solution?
Shorter product life-cycle leads to a faster increase in inventory of outdated or slow-sold products. The challenge for retailers is to find ways to strengthen the management and optimal control of sales programs to minimize the loss for electronics retail industry due to inventory factors.
Difficulties in confronting the challenges that inventory factor brings
Despite being aware of the need to manage and control the flow of products in retail, many business clients of FPT Digital only stop at human control level and have not had any optimal system or method yet, specifically:
• Select items and time for discount based on experience or discrete reports which have not been coherently linked.
• Choose discount level based on experience, according to market trends, without any supportive analysis background, and has not yet utilized much historical data.
These manual methods do not optimize the sales program and reduce profit per each product line in comparison to the achievable level.
The optimal Markdown solution
We have built a tool to determine the discount level, the discount time for products, accessories to achieve the goal of clearing inventory at the end of the season while ensuring the highest revenue and profit based on historical data.
Discounted items at discount time are those that are at the end of the saturation stage or are in the downturn of the product lifecycle. The task is to minimize inventory at the end of the season or at the end of the product lifecycle.
Data is a valuable asset of any enterprise, by knowing how to utilize and analyze data appropriately and accurately, businesses gain an important information basis that help them make quick and effective action decisions. With this in mind, we develop a forecasting support tool, that helps select discount scenario that ensure the achievement of optimal price at each time by utilizing historical data, in two stages:
Phase 1 involves analyzing and building a model forecasting the number of customers as a platform system. Specifically, this phase consists of 2 main tasks:
• Historical data collecting and processing: Collect discount history, inventory data, and the corresponding stock-out ratios of the products.
• Model building: Build a forecast model of sales quantity based on a number of variables such as the amount of inventory to be sold, the discount rate, the age of inventory to build the model and apply to the whole group.
In phase 2, the Markdown pricing policy options for products will be optimized based on historical data and forecasting model built from phase 1. Specifically, this phase will have 2 main tasks:
• Products selection: Build a model to identify products that are about to move to the end of the product lifecycle to prioritize for discounts.
• Markdown pricing policy options optimization: Optimize based on products sales forecast model to estimate the sales quantity at a specific discount price in the selected time period. This data will then be used as input data for later stage.
The optimal discount scenario program with Markdown method
Rapid assessment test to evaluate idea – PoC (Proof of Concept)
In order to test the feasibility of the idea and prove that the idea brings benefits that are superior to the traditional way of formulating and managing discount plans, this proposed idea has been applied with the quick testing method at two groups of shops having similar sales and selling power. One group applies Markdown discount method and another follows the traditional method. The implementation of the idea in comparison with the traditional method helps business realize clearly its effectiveness.
Learn more about our Digital PoC service
Reducing inventories and increasing profits are the results of implementing the Markdown method
After 6 months of performing PoC, the results showed that Markdown method had a coherent effect. Stores that apply Markdown discount method reduce their inventories at the end of the season by more than 70% and improve their profits by 10% compared to store that apply traditional method. With its feasibility, the optimal product pricing Markdown method is continuing to be applied widely in other stores of business client.
