A replenishment tool selection

One of the best-known methodologies to select a stock optimization and replenishment tool, or any software, is to run a selection process also called RFQ or RFI (Request For Quotation or Request For Information). This selection process consists of several steps. First, to identify a long list of potential tools available in the market that could meet, in general, the objective defined by the client: to work with forecast and to optimize the stock. In addition, specific functionalities of the business must be considered related to the sector or the type of company.

The next step is to meet the vendors of the long list. It can be interesting to know if the company has offices or partners in the same country, or in the same city of the client, if it has relevant references in its sector or if it has a fundamental requirement that the client needs to cover. This step is called pre-qualification.

Once we have the right candidates, a formal invitation is sent to each one, the process calendar is shared, confidentiality agreements are signed and, a detailed form of expected functionalities and processes is sent. This form includes the technical requirements, the project plan to be developed for each participant and the cost model.

What are the most common features requested in an RFQ form? We show some of them below:

Forecasts

• Forecast calculation horizon.
• Time unit in which the forecast is calculated.
• Inclusion of seasonality and special calendar effects.
• Automatic calculation of the effects of promotions.
• Sale lost calculation due to stock breakage.
• Product life cycle management.

Stock optimization

• Stock management in scarcity.
• Redistribution of stock among stores.
• Ability to differentiate the stock: stock for visual merchandising, stock to supply demand, stock for promotions, etc.

Orders generation

• Supplier order restrictions management: minimum order quantity, transport optimization, discounts for purchase volume application.
• Management of delivery schedules.
• Consider purchase opportunities according to suppliers’ price change.
• Shelf-life management.
• Distribute orders according to warehouse capacity.

In addition to the functionalities, it is essential to measure the forecast accuracy. We mistakenly assume that all vendors have a good forecast performance because the most widely used statistical methods are more than 50 years old. With both statistical models and Artificial Intelligence algorithms, the forecast calculated by each tool with the same historical data could be very different, as we discovered when we run the forecast challenge. We also learned that the outcome of each tool depends on the data. Another important learning was the company that makes the best forecast for one business, doesn’t have to be the one that makes the best forecasts for other.

We have identified too, that most of the companies don’t know the quality of the forecasts they work with.

Why is the quality of forecasts essential? Because orders generations and any stock optimization is based on the sales forecasts and the forecast error is transferred to the rest of the decisions made by the company. All optimizations based on bad forecasting will give a bad result.

In the next article we will use an example to explain the impact of the forecast error.

Author: Casandra Cabrera
Publication date: 20 May 2021