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4 Steps To Better Demand Planning For Mid-Market Retailers

Woman with credit card deliberates on a purchase

Demand planning might feel like aiming at a moving target, but forecasting is vital to pinning down a plan for business growth.

A forecast is essentially a prediction of what a retailer thinks is going to happen in the future. For mid-market retailers, here’s a step-by-step approach to taking historical data, inventory variability, replenishment and Big Data to create a retail sales forecast focused on strengthening future operations.

  1. Demand planning is rooted in historical data: Forecasting primarily relies on historical data. Retail ERP software helps to smooth out erratic usage trends as well as to track and manage historical information of multiple inventory items, providing you the foundation for creating a demand planning forecast.
     
  2. Assess your inventory’s variability: Your variability is going to depend on the market you’re in. For instance, a fashion retailer is subject to a high degree of variability, meaning its inventory relies on seasonality of product styles. A kitchenware store, on the other hand, is more likely to carry the same inventory throughout the year. 
     
  3. Determine ideal replenishment schedule: The variability of your inventory helps to determine how much you should rely on historical data to predict sales demand. For a fashion retailer with high inventory variability, open-to-buy budgeting is helpful. This forecasting method helps you to make changes on the go, providing the necessary flexibility to adjust inventory according to industry trends or style genres, rather than continuously stocking specific clothing items throughout the year.

    Let’s say that a fashion retailer sets an open-to-buy budget of women’s cardigans. A retail ERP system keeps track of what the store sells against what was forecasted. If the item sells well, the open-to-buy budgeting provides the retailer with the flexibility to refine the inventory to maximize sales. That includes ordering more cardigans, switching vendors or stocking a different color of cardigans. 

    If you’re a retailer that sells the same type of products year-round, you should base your replenishment schedule on those items’ historical sales data.

    Keep in mind that you could have various product replenishment schedules for different items. For instance, a department store might sell clothing basics like underwear, which are probably on a minimum order replenishment schedule, and also sell seasonal clothing items like winter jackets, which likely follow an open-to-buy budgeting schedule.

    Another demand planning tactic that helps with planning is to stock seasonal items, like snow shovels or Halloween costumes, on a set replenishment schedule. You might keep a minimum of five snow shovels in stock during the spring, summer and fall months, but increase your minimum stock level to 50 during the winter months. That way, for items that are stocked year-round, you’ll ensure that you keep more products on the shelf during specific seasons. 
     

  4. Consider Big Data: Compare your historical data to Big Data trends, which involve data and statistics occurring outside of a retailer’s capacity. As an example, if the long-term weather forecast is predicting a warm winter, you might adjust your plans to stock fewer heavy coats and snow boots compared to past seasons.

    In addition, retailers should be open to basing a forecasting decision on a gut feeling, even when historical data doesn’t support an event or Big Data isn’t available. Perhaps your store is located in a region that rarely ever receives snow. If you know about an approaching winter storm, it’s certainly a good idea to try to stock up on winter essentials like ice scrapers.

In the end, knowing where you’re going requires knowing where you’ve been. For a retailer, that means to effectively plan for future growth, you’ll need to analyze historical data. This four-step approach should help mid-market retailers leverage the necessary data to guide them in their demand planning efforts.

Author: Wm. Matthew Street, Solutions Consultant/Retail Product Lead at ArcherPoint

To learn more about inventory replenishment, schedule a demo of ArcherPoint's Retail Management Solutions.