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How Can A Retail ERP Improve Your Demand Planning And Sales Forecasts?

Businessman charting demand planning on a touchscreen

A retail ERP system can put the science back into the art of creating accurate demand planning and sales forecasts, which are crucial for your business to maintain customer satisfaction, maximize sales and reduce inventory carrying costs.

Here’s a look at how a retail ERP system can do the heavy lifting of demand planning, such as calculating when to replenish inventory, while still enabling retailers to give approval or manually make inventory adjustments when necessary.

First, identify your seasonal inventory. To improve your demand planning and forecasts in this area, you need to balance historical sales data with external factors that could affect your sales. For example, your retail ERP data says your stores sold an average of 100 umbrellas a week in spring for the past three years. You compare that data with the amount of recorded rainfall, which was consistent during that three-year period. But for the upcoming year, the Farmers’ Almanac says to expect less rain than in the past.

For apparel retailers, their seasonal inventory could be based on what’s in style. For example, the historical sales data says you typically sell a lot of tank tops during a specific season. But if the current fashion trend doesn’t emphasize tank tops, you can order fewer tank tops than usual. Likewise, if the latest rising celebrity is wearing a tank top, it should be an indicator that tank tops are in fashion and that you should stock up.

Secondly, identify your inventory staples or bread-and-butter items that consistently sell all year. For example, gasoline retailers may be able to predict the amount of gasoline sold monthly. When the price per gallon stays within a certain range, the amount of gasoline sold won’t be affected much. However, if gas rises to $6 a gallon, you expect a decrease in your sales; if the price of gas drops to $1 a gallon, you should get as much gas as you can.

With clothing retailers, identifying bread-and-butter items is more complex because what sells depends on what’s currently in style. This is especially true with the female clothing line. As a clothing retailer, you may know that you need to order more tank tops during the summer season, but the trick is identifying which style tank tops. That’s going to be based on the latest trends.

Another complexity in the apparel industry is determining how much inventory to stock for different clothing sizes. That’s where a retail ERP system can help. With a retail ERP solution, you can define allocations for specific products. For example, you could set up a default allocation of women’s clothing sizes for 20 percent small, 50 percent medium, 20 percent large and 10 percent extra-large.

You can also adjust the allocations in your retail ERP system based on specific products, such as using different allocations for a Calvin Klein trendy top and a classic tank top. And, if you have a central warehouse and 10 stores, you can enter each store allocation into the retail ERP system. So, if you get a price break when you order 1,000 clothing tops from a vendor, the retail ERP system can do the initial calculations on how many of a certain size and color should be allocated to each store based on the allocation information you entered in the system.  Of course, you should also have the option of adjusting those quantities before the PO is issued.

This is the difficult part of implementing a retail ERP system: thinking through demand planning and setting it up in the system. Retailers are so used to making product allocation manually, but a retail ERP system puts factual structure and consistency behind your demand planning.

When you have a good product and sales forecast, it improves your supply chain; the more accurate you are in what you are going to sell, the better off you are in managing your supply chain. So if you only have so many of a specific item, your retail ERP system can alert you to potential projected low stock conditions.

In the end, with more accurate demand planning, you can increase customer satisfaction by avoiding out of stock conditions, reduce inventory-carrying costs resulting from overbuying and hopefully maximize profit to the bottom line.