Friday, October 10, 2014

Forecasting Grocery Stores

Inventory management is the central and recurring theme for a successful supply chain.  By controlling inventory levels, supply chains are able to keep the appropriate amount of goods in stock and fulfill a customer's orders immediately as they come in.  Good inventory management hinges heavily on knowing the demand of customers and timeline of such expected orders.  This introduces the importance of forecasting in supply chains.

Forecasting is especially important in an industry with goods with a short shelf life, such as the grocery industry (1).  Grocers have to figure out how much of a product a customer will want at a specific time, make sure they will have it in stock, and not over-order to a point where they have to throw out a lot of the product if it goes bad.  Many fresh foods have a very limited shelf life; breads, meats, and produce all fall into this category (2).  Accurately forecasting customer demand of these products will ensure that customers will get the amount they are looking for, and that groceries won't have to throw out a large amount of excess stock.

The best way for a grocery store to forecast is to go on historical data (3).  As a food store is in business for a longer time, it can better assess what kinds of products people that shop there are likely to buy.  For instance, in a neighborhood that has a strong Asian community, traditional Chinese cooking ingredients will sell much more strongly than the ingredients would sell in a neighborhood that has a strong Indian heritage.  The store can adapt to the tastes of the surrounding community, analyze what quantities of what products will sell better, align their shelf space accordingly, and manage their subsequent inventory and orders based on sales.

Historical data can also come into play in seasonal forecasting.  Apple and pumpkin baked goods sell exponentially more in the months of September and October than any other time of year.  In being able to forecast customer demands, grocery stores are able to keep the right amount of stock for varying demands throughout the course of the year.

By accurately forecasting customer demand, grocery stores will be able to allot the appropriate shelf space to certain products.  They will save money on not throwing out expired products, be able to order the right amount of products from farmers, distributors, and manufacturers, and save money on shipping and shelving costs.  A grocery store that can forecast customer demand will be able to save money on inventory, and ultimately become much more profitable.

Questions for further thinking:

What types of products are harder to forecast demand?
How do you keep up with a neighborhood's changing tastes?
How do you extend the shelf life of products that can go bad?
What's more costly: to not order enough of a product, or to order too much?

Works consulted:




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