Experience how Avercast can help you to Balance Demand & Supply for your business.
Experience how Avercast can help you to balance Demand & Supply for your business. Please complete the form:
If you have had the opportunity to work with any mid-large size company, chances are that at some point you have had to think about how supply chain and logistics affects your profession. From the goals of a sales department to the gauged demand of a marketing department; from the tracked supply of an operations department to the measured profit of a finance department, nearly everyone is affected by logistics. For this reason, basic planning and forecasting processes using non-industry specific spreadsheet software likely will not cut it.
The cohesive solution to these logistical coordination issues is revenue forecasting software. In simple terms, sales forecasting software allows you to view a “forecast” of your upcoming sales. This forecast provides information such as how many sales will take place and which SKUs and locations are responsible for those sales. From that information you can then gather what your best-selling products are, what your best locations are, what your slow-moving products are, etc. That information can be broken down even further to determine which products may be taking up valuable inventory space and which product should have more stock.
Because of the wide impact supply chain has on every department within a business, improving operations directly with sales projection software will have an impact on every department as well. By getting the quickest moving items to each of the locations that they sell the best in, a company can avoid not having enough supply to meet the demand. Adversely, slow-moving items, especially the ones that expire in some way, can always have around the exact amount needed. This can potentially save the company a significant amount of resources in avoiding both stock-outs and overstocks.
The question then arises, how does sales forecasting work? Most solutions use historical history trends to project an outcome. For example, let’s say that you own an ice cream business. One metric included in the forecasting algorithm is seasonality. It’s likely that your ice cream sales will be higher in the summer than any other season because it’s hot outside and people want ice cream as a treat to cool down. Your forecast would take that into account, as well as how well each flavor performs during which periods of the year. The history is then run through algorithms and the most closely predicted accurate one is chosen to represent the forecast.
There is even small business sales forecasting software that can use just a couple of years of sales history and can help you launch and forecast new products by comparing them to similar existing products. Inconclusion, sales forecasting is a deep and complex world with a lot to be said, be sure not to underestimate its importance and how it can impact your savings and profit margins.