• Demand forecasting helps companies purchase new inventory at the proper time, ensuring warehouse space is maximized.chart background image by Stasys Eidiejus from Fotolia.com
  
  Demand forecasting helps companies devise plans for future product sales. The goal of demand forecasting is to determine the amount of merchandise that customers will buy. Techniques include the informal method of educated guesses, as well as formal methods such as analysis of historical data and data from current test markets.
  
  

Integrated Inventory Planning

• Any demand forecasting software must be able to help the user determine the amount of inventory he needs to order. However, demand forecasting works in a range, not an exact number to be ordered. An important factor to consider for an accurate range is safety stock. This is product ordered over the forecasted allotment to act as a buffer. When working on the integrated inventory planning, users must understand that ordering is never a fixed amount per month. Instead, calculations go into deciding the amount to order, as well as the safety stock. Calculations include lead time, replenishment frequency, and forecast error. If a company uses a fixed order system rather than integrated planning, it often ends up with too much of some product and not enough of others.
  
  

Selectable Forecast Calendars

• An organization that sells multiple products knows that some products move quickly, such as those found in a grocery store, while others move slowly, such as high-end sports cars. High quality demand forecasting systems have a database of every product a company sells. This allows a custom ordering time frame for each item based on the frequency of sales. Users can tailor the ordering schedule of each item, allowing fast moving units to be ordered on a bi-weekly or weekly basis while the longer standing items can go on a quarterly ordering program. This helps save workers from doing tedious inventory of each item.
  
  

Error Measurement

• Forecasting software should offer the ability to check the percentage error for each item. Successful packages tell the user the dollar amount of every piece of inventory, and the amounts of inventory needed to achieve the goals of the organization; newer software packages can alert users of potential dangers and errors if inventory is too low. Modern software for error measurement features the calculation of standard deviation, which determines the error percentages of each product by computing the mean, or average, of the data; ensuring the data follows a normal distribution. However, some older packages may include the use of mean absolute deviation (MAD), which should be avoided because it only calculates the median, or central point, of the data; MAD is an obsolete calculation used before the standard deviation could be calculated quickly.