A planning tool that helps management in its attempts to cope with the uncertainty of the future, relying mainly on data from the past and present and analysis of trends.

Forecasting starts with certain assumptions based on the management’s experience, knowledge, and judgment. These estimates are projected into the coming months or years using one or more techniques such as Box-Jenkins models, Delphi method, exponential smoothing, moving averages, regression analysis, and trend projection. Since any error in the assumptions will result in a similar or magnified error in forecasting, the technique of sensitivity analysis is used which assigns a range of values to the uncertain factors (variables).



Preparing Forecast inside company has many advantages. On of them that whoever is preparing them, is close to the business. But that can also be main disadvantage of such approach. Many research show that most of errors in Forecasting arise, when someone wants to enrich it with business insight, because he/she “feels” it will go this way.

Objective approach, based only on statistics and econometric, was proven to give better results in Forecasting. The rule of thumb is not sufficient any more. Properly implemented, quantitative process can give business much more information on volatility of sales, proper segmentation needed to manage portfolio and much more insight in to what drives demand.

There many threats your business can avoid by outsourcing Forecasting process:

  1. Sandbagging – underestimating sales in order to set expectations lower than actually anticipated demand. This tactic sets low sales quotas in order to ensure the are exceeded, resulting in payment of bonuses and other compensation or just for raising the morale of the company by exceeding expectations. Inaccurate information may result in manufacturer scheduling less production than may actually be needed to meet sales. When higher sales volumes materialize, there may not be sufficient time and flexibility to react; customer orders will not all be filled, leading to lost sales and potentially lost customers.
  2. Hedging – overestimating sales in order to secure additional product or production capacity. When capacity shortages exist, field salespeople and customers use this tactic to gain a higher proportion of the available goods that would normally be allocated to them. Overestimating sales ensures that any potential “upside to the Forecast” can be covered. Such behavior can send wring signals through the company’s supply chain, triggering detrimental actions that can eventually lead to overproduction of finished goods and excessive purchasing of materials. 
  3. Enforcing – maintaining a higher Forecast than actual anticipated sales, in order to keep Forecasts in line with the organization’s sales or financial goals. This misbehavior wastes company resources by prompting production of goods that will not be sold at a profit or, worse, will be obsolete. Money spent on buying components to produce those goods, paying for labor to make the products, and inventory carrying costs incurred in storing the products could be put to better use.
  4. Second-Guessing – changing Forecasts based on instinct or intuition about future sales. When an individual or group has little faith or trust in the sales Forecast, they may prefer to override the Forecast baed on their experience and/or position in the company. From corporate standpoint, it subjects the Forecasting to new biases.
  5. Withholding – refusal to share current sales information with members of the organization who need it. Person holding that information can wait till it is certain, that the agreement will actually happen. It can result in shortage of products, lost orders, lost of customers. Such behavior within organization can also undermine the trust required for effective collaboration in the supply chain, leading to service failures throughout the suppl chain.
  6. Spinning – manipulating forecasts to obtain the most favorable reaction from individuals or departments in the organization. Is used to hide sales forecasts, at least temporarily, that may not be well received by upper management who may react poorly to the bad news of lower sales expectations. It involves manipuation of data to show a forecast higher than truly anticipated. It doesn’t alert the company of potential sales shortfalls that may have to be dealt with, particularly if there is an opportunity to slow production of unwaneted goods.