Introduction To The Role Of Forecasting In Your Supply Chain

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Being able to estimate material needs is a crucial activity for those companies looking to have available stock to cover customer requirements rather than making product to order. By forecasting the top level / finished goods demand, production and planning teams can then explode the bill of material then utilize lead times to quantify and schedule the procurement and supply of component parts.

To avoid stock outs or purchasing/manufacturing within shortened lead times accurate forecasting is critical. Faced with the task of forecasting how much of something you will need can have serious business consequences especially for businesses operating with products that have long lead times. Getting the forecast wrong can result in either surplus materials, where the forecast is higher than the actual demand or at the other end of the scale stocks outs or a failure to meet customer demand.

There are various ways in which organizations can calculate forecasts

Statistical Forecasts

For many companies the primary process for calculating forecasts is to utilize software tools. Whilst these tools are often embedded within the organizations ERP system dedicated forecasting software packages are available.
Data is taken from the ERP system including previous demand and current transactions, a standard set of variables is then configured (typically including desired service level and length of forecast) and the likely demand is then generated.

Statistical forecasts are very much based on actual data created from system transactions. The information used has to be comprehensive enough to ensure that a reliable output is produced. One of the challenges of this approach is that there may be market intelligence that the can influence the forecast that is not transactional – for example the award of a new customer contract, or a new product launch – which maybe difficult (if not impossible) to predict on historical transactions alone. This form of forecasting is also reliant on ERP system data integrity.

Non Statistical Forecasts

Another method of forecasting is without the use of statistical data. These are forecasts that have been devised from subjective estimates of what demand might be. The forecast may take a number of inputs from previous demand through to market intelligence but is often based on current or near term demand. The non-statistical forecasts can take into account sudden changes in production, sudden fluctuations that are not based on statistics, so there are times when both types of forecasts are required.

Summary

Forecasting is obviously difficult, simply because it is not an exact science and it as the supply chain is subject to sudden changes, difficulties and external factors – forecasts must be maintained. Forecasting provides the organization with a guide to future demand. Remember though, despite both experience and knowledge of the current and future environment no forecast will be fully accurate.

Introduction To The Role Of Forecasting

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The forecasting process is extremely important for most businesses. In many cases the forecasting activity drives supply chain processes including the procurement of goods and corresponding inventory control. It can be a challenging and complex activity depending on the business environment and in many cases is analogous to crystal ball gazing albeit one in which you are armed with some level of information.

The key output required from forecasting is determining how much of a product will be bought by customers (or consumed by internal customers). Overly optimistic forecasts may result in the acquisition of too much raw materials (therefore wasting valuable capital). Where the forecast is too low and does not match demand then the company may not meet customer demand and may either lose customers or fail to meet agreed service levels.

What you create when you carry out a forecast

A forecast will typically deliver the anticipated demand profile over a number of months/years for the top level product/part– in many environments this in turn will drive procurement activity that will utilize known lead times to order to procure material in time to meet the the requirements of the forecast.
While the actual forecasting processes may vary from company to company the key concepts are fairly common and are utilized by most businesses.

Statistical Forecasts

Many organizations choose to utilize specialist forecasting software that commonly take data from the ERP system and extrapolate it into a future demand profile. For many organizations this data analysis is supported by what is known by the organization (i.e. market intelligence) to tune the demand profile into what is thought to be realistic.
Data integrity is obviously key for organizations following this approach and the benefits include that the organization is basing its forecast on non-subjective transactional data (often that which is happening in real time) the forecast is configured in such a way that the forecasting solution can deliver a number of outputs or models depending on pre-configured criteria.

Non Statistical Forecasts

There are other forecasts that are often grouped together as non-statistical forecasts. These are forecasts that have been devised from quantities that are determined by production planners. The forecast is usually based on current demand alone.

The Importance Of Forecasts

Forecasts are vital if the supply chain is to be kept stable. If the supply chain becomes vulnerable to stock outs or if there are no accurate forecasts made, then the manufacturing function can be severely impacted putting strain on the supply chain and supplier lead times as the result of inaccurate forecasts are attempted to be mitigated.