Demand forecasting, sometimes also referred as sales forecasting and demand planning, is the first and the most crucial step of a supply chain planning process. Level of accuracy in sales forecasting and effectiveness of demand planning in an organization determines how efficient and successful the company’s supply chain is going to be. In sales forecasting process, sales and marketing department collaborate with each other and forecast the sales figures. Forecast of these sales figures is usually based on various factors such as targeted customer segment, geographical area, product type, past sales, promotion campaigns, season, competitors’ marketing, sales or pricing strategy, and product’s sales growth trend etc.
Let’s take an example of an assumed company AM Promotional Products and Gifts Inc. (AM PPG Inc.) and break the sales forecasting and demand planning process into sub processes to understand this more clearly.
Historical Data Collection:
AM PPG Inc Company is engaged in the manufacturing of promotional products and gift items and intends to forecast sales of coffee mug in US market for the coming year so that they can determine, as accurately as possible, how much quantity of the product they need to manufacture. The sales forecasting process starts with the meeting of sales team. Each sales team member collects previous years’ sales data of his assigned sales territory depending on how many years’ of data is available but usually it is 5 to 10 years for a well established company. If it is a new product, the sales forecast is usually based on the sales analysis of similar products either produced by the company or by the competitors.
Now, depending on the requirement historical data can be drilled down to various disaggregation levels for a more in–depth analysis e.g. product, product category, product size, customer type, geographical area, distribution channels etc. In our example I have drilled down the historical data on product, product size and distribution channel levels:
Data Cleansing and Demand Planning:
This historical data is handed over to a team of demand planners. If you look at our charts carefully, you will see that in our example this historical data reflects a specific pattern in sales growth or sales loss but it also shows some exceptionally high sales in certain months. Now demand planners analyze this exceptionally high (or exceptionally low) sale to find out what causes such a high deviations from the normal sales pattern. These exceptional deviations are called Outliers. Number of workdays is also a good example of outlier as not all the months have same number of workdays thus increase in sales in some months may be higher than other months and so needs to be adjusted before going into forecasting process. Sales hike in the last quarter of 2012 may be because of the festival season and then sudden drop in the first two months of 2013 may be because of the financial year closing or may be people just got done spending a lot of money during the festival season. Then it gets back to normal in March, April and takes a further drop in May and June which can be caused by the season change from winter to summer.
Demand planning team’s job is to analyze these sales figures, make the necessary outlier corrections to minimize the effect of causes and figure out the normal trend. Once the sales trend is normalized, the figures taken from sales team are consolidated and a meeting is convened where sales team further analyzes the data, comes up with a better forecast and that forecast is discussed with marketing team to make sure if they have any promotion campaigns planned or any kind of change in pricing or any other future event may bring a sudden hike in sales. Now sales teams and marketing teams further discuss the forecast and put down more realistic figures. These new sales figures are called Sales forecast which is further validated and then the team of demand planners develops a more accurate demand plan.
This demand plan is a long term plan, generally 12 months to 18 months- known as planning horizon and is further divided into future monthly buckets (known as time series) with forecasted figures (just like historical sales figures) and is discussed in S&OP (Sales & Operations planning) meetings with production department. Production department evaluates the resources such as availability of resources, capacity of resources etc to check the feasibility of meeting the targeted production. This is further discussed with purchase department that develops the sourcing strategy as per the requirement and gets back to the production department with sourcing plan. This sourcing plan is an integral part of the production planning process and accordingly production department finally develops a Master Production Plan and Production Schedule (MPS).
Ok so now let me rephrase it this way- demand planning is nothing but a process of reproducing the past sales pattern derived from the historical data to predict the future sales.
The above mentioned explanation is for informative purpose only and is meant to give you an idea, in the simplest way possible, about how the sales forecasting and demand planning process works. Besides the above mentioned description, there are lot more things involved in this process to predict the accurate key figures for future sales projections. If your company does not practice S&OP and demand planning process at all, I would advise you not to try this process only on the basis of above mentioned description and consult a skilled professional with a hands on experience in demand planning area.