Demand forecasting – basics and benefits
Demand forecasting is the estimation of the volume of sales in a specific period, with the aim of planning production resources more efficiently, assessing the inventory needed and developing a budget.
An effective forecast is a valuable source of information if a company would like to optimize the use of warehouse space, or predict the best stock proportions of given products. This can be a source of considerable savings, as it saves the company from placing capital in products that are not very popular, while at the same time protecting itself from delayed delivery of a product that will be in high demand.
In summary, an effective demand forecast results:
- Increasing the use of production resources;
- Reducing purchases of unnecessary raw materials;
- Minimizing the backlog of finished goods;
- Reducing overhead costs. The following graphic shows the course of demand forecasting
Stages of demand planning
Source: own compilation based on: https://www.ey.com/pl_pl/business-5-0/inteligentneprognozowanie-popytu.
Analysis of historical data
If one were to look at historical sales data as a time series (that is, data in which the order of occurrence of observations is counted, they can present the variability of a phenomenon, for example, over time), then conclusions about sales can be drawn from the decomposition of a time series. Decomposition of a time series is the extraction of its individual components, and these can be:
a) Trend;
A trend is a tendency towards unidirectional changes, i.e. an overall increase or decrease (e.g. sales)
Source: own study.
(b) Seasonality;
Seasonality is the periodic rhythmic fluctuation of the value of a variable over the course of a year
Source.
(c) Cyclicality.
Cyclicality is understood as long-term rhythmic fluctuations in the value of a variable, it can be compared to seasonality over the years.
Source.
SAP Integrated Business Planning
Statistical forecasting can be done with the help of a variety of tools, which vary in both effectiveness and intuitiveness and transparency of operation. Demand planning can be done with a manually built model, such as in Python or R language, but also in Excel or with the help of programs designed strictly for forecasting. This article will present a specialized module of the SAP system, in which just such a forecast can be made.
SAP IBP stands out because of its ability to make predictions based on several models, as well as to manage their proportions. In the final forecast, for example, you can use 80% of the model created in SAP, and 20% of the model independently created by the planner. This reduces the limitations of the model created automatically, as well as increases the quality of the model with varied data, making it immune to errors.
The program offers demand planning taking into account several important factors, such as product life cycle and historical data. The table below shows the basic demand-related functionalities of SAP Integrated Business Planning.
Demand planning capabilities in SAP IBP
Summary
Effective demand planning leads to measurable benefits. At the same time, it is a very complex issue and requires not only statistical knowledge, but also the right tools and the ability to make the best use of them. If you would like to explore the topic further, or get specialized guidance tailored to your industry, contact us!
