Polish company Netwise S.A. joins the collana Group
Home / Polish company Netwise S.A. joins the collana Group The
Paul M.
13 August 2026
Any company that manufactures goods and requires materials to produce its end products must take account of its material requirements. What are the respective material requirements, and what demand for products, spare parts and saleable intermediate goods can you expect in the future? Accuracy is essential here to ensure that production does not come to a standstill.
The solution lies in demand forecasting, for which various mathematical and statistical methods are also used. Which types of demand are necessary and appropriate, what methods of demand forecasting are available, and how can you apply them in practice? We provide key definitions and clarify these questions in our article.
By definition, demand forecasting is a business management process that companies carry out to determine their requirements. In materials management, demand forecasting is one of the most important methods, as it ensures the company’s supply of materials and identifies future material requirements. By definition, demand forecasting is also known as demand quantity planning, material requirements planning and procurement planning.
Because it helps to optimise costs and storage space. When it comes to material procurement, precision is essential to avoid both overstocking and understocking. This applies equally to goods, spare parts, saleable semi-finished products or assemblies, and production materials. In other words: determining demand forms the basis for all procurement strategies.
It is not only procurement that benefits from this analysis, but also production. What raw materials, semi-finished products, assemblies and individual parts do you need to complete orders or keep production running?
Here’s an example: A company manufactures wooden garden benches. In this case, it makes a real difference whether the requirement is for 2 tonnes of wood, 12,000 screws and 30 litres of oil, or whether you only need 1 tonne of wood and 4,000 screws. An order for 4 tonnes of timber and 16,000 screws would, in fact, be an over-order, which incurs storage costs and ties up capital. Ordering too little, on the other hand, causes supply bottlenecks.
Before we move on to the methods for assessing needs, it is first necessary to categorise them according to the following types of need:
| Available stock = | +Stock -Reserved materials +Open purchase orders and production orders -Safety stock |
| Net requirement = | Gross requirements – available stock |
There are various techniques used in demand forecasting. In addition to estimates, you can, for example, obtain some figures directly from ERP software. Various mathematical and statistical methods are also used. The following methods are available for demand forecasting:
This method is based on current production plans and bills of materials. Primary requirements are determined by existing orders and plans. Using these, you can then plan secondary and tertiary requirements, calculate the necessary auxiliary materials and resources, and determine the gross and net requirements.
Under the consumption-based (stochastic) method, future requirements are determined on the basis of past consumption.
An example? For July and August, the method calculates a quantity based on previous consumption and possible forecasts. Mathematical statistical methods (stochastics) are used, which allow you to optimise the results. These are particularly useful when sales volumes fluctuate.
The key factor is the pattern of demand, which may be constant, trend-based, seasonal, sporadic or highly volatile.
Put simply, rule-based demand forecasting is an ‘if-then’ scenario. If a particular situation arises, a specific material requirement results. For example, if a customer orders a car with specific features, this creates a requirement for specific parts and materials (e.g. leather in an unusual colour, an on-board computer, etc.).
If only limited historical data is available, you can estimate the expected demand. The estimate should then be based on empirical evidence and a certain level of expertise. However, this method is not recommended if another method is better suited to determining demand.
Each of these methods has its own advantages and disadvantages, which you should weigh up. We have therefore put together an overview of the key points below.
| Method | Advantages | Disadvantages |
|---|---|---|
| Programme-based needs assessment | Lower stock levels, as production is carried out to order | Reduced ability to fulfil orders, as production only begins once an order has been received |
| High accuracy in determining requirements based on bills of materials | Longer lead times due to the procurement period | |
| Consumption-based demand forecasting | High delivery reliability and short lead times, as products are already in stock | Higher warehouse utilisation, as production is geared towards the market |
| Minimal effort required as calculations are based on historical figures | Inaccurate stock figures due to historical data | |
| Rule-based demand forecasting | High cost-effectiveness thanks to standardised processes | Low volatility, as seasonal changes or market fluctuations are not taken into account |
| Easy to plan due to fixed parameters | Limited adaptability | |
| Subjective estimate | Minimal effort, as no analyses and, in most cases, no data are required | Decisions are subjective and prone to error |
| Can also be applied to new products, even without historical data | Decisions depend on the expertise of individual people |
Bear in mind, however, that these methods can have a particularly positive or negative impact on certain types of products and product groups. For example, programme-based demand forecasting is particularly suitable for specialised products, whilst consumption-based demand forecasting is particularly well-suited to mass production.
When carrying out a needs assessment, you should, in practice, take additional precautions and monitor developments. To this end, you can make use of other methods, which we outline briefly below.
As a rule, warehouse capacity is limited. It is therefore not always possible to actually stock the optimum quantity of goods for all end products. This is where ABC analysis comes into play; it helps you to set priorities and determine for which goods you should optimise your demand forecasting.
Put simply, divide your products into three categories:
A-grade products: These generate particularly high turnover and are a top priority
B-grade products: These make a moderate contribution to turnover and are only of medium priority
C-products: These are items with low sales figures and are therefore given low priority
Focus on Category A products and optimise demand forecasting for them.
The target/actual method, on the other hand, helps you to check whether current figures match the planned figures. This approach is particularly useful in rolling planning, as it enables you to control and adjust the flow of materials. For example, how much of the requirement (gross requirement) is actually available, and what is the current delivery status? You can quickly identify discrepancies in requirements planning and prevent delivery bottlenecks or production stoppages.
Now here is another real-life example that illustrates how to assess requirements.
Example: A company manufactures pyjamas. It expects to produce 100 pyjamas during the planning period.
| Explanation | Quantity of material | |
| Basic needs | The pyjamas are the end product | 100 pyjamas |
| Secondary requirements | To make a pair of pyjamas, you will need: 3 metres of fabric, 2 buttons, 5 metres of thread | 300 metres of fabric, 200 buttons, 500 metres of thread |
| Tertiary needs | As an aid, add 10 ml of lubricant to the sewing machine for each pair of pyjamas. | 1,000 ml of lubricant, 1 sewing machine |
| Gross requirement | Secondary needs + tertiary needs | 300 metres of fabric, 200 buttons, 500 metres of thread, 1,000 ml of lubricant, 1 sewing machine |
| Net requirement | Gross requirements – available stock. Available stock: 100 metres of fabric, 150 buttons, 200 metres of thread, 80 ml of lubricant, 1 sewing machine | 200 metres of fabric, 50 buttons, 300 metres of thread, 920 ml of lubricant |
In order to comply with the planning period, the business must purchase the funds to meet its net requirements.
High-performance ERP systems such as collana diva now help you to simplify your materials management and optimise your materials planning. collana diva now brings transparency to your stock levels, so that you know your primary, secondary and tertiary requirements at all times. You can use both historical data and forecasts to determine your requirements.
Home / Polish company Netwise S.A. joins the collana Group The
The collana Group has launched the video podcast ‘CoreShift by collana’. The topics covered are: AI, digitalisation and transformation.
The collana Group has achieved a milestone that few Microsoft partners can boast: as a group of companies, it now holds all six available Microsoft Solutions Partner designations and is therefore automatically awarded the coveted „Microsoft Solutions Partner for Microsoft Cloud“ distinction.
This status is not down to any single area of expertise, but rather to the combined expertise of the Group’s ten specialist subsidiaries: from ERP implementations in manufacturing, retail and the healthcare sector, through bespoke software development, to business intelligence and AI solutions.
The benefit for you? With collana diva now, you can manage demand forecasting effectively – without overstocking or understocking. Processes run smoothly and efficiently, and you can fulfil orders on time.