Requirements analysis is a systematic process for determining and quantifying a company's current and future material requirements. It forms the basis for efficient procurement planning and helps the purchasing department to avoid supply bottlenecks and achieve cost savings through optimized order quantities.
Example: An automotive supplier carries out a quarterly demand analysis for electronic components, in which an annual requirement of 50,000 units is determined by evaluating consumption data, forecasts and seasonalities, resulting in a 25% reduction in stock levels and a cost saving of 120,000 euros.
The requirements analysis is a fundamental step in the procurement process in which a company's exact need for goods or services is determined. It serves to define the requirements in terms of quantity, quality and delivery time. A thorough analysis allows resources to be used efficiently, costs to be optimized and security of supply to be guaranteed.
In purchasing, the requirements analysis forms the basis for all further process steps. It enables procurement strategies to be planned and implemented effectively. By knowing the exact requirements, companies can select suppliers in a targeted manner, take advantage of quantity discounts and optimize delivery times. It also helps to minimize stock levels and avoid bottlenecks.
The requirements analysis enables purchasers to determine the exact demand for materials or services and thus optimize procurement processes. This reduces storage costs and ensures that the required resources are available on time.
Situation: A furniture manufacturer is planning the production of tables and needs to determine the demand for wooden boards for the next month.
1. planned production quantity: 1,000 tables
2. Material requirement per table: 2 wooden boards
3. Safety stock: 5% of the total requirement
Calculation of the total requirement:
Basic requirement = production quantity x material requirement per table
Basic requirement = 1,000 tables x 2 wooden boards = 2,000 wooden boards
Consideration of safety stock:
Safety stock = basic requirement x 5%
Safety stock = 2,000 x 0.05 = 100 wooden panels
Total requirement including safety stock:
Total requirement = basic requirement + safety stock
Total requirement = 2,000 + 100 = 2,100 wooden panels
Application: With this result, the purchasing department can order 2,100 wood panels in order to implement the production plan without interruptions and at the same time minimize risks due to material shortages.
→ Precise data acquisition: exact documentation of historical consumption data and production planning as the basis for reliable demand forecasts
→ Cross-functional collaboration: close coordination between purchasing, production and sales to determine requirements holistically
→ Dynamic adaptability: flexible systems for prompt updating of demand quantities in the event of changing framework conditions
→ Forecast uncertainty: fluctuating market conditions and volatile customer requirements make precise predictions difficult
→ System complexity: integration of different ERP systems and data sources for uniform requirements planning
→ Cost optimization: balance between sufficient stock and minimal storage costs
Future trends and strategic implications:
"Demand analysis is evolving from a reactive to a predictive function thanks to AI and machine learning."
→ Predictive analytics for automated demand forecasting
→ IoT-based real-time recording of consumption data
→ Digital twins for simulations of different demand scenarios
→ Blockchain-supported transparency in the supply chain
Demand analysis is an indispensable tool of modern purchasing, which contributes significantly to the company's success through precise planning and systematic implementation. It not only enables cost savings and increases in efficiency, but also minimizes risks in the supply chain. With increasing digitalization and the use of AI-supported technologies, demand analysis is constantly evolving and offers companies new opportunities for even more precise and future-oriented demand planning.