Should-cost modelling is one of the most valuable techniques in procurement. However, despite its immense value, it’s surprisingly underutilized and rarely trained. This gap is astonishing given how versatile the technique is—it can be applied to almost any raw material.
So, what exactly is should-cost modelling, and how can it be used to enhance procurement strategies? Let’s explore the fundamental concepts and walk through an example to illustrate this concept.
Should-cost modelling is a strategic tool used to estimate the ideal cost of a product or service based on its raw materials, manufacturing processes, and overheads. Unlike simple cost breakdowns, which merely provide a directional estimate, should-cost models dig deeper to create a detailed, data-driven analysis that helps organizations understand the true cost drivers.
A typical cost breakdown might look something like this:
Product: Organic Almond Butter
Cost Element |
% |
GBP/T |
Organic Almonds |
50% |
500 |
Packaging (Glass Jar) |
8% |
80 |
Processing |
15% |
150 |
Sales & Admin |
7% |
70 |
Central O/H |
10% |
100 |
Logistics |
5% |
50 |
Profit |
5% |
50 |
Total |
100% |
1000 |
This breakdown gives a high-level view of cost allocation but lacks the granularity to pinpoint inefficiencies or negotiate better prices.
A should-cost model, on the other hand, determines almond butter production should actually cost by evaluating key factors such as raw materials, labour, energy, and profit. It provides a clear picture of what the product should cost under efficient and realistic conditions.
A should-cost model goes beyond this simple breakdown by including a combination of hard data and estimated elements, providing a more comprehensive and realistic cost estimation. This model can incorporate:
Here’s an enhanced version of the previous example, focusing on almond butter production:
Item |
GBP/T |
Whole Almonds |
500 |
Additional Ingredients (e.g., salt, oil) |
10 |
Jar Packaging (Glass + Lid) |
20 |
Label & Branding |
10 |
Pallet |
15 |
Labour |
50 |
Energy |
40 |
Factory Overheads |
25 |
COGS (Cost of Goods Sold) |
670 |
Road Haulage |
40 |
This breakdown provides a detailed view of the key components driving the cost of producing almond butter, showing where resources and expenses are allocated in the production process.
It is important to think carefully about the exact questions you want to answer and the different scenarios you want to depict before you start to build your model. This will help you to determine the data you'll need to gather and incorporate, in addition to directing the overall design. You can make sure the model stays focused and in line with your business objectives by outlining your goals precisely and knowing the kinds of analysis you wish to perform. More accurate simulations and forecasts are made possible by taking potential variables and restrictions into account up front. Building a strong basis during the planning phase enhances the model's quality and applicability, making it an effective tool for decision-making.
A should-cost model is normally based on these 3 equations:
COGS = Raws + Packaging + Conversion
Gross Profit = Revenue - COGS
Net Profit = Gross Profit - Central Costs
It’s important to thoroughly understand these equations when structuring your should-cost model.
The art of should-cost modelling lies in completing the data accurately. This often involves:
The more accurate and detailed the data, the more valuable the should-cost model becomes for procurement teams looking to control costs, negotiate better terms, or identify potential areas for cost-saving improvements.
Once your model is made, it becomes a powerful tool for extracting valuable insights across multiple areas. It can be used to evaluate specifications by providing a structured approach to determining product or service requirements based on real data. This helps ensure that all technical and performance standards are clearly defined and achievable. Additionally, your model can serve as the foundation for contract negotiations, offering a data-backed framework to support terms and conditions, ensuring they are both fair and realistic. It can also enhance forecasting accuracy, helping to predict future trends with greater precision and enabling proactive decision-making. By incorporating benchmarking, you can compare different suppliers or alternatives, making it easier to identify the best value. Moreover, the model can be used to experiment with various variables, such as energy consumption or material costs, providing a deeper understanding of their potential impacts. Finally, it serves as a strategic asset in negotiations, giving you leverage with well-informed, data-driven arguments that enhance your bargaining position.
Should-cost modelling is a powerful yet underused technique in procurement. By providing a granular, data-driven view of costs, it allows procurement professionals to move beyond mere cost breakdowns and make more informed, strategic decisions. Whether you’re negotiating with suppliers or seeking to reduce overall costs, incorporating should-cost modelling into your procurement strategy can give you a significant edge in today’s competitive marketplace.
So, are you ready to harness the power of should-cost modelling for your procurement needs?
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