How a should-cost model/analysis can benefit your procurement process
A should-cost model (also known as should-cost analysis, cost breakdown analysis, or clean sheet analysis) refers to the exercise to determine what a product or service should cost based on several cost drivers including:
- Raw materials cost
- Manufacturing cost
- Labour rates
- Overhead costs
- Tax & transportation costs
- Addition of fair markup for profit
Understanding what a product or service should-cost is crucial to identify cost savings opportunities. If your organization doesn’t have full visibility into the relevant cost drivers and production processes, you will most likely struggle due to incorrectly priced components. This weakens your bargaining power as well as makes it more difficult to cut costs.
A should-cost model helps estimate costs, but even more important, it provides crucial evidence to suppliers that you can utilize in negotiations. Performing regular should-cost modelling, skilled procurement professionals will be able to achieve supplier costs much closer to their desired target price.
Before anything else, it’s important to have a solid understanding of the product and the processes to produce it from the raw material stage, while at the same time adhering to compliance and quality requirements. The accuracy of it is highly dependent on the knowledge and skill of the person or team building the should-cost model.
So, who’s supposed to build it? The procurement team with the insight into the processes that are likely to be outsourced? Or the engineering team with the deep knowledge behind the product design and its numerous nuances? In the end, it’s a joint effort where everyone will have to chip in to properly build the should-cost model to ensure its accuracy.
The should-cost methodology generally consists of three steps:
- Data collection: The first step of the should-cost methodology is gathering relevant data for the product or service. This includes current data – if there is any – from your suppliers, as well as global data from suppliers all over the world regarding materials, labour, conversion costs, overheads, logistics, profit, etc.
- Systematic expansion: Expand upon the key cost drivers mentioned in Step 1.
- Analyzing and developing cost insights: Analyze the gathered data and information, compare your current data against the global data to identify cost insights and potential cost saving opportunities.
Optimize your negotiation game with Prognos
With Prognos platforms and tools, you get access to the cost data you need to successfully create an accurate should-cost model to identify potential cost savings opportunities and get the most out of your suppliers, with data tailored for your specific situation.
We want to be clear from the start and preface that Prognos solutions are NOT capable of automating the process of creating a should-cost model. We can, however, on a consultary level, help you perform one manually.
Through our platform Prognos Tailored you get access to continuously updated, interactive reports supporting the whole process of creating a should-cost model. Here you can dig deep into your materials, compare prices to your cost development, export the graphs, or export the underlying data for further analysis.
Prognos Online is a supporting should-cost analysis tool, giving you access to all data you require to perform a should-cost analysis on your own. It’s an interactive online tool capable of transforming the data to fit your needs. Prognos Online gives you access to over 8 000 up-to-date indices on raw materials, components, wages, and currencies.
We also deliver should-cost Trackers where we perform the should-cost analysis for you. Our experts analyze the cost structure of your product and deliver a tailor-made report with indices for all included cost drivers. Do note this doesn’t result in the should-cost for the specific product (the par value), rather a should-cost development model about how your price SHOULD have progressed until today. The should-cost model enables you to evaluate and compare price development against cost development, and can be reused to perform continuous should-cost analysis of the same product or service in the future.