In the previous two articles (see Setting a Performance Level (Part 1) and Setting a Performance Level (Part 2) we discussed the general requirements for setting performance levels in a Performance Based Contract (PBC). In this final part we are going to look at how to set the performance level.
In most PBCs setting the performance levels will ultimately be the role of the buyer regardless of whether the performance levels are collaboratively developed. They will typically define the expected level of performance that a seller will have to deliver to meet the buyer’s outcome (the Required Performance Level); that is, what performance level defines success for the buyer. The buyer will also define the level of performance where they no longer get any benefit from the product / service delivered by the seller (the Minimum Performance Level).
In establishing both these performance levels the buyer can take either of the two following approaches (although sometimes you may use both):
- Top-Down Approach, or
- Bottom-Up Approach.
Top Down Approach
In a top down approach, the performance levels can be taken from a range of ‘strategic’ documents that reflect the buyer’s need in terms of what performance levels would define overall success. Documents may include white papers, business cases, etc. typically used to describe the need of a buyer outlining performance expectations in order to respond to a new or changed business need. For example, the business case to outsource a particular product / service may need the seller to deliver a specific performance level to make sure the buyer can continue their internal business.
A top down approach is typically used in establishing a new product or service.
Bottom Up Approach
Unlike the top down approach, the bottom up approach uses historical performance data to set a realistic performance levels noting that it is relies on existing and relevant performance data for assessment. However, at times this may not be possible and other sources of data will need considering. In order of preference these are:
- historical data – using historical performance data for the same (or similar) products / services) is the most accurate method of performance predictions. However, before using historical data PBC practitioners must verify whether there are any changes in the following since they can lead to significant changes in performance estimates from the historical basis:
- Configuration. Is the complexity of the product / services similar? Are there more or less products being supported under this PBC? Is there a variation in the model of the product being assessed and the new contract?
- Role. Is the future usage the same between the current fleet and the new fleet? For example, the current fleet is only used 8 hours a day Monday to Friday and the new fleet is required 24 hours per day 7 days a week.
- Environment. Is the future operating environment the same as the historical fleet? For example , the current environment is used inside climate controlled buildings and the new fleet is required to be used outside from -10 degrees Celsius to +45 degrees Celsius.
- mathematical predictions / simulations – this method uses a range of techniques to find the likely performance of the products / services including the likely variation or spread of performance.
- professional judgement – least preferred way of predicting future performance since it is subject to the person undertaking the judgement (e.g. ‘gut feel’) and is subject to agendas and biases (e.g. risk aversion, loss aversion, etc.).
As discussed at the start of this article it is very common for both the top down and bottom up approaches to be used together. When used together the bottom up approach is used to define the performance of the current product / service (i.e. what performance the buyer is getting), while the top down approach is then used to define the new performance levels. The used of both approaches allows a comparison the current performance and the future desired performance and can quickly highlight the business need for change (e.g. reduce the cost per item delivered, reduce in the cost per operating hours, etc.).
Regardless of which approach you use, the key is understanding the source of the performance level and if using a bottom up approach, ensuring it takes into account any of the variations listed above.
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