Creating effective process KPIs
A quick guide through the different steps
By our Consultant Marieke Gernay
What are effective process KPIs?
Key performance indicators (KPIs) are quantifiable measures used to define success and evaluate the performance of an organization regarding a predetermined objective. They provide a way to align the mission, values, vision, strategy, and behavior within a company. These indicators are present at all levels of an organization. From the strategic to the operational. They also vary with their purpose. In this guide, the focus will be on key process indicators, which we will refer to as KPIs. You can read more about strategic indicators here.
To make KPIs effective, they need to be presented clearly. This way decision makers quickly get an overview, which allows them to act when and where necessary (read more on making insights actionable).
So, how do we make and use effective KPIs? To explain this, we distinguish four parts.
- Define the objectives: What do we want to achieve with the process? What are the goals of the process?
- Define the KPIs: Which key measurements will show progress on these goals or flag issues?
- Gather the data: Collect the data for the KPIs defined in the previous step.
- Analyze the data: What are the issues? What causes them?
This is an iterative process. The analysis of the indicators may lead to changes in priorities, adjustments in what is measured and/or how it is analyzed.
Define your process goals
On a high level, processes can be broken down in a few stages:
- Input: What is necessary at the start of the process?
- In process: Which steps are needed to go from the input to the output of a process? This may go from very simple process variations (e.g. only sequence of steps) to very complex (many built in process variations).
- Output: What is the direct result of the process? What is delivered?
- Outcome: What are the indirect results from the process (expectations)? This may include customer satisfaction or loyalty. It may be harder to measure, let alone identify the root cause for improvement. In other words, the outcome describes the reasons why you do the process. These are the goals.
Each goal defined in the previous step needs to be broken down in measures that can be monitored. These are the KPIs. They may look at the entire process or part thereof. For example, looking at the entire process the total throughput time may be long. However, part of that time may be due to waiting for information from an external party (e.g. action from client). This cannot easily be controlled in the process and it would be more useful to look at the parts of the process that are within the company’s control.
These measures do not only need to be SMART, but we also need to balance the different performance perspectives.
The commonly used balanced scorecard (BSC) methodology describes four perspectives for strategic KPIs that should be kept in balance: financial, customer, internal processes, and learning and growth. For process indicators the perspectives that need to be balanced are slightly different:
- Time: Time can refer to the throughput or lead time (of parts) of the process, from input to outcome. It can also mean timeliness (being on time, deliver on promised time). Identifying and dealing with bottlenecks (queues) could make the process faster.
- Cost: Costs can be reduced by reducing non-value added activities, rework, and waste. Identifying those steps will make the process more efficient and therefore reduce cost.
- Quality: Is the quality of the output as described/intended? How much input/in process/output is rejected? Can this be reduced?
- Customer: Defining process performance from an organisation’s perspective may not fully align with that of a customer. One common example is that the customer wants things on time. On time may not mean as soon as possible, but that the previously set expectation is met.
- Complexity – Flexibility: Process compliance and limiting process variations are important. On the other hand, if elements that affect the process suddenly change (such as ‘Can the system handle exceptions?’), then the process and systems should be flexible enough to deal with those changes.
- Process automation: This is a big driver in business today. We should measure how often (part of) the process is successfully completed without the intervention of an employee (touchless cases). Doing so will allow employees to focus on more complex cases/tasks that require their expertise.
What is key?
Looking at different objectives from multiple perspectives may lead to the definition of many indicators. On top of that, current software can provide almost any indicator you can think of. Part of the challenge is therefore to determine which indicators are key.
A car dashboard is a good example. It only provides essential information for you to drive safely. There are only a handful of lights that will come on when something is wrong. If there were too many indicators the overview would be lost.
Gathering data for process KPIs may require the combination of information from different sources of information and may go across different departments.
Traditionally, gathering data was a manual process often involving the combination of different sources of information. These days tools like process mining allow for a much more automated process. Unlike BI, which needs to make assumptions, process mining is based on the real situation.
Analyze in order to identify, investigate, and predict issues.
Lastly the data that was presented in the previous step needs to be analyzed and interpreted. There are various ways of doing this. Most notably using BI and/or process mining dashboards.
Presenting the data in a multi-layered dashboard using the DAR principle allows a quick overview, while also permitting to investigate issues further. Read more about efficient dashboard design in our previous article. And feel free to use this checklist to improve your dashboard.
Great KPIs should not only identify issues in the past (lagging indicators). They should also have the power to identify issues at an early stage, before they become problematic. Or even predict them (more information in this recent article).
Independent of the methods, the analysis may require further investigation in the root causes of the issue.
The analysis may lead to a change or refinement of the earlier defined indicators, which brings us back to the start of the cycle and the end of this guide.
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