Happy path is the designed process flow that leads to a happy customer. The happy customer is the most important process KPI. Achieving a happy customer outcome alone would be quite easy if there were no financial restrictions. The ultimate goal for every private company, however, is not just to create happy customers but to increase shareholder value. Sure, this is achieved through happy customers but it also requires efficient processes. The better the internal efficiency, the better there is to be shared - not only with shareholders but also with employees and society. In our process mining projects, we have discovered that often less than half of sales orders follow the process designed to be efficient.
What is Happy Path?
What actually is internal efficiency and what does it require? Internal efficiency is achieved through harmonized and optimized processes. That is the reason why each organization has at least at some point spent time in designing their business processes. The objective of the process design is to define an operating model that results in happy customers as efficiently as possible. The optimized business process is called the happy path within the QPR's process mining solution.
Why Happy Path with Process Mining?
During the last year, I’ve visited dozens of leading enterprises and I’m yet to meet one with a happy path KPI or similar in place (existing QPR ProcessAnalyzer customers are obviously an exception). Most companies have some process KPIs in place, like lead time, and different measurement points to different parts of the process. The challenge with these individual snapshots is that they are all independent measures and don’t provide real insight to process flow. A good example of a process KPI that many companies would like to use but currently lack the means to implement is First Time Right. In order to measure first time right and happy path, you need technology that understands the flow of events – and currently, the only available product category that does this is process mining.
Why then is a happy path process KPI so important? What does happy path mean in practice? The concept is very simple. It tells us what percentage of cases such as sales orders, purchase orders or service requests have been handled in line with the agreed process. Any variation from the designed process results in not being counted as a happy case. Companies not having the happy path process KPI in place are at the same time doing process improvement projects and even big investments into improving process efficiency. This is all done without having fact-based information about current process performance.
Imagine that in reality, the current happy path result would be less than 50%. In practice, this means that less than every other process instance is flowing through the agreed process (based on our experience from dozens of projects this is quite a typical result). In other words, the process is far from being well harmonized and has lots of different variations. Implementing a change as a result of a process improvement initiative in such a circumstance has a random effect: the improvement is based on the existing process design which in reality is followed in less than half of the cases. I wouldn’t spend a dime in a process improvement project without having the happy path available. The beauty of process mining is that you don’t only get the happy path but also all possible fact-based details behind those unhappy cases. For instance, all different process variations are visualized and their root causes can be analyzed.
To summarize I suggest the following approach to process improvement:
1. Implement the happy path process KPI. Utilizing QPR’s patented process mining technology, the KPI can be implemented in two weeks regardless of the underlying operative IT system.
2. Analyze the process variations and unhappy cases with their root causes.
3. Begin process improvement from the business that has the biggest effect i.e. the lowest happy path result and highest volume (QPR ProcessAnalyzer has an out-of-the-box analysis that provides this information). Do not implement a change in the process but reduce the variation first.
4. Enjoy and celebrate the instant results that this new data-driven approach delivers!