If you’re looking for a way to optimize your processes — and these days who isn’t? — you will almost certainly have come across both Lean Six Sigma and process mining. Both are tried and tested methods for making your processes run better — delivering bottom, top, and green-line value for businesses.
But should you be using one, the other, or both?
It’s a big question, and one I think we have a definitive answer to. In this blog post we’re going to briefly touch on what each brings to the table, then dive into how you can use them to drive massive value, fast.
Lean Six Sigma is the combination of two different methodologies:
Lean Six Sigma helps make sure improvement initiatives are well-planned, executed, and monitored for sustained results by using a methodology called DMAIC (Define, Measure, Analyze, Improve, Control).
As we’ll be diving into each of these stages in more detail later, we won’t define each here.
Suffice to say at this stage that it is a highly manual process to approach problems by systematically identifying inefficiencies, analyzing root causes, implementing improvements, and continuously monitoring their impact.
Process mining uses the data from businesses’ transactional systems to automatically create a process map that shows how their organization really runs — and provide recommendations for value opportunities hiding in those processes.
This allows process improvement to be far more objective, targeted, measurable, and hands-off than ever before. Not to mention faster and less labor intensive than an interview-based approach like some Lean Six Sigma or more traditional consulting methods.
It was created in the late 90s as an academic exercise in drawing together the two principles of process science and data science, before making the move from the classroom to the boardroom in 2011, where it’s helped thousands of businesses discover millions in hidden value.
The truth is Lean Six Sigma and process mining aren’t competing methodologies, but complementary ones.
There’s a very good reason that Lean Six Sigma has stood the test of time: it works. But it’s not without its shortcomings, and there simply isn’t a Lean Six Sigma 2.0 that fixes the issues. This is where process mining comes in.
One of the major limitations of Lean Six Sigma is that it can be time-consuming and resource-intensive. It is unfortunately quite easy to spend hours in workshops, drawing up and discussing processes with a large number of experts, only to discover that what you’ve captured neither reflects reality nor depicts all the variants.
By using process mining during each phase of the Define, Measure, Analyze, Improve, Control process, you can help to mitigate this risk, and make sure your process for improving processes actually works well.
To demonstrate how the two work together, let’s take a look at each of the phases of Lean Six Sigma, and talk about how process mining can help.
At this stage you figure out things like the problem, team, scope, and timings of the project.
The fit for process mining is obvious here. By ingesting real-time data, you instantly get an objective view of exactly what’s going on in your processes, can define the problem, identify your stakeholders, and depending on your process mining vendor, can even set the scope of your project by saving a selection of just the process variants you want to focus on.
Here you measure the performance of the process as it currently is, and set your KPIs so you know your improvements are actually having a positive impact.
Process mining does all the heavy lifting in terms of measuring and reporting the current performance of the process. Then once you’ve set your KPIs, they can be shared with the team, so it’s easy for everyone to see how process improvements are going.
Now you know what you’re hoping to achieve, it’s time to figure out what’s causing your issues in the first place.
There are many ways process mining can help here, and this phase is where the strength of combining both methodologies really comes into play. Process mining perfectly supports the evaluation of hypotheses, which you have created with traditional exercises such as Ishikawa.
But let’s look at one example of Root Cause Analysis, the 5 Whys, in a more detailed way. In the 5-Whys, you start with a problem then ask why 5 times until you get to the root cause. Let’s look at a real example to see how process mining can help.
In this instance you can use process mining to identify and confirm root causes, completely eliminating guesswork or additional research.
Continuing with the example above, you can also identify possible fixes, like switching to different suppliers, amending your lead times, bundling orders differently, or communicating with customers to better manage expectations.
And because you’re figuring this all out in a system you’re already using, the time to implement is significantly less. In many cases you would have to wait a few months for any kind of IT implementation, but with process mining, you can create automations that write back into your source systems and get to work almost immediately or create action lists to efficiently orchestrate and standardize work across systems.
Now that you’ve got your improvements in place, you need to make sure the changes stick. Usually this would involve creating quality control plans and statistical process control, but with process mining you can use the KPIs you defined in the Measure phase to keep track of how the process improvements are affecting performance, and set up an alert for if performance drops below a certain level.
