As your business grows and evolves over time, your processes do too. It's not easy to admit, but your business processes probably aren’t running at optimal performance. Unless your organization has truly committed to a culture of continuous improvement, your older processes might not work as well as they should. The same can be true for new processes that have never been evaluated.
That’s where business process improvement comes in. Process improvement is exactly what it sounds like: making processes better. And to achieve process improvement, you need a plan.
A process improvement plan is a detailed roadmap of the steps an organization will take to identify and implement changes that improve an existing business process. Process improvement plans help organizations address problem areas within processes, uncover new opportunities for improvement, and be more efficient.
Before you start building a process improvement plan, you’ll need to decide which method to use. There are several well-known methods, all with similar but slightly different approaches to process improvement. And while you don’t necessarily have to follow a proven process improvement methodology, doing so can establish a common language for projects, create more internal alignment, and, ultimately, help you achieve success. So why reinvent the wheel?
For this example, we’ll walk through how to create a process improvement plan following the DMAIC cycle. DMAIC refers to the cycle’s five phases: define, measure, analyze, improve, and control. Most process improvement methods use a variation of these phases.
This phase sets the stage for your process improvement project. Here, you’ll establish a project team and work with them to collect knowledge about the process. This includes collecting information from stakeholders involved in the process, building a high-level model that shows how the process works, and establishing a focus for the project that aligns with organizational goals.
If you aren’t new to process improvement, this is a great time to consider how to push your business goals further. Look beyond “problem” areas and into “opportunity” areas that can position your process to exceed expected performance—especially for areas that can help you deliver more innovative products or superior customer experiences.
To better understanding the problem and process:
Technology such as data fabric makes it easy to discover, unify, secure, and optimize your enterprise data so you can more quickly run process improvement projects.
Phase two is all about digging into the process details. In this phase, you’ll determine how the process is currently performing and define specific measurements that you’ll track throughout the process improvement project. Some common measurements include cycle time (how long it takes to complete a process—for example, how long it takes to make a product or solve a request), lead time (the time from when an order or request is placed to when it is fulfilled), and throughput (the amount of units that go through a process, such as cases or orders).
To measure process performance:
Use process mining to automatically visualize your actual process with all its variants—a feat that would be almost impossible to do manually.
Uncovering the actual cause of a process problem is arguably the hardest (and most important) part of process improvement. This phase is critical to the success of your process improvement plan because it determines how you choose to solve the problem. Without careful analysis, the wrong solution can easily be chosen, which wastes time and resources and could end up causing other process problems.
The traditional approach to root cause analysis involves a combination of manual statistical analysis and observation to form a hypothesis about the cause of the issue. However, process mining software can automate these activities by using machine learning algorithms to identify patterns and provide suggestions for potential causes of a deviation or variant.
To analyze the root cause of a process problem:
Use process mining to auto-generate a target model, analyze all the attributes in your data, identify patterns, and see suggested causes for problem areas.
Now that you’ve done all of the hard work to understand your process, analyze how it works, and uncover the root cause of problems, it’s time to figure out the solutions you need to implement to make your process better. This involves identifying, implementing, and ensuring that you can measure the success of the process improvement cycle.
As veterans of process improvement work know, solutions you’ve applied in the past may have improved KPIs but not quite enough to meet KPI goals. In this case, consider the role of automation in your processes and how it can help you gain that extra bit of needed efficiency.
To improve process performance:
Use process automation solutions like robotic processing automation (RPA) or intelligent document processing (IDP) to help address process inefficiencies.
Making improvements to your process is only part of a broader process improvement plan. In the control phase, you’ll measure the effects of your improvements and monitor process performance over time. With continuous monitoring, you’ll know if performance dips and be more prepared to respond.
To benefit from true continuous improvement, this is a step you’ll constantly come back to. As your processes meet and exceed your KPIs, consider refining your performance measurements and goals over time. This can help ensure that processes continue to meet your needs as they evolve.
To implement continuous process improvement:
Use process mining features like dashboards to monitor KPIs, track performance trends, and understand the return on investment from improvement efforts.
Implementing a successful process improvement plan requires consistent effort. And it will likely look a little different for every project and business. But regardless of the path you take, the same best practices apply.
Here are a few tips to keep in mind when implementing a process improvement plan: