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Introduction
The DMAIC cycle is an important framework for improving processes. However, it can also take many months if not years to complete the cycle, meaning that the information feeding into the cycle is often less relevant by the time it becomes actionable. In this article, we will explain how Business Process Simulation can help six sigma consultants to iterate through the DMAIC cycle in as little as five minutes!
What is Business Process Simulation?
Business Process Simulation (BPS) is a method for creating Digital Twins of a company’s processes. It allows for the impacts of different process management or change initiatives to be quantified and evaluated before being implemented. As such, optimal process design and management decisions can be identified and implemented. At the same time, BPS models can be used to monitor a process in real-time and simulate it in the future to anticipate challenges ahead of time.
The DMAIC Process
The DMAIC process is a framework used by Six Sigma professionals to improve the quality of a company's processes. The acronym stands for the following phases:
1. Defining: Decide on the process you are going to focus on, map what that process looks like, and be clear on what the issue with this process is.
2. Measuring: Establish a baselines to assess the performance of the focal process.
3. Analysing: Identify and test the root causes of problems to ensure that improvements focus on where the problems stem.
4. Improving: Design process improvements that solve the identified issues and improve process health and performance.
5. Controlling: Once process changes are implemented, monitor and control the new as-is process.
However, one of the challenges of the DMAIC process is that it can often take months to iterate through the cycle a single time - from defining the problem to controlling the impact of changes. Finding a way to iterate through that cycle faster and more effectively could provide huge value to businesses’ seeking Process Excellence.
How Business Process Simulation Can Speed Up the DMAIC Process
Here’s how BPS can help to make your DMAIC process more efficient, and quicker:
- Define Stage - identify problems before they occur: Silico can not only be used as a tool to map the as-is process, it can also simulate a future state of your current process. By anticipating problems ahead of time, you can support your problem statement with simulations of what will happen if nothing is done about the issue. Using the standard DMAIC cycle, an issue may already have significant negative impacts on the business by the time it gets identified. By simulating that process into the future, Process Twins allow businesses to anticipate problems before they have any impact on the business. This means that transformation and improvements teams can get a head start and take corrective action before future issues impact the business.
- Measure Stage - forecast your future performance today: A Process Twin forecasts your as-is process into the future. This provides the perfect baseline data against which you can compare future process data after process improvements have been implemented. This can be a more accurate way to learn the impact of process improvements, as opposed to comparing against the process’ historical data which was in a different context (for example, different case volume flowing through the process). At the same time, Process Twins can import data in real-time, such that the necessary data is always ready at hand to make comparisons in an easy way.
- Analysis Stage - have data and insights available when you need them: By capturing and presenting the process and its data in the clear language of cause and effect, Process Twins allow analysts to easily identify where the issues are occurring and when they occurred. Six Sigma clients can then use tools such as fish bone diagrams and the 5 Whys to dig deeper into the causes of this issue.
For example, a BPS model of an Order-to-Cash process might show that the increase in lead times occurred due to a sudden surge in order volume, which increased backlogs at a certain under-resourced step of the process. The Twin can help quantify to what extent different events and process management decisions caused different issues. This then provides a clear basis to develop ideas for the next stage though a quantitative root cause analysis.
- Improving Stage - instantaneously quantify the impact of changes: Processes are interrelated by their nature and so are complex to understand. It is very difficult to anticipate how changing one part of a process will impact other parts. Your analysis might reveal that there is a bottleneck at one stage of a process. If you rely on intuitive or qualitative analysis, you might conclude that improving capacity/productivity at this step of the process will solve the problem. In reality, however, reducing the bottleneck at one point of the process might simply shift the bottleneck further downstream in the process. This is why simulation is needed: without it, the business would only become aware of this consequence several months after implementing the “fix”. With simulation, clients can better anticipate the outcomes of process changes, because these complex dynamics can be anticipated ahead of time. This allows you to identify the more optimal solutions the first time round, without having to get an expensive reality check.
- Controlling Stage - always stay up-to-date about process changes: Collecting data about a new as-is process can be time consuming. Presenting it in a consumable format can also prove difficult. Process Twins help on both fronts. With Process Twin software like Silico, data can be automatically integrated into the Twin, such that actual data is consistently compared against simulated data. The simulated data is essentially a variable-by-variable blueprint of how the improvements are expected to impact the business and its KPIs, whether that be the lead time of the process or FTE requirements. By integrating actual data into the model as it becomes available in real-time, Process Twins allow for a fast and effective way to monitor the impact of changes, and learn about the causes of divergence from expectation, when they occur.
Conclusion
To conclude, this article describes how the BPS method and the Process Twins developed through it can help analysts speed run the DMAIC framework during process improvements. Process Twins help businesses anticipate problems ahead of time (Define), have measurement data ready at hand (Measure), support with further root cause analysis (Analyse), find truly optimal solutions (Improve), and monitor their impact and course correct when expected changes don’t happen (Control). Analysts can iterate through this cycle in as little as 5 minutes to ensure to speed up their learning and identify the process improvements that truly address root causes.
Are you using the DMAIC process to improve processes in large organisations? How do you think the business process simulation method can help you? We hope this blog helped you understand what the DMAIC process is and how business process simulation can help you save time and make better decisions.
