Transforming Six-Sigma with Process Intelligence

Six-Sigma is All About Process

Six-Sigma pertains to a group of analytical methods that companies across industries leverage to eliminate defects in their products and processes. The core crux of this methodology is simple- every step in a business process that helps deliver a product or service is also an opportunity to introduce a defect and the methodology focuses on reducing the variation in the processes that lead to these defects.

Improving process quality emerged as a key requirement that SAPinsiders identified in SAPinsider Process Automation and S/4HANA research report. Considering that Six-Sigma is all about improving process quality, and is a methodology designed around business processes, there is a big opportunity to leverage process intelligence to further enable Six-Sigma methodologies. This article explores how process intelligence tools can help organizations build robust Six-Sigma capabilities. These tools help capture the process as-is through process discovery and help gain process insights, build simulation models around existing processes, measure performance, etc. A key point to note however is that process intelligence tools are often used with systems like ERP, CRM. HCM etc. It is hence imperative that the data needed is being captured by the ERP system that the process intelligence tool will interface with. Leading process intelligence tools, like SAP Signavio , Celonis, UiPath , BluePrism and AutomationAnywhere can help you build and automate robust Six-Sigma programs.

Leveraging Process Intelligence Tool in The DMAIC Process

Six-Sigma methodology is employed in a systematic project-oriented approach through the define, measure, analyze, improve, and control (DMAIC) cycle, as shown in the figure below.

Figure: DMAIC methodology as defined by the American Society of Quality (ASQ)

Define- The first step, define, is where most of the input comes from customer intelligence tools. In this stage, customer priorities and critical-to-quality (CTQ) characteristics important to customers are identified. This then helps define the project itself. The project is based on business objectives, customer needs, and feedback. However, a robust understanding of the current state processes involved in delivering the product to the solution is critical. This is where the process discovery capability of process intelligence tools comes into play. Using data from process discovery approaches like run charts and process maps can be created that help define the project.

Measure and Analyze– Measure is the step where process intelligence tools start playing a key role.  This step is all about determining how to measure the process, understand process performance, identify key internal processes that influence critical-to-quality (CTQ) characteristics, and measure the current level of defect.

In analyze phase, you determine the most likely causes of defects, understand the drivers behind them, and identify key variables that are most likely to cause process variation.

Process mining and discovery capabilities within process intelligence tools can help with these two critical steps. The discovery capability helps you understand your current state of operation, see your real process data points and understand your process dynamics. Using the process discovery data, you can create Pareto charts, root cause analysis (RCA), Failure mode and effects analysis (FMEA), and fishbone (cause and effect) diagrams to understand the drivers.

Figure: Pareto Chart (Source: American Society of Quality, https://asq.org/quality-resources/pareto )

 

Figure: Fishbone diagram (Source: American Society of Quality, https://asq.org/quality-resources/fishbone )

Improve -Improve process pertains to implementing the fixes to the drivers identified in previous phases. In this step, you identify the means to remove the cause of defects, confirm the key variables and their impact on CTQs, identify the minimum acceptance ranges of key variables, and define a system for measuring variations of the variables. Finally, you then modify the process so that it stays within the acceptable range.

As you can envision, all the data for Improve phase is the data that you have already captured via process discovery for use in the previous phase. You can use this data to build design of experiments (DOE) and opportunity flow diagrams that will help with all the key tasks that fall under “improve”, as defined above. Simulation functionality in many process intelligence tools will help you evaluate your approaches as you move along the tasks in the “improve” phase.

Figure: Opportunity flow diagram (Source: https://baelearn.uncg.edu/wordpress/ism678/wp-content/uploads/sites/12/2012/02/Opportunity-Flow-Diagram.pdf)

Control – This is the phase where you monitor the process post-implementation and ensure that the improvements made are maintained. The goal is to implement tools that the key variables remain within the maximum acceptance ranges under the modified process. Process mining and intelligence from improved processes can be monitored using process control charts to ensure that improvements or enhancements are working and reducing process variability.

Figure: Process control chart (Source: https://asq.org/quality-resources/control-chart)

What Does This Mean for SAPinsiders?

It is about the culture. Six-Sigma methodology has existed for more than half a century now. Some companies embraced it effectively, making it part of their culture and flourishing. Others who tried embracing failed. Why? Because like many other things, this is more about the initiative, the will of your workforce to embrace the method. A half-hearted approach means that you can check a box but will not be able to leverage the benefits. In the context of leveraging process intelligence tools for Six-Sigma, the same principle applies. Technology now allows you to build Six-Sigma capabilities rapidly however, the key to extracting actual benefits lies in how you make such methodologies part of your culture.

Customize and enhance. The important foundational aspect is to have access to data, flows, and analytics through a process intelligence tool. If you want, you can then use that foundational capability to build a customized Six-Sigma solution on top of it using open-source or vendor-provided add-on tools to automate your continuous process improvement journey. Some exciting possibilities exist to leverage AI and ML to take this beyond fundamental approaches like DMAIC.