The origins of Lean Six Sigma lie in manufacturing, seeking to improve performance by eliminating resource waste and removing non-value-added activities from production processes. The DMAIC phases of Lean Six Sigma are a five-step method to optimize business and manufacturing processes: define the problem, measure the current process and how it contributes to the problem, analyze the data to finalize the exact nature of the problem and its cause, improve the process and solve the problem, and control, monitor and continue improvements.
Today, task mining uses AI to follow a similar data-driven approach to helping organizations understand and improve their business processes by eliminating non-value added activities. Task mining is technology that records and analyzes user actions on a desktop (such as checking emails or accessing spreadsheets). The output of task mining is a detailed process map showing the time spent doing named activities across all applications — highlighting inefficiencies and identifying opportunities to streamline, standardize, or automate key processes. Process intelligence is data that has been systematically collected to analyze individual steps within a business process or operational workflow, helping organizations see how people are spending time and the specific actions they are taking across all the steps and systems to accomplish their jobs.
The result of these improvements is the elimination of tens of thousands of hours and millions of dollars wasted on manual, repetitive work that could be automated.
A six-step, data-driven roadmap to process optimization
Mimica’s proprietary AI automatically categorizes tasks across unstructured, cross-system work via a six-step, data-driven roadmap to process optimization that focuses on the highest ROI improvement opportunities.
- Pick a use case and learn how the experts work— the task miner records the desktops of several subject matter experts for one week. All captured data is anonymized and all users have full control of what gets recorded and when.
- Acquire and map task-level data — GenAI is used to accurately categorize all tasks into named processes, measure how much time is spent on each, then automatically generate an end-to-end process map containing all decision points, business rules, exceptions, and variants.
- Find the highest ROI opportunities for automation — process intelligence highlights both opportunities for automation and unnecessary steps for elimination — allowing improvements to be made before automation occurs.
- Get proactive, data-informed AI recommendations — process intelligence ranks automation opportunities by time savings, automatability, and ease of automation. It then determines the best technology — GenAI, IDP, OCR — to take these opportunities forward.
- Accelerate deployment with automation blueprints — Actionable insights can be exported in various formats including PDD, BPMN, and CSV, to accelerate deployments and inform your business analytics.
- Measure and continue improvements for additional cost savings — Mimica Measure compares how work is actually being done to your process model and measures conformance to productivity benchmarks on an ongoing basis.
In just 1-2 weeks of recording your team’s work, Mimica measures and categorizes clicks, keystrokes, and actions across all systems and delivers transparency on your end-to-end processes. That transparency, an understanding of how your teams’ work gets done, is key to eliminating waste and removing non-value-added activities from your processes. Request a demo today to learn more about how Mimica’s task mining and process intelligence has helped Fortune 100 enterprises such as Merck and Goodyear to improve and power their operational excellence.
