Process automation is all the rage as companies seek to drive out cost, operate with greater speed and free employees to focus on more high-value tasks. But in our experience, processes as they’re performed day to day are often run more on tribal knowledge than on codified, documented directions and may not be fully known even by the teams that created or inherited them. Ineffectively designed processes can slow business performance and hurt productivity.
We recommend starting the redesign with a clear snapshot of the “as is” process and the application of tools to assess how key processes are performing. That’s where process mining comes in. An insight-driven approach, process mining pulls event-related data from customer relationship management (CRM), enterprise resource planning (ERP) and other applications to form a model of the way a business process actually, versus theoretically, functions within the organization. By capturing how work happens, including who did it, how long it takes and any deviations from average, process mining ruthlessly exposes bottlenecks, non-compliant paths and other impediments often unseen.
Applied properly, process mining precedes intelligent process automation (IPA) and robotic process automation (RPA) initiatives; process mining suites can be used to create automation templates and gauge the health of existing processes — identifying which are efficient and which require an overhaul.
Given the value of automation, it is no surprise that companies are beginning to invest in process mining to optimize how work gets done. Since process mining is relatively young, we field many questions about prerequisites and benefits. We’ll start with where to start and follow with examples for what can be achieved.
When preparing for a process mining initiative, carefully consider what to tackle first. While some companies understandably begin with a small proof-of-concept project, we recommend instead focusing on processes that require improvement and have significant potential impact. Order-to-cash or procure-to-pay are examples. Improving them can not only drive out cost but also improve productivity and efficiency.
With many organizations investigating this emerging technology, we’ve used our experience to develop a checklist to help simplify a path forward:
Identify business goals
Determine a timeframe for data analysis
Identify potential benefits
Identify key stakeholders
Identify data sources for the process
The following figure shows a typical timeline.
What does this look like in practice? We’ve worked with clients worldwide on process mining projects; here are some examples of client work that shed light on real-world impact.
For a mortgage lender client’s collateral management claims process, anecdotal evidence suggested there was excessive rework, unnecessary employee effort and non-conforming process variations. Worker productivity was highly variable, and a significant percentage of claims were charged off, rejected or required resubmission.
Our process mining/analytics included:
The outcome included improved workflow processing, resulting in a $3.8 million improvement in cash utilization due to a reduction in the claims rejection rate, and improved customer satisfaction.
We recently helped a large healthcare provider identify solutions for the higher-than-normal cycle times required for configuring member benefits. To address the issue, the company sought to identify levers to drastically reduce the baseline cycle time of 26 days while ensuring critical access for all members.
We assessed their operations using process mining to run what-if scenarios and simulations that identified specific opportunities for change, such as process bottlenecks. We identified ways to improve the processes and reduce cycle times. For example, one improvement automatically routed cases of family members with disabled dependents to an agent with specific knowledge in that area to ensure more effective handling, improving customer service.
Using time-and-motion studies, in which screen activity was recorded, the client’s business process team identified thousands of the same clicks being made each day — identifying a manual, necessary process that added time to an already convoluted system.
By applying artificial intelligence to these time-consuming processes, we helped the client reduce cycle time by 70% — resulting in a target of under seven days.
The changes introduced by process mining improved customer experience, reduced human error and created processes that are more efficient and assured. The business process optimization team was able to redeploy employees to focus on more complex, challenging projects that directly created value for the business.
A wealth management firm sought to address issues in its treasury disbursement process:
Pulling data from a Pega workflow log and other sources, we applied process mining to create an operational dashboard that provides detailed insights on all cases (status, progress, ETA) and predicts completion time for each case, enabling proactive customer management.
The result: A 90% productivity improvement with near 100% compliance with disbursement service level agreements (SLA).
The relentless pace of change is here to stay. Process mining, especially when paired with automation and analytics, will help enterprises respond more nimbly to market opportunities. Augmenting human experience with new technologies such as process mining will enable employees to apply precious time to higher value work such as strategic planning, serving customers and innovating new products.