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.
Getting started — a checklist
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
- What are known pain points/problem areas for the process?
- What are primary key performance indicators (KPIs) for both operations and business outcomes?
- Are there compliance or control concerns related to the process?
- What are the top two or three desired outcomes from process mining?
Determine a timeframe for data analysis
- How many instances are processed annually by this process?
- What is the end-to-end cycle time for the typical case?
- Have there been any material changes to the process execution in the past year?
Identify potential benefits
- How many full-time employees or equivalents are executing the process (with breakouts by location)?
- Aside from operating expenses, are there expenses (such as penalties, discounts or deductions) or revenue leakages (such as customer/application losses or reimbursements) from the process?
Identify key stakeholders
- Who are the business owners, process subject matter experts (SMEs), process excellence resources, source data SMEs, and IT resources (to support process mining application deployment)?
- Who will be responsible for implementing any identified opportunities?
Identify data sources for the process
- What are the data sources for workflow/event log data, and how will this data be fed into the process mining tool?
The following figure shows a typical timeline.