This blog was co-authored by Carl Aridas and Joel Thimsen.
In the dynamic environment of highly regulated industries like healthcare and financial services, leaders often balance competing goals to delight customers while cutting costs. This has challenged many organizations to better optimize and intelligently automate business processes and experiences.
According to The Forrester Wave™: Process Intelligence Software, Q3 2023 report, “Customer-obsessed companies are adapting how they work internally to deliver shorter turnaround times at higher quality and/or lower cost. They are shifting from an efficiency model where improvements focus on optimizing internal functions to an effectiveness model that looks at customer outcomes holistically.”
Imagine a technology that can precisely pinpoint where a process bottlenecks, track where inefficiencies lie, and offer ideas for automation opportunities.
Process mining offers a data-driven, automated, and objective approach to analyzing business processes. When approached well, it enables organizations to:
- Unearth hyper-detailed insights into how work is done
- Identify processes that hinder productivity and are ripe for a rethink
This is accomplished by combining data science and process management to deeply understand operational processes based on an organization’s widely available activity logs. From there, business processes can be modeled, analyzed, and then optimized.
Diagnosing and Correcting Process Failures
Despite the billions spent yearly to digitize processes, companies often are not operating at their maximum potential. This is partly due to processes being forced to run across a rigid and fragmented technological landscape. Instead of creating value, digitization often creates execution gaps.
Common signs that your organization is suffering from execution gaps:
- Inability to measure how your processes run
- You do not know which gaps and root causes have the biggest impact on KPIs
- You cannot act quickly enough (or do not have the means to remove) the gaps in the underlying transaction systems, forcing costly action workarounds
Process mining is technology-agnostic, so it works on any system with an activity log that contains as few as three data points: unique identifier or item ID, timestamp, and activity (i.e., what was done).
Process mining helps organizations MEASURE and KNOW so they can most effectively ACT:
- MEASURE capacity and see how processes really run. An ideal solution combines top-performing analysts with innovative AI.
- KNOW which gaps have the greatest impact, and the right course of action to close them. View custom-tailored results to make data-driven decisions that clearly outline opportunities and plans.
- ACT to remove gaps in real-time and unlock your capacity. Accelerate implementation with proven delivery methodologies that power the seamless execution of the plan.
The “People Factor” Of Process Mining
Every process is backed by the people who rely on its accuracy and impact. For this reason (and more), process mining reaches its potential when coupled with experts who can provide interpretation and drive iterative improvements.
Ideally, process mining combines sophisticated mathematical models and algorithms with human expertise to discover patterns, analyze, and quantify improvement areas across all systems involved in a process.
After discovering and analyzing these complete business processes, they can be optimized and automated for real, tangible, impactful results.
You May Enjoy: Perficient Named in Forrester’s Digital Transformation Services Landscape, Q3 2023
GOAL: Turn Event Data Into Process Optimization Insights and Actions
Process mining can compare the discovered process models against predefined ideals or regulatory standards. This comparison enables your teams to assess process effectiveness and identify deviations that require attention due to inefficiencies and/or non-compliance.
Process mining is particularly valuable in industries like healthcare and finance where strict regulatory requirements and compliance are especially critical.
Healthcare: Highly Protected Data
Automation Examples: Compliantly manage HIPAA-protected patient/member data while increasing accuracy, efficiency, and productivity to help improve patient outcomes and mitigate risk. Reduce denial write-offs and streamline the revenue cycle by pinpointing common data issues, like missing patient information, that can be rectified through data automation and accurate, proactive account updates.
See Also: The Healthcare Executive’s Guide to Intelligent Automation
Financial Services: Regulatory Compliance Complexities
Automation Examples: Ensure rapid response times to address complaints, while adhering to response compliance regulations. Build a reliable risk management strategy using accurate estimations and predictions. Quickly and consistently evaluate transactions against set business or regulatory policies and route cases to the appropriate domain investigators.
Related: Automation Industry Trends and Business Outcomes
Jump Start Greater Efficiencies + Business Outcomes
Process mining simplifies critical, complex business processes that often span multiple steps and stakeholders, and helps to isolate the inefficiencies, errors, and/or delays that can negatively impact organizational performance.
In the true spirit of efficiency, our process mining operating model pairs Perficient experts with your business leaders for rapid, data-driven understanding and a clear path forward. We accurately define process models, outline variations to those processes (identified from most to least common), and equip your enterprise with a report of prime opportunities to automate manual workflows and optimize existing automation.
View our Process Mining Strategic Position, or we also invite you to our expertise in intelligent automation, financial services, and healthcare.
