How Understanding Behavior Will Improve Process Performance
I talked to Russ Gould of Kofax about the role of behavioral analysis in improving process outcomes. Russ will be presenting ‘Understanding How Behavior-Based Analytics Affects Process Outcomes in a Healthcare Scenario’ at APQC’s 2017 Process & Performance Management Conference October 2-6.
What role does business intelligence play in managing process performance?
You need to measure something in order to manage it. Business intelligence (BI) is limited in its ability to manage process performance because it typically looks at each type of data point in a process individually, providing no means to capitalize on the process context of the data. To better understand how a business process is performing, we must extend BI to track metrics on process behaviors including what steps are done, in what sequence, and how long each step takes.
What are the limitations of traditional analytics dashboards when it comes to process management?
BI traditionally aggregates identical data points to measure discrete aspects of process performance, yet provides no support in understanding factors such as profitability, customer satisfaction, or turnaround time related to specific process rules. Process intelligence is required, using all relevant, real time data sources to calculate process metrics based on timing, sequencing, and properties of the steps in each process instance. The resulting range of dashboard views make it easy to see a process following an expected flow, identify deviations and bottlenecks, and define alerts when specific process behaviors are detected. It’s essential information that supports better operational decisions than BI dashboards limited to only traditional non-process aware metrics.
What drives the need for real-time visibility in each process step?
Because organizations are made up of processes, process effectiveness is fundamental to achieving objectives and success. Certain aspects of process optimization can be accomplished with process intelligence and behavior based analytics operating on historical data. Near real-time data extends a platform’s capability by showing process bottlenecks developing in real time. Alerts signal if a process instance is not in compliance with sequence or timing rules, providing an up to the minute view of the health of any business process.
What are some approaches that organizations can use to capture behavior-based analytics?
Organizations typically go one of three routes. Solutions can be built from scratch relying on programmers; they can employ a traditional BI tool, using programmers to code the process intelligence capability; or they can deploy analytics and process intelligence software with these capabilities already built in. It’s important to recognize that the homegrown options can be very costly in terms of time to value, expensive programmers, and inflexibility for the business user. For example, behavior based analytics should ideally allow end-users to define a process behavior of interest and see how it relates to metric outcomes. This does not require process behaviors or rules to be defined ahead of time and implemented by a developer. In its third release supporting Behavior Based Analytics, Kofax Insight now supports end-users in defining increasingly complex process behaviors that closely map to business requirements and are typically not implemented in a BPM or workflow tool. This means that an end-user can experiment with defining process behaviors of interest, gaining insight on varied metric results when rules were or were not followed.
What’s the biggest challenge in understanding how behavior impacts process performance?
BI tools don’t analyze process behavior. Process monitoring and mining tools don’t track traditional metrics. To see how process behavior impacts process performance, you need a platform that monitors and quantifies process behaviors, captures the metrics that relate to each process, and uses these two together to demonstrate how process behaviors relate to metric results.