Addressing Performance- and Process-Management Challenges with AI and Automation
In January 2022, APQC released a survey report about process and performance management challenges and priorities for the year. While the full "2022 Process and Performance Management Priorities and Challenges" report is available on the APQC website, there are a few areas I found particularly interesting. Especially when those areas are viewed from the lens of how the right technology platform can address performance management challenges and help organizations move forward on these priorities.
The survey covered respondents from a wide range of industries and enterprise sizes, indicating that challenges and priorities are equally prevalent across these spectrums.
The good news is that these challenges have been identified, because the very first step towards progress lies in knowing the problem to be solved. The better news is that these challenges can be addressed by choosing the right technology solutions.
Among the most cited challenges in the APQC report are the ability to define and map end-to-end processes. Also mentioned was the need to ensure that the efforts made towards process management are aligned to the organization’s strategy. Those of us who have been involved in process documentation instantly understand these challenges. Traditionally, these exercises have involved extensive discussions, interviews, and whiteboarding sessions with subject matter experts (SMEs). Despite the good intentions of SMEs, it is often found during the implementation phase that localized nuances have been missed out. Typically, this results in rework or, worse, patchwork.
Further, executives cited challenges not only in creating a culture of continuous improvement across their organizations but also in creating a systematic approach to identifying improvement opportunities. As the old saying goes, “the road to hell is paved with good intentions.”
Far too often I’ve seen organizations start on the path to continuous process improvement with a lot of pomp and fanfare. However, it soon dissipates into individual initiatives in different corners of the organization without a coherent and synergistic program that helps the organization move forward on strategic objectives.
Related to the above, survey respondents cited challenges around:
Establishing a culture that's driven by data
The ability to identify the right mix of metrics that include both in-process and lagging metrics
The ability to aggregate and present data into meaningful dashboards (or what I would call ‘useful dashboards’)
If you’ve spent time collating data and massaging spreadsheets, you’ll instantly identify with those challenges. Especially the challenge around measuring and tracking key in-process metrics on a near real-time basis (versus becoming aware of them when it's too late to act).
To date, addressing the above challenges with technology solutions has meant implementing a multitude of point solutions. More often than not, it has also resulted in additional spend for integrating solutions, or burdening analysts put in manual effort to achieve the same outcomes.
Now, however, the UiPath end-to-end platform addresses all these needs in a single, seamless platform. The traditional mechanism of capturing SME knowledge to define processes can be achieved with UiPath Task Capture. UiPath Task Mining takes this further by unobtrusively leveraging screen capture (in a manner compliant with privacy and security regulations) and artificial intelligence (AI) to provide the details of all variants of a particular task, even the most complex of nuances.
UiPath Process Mining elevates this to an end-to-end process view, tracking and tracing transactions as they navigate across users and departments. Process Mining can be used both for post facto analysis of processes, as well as in a near real-time manner to trigger users to act on transactions via UiPath Action Center.
Process Mining can also be used to trigger robotic process automation (RPA) robots that are deployed in UiPath Orchestrator. RPA bots that execute the processes are themselves capable of logging the right type of information so that meaningful, near real-time dashboards can be generated that include both in-process and lagging metrics. These metrics can also be fed back to Process Mining to measure and observe improvements in process performance over time.
The UiPath Platform offers a unique capability to seamlessly move from a process map view down to actual transactions, or to triggering unified human plus digital workforce actions. Reporting and dashboarding capabilities include in-process and post facto dashboarding. Together, all these capabilities offer a very powerful mechanism for addressing the challenges that were mentioned earlier in this blog post.
A seamless platform like UiPath not only offers mechanisms to identify and define processes, but also to monitor and govern their performance. Moreover, having these capabilities as integral parts of the automation platform results in significant impact on the value achieved from the overall program, by obliviating the need for integrations and workarounds.
UiPath also provides the ability to enforce enterprise-wide policies and processes while simultaneously allowing for differences and nuances to coexist at any level (such as line of business, department, region, geography, etc.). All these capabilities put together enable organizations of all sizes to synergize their process management and improvement activities with their overall corporate strategy.
Find out more about how to use automation to address your process-management challenges. Claim your copy of our latest process mining report.
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