3 Takeaway Tips from Recent Process Intelligence Research

Market interest around process intelligence emerged in 2020 and kicked into overdrive in 2021. From investments to acquisitions to products, it is an exciting time for this technology by any measure. Analysts have also taken notice and stayed on the leading edge by encouraging companies to explore process technologies. Recent reports from Gartner, Forrester, HFS, Everest, ISG, and others suggest continued enterprise growth and wider adoption. While each takes a unique angle on the technology, a few common themes have emerged from the industry research. Here’s a quick recap of these themes.

Theme #1 – An Emerging OpEx Ecosystem

While traditional process mining can trace its roots back to IBM in the 1990s, the technology remained largely an academic exercise until just a few years ago. The emergence of artificial intelligence (AI), cloud computing, big data, and advanced analytics helped push process technologies out of the lab and into the workplace. 

It’s similar to the path of RPA. This automation technology started primarily as a stand-alone task automation tool and has since evolved into “hyperautomation” to include AI/ML, data extraction, recorder, and BPM capabilities. Process intelligence has also evolved into a complementary tool to drive increased business value. Microsoft, SAP, Oracle, and other large software platforms are establishing operational excellence solutions that integrate previously diverse technologies into a comprehensive approach to deliver enterprise value.

Theme #2 – A Pathway To Transformation Success

McKinsey reports only 14% of companies have achieved sustained and material improvements from transformation programs at a cost of nearly $1 trillion annually. Despite the low propensity for success, companies continue to pour resources into complex change programs. BCG notes more than 80% of companies plan to accelerate their digital transformations. The dichotomy exists because executives realize that doing nothing is not an option because a company can’t be competitive if it fails to transform.

The biggest challenge to any complex change is the lack of knowledge on current state activities. Unfortunately, most companies do not understand how they truly operate on a day-to-day basis. You cannot get to the targeted future state efficiently without a clear view of your current operations. Process intelligence gives you that “what are we doing today” operational insight to then improve and drive value for the organization. Too much of the focus on transformation has been directed towards technology as the answer without considering the people and process dimensions. Through a more balanced people-process-technology approach, transformation success rates can be improved dramatically. 

Theme #3 – Better Together: Process Mining and Discovery

Comprehensive process intelligence requires a mix of process mining, modeling, and documentation. Used individually—and properly—each solution can certainly drive value for the organization depending on the use case. When combined, it creates a 360-degree view of your operations and creates an opportunity to deliver a value-driven, process-led, and data-based transformation. 

Consider how the different approaches work better together. Process mining offers higher-level, top-down insights on core end-to-end business processes. Task discovery provides granular, bottom-up detail on user activity to define task completion. By combining the two technologies, stakeholders can answer both what is happening and how it is happening. The integrated insights accelerate value creation regardless of whether the targeted outcome is an automated workflow, streamlined process, improved experience, or enhanced compliance.   

Theme #4 – Order of Operations is Critical

Too often companies adopt a “ready, fire, aim” mentality with emerging technologies. The promise of the shiny new tool is overwhelming and proper strategy takes a back seat to pursuing a quick win. Bill Gates’ second rule of technology teaches us that automation applied to an inefficient operation will magnify the inefficiency. Furthermore, many critics of RPA highlight the challenge organizations have in scaling RPA operations: a majority of companies still have less than 10 bots deployed.

After the initial low-hanging fruit automation opportunities are addressed, companies struggle to find next-level candidates. Most RPA projects that get started never make it to production, and bots are more brittle than expected. But, with proper strategy and planning, RPA programs can be scaled. The key is the order of operations. The first step is process discovery. The second step is process reengineering. The third step is automation. In any other order, or if any steps are skipped, the flow is disrupted very quickly.

3 Tips for Companies Looking to Master Process Intelligence

Process inefficiency costs companies anywhere from 20% to 30% of their revenue every year. A recent article in Harvard Business Review noted that there are not dollar bills lying around on the floor, but there are 10,000 pennies. If you want to master process intelligence and start putting those pennies back into the business, here are three tips for getting started:

  1. Start Now – The technology is changing fast, but it is available today. There is no reason to delay programs waiting for the next advancement.   
  2. Think Big – Companies succeeding with process intelligence are planning appropriately. There are many use cases across the enterprise that the technology can address.
  3. Go Fast – While many of our clients are running successful programs internally, process intelligence technology requires deep and wide expertise. Consultancies and SIs are a great resource to jumpstart adoption and utilization of the tools.

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