ISO 9000 is a set of standards for quality management developed in the late 80s. It was based on procurement standards used by the U.S. Department of Defense. But, in a long-ago training session, the entire premise was summed up by the instructor as, “Document what you do, then do what you’ve documented.”
The reasons those types of programs exist is because the documented process is rarely the actual process. But today, given the massive scale and breadth of change over the past year, it’s likely many of your processes have been altered in one way or another. In fact, a survey by McKinsey found that organizations have accelerated their digitization efforts by three to four years during the pandemic. So, before enterprises can change, improve, digitize, or automate a process, it’s imperative they first understand what’s really going on.
A recent article in VentureBeat, “Why process mining is seeing triple-digit growth”, points to the past year’s massive change, along with many other factors, as what’s driving explosive demand for process mining tools and technologies. Gartner estimates that the market for these solutions has already tripled since 2018, and there’s more to come. Here’s a quick overview of why, according to VentureBeat.
RPA Isn’t Living Up to Expectations
Robotic process automation (RPA) initiatives and their expected ROI are based on the underlying process. Saving an hour per day for a documented process completed by your expensive procurement team could generate a nice return, for example. But, if Procurement is, in reality, already working around the systems and tasks that slowed them down, the return could be considerably lower, or it could even cost you money. Or, maybe that entire process is done differently in other regions or isn’t really valuable for Procurement, so you’ve spent money automating a bad process you’ll eventually need to spend more money to rework.
Companies are now finding that, in their haste to automate, they neither understood the actual process nor developed an optimized, scalable process built for their current needs. As the article states, “Many enterprises are finding it difficult to scale beyond a few software robots or bots because they are automating a bad process that cannot scale.”
Process intelligence, however, is giving enterprises detailed information on why their RPA isn’t driving more value. It’s also giving visibility to the true as-is processes, how they vary across the business, and where optimizations might make those processes better well before RPA is considered.
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Benefits Beyond Simple Process Mining
Process mining, which “involves mining data logs from applications like ERP and CRM to assemble an accurate model of how a business process, like order to cash (OTC), works,” is inherently limited. Many tools in modern enterprises, such as Microsoft Office, virtual desktops, and email, don’t produce data logs. Process intelligence, or what VentureBeat refers to as “task mining,” uses computer vision, artificial intelligence (AI), and machine learning (ML) to directly record how a worker accomplishes any given task.
See our related post: What is Process Intelligence?
Since process intelligence doesn’t rely on data logs, it can capture more data from more applications, but also how today’s workers jump between applications. For example, maybe the OTC process requires a clerk to copy order data from an ERP system and paste it into an invoicing system, which then generates a PDF invoice that’s manually emailed to a vendor. Process mining would likely capture the ERP and invoicing logs, but process intelligence would provide insights across the end-to-end process and all applications, including the manually created email.
Those cross-application actions are more indicative of how today’s workers work, and that’s the level of data enterprises are now demanding. Process intelligence adds AI and ML to uncover the nuance of processes and surface opportunities to optimize before you might apply RPA to automate suboptimal subtasks.
New Applications Across the Enterprise
The inclusion of advanced AI and ML, along with the benefits of the cloud, enables enterprises of any size to quickly capture and evaluate data on enterprise-scale processes. But it’s not just limited to processes, per se, since other insights can be gleaned from knowing how your enterprise operates today and at a detailed level. VentureBeat calls it “a new sensory system for organizations.”
“In the ecology of companies battling for market share, a company with even a primitive capability of seeing invisible workflows better than the competition has a huge advantage over companies that cannot see. As Erasmus stated in 1500 AD: ‘In the land of the blind, the one-eyed man is king.’”
Some examples of these in-demand capabilities of process intelligence include:
- Understanding and mitigating complex cybersecurity threats
- Optimizing the physical logistics of warehousing
- Improving manufacturing processes
- Breaking down organizational silos
- Reducing training time
- Identifying the root cause of quality issues
It’s also being used to enhance how humans work, such as increasing safety and automatically altering workers when steps are missed by mistake. So while the word “automation” may sound like jobs are at risk, one of the most human benefits of process intelligence is in making humans better at how they work.
“Rather than just looking at process mining as something to impose on workers, companies may see the biggest gains by finding ways to include and reward employees as part of the adoption. After all, thousands of eyes in the field may see some opportunities that a few experts in the office might miss.”
You can read the complete VentureBeat article here.