Business process analysts were everywhere in the Business Process Re-Engineering era of the late ’90s and early ’00s. Their job was to document the “As Is” environment by observing and interviewing everyone involved in the work. They could plot a path to re-engineer the business processes for the’ To Be’ situation with that knowledge. But that proved to be hard work, expensive, and time-consuming. It made perfect sense; it was essential, but somewhere or other, the momentum was lost, and quick fixes and, quite frankly, common sense went out of the window. It’s a key reason why 70% of IT projects fail or fall short of expectations. Fast forward to today, and we see the rebirth of business process analysis and renewed interest in thoroughly understanding the ‘As Is’ situation before going in with all guns blazing and finding unfortunate obstacle after obstacle to navigate. The reason for the renewed interest is that much, though certainly not all, of the work of business process analysis, can be automated today, or at least there are tools available to capture the situation automatically.
Today, there are tools on the market that leverage AI & ML to read and analyze log data for both processes and tasks. There are even tools to observe what users do in business activities, rather than what their managers think they do. That’s important as in our experience; managers often have wildly different and spectacularly optimistic ideas of what is happening, versus the real world of workarounds, screen jumping, and messages to colleagues required to complete even simple tasks. This is all to the good, as business process management isn’t really about business process management software. Despite ambitious attempts to automate, human expertise is critically important in most process situations. The software can automate some activities but not others, and that will always likely be the case. It’s at this point where things seem to fall.
Applied Artificial Intelligence is super smart, robust, scalable, and accurate – the technology itself works well. But it can be hard to replicate in real-world working environments. Recent studies have suggested that less than 10% of AI projects even return on the investment made. The problem isn’t the technology itself it is in how it is applied. Though this is an oversimplification, we can bucket the reasons for failure into three categories.
1: Oversold and over-promised results
2: Unrealistic buyer expectations
3: Insufficient business analysis before deployment
The first two are commonplace across enterprise software, technology vendors touting their wares as silver bullets, panaceas for all ills, magical elixirs. There is no doubting the sales pitch from many vendors is overblown and, in many cases, unbelievable. But it takes two to party; such wild claims should be evident from the get-go, but (and this has never been more true), people hear what they want to hear. How much easier would it be to buy some pixie dust to solve your business problems, rather than roll your sleeves up and do the necessary hard work? That’s why we believe the real issue is number 3, insufficient business analysis. Or, to put it another way, a fundamental failure to work out what your current state looks like (As Is), define how you really want it to look and operate (To Be), and then carefully map a roadmap to that endpoint.
AI grounded analysis tools such as ABBYY Timeline (one of this year’s Innovation Award winners), Minit, Signavio, Microsoft Process Advisor (just released), and FortressIQ, among others, all bring powerful tools to the market to help in this work, and we highly recommend you look at them. But without a sense of reality, the willingness to do some hard work, and a recognition of the need for human expertise to understand what’s going on and what you need, then they will not work.
2021 should be the business analyst’s year, the process analyst year. We need those skills in the enterprise more than ever, for there are no magical fixes, no tools that can transform your organization. But some technologies can help you and your team transform. Yet as any psychotherapist will tell you, transformation comes from within. So let’s start thinking less about how AI will transform our organizations and business processes and more about how our people can use AI to change.
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