Harmon on BPM: Major Transformation, Incremental Improvement and AI

For well over three decades the biggest issue in business process work involves the scale of change that practitioners ought to attempt.

In the Nineties, Michael Hammer led the charge for large scale process transformations. Hammer argued that IT made wholly new business processes possible. He likened early business processes to winding cow paths that followed old constraints that had dominated business activities for decades. Now, Hammer argued, was a time to be bold, to ignore the old cow paths and to boldly redesign, replacing cow paths with super highways.

Others, from Six Sigma to Rummler, spent their time teaching how existing processes could be systematically improved. They relied on careful analysis and incremental improvements to maximize the efficiency of business processes.

Arguments can be made for both approaches, and the techniques derived from each approach can be used effectively in any large organization. In organizations where top management is resistant to bold changes, incremental improvements are often all that process practitioners can pursue.

Over the years, however, in several different studies, its been shown that the really great rewards to be obtained from process work involve major transformations. Incremental improvements are fine, but they take time, cost money, and rarely add much to the bottom line. Few process practitioners become company heroes by making an established process more efficient. On the other hand, an individual that transforms a process and cuts costs in half is on the fast track for advancement.

Add to that the pace of change and the worldwide competition introduced by new technologies, and companies are much more focused on undertaking major business transformations. Indeed, few organizations stay the same long enough, these days, to justify working on lots of incremental improvements. Why spend money to improve a process that will likely to be wholly replaced in a couple of years?

In recent years, lots of process gurus have argued for defining all of your organization's business processes by means of a Business Process Architecture. It's a great idea, and a well-documented and up-to-date architecture can be very useful. But who has the time and money to develop and maintain such an architecture. More to the point, who would choose to put resources into a process architecture effort while ignoring the impact of technological changes on your industry. Most organizations find themselves focused on urgently updating and transforming processes just to survive. They don't have the extra resources to document processes that will likely be changed before one can even document them.

As we said earlier, both large scale process change and incremental improvement have their places and both are widely practiced, but if your goal is to really change the way your company does business, you need to focus on opportunities for major transformations.

Now let's consider Artificial Intelligence (AI) and Robotic Process Automation (RPA). Recall what I've said many times in the past: AI isn't a technique, it's a whole collection of techniques, including vision and auditory techniques, vocal systems, robotic techniques, like sensors and devices to steer cars in traffic, and ways of capturing information, analyzing data and making logical decisions. Talking about AI is vague, unless you get down to specifics.

RPA is a very specific AI technique. It has nothing to do with robotics as that term us normally used. Instead, it refers to automated programming techniques designed to automatically link the output of one software system to the input of another. Thus, if you have a situation where a human routinely reads data from one system and uses that data to make inputs on a second system, you have a situation that would probably benefit from an RPA system. It could link the two and replace the human that is now simply transferring data from one app to another. Obviously there are good uses for RPA systems and some business processes will incrementally benefit from RPA use to become more efficient and less costly.

The question I am interested in, however, is whether RPA is a great example of AI or a good way to introduce AI to your organization.

RPA is not a great example of AI – it is simply one very specific example of how AI can be used to help solve a very specific set of problems. And it hardly constitutes a good way to introduce AI to your organization. It just an example of one more specific tool that can be used to solve a specific type of problem.

As I've already suggested: there are lots of AI techniques and they can be used in different combinations to solve all kinds of problems. You can consider using AI to revolutionize the way your organization makes major decisions, the way it helps customers configure the systems they buy from your organization, or you can use it to link apps an eliminate a few human jobs.

The risk of focusing on RPA is that you'll develop an app that links two other apps and eliminates a half dozen technicians. Looking at the results, senior management may will conclude that AI is useful, but not very impressive.

Don't get me wrong. I'm not against RPA, and I can easily imagine using it if I was in an organization and had a need to smooth the flow between apps. But I'd be cautious not to try to use it to sell or explain AI. AI can be so much more!

Let's recall what Hammer said. If you really want to improve your organization, you need to find a way to transform it! You don't want to focus on saving thousands of dollars a year. You want to focus on earning additional millions a year! That means replacing cow paths with super highways. AI is just the technology to use in creating super highways. AI will soon automate cars, and automated cars and trucks really well transform industries. Stock market trading systems that run themselves really will change the financial industry. Systems that configure large software systems in response to spoken customer demands will really change the ways industries perform.

AI is a call to think big – to imagine new futures and new industries – to imagine transformed business processes. Don't squander your chance by leading people to think that AI is nothing more than RPA.

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Paul Harmon

Executive Editor and Founder, Business Process Trends In addition to his role as Executive Editor and Founder of Business Process Trends, Paul Harmon is Chief Consultant and Founder of BPTrends Associates, a professional services company providing educational and consulting services to managers interested in understanding and implementing business process change. Paul is a noted consultant, author and analyst concerned with applying new technologies to real-world business problems. He is the author of Business Process Change: A Manager's Guide to Improving, Redesigning, and Automating Processes (2003). He has previously co-authored Developing E-business Systems and Architectures (2001), Understanding UML (1998), and Intelligent Software Systems Development (1993). Mr. Harmon has served as a senior consultant and head of Cutter Consortium's Distributed Architecture practice. Between 1985 and 2000 Mr. Harmon wrote Cutter newsletters, including Expert Systems Strategies, CASE Strategies, and Component Development Strategies. Paul has worked on major process redesign projects with Bank of America, Wells Fargo, Security Pacific, Prudential, and Citibank, among others. He is a member of ISPI and a Certified Performance Technologist. Paul is a widely respected keynote speaker and has developed and delivered workshops and seminars on a wide variety of topics to conferences and major corporations through out the world. Paul lives in Las Vegas. Paul can be reached at pharmon@bptrends.com