Once upon a time, I found myself pitted against a pack of fire-breathing dire wolves with only a spoon and cereal bowl to defend myself. Let’s try that again. Once upon a time, I attended the kind of meeting that every single IT worker eventually attends. It’s the usual story, some folks outside of IT desired to automate a number of workflows that were, at the time, almost entirely manual. They wanted to make them go faster. So, of course, we needed to look at their workflows, so we sat down and had a meeting. We started to walk through the workflows, seeing where we could automate. As the meeting progressed, the number of exceptions, sub-processes, changes in status due to special attributes, judgment calls, and other decision points began to overwhelm all the participants in the meeting. It was maddeningly byzantine from soup to nuts. It didn’t take long before the complexity became apparent to everyone present and the individuals that had called the meeting eventually paused, looked at each other, looked at me, and told me that they’re going to have to go back and map all of this out and come back. Yikes! The question that entered no one’s mind (sadly, including mine) was this, “Who’s doing all this work currently?” The answer is human middleware.
Mark McDonald’s blog post has really stuck with me since I’ve read it. Organizations will use people to keep themselves from doing the scary and difficult work of changing the way they do business. The world has changed; the nature of work has changed, customer expectations have changed, and yet, the organization continues unthinkingly in the way it always has. With my own example, no one ever called a time out and said, “Who is the customer? Can they navigate this system without assistance? Why is it this way in the first place? Can we change? What are the consequences of changing it? Is changing it worth investing in?” Instead, we all (including myself, I’m quite guilty in this story) just wanted to automate the current existing process. There was no impulse to make it simple. To make it repeatable. The consequences, had we proceeded, would have been to create a digital Rube Goldberg machine. Digital paper shuffling is still just paper shuffling.
Some of the symptoms Mark describes we all see (from his blog post):
- Inconsistent business processes, which create multiple versions of the truth, conflicting business rules, complex operational interfaces, and different ways to get things done. All of which create bottlenecks, backdoors, and conflicting answers requiring people to figure it all out
- Baseline budgeting, that makes resources decisions based on a prior year’s baseline that bakes in inefficiencies and creates an incentive to keep and grow the middleware and budget as a symbol of executive influence or power.
- Accretive change which is constantly asking for more, different, and additional stuff rather than favoring of keeping the organization capable and lean.
What’s the way out? Well, it will require an evolution of your organizational culture. Evolution doesn’t tend to be self-initiated, there’s usually some form of pain required. The good news is that the pain doesn’t necessarily have to come in the form of layoffs. It can come in the form of asking the tough questions we tend to shy away from. At the tactical level, good work can be done. If we go back to the example I led with, we shouldn’t have had just a simple meeting with workflow diagrams. We should’ve had some form of Kaizen event. We should’ve reframed the conversation from mere automation to true improvement. We should’ve asked the, “5 Whys”. We should’ve led with customer value instead of looking at merely improving efficiency, especially as some reductive coefficient to the current workload.
Complexity is inevitable but not all complexity is created equal. We should strive for the complexity in our organizations to be the end-result of simple rules being applied over and over again not as a result of unmanaged and informal processes. When we can place powerful computational resources at our backs, we can move people from being cogs in the machine to providing real value. They can start doing things computers fail miserably at such as delivering empathetic and creative value. Fact of the matter is, computers suck at giving advice. Customers will need advice. They will need human contact. Is your organization using humans as humans or as fuzzy logic gates?
Note about the title: The title corresponds to the computer science concept of big O notation; that is, the understanding of the limits of algorithms as their set sizes approach a particular value. I have no empirical evidence that people working together are O(2^N), also known as EXPTIME. There’s probably a study out there. I just haven’t found it yet.