I interview people at all levels of an organization during a Digital Transformation. Since the business case for transformation assumes lean process improvements, I have two goals:
– Make the information that runs the business into data a computer can “understand”
– Replace the non-human, monotonous tasks related to information with computers

To give away the ending here – the robots aren’t taking over. When I am done, all the social context, human relationships, and important judgement calls are still human-made. What we change is how quickly the mundane data-massaging, tiring research, and waiting between email chains that delay all of those human decisions. So I have a goal when I start interviewing: remove inefficiencies and make existing workflows more scalable. This implies automation.

One key thing here: nothing your business does is just chaos. I absolutely spend more time convincing people that an algorithm can capture the complexity of what drives decisions than I do formulating the algorithm. No matter how loosely controlled or gut-feel driven the decisions are, once a business grows into the 100s of employees, I can represent most of your processes with an algorithm. I could even replace the important human decisions with another algorithm that would succeed within a reasonable margin of the average employee, but that’s too risky. Instead, we make notifications and intuitive user interfaces to let one person make the same important decisions 10x or 100x as efficiently, making everyone more scalable. Don’t lay people off. Make it easy for them to increase their value-add.

Interestingly, there is a powerful cultural influence in these conversations due to the mistaken belief that “automation” somehow equals “artificial intelligence” – when what it really means is “fairly basic math equations tied together into one big powerful formula”. The intelligence is completely human-created, human-programmed, and human-managed. So I inevitably but happily show it works prior to convincing someone it works, because depending on their place in the company, the idea of automation replacing humans can be an ideal direction loaded with false optimism or a terrifying slippery slope where unrealistic pessimism prevails.

Both cultural perspectives ultimately distort the conversation.

In its really old roots in the Toyota Production System, the introduction of an “ejector” was a huge benefit to the safety, well-being, and efficiency of a machine worker. Before the ejector, a worker would carry a part to a machine that had just finished its task on a previous part. The employee would put down the part they were carrying, take out the previous part, pick up the next part to put it in the machine, then pick up the previous part. With an ejector system, the machine gets the previous part out of the way so that the worker just walks up and loads the next part, then takes the previous one, checks it for quality, moves it along the line.

Think of all your manual spreadsheet updates, paperwork, phone calls, and email chains just like that. You’ll still check the output for quality before passing along information or making a decision, but automation, notifications, workflow rules, and algorithms can save you a fair amount of your pain by pushing or ejecting what you need when you need it (keeping it out of your way the rest of the time).

This makes the value-add or revenue potential of every existing Customer Service or Sales or Marketing employee scalable beyond what additional hiring can accomplish. Lean Process automation doesn’t mean replacing all operations with an AI. This is the foundation of “Autonomation” – where a worker no longer manually labors at one machine, but becomes a manager of multiple “machines” – multiplying the value-add per employee. Replace the painful, slow, or unnecessary steps with a computer, while keeping the human element – the important decisions, the social context, the gut feel, human.