Automation is an Infinite Game
According to New York Times bestselling author Simon Sinek, there are 2 types of games – finite games and infinite games.
Finite games are played by known players, have fixed rules and agreed-upon objectives to be achieved within a finite period. For example, soccer is a finite game.
Infinite games, on the other hand, are played by both known and unknown players, with no agreed-upon rules and an infinite time horizon. Crucially, there is no such things as “winning an infinite game”. Business, for example, is arguably an infinite game.
In infinite games, when you are there, there is no there there. Put it in another way, infinite games are all about the journey.
Now, what has this got to do with automation, you may ask.
A lot, it seems.
Scale or Kill – Avoiding the PoC Trap and the Pilot Purgatory
According to research from Deloitte, only 11% of survey respondents have moved beyond the Proof of Concept/Value and Pilot phase (herein defined as having 1-5 robots and 6-10 robots in production respectively).
Admittedly, number of bots deployed might not be a good metric (this is a blog post for another day), but the underlying trend is clear – many organizations are still struggling to implement RPA in any meaningful scale vis-à-vis the size of their operations.
Lest you think that this is unique to the RPA world, the same ailment is afflicting Internet of Things (IOT) adoption. According to research from McKinsey, some 85% of companies surveyed spent more than one year in pilot mode, while 28% spent more than two years.
Clearly, regardless of the technology, it appears that scale is the holy grail.
Change the Way You Look at Things and the Things You Look at Change
Our point of view is that automation at scale, in and of itself, is meaningless. How many bots an organization has deployed, or the number of business units that have implemented automation is of secondary important. To quote Phil Fersht, “Intelligent Automation is a marathon, not a sprint.”
What’s crucial is how organizations are leveraging automation to achieve real, sustained value over the long term such as a superior customer experience or enhanced compliance to regulations.
In the business world, one of the keys to successful globalization or regionalization for a company is, somewhat paradoxically, localization. After all, we now live in the era of mass personalization.
Likewise, in our automation world, scale cannot be achieved without a culture of bottoms-up innovation. Because only then can we aspire to capture the long tail of Robotic Process Automation.
Daniel Dines, the charismatic co-founder and CEO of UiPath, an industry leader, is now championing “a robot for every person” (a la Bill Gates’ “a computer on every desk”). Not everyone might agree with that, but what we can all agree upon is that there is currently a robot in every person.
And an automation-first mindset is required in each and every one of us to lift that robotic work and shift it onto a digital worker. Just to be clear, reskilling or upskilling current employees with the technical RPA skills is the easy part. After all, most RPA software are low or no code with intuitive drag-and-drop interfaces.
But to adopt an automation-first approach against the noisy backdrop of automation anxiety is an ongoing and never-ending process of cultural change management and mindset shifts. After all, as Upton Sinclair proclaimed, “it is difficult to get a man to understand something, when his salary depends upon his not understanding it.”
That is why true digital transformation is so elusive. It is in fact 3 transformations rolled into 1 – organization, business and technology. And as we have repeated so often, the 3-word mantra for implementing RPA successfully got to be people, process and (only then) technology.
The Infinite Game of Automation
Change is hard because people tend to overestimate the value of what they have and underestimate the value of what they may gain by giving that up.
In the IA Global Market Report 2019 (H1) published by SSON, insufficient change management is cited as the number one reason why RPA/IA projects fail. And according to EY, as many as 30-50% of initial RPA projects fail.
Perhaps it is time for us to re-evaluate how we are playing this game of Automation? What do you think? Please share your comments below.
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***The Three Laws of Robotic Process Automation:
The purpose of the RPA software robots is to augment the existing human workforce.
The human managers are responsible for the actions of the RPA software robots.
The learning and development needs of the RPA software robots are no less than that of the human employees.