Editorial
With all the noise about AI and automation, there’s still one big question that every organization has to face: if this technology is introduced, how will it land?
There’s a spectrum of possible scenarios, from either a soft or bumpier landing, right up to the possibility of a hard one. It’s the prospect of a hard landing that puts fear into individuals and strikes at the heart of the problem facing many would-be adopters of the technology.
But there are ways to allay these fears, two of which we’ll go into here: one, involve people more deeply in defining the change that will impact them, and more critically, simulate the impact of the change, before any actual work takes place.
Stakeholder engagement is the more obvious response of the two: a lack of it is, after all, one of the key reasons that technology-related projects fail.
Simulating the impact of user-suggested change is less obvious and will require specific software that is capable of performing this action. However, it is worth its weight in gold.
This combination of interpersonal engagement and simulation of user-suggested change is how leading organizations are activating automation programs and getting results.
Asking the Question
When automation invokes a fear-based response, it’s often because things are moving too quickly, and without a lot of necessary pre-work. Successful adopters put people, not technology, first: they determine the sentiment about automation and try to work through any issues before they do anything else.
One of the things I do with my team is to ask them what their job would look like in a dream scenario. What in their current role would they like to replace with something that offers more of a value-add?
This serves a couple of purposes.
Firstly, it engages teams to actively redefine their current roles. This is critical because it reaffirms to people that their role is going to constantly evolve, that evolution isn’t negative and that they can take control by playing an active role in defining that evolution.
Secondly, it builds the foundations for a discussion about AI and automation, two key augmentative technologies that provide people with opportunities to evolve their job roles in ways that positively impact them personally, as well as the broader team and organization. What are the things they enjoy about their role today and want to do more of? Is there an opportunity to automate away some less desirable parts to free up time for the more enjoyable bits, or to invest in career or professional development opportunities?
Thirdly, if automation (or AI) is introduced, and succeeds in evolving people’s roles in the way they want, it seeds a continuous improvement discussion. People become motivated to consistently ask: “Is there a better way of doing this?” That’s the needle shift on internal sentiment that organizations need if they are to get sustained benefits from automation and AI initiatives.
Related Article: Change Management in the AI Age: How to Sidestep Common Mistakes
Simulating Change
Having people themselves define the path for introducing automation (or AI) into their own roles may not be enough to guarantee success.
One way that successful organizations double down on this engagement is to simulate what the agreed change would look like on an existing process or role.
Simulating a change can be used to reinforce that the right decisions are being made, which increases assurance and comfort levels for individuals.
In addition, a quick way to find inefficiencies or bottlenecks in a process is to simulate the cost of running it. When teams are asked what each full process “run” costs them, they often don’t know. It’s immediately helpful to break down the process, map out its constituent parts, and define how much time, on average, each part requires to complete.
In an onboarding process, for example, there’s the interviews; approvals; the making of an offer; the assembly, delivery and return of paperwork; and the setting up of systems — so that the new hire can hit the ground running.
When each of these is timed, it can also be costed out. Inefficiencies, either in time taken or costs incurred, can be easily identified. These are opportunities for automation. The impact of introducing automation at each stage of the process can then be simulated, and the flow-on impact on time and cost understood, before any real action is taken.
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Asking the right questions and simulating any changes removes the FUD (fear, uncertainty and doubt) around automation and helps justify that it is the right path to take. It shows individuals and organizations what their future can look like and, in doing so, creates a path of least resistance to automation adoption.
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