We talk to clients all the time who are excited about the prospects and tantalizing benefits of automation technologies. They have real problems to solve, and the faster the better. Unfortunately, to do these implementations well—where humans actually adopt the technology and even scale it–the journey, like most things worthwhile, takes time and effort. There is no silver bullet.
The closest thing to it however, already exists within your organization. So that’s good news! The bad news is that it’s unlikely documented anywhere and you’re going to have to talk to humans to extract it. And unfortunately, up-front collaboration with the business is not generally a known strength of technology teams.
I am referring to a most valuable resource—tacit knowledge. Tacit knowledge is the information that employees are aware of from their experience of doing their jobs. This undocumented knowledge drives decision-making and must play a central role in the design of your automation solutions. It is the golden spike of data that turns automation from basic to revolutionizing how work gets done.
Here is an example: North Highland uses Workday for its timesheets. Somewhere in Workday there is a job aid or user guide that covers the very black and white process of entering one’s time. What it does not include, and what every employee I know does, is the step of looking at our Outlook calendars to verify and even remember what the heck we did that week in detail. That is really how I fill out my time, on top of the formal Workday business process. If you were to build a bot to automate this process for a human, and you take only my tacit knowledge or only the documented business process, you are unlikely to get an optimized result because at best, you are working with a limited portion of the necessary information. The end product would inevitably fall short.
The same is true for automation. If you want it to replace or augment the work of humans, and generate cost takeouts and efficiencies, the subjective knowledge that your workers know from experience is critically important.
Capturing this knowledge is the reason these are not typical technology implementations. To be successful in automation, the work must be human-centered design meets data science meets technology. This approach can help you uncover new data sources, identify better applications of cognitive solutions for more immediate and viable ROI, and empower businesses to not only adopt these technologies more quickly, but to drive making them better, faster.
Don’t foolishly overlook the goldmine of information that walks past your desk every day—in more ways than we can name in a blog format, your people and what they know about the real, day-to-day experience of your business is the key to unlocking your automation potential.