The technology industry is abuzz with excitement relating to the next industrial revolution, the AI fuelled robotic revolution. The promise is that advances in computer comprehension will bring a new age in terms of decoupling employees from process and provide new levels of efficiency and creativity.
However, while AI is certainly important to this process the other key technology is automation, the technology which provides the pathways for computer initiated actions. Automation technology is what disconnects analytics and understanding from static reports that need to be digested by humans and instead triggers responsive or investigative actions affecting routine business operations. And while AI, what is also referred to as advanced analytics, may serve a key purpose in some automation processes, automation itself has a wider applicability in terms of continuous delivery of the existing, potentially simple, processes which exist in most businesses today.
For over a decade I have led a team building platforms that marry analytics with automation (focused within specific domains). And while we certainly leverage advanced analytics for complex processes, what is interesting is that much of the initial gains (efficiencies, productivity, quality etc.) actually come from automating what is already well known, understood and may be comparatively simple.
A limited resource in any organisation is the number of employees and every employee is limited by the number of working hours in a day and the number of working days in the week. If you speak to those in operational roles, most will be able to recite lots of things that they would like to be doing but don’t have time to do. Available time may mean what is urgent gets done, whereas what is ideal gets done at much lower frequencies that optimal.
This is where automation helps and becomes itself a mechanism supporting the advancement of automation in an organisation. By automating albeit simple common key tasks first you achieve several things:
- You can get quick wins, this is important for any initiative.
- You can achieve improvements in efficiencies and quality by doing “what you already know” consistently without it necessarily being complex
- Doing this frees up resources with domain expertise and now automation experience who can help drive the cycle of progressively more complex processes which may include decisions leveraging AI
It seems often those going down an automation path start trying to think of the hardest problems utilising the most complex of analytics first, as on-paper these would seem to be the ones most likely to generate value. However, in practice I have found that automation of simple but poorly attended tasks may bring substantially more value than initially expected. Going forward the “banking” of efficiency gains can then utilised to fuel a continuous cycle of improvement through automation of increasing complex processes.
"automation of simple but poorly attended tasks may bring substantially more value than initially expected."
Therefore, I feel automation is currently the most important concept that organisations heading down the robotic path need to consider. This itself has many considerations which should be factored into the IT landscape and the ability to integrate automation may influence future device and software decisions. Triggers and actions may be driven by AI, but equally many processes may continue to be relatively simple workflows of checks and actions based on simple logic or conventional analytics.
The opinions and positions expressed are my own and do not necessarily reflect those of my employer.
Author: Tony Bain
Tony has 20 years experience building software and services business using advanced analytics, collaboratively using computers to do what they do best and empowering people to do what they do best.
He is the co-founder of RockSolid SQL (now part of DXC Technology) and has grown the business to over 130 customers globally, and is also an adviser for LiquidityCube, one of the most exciting emerging fintech startups right now. Tony has written numerous books, articles and posts on data driven business and regularly presents at data focused conferences.