Skan: Visualizing the Future (of Work)
The last three decades have seen office work transformed by successive major technology platform shifts: the desktop computer, the internet, the cloud, and mobile. At Zetta, we believe AI is the next generational shift, with the potential to power new tools and automation in almost every industry. That’s one reason we were excited to meet Skan, a company that seeks to better understand the nature of work itself with the help of computer vision and machine learning.
“Information work” - task-based work done by humans with computers, like data processing - has been frequently outsourced (the Business Process Outsourcing market was over $200B in 2019.) This kind of work is also a favorite target of automation with RPA or special purpose machine learning tools. But offshoring and automation are not goals in and of themselves - they are a means to the end of improving efficiency, reliability, and speed. But not all processes are well suited to automation, and stories of failed automation are all too common. If we can’t clearly describe the work, how can we possibly expect to automate it - or even to know if automation is the right prescription?
Human workers are creative and resourceful, which makes them good at performing complex tasks and adapting to exceptions and changing conditions. That’s great news for delivering results, but it means that the real work being done by office workers can diverge sharply from the documented process, even for supposedly simple tasks like processing an insurance claim or sending an invoice. When Skan’s founders worked with big enterprises on digital transformation projects, they found that businesses didn’t really have a handle on what their team members had to do to accomplish their work. Even enterprises with sophisticated process mining technology didn’t have a clear understanding. Examining the logs in your system of record shows you what a human entered into the system, but doesn’t show you the ingenuity and tribal knowledge that went into achieving that result.
Skan provides (privacy assuring) instrumentation that helps customers map out what people are actually doing when they are doing their jobs. With that insight, enterprises are finally equipped to make better decisions. Let me show you what I mean.
Exhibit 1: A process map from Skan
Skan’s telemetry provides a graphical view of the work being done, the time spent, the interdependencies between tasks, and more. Now we can see bottlenecks. We can see what’s happening with “outliers” - instances of a task that take much more time than average. We can also see if shortcuts are being taken that might risk violating SLAs or compliance with regulatory rules. We can see redundancy or opportunity for parallelization.
This kind of granular view into the work itself enables enterprises to make informed decisions about process design, organizational design, adoption of tools, and yes, outsourcing and automation.
Skan achieves this with computer vision and machine learning - systems that watch pixels on a screen and abstract that raw input into a higher level understanding of work tasks situated in a context.
Without a product like Skan, enterprises make their best effort to figure this out, typically by hiring consultants to sit and watch employees do their jobs. It’s manual, slow, error prone, and based on much too sparse a data set. And the results are sub-optimal. One CIO told me, “I can’t imagine doing a digital transformation project without this. It would be like driving full speed down the highway with snow all over my windshield.”
Too many AI partisans advocate automation across the board. Skan and Zetta think this is exactly backwards. You have to start with a deep understanding of work, and only then does it make sense to ask where automation has a role to play, and how to implement it.
Skan’s founders are Avinash Misra and Manish Garg, two industry experts who led large scale enterprise digital transformation projects at Genpact. They predict that the future of work will not be a rigid separation of work done by humans and work done by robots, but rather a mosaic of humans, tools, and automation, working in tandem. We’re inspired by this vision and are excited to be supporting them on their journey!
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