HomeRoboticsAvinash Misra, CEO & Co-Founding father of Skan.AI - Interview Collection

Avinash Misra, CEO & Co-Founding father of Skan.AI – Interview Collection

Avinash Misra is the CEO and co-founder of Skan.  Avinash is a lifelong entrepreneur with a confirmed report of taking ventures from seed to liquidity. He has constructed profitable ventures within the enterprise digital transformation area and his final enterprise was acquired by Genpact (NYSE : G). Avinash’s perception for Skan took seed in giant scale Enterprise Course of Transformation initiatives which he has led during the last decade.

Your earlier firm Endeavour Software program Applied sciences was ultimately acquired by Genpact. What was this firm and what have been a number of the key classes that you simply discovered?

This firm was a front-office digital transformation specialist. That’s, it specialised within the construct and deployment of particular applied sciences resembling laptop imaginative and prescient, chatbots/ pure language processing (NLP), and enterprise cellular apps to enhance and rework customer-facing enterprise processes. 

We discovered two key classes. First, when expertise is utilized for its sake solely, it creates each technical and course of debt. Second, probably the most worth is derived when expertise particularly approaches the tip consumer with empathy and a design-think mindset. 

May you share the genesis story behind Skan?

“Automation begins when automation fails.” In a single sentence, this was our starting. Once we constructed RPA bots for advanced enterprise processes, we repeatedly observed that when a bot was deployed it failed shortly as a result of it didn’t take into consideration all the nuances, permutation, and exceptions of that enterprise course of. Each time a bot failed, it grew to become another lacking permutation of labor. It was an limitless cycle of deployment and failures. 

So, why don’t we all know all of the nuances of enterprise processes?

We don’t know all of the nuances of enterprise processes as a result of all course of discovery is completed by human enterprise analysts who ask the method brokers to explain work. People are spectacularly unreliable in describing issues which have a way of familiarity or routine and routine. These are sometimes issues they will do nicely, however can by no means describe with the wanted accuracy. Therefore, we constructed Skan to look at actual work and perceive that work and the processes, somewhat than interview and doc people.

Skan is partially a course of discovery platform. May you outline what course of discovery is for our readers?

Course of discovery is a broad time period that refers back to the act of discovering or studying how processes work at an operational or structural stage. That is significantly difficult with processes that contain human-system interactions with a whole lot or hundreds of staff, dozens of software program functions, and sophisticated workflows. An ideal instance is the claims administration course of.  

In the present day, Skan is definitely greater than a course of discovery platform. Skan generates a deep understanding of labor (course of discovery) and gives superior analytics to assist course of house owners and transformation leaders measure, analyze, and enhance KPIs that drive enterprise outcomes such because the buyer expertise, income, and value.  We name this broader functionality: course of Intelligence or the systematic assortment of information and the end-to-end course of and utility of that data to manage enterprise outcomes or to study, perceive, and make choices. 

In line with a examine carried out by Ernst & Younger, 30% to 50% of automation initiatives fail. Why do you imagine that is so excessive?

Based mostly on working with our prospects, we discover that one of many key obstacles to automation success is lack of visibility into present state of KPIs throughout the lifecycle of automation initiatives. 

As an illustration, with the intention to qualify an automation mission, we have to baseline the present state KPIs and construct a enterprise case. Within the experimentation section, we have to determine expertise patterns and outline goal (to-be) KPIs based mostly on present state KPIs. Throughout the design, develop, check, and operationalization section, we have to align with the foundation reason behind the issue to resolve. 

Lastly, within the validation section the place we measure funding payback and advantages realization, we want traceability to the to-be KPIs. So, we see that throughout this whole lifecycle, transparency and traceability to present state KPIs and root causes is required. And, but, in line with Forrester Analysis (2021), solely 16% of organizations say they’ve full visibility into how processes work. It’s no surprise automation initiatives battle to ship worth. 

Are you able to clarify what procedures Skan takes to guard the privateness of individuals which can be being monitored and delicate enterprise knowledge?

It is very important word that we don’t monitor folks. We solely observe particular components of labor (not the entire display). These components are particular work functions which can be predefined upfront.

That stated, for any functions noticed, all delicate work knowledge is redacted. We even have the flexibility to anonymize the hyperlink between the one that did the job and the method. The names of people working within the course of will be anonymized, too.

May you focus on how Skan makes use of machine studying and particularly deep studying?

Skan incorporates a number of AI and machine studying algorithms to deal with numerous issues resembling anonymizing delicate info (each textual content and picture knowledge), abstracting low-level occasions to enterprise actions, inferring course of graphs, and discovering course of variations.

What are some examples of actionable insights which have been gained from this course of?

Skan helps course of house owners and transformation leaders measure, analyze, and enhance KPIs that drive enterprise outcomes. Some instance insights are:


  • Unit value of manufacturing
  • Useful resource (workforce) utilization
  • NPS enchancment


  • Automation discovery
  • First cross fee
  • Course of compliance
  • Capability (workforce) planning
  • Diminished course of variability

What’s your imaginative and prescient for the way forward for course of intelligence?

Our imaginative and prescient for the way forward for course of intelligence is to rework the best way folks work to allow them to enhance productiveness and attain their full potential. 

In the present day, the worldwide pyramid of labor has a broad base of non-value added duties and a really slim prime of value-adding duties. Our imaginative and prescient is for course of discovery to invert this pyramid.

Thanks for the nice interview, readers who want to study extra ought to go to Skan.


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