Last Mile of the Analytics Journey

What did you believe is to be the next evolution of analytics?... and more importantly can AI & Voice be leveraged within an enterprise to equip decision makers with real Analytics. We had our own assumptions and mostly based on experience and varied level of interaction we had with CXOs, business heads, BI teams and analysts.

We were invited to the Deloitte 2018 Convergence event to showcase alphaa.ai and discuss our take on driving analytics within organisations, journey of an enterprise from data to decision. Answer lies in simplification.

Good thing about life is that it's never done teaching you. :)

At the #Convergence2018 we interacted with Deloitte partners, heads of service lines, C level leadership & project teams from India & US who have vast experience with 100’s of clients across scores of projects in numerous industry sectors across major geographies. Our discussions centered around:

• How can an organization be information driven?
• How can data silos be conquered?
• Can business users be enabled with insights in minutes?
• How do we convert more business users into explorers of information?
• Could there be a better way to determine ROI from Analytics?
• Can the enterprise decision process be standardized?

Learning was immense and more than that the validation of idea and direction. There was a universal agreement that businesses around the world are facing analytics challenges around Insights, Collaboration & Decisions which needs to be solved with simplicity, agility & high ROI.

Organizations attempt to increase adoption & usability of dashboard assets through training & change management phases where they are suppose to learn how to point & click and try to determine their business insights. Even after the change management process, consumption skews largely towards, viewers, users that only want to view limited KPI’s, whereas a smaller group, explorers, are utilizing the dashboard asset to determine business insights. 

Yet another problem dawns with organization’s crucial dashboard assets - Human Comprehension, interpretation of a/various visualization and what they are attempting to convey through numerical numbers.

As the decision makers progress with framed data they face another concern, missing KPI’s or dimensions that were never included on the dashboard since there was limited space on the canvas (real estate). So what is the natural process, download some parts of this data into an excel file and merge with missing data - now you have another problem Data Silos: the very problem dashboards were suppose to fix.

Well that closes the loop and you are right where you started. Congratulations :)

For us it was an amazing opportunity and as a startup we managed to take feedback of our intended users and even surprise many of them. And made new friends. :)

Looking for the answers? Well I am not really sharing the learning arounds the questions raised yet but you can read the detailed version my colleague @Uday Gupta put down here (Click Link) and hopefully add your thoughts.