Virtual Assistants to Virtual Data Brokers…

“Ok Google!! What next?”

The way the Virtual assistant world is shaping up, at least in the consumer space, I wonder how dependencies will shape up as we learn and unlearn new ways of life. Google Now is a god send for sure, half of the time as I unlock my phone for one reason or another (most of the time it’s just habit!!), I inadvertently look at the google now page and smile – as it tells me that I should be all set for my upcoming trip to Delhi in two days and that it’s damn hot as always). The other half is…what who wants to read this and why should I listen to this song. You are left for more and I wonder why Google can’t pull it off with the army of great engineers at their disposal.

Challenge accepted, however it’s not an easy problem to crack. After all of us are dissimilar at so many levels that building an engine which learns me and responds/ interacts with me in a totally personalized way is still a dream.

Having said that, how about the enterprise world. Let’s look at an organization. Although there are different stakeholders and departments, the processes that define the organization, the language, the interpretation of numbers, the implicit and explicit understanding has a lot of similarity and hence makes it a good candidate to model. To build a system like this – what should be the starting point? Most of the enterprises have internal insights group that becomes the one department working with research vendors, internal stakeholders in answering business queries and helping businesses with insights. Most of the time the challenge with the insights group is that they spend a lot of time in administrative work – working with vendors, ensuring research is done in time, is of quality and then working on business queries that come to them at unpredictable rate.

Imagine a situation, where the insights team & the business teams have a data insights assistant at their call.

“Ok Doodle!!” “What is the screen size preference of segment A in China”

“Ok Doodle” “Forecast our current sales performance for the rest of the year”

This will not only free up a lot of time, it will also help the insights group in focusing on more complex studies. Mind you – the backbone of building a model like this will be the learnings that the machine will infer from the general behavior of the insights team. In my mind solving this has a larger purpose for organizations and will open up the next frontier of battle royale. Till that time –

“Ok Google” “Make me Sleep now”

Ashish Rishi, AVP Analytics

Follow: @rishilost

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