MALO 019 May 16 – Avinash Kaushik

Madonna - Bono - Oprah - Lizzo. You know who I mean.

In the world of digital analytics, the same goes for Avinash.

Avinash expounds on his career, his philosophy, his impact on the analytics industry - and just what the heck he's doing now that he's left Google:

• Where did Avinash Kaushik get his lifelong obsession about customer centricity?



• How much money has he raised for charity through the sale of his books and newsletter?



• Where did he develop his data chops?



• How did he get hired at Google?



• How did he end up using data to explain the value of marketing to the CFO of Google?



• How does he manage to crank out such great content for his blog and now his newsletter?



• And - just what the heck is he working on now?

Lots to learn here, including

Advice from Avinash Kaushik: Never make yourself indispensable

"If you make yourself indispensable, you never get promoted. That was my problem at DHL. I was so good at my job that I was the only person who could do that particular job at DHL. And after a while I could never get promoted, because they were like, 'Oh, if you promote him who's gonna do the job?' And so since then, within the first like, two years, I put in succession planning; invested in growing people, their skill sets, hiring people smarter than me, who can replace me on any day. Because if they can - if there's a replacement for me - that means I can go do other things.

Avinash Kaushik's view forward is Algorithmic Intelligence and Intelligent Automation.

"We go into a tool and write reports and the KPIs and segment and find assisted conversions and go down user journeys. All that is such a waste of time, because for the most time we're playing in the known known space. We're not so good at the known unknowns, and definitely, completely not good at the unknown unknowns. (Using AI), I can find the unknown unknowns a lot better... Let these algorithms go in and parse data, find patterns, and discover patterns that a human doesn't even know to ask for, right? 

But then you run into this problem... you still rely on humans and fragmented platforms to activate the insight and find value... so, the second part is Intelligent Automation. Spend a lot of time figuring out how to build connectors and pipes and take advantage of API's... so the decision can skip the human. Humans are the problem.