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Inderpal Bhandari, IBM | IBM CDO Fall Summit 2018 - YouTube
Channel: SiliconANGLE theCUBE
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live from Boston it's the cube covering
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IBM chief data officer summit brought to
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you by IBM
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welcome back to the cubes live coverage
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of the IBM CDO summit here in Boston
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Massachusetts
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I'm your host Rebecca night along with
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my co-host Paul Gilliam we're joined by
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Interpol Bhandari he is the global chief
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data officer at IBM thank you so much
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for coming back on the Q Vander Paul
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it's my pleasure great to have you thank
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you for having so I want to talk I'm
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gonna start by talking a little bit
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about your own career journey you start
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your first studio job was in the chief
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in the early 2000s
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you were one of the first Studios ever
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in the history of chief data officers
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talk a little bit about the evolution of
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the role and sort of set the scene for
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our viewers in white terms of what
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you've seen in your own career Yes No
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thank you at December 2006 I became a
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chief data officer for major healthcare
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company and you know it turned out at
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that time there were only four of us -
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in banking one in the internet I was the
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only one in healthcare and now of course
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they're well over a thousand of us and
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the professions taken off and I've had
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the fortune of actually doing this four
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times now so leaving a legacy in four
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different organizations in terms of
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building that organizational capability
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I think initially when you know when I
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became chief data officer the culture
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was one of viewing data as exhaust
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something that you had to discard that
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came out of the transactions that he
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were you know your business was doing
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and then after that he would discard
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this data he didn't really care about it
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and over the course of time people have
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begun to realize that data is actually a
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strategic asset
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really use it to drive not just the data
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strategy but the actual business
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strategy and maybe enable the business
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to go to the next level and that
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transitions been tremendous to watch and
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to see I'm just being fortunate that
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I've been there if you see any consensus
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developing around what background makes
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for a good CDO what are the skills in
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the CDO needs yeah no that's a very very
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good question and that my view has been
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evolving on that one to you over the
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last few years right as I've had these
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experiences so I'll jump to the
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completely so maybe panel to answer your
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question as opposed to what I started
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out there the CEO has to be the change
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agent in chief for the organization
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that's really the role of the senior so
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yes there's the technical chops that you
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have to have and you have to be able to
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deal with you know people who are who
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have advanced technical degrees and to
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get them to move forward but you do have
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to change the entire organization and
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you have to be adept going after the
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culture changing it
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you can't get frustrated with all the
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pushback that's in available you have to
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almost develop it as an art as you move
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forward and aggressive not just bottom
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up and you know natural we'll also talk
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now and I think that's probably where
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the up gets the most interesting because
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you've got a push for change even at the
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top but you can push you know just so
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far without really be mailing everything
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that you're trying to do and so I think
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if I had to pick one afternoon it would
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be that the video has to be the change
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they're going to have to be adapt and
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addressing the culture of the
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organization and moving it forward
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you're laying out all of these sort of
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character traits that someone has to be
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indefatigable inspirational true
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visionary you also said during the
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keynote you have six months to really
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make your first push you have six month
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the first six months are so important
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when we talk about presidents it's the
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first 100 days describe what what do you
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mean by that you have six months so I'm
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talking to mainly about a large
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organisation like an IBM a large
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enterprise when you go in
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[Music]
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the key the key observation is it's a
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functioning organization it's a going
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concern it's already making money is
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doing stuff like running down although
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they have their own needs and demands so
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very quickly you can just become
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somebody who ends up servicing multiple
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demands that come from different
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business units different people and so
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that's kind of one aspect of the way the
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organization takes over if you don't
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really come up with an overarching
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strategy the other way the
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organization's take over is typically
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large organizations are very silent and
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even have the lower levels you have you
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know people who develop little fiefdom
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when they control that data
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and they say this is why I'm not gonna
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let anybody else have it they're the
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only ones who really understand that
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curve and so you're pretty much unless
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we were able to get them to align to a
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much larger form we will never be able
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to break down those silos culturally
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just because of the way they set up so
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it's a pervasive problem it goes across
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the board and I think when you walk in
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you've got that for pollen honeymoon
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period or whatever my estimate is based
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on my experience six months if you don't
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have it down in six months in terms of
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that ladder Falls that you're going to
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push forward that you can use to at
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least align everybody with the wizard
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you're not going really succeed in
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succeed tactically but not in a
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strategic sense you're about to
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undertake the largest acquisition in
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IBM's history and as the chief data
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officer you must be thinking right now
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about what that's going to mean for data
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governance and and data integration how
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are you preparing for an acquisition
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that large yeah so you know the
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acquisition has still gotta work through
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all the regulations and so also there's
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just so much we can do it's much more
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from a planning standpoint that we can
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do things I'll give you a sense of how
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I've been thinking about it but we've
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been doing acquisitions before so in
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that sense we do have a set process for
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how we go about in terms of evaluating
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data how are we going to manage the data
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the interesting aspect that was
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different for me in this one is I also
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brought back on our data strategy itself
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and tried to understand now that there's
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going to be this big acquisition of news
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following the planning standpoint how
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should I be prepared to change with
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regard to that activation and because we
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were so aligned with the overall IBM
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business strategy to pursue cognition I
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think you could see that in my remarks
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that when you push forward AI in a large
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enterprise you very quickly run into
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this multi-cloud issue where you've got
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what there's different clouds but also
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on cram and private clouds and you have
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to manage across all that and that
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becomes a pain point that we have to
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scale the scale you have to get past the
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pain point and so we were already
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thinking about that we actually I I just
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did a check after the you know the
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acquisition was announced asking you
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know my team to figure out well how
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standardized are we with red have looked
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and I find that we're actually
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completely standardized across with Red
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Hat Linux we pretty much will have use
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cases ready to go and I think that's a
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facet of their you know because we were
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so aligned to the business strategy to
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begin with
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so we were discovering that pain point
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just of all our customer here and so the
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corporation acted as it did in some
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extent they were already ready to go
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with use cases that we can take directly
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to our clients and customers I think it
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also has to do with the fact that we've
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had a partnership with pretty studio do
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you think people understand AI in a
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business context I actually think that
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that's people don't really understand
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that's was the biggest in my mind anyway
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the biggest barrier to the business
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strategy that we have embarked on you
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know several years ago to take AI or
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completion to the elephant people never
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really understood it and so our own data
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strategy became one of enabling IBM
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itself to become an AI enterprise and
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used that of a showcase for clients and
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customers and all of the journey in the
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last 50 years that are meeting at IBM
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we've become more heaping putting
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forward more and more collateral but
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also technology but also you know
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business process change ideas
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organizational change ideas so that our
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clients and customers can see exactly
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how it's done
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not that it's perfect yet but back to
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their benefits right they don't make the
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same mistakes that we do and so we've
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become
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your colleagues have been covering this
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concert so they will know that it's
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become more and more clear exactly what
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we brought you made an interesting
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comment in the keynote this morning you
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said nobody understands AI in a business
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context what did you mean by that so in
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a business context what does it look
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like right what does the eye look like
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from okay all right well we can talk
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about this a little bit too well well I
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think we understand AI you know as
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Amazon echo right we we understand it
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isn't as an interface medium but but I
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think what he was getting at is that
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impacting business processes is a lot
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more complicated right and so we tend to
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think of AI in terms of how we relate to
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technology rather than how technology
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changes the rules right and clearly
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clearly it's such a it's on the consumer
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side we've all grasped this and we all
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are excited by its possibilities but in
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terms of the business context it's the
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season
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[Laughter]
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to your question with regard to how a
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INF Innocence Project consumer context
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everybody understand but in a business
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context water that really mean that's
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difficult for people to understand but
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eventually it's all around making
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decisions but in my mind it's not the
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big decision it's not the decisions that
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we regatta a virus and stop those
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decisions
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it's the thousands and thousands of
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little decisions that are made in a day
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in and night out by people who are
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working the rank-and-file who are
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actually working to different causes
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that's what you really need to go after
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and if you're able to breathe out it
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completely changes the process and
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you're going to have just such a lot
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more out of it not just in terms of
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collectivity but also in terms of new
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ideas that need to revenue and
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new products for several summers that's
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what a business business AI enterprise
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looks like and that's what we've been
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bringing forward and showcasing what
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today's keynote actually at Sonya one of
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our data governance people SMEs who
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works on metadata generation which is a
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very difficult manual problem little bit
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data about data specifically labeling
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data so that a business person for the
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standard it's all being done manually
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but now it's done automatically using AR
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and it's completely changed the process
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but Sonia is the person he's at the
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forefront of that and I don't think
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people really understand that they think
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in terms of AI and business and they
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think this is going to be you know
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somebody who the data scientists
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technologists you know somebody who's a
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very talented technical engineer but
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it's not that it's actually the
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rank-and-file people who've been working
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these business processes now working
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with an intelligent system to take it to
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the next level is the change agent in
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chief because it is it does require so
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much buy-in from as you say the
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rank-and-file it's not just the top
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decision makers that you're trying to
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persuade effective change at all levels
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stop down bottom up laughs early you
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have to you have to go out to it across
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the board and it talks in terms of
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talking about the data it's not just
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data for data's sake you need to
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you need to talk about it in terms that
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a business person can understand during
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the keynote you described an earlier
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work that you were doing with the NBA
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can you tell our viewers a little bit
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about that and Edmund sort of how the
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data had to tell a story yeah so that
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was in my first go-around with IBM from
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1990 through 97 I was with IBM research
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of the Watson Research Lab as a research
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staff member and I created this program
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called advanced scout for the National
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Basketball Association ended up being
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used by every team on the NBA and it
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would essentially suggest who to put in
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the lineup you know your mapping lineup
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and so forth by looking at a lot of game
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data and it was particularly useful here
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in the playoff game the major lesson
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that came out of that experience for me
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at that time right this is before
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Moneyball and before you know all the
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stuff it was like 90 93 92 I think if
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you google it you would still see
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articles about this but the main lesson
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that was you know that came out for me
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was the first time when the program
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identified a pattern and suggested that
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to a coach during a playoff game where
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they were down to zero it suggested they
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start to back up player and the coach
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was just completely flabbergasted and
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said there's no way I'm going to do this
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this is the kind of thing that could get
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me you know and not only get me fired to
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make me look really silly and it hit me
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then that there was context that was
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missing but you know the coach could not
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really make a decision and the way we
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solve it then was we tied it to the
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snippets of video when those two players
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were on call and then they
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we made the decision that went on the
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one that game and so for today's today's
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a I system can actually fathom all that
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automatically from the video itself and
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I think that's what's really advanced
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the technology and the approaches that
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we've got today to move forward as
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quickly as they have and that they can
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hold across the board right you know in
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the sense of a consumer setting but now
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also in the sense of a business setting
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where we are applying it pretty much to
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every business parcels that we have
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wonderful thank you so much for coming
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back on the cube oh oh is pleasure
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talking to you it's my pleasure thank
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you i'm rebecca night for paul g眉len we
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will have more from the cubes live
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coverage of IBM CDO coming up in just a
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little bit
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