CIO Leadership Live with Vince Kellen, CIO at University of California, San Diego | Ep 17

CIO Leadership Live with Vince Kellen, CIO at University of California, San Diego | Ep 17

October 14, 2019 0 By Stanley Isaacs


hi good afternoon and thank you for
joining us for another episode of CIO leadership live I’m Mary Fran Johnson
I’m the executive director of CIO programs here at IDG and I’m very
pleased to have with me today Vince Kellen who is the CIO of the
University of California at San Diego Vince joined UC San Diego back in 2016
to provide leadership and management for all aspects of IT resources and program
initiatives last year this university was ranked as the 15th best university
in the world by the prestigious academic ranking of world universities Vince is
also responsible at UC San Diego for supporting an innovative and robust IT
environment across the campus the university is a five billion dollar
enterprise that is home to sixteen nobel laureates 20,000 employees and more than
39,000 students taking 100 different degree programs before he arrived in San
Diego Vince was the senior vice provost for analytics and technologies at the
University of Kentucky where he spent eight years in addition to his current
role at UC San Diego he has been since 2007 a senior consultant and fellow in
the Qatar consortiums business Technology Council and like many of his
peers in CIO plus augmented roles Vince has served on advisory boards for
numerous IT companies and technology vendors and today’s he is a member of sa
Pease customer advisory board throughout his career he’s also authored four books
on database technology and more than 200 articles and presentations on IT and
business strategy topics Vince welcome thanks for joining us today thank you
glad to be here yes and I thought we ought to dive in right now most of our
audience may not be as familiar with the way digital transformation and the
issues that we we write and talk so much about in this industry the way they are
impacting higher end so I wanted you to kind of give us a
50,000 foot view of how digital transformation what it means for higher
ed today and what you see in the near term future sure and higher education is
a really big market with lots of different interesting players from our
traditional universities of which we are too many that are much more focused
online and professional education so we got a whole range but broadly speaking
universities have three basic missions one of them is to help with education
and teaching an instruction another mission related to research which is
often very technical uses a lot of Technology and the third one is using
technology in our own administration and our own efficiencies that we try to get
and what’s happening in higher education is happening in business and that is the
inclusion of a ton of Technology in many things we do we’re somewhat aided by the
fact that we have young students who are coming in with a you know a collection
of technologies between cell phones iPads laptops gaming devices etc our
universities are chock-full of computers and devices so we’re very technology
rich in terms of the number of pieces of technology around us and so the
transformation is now hitting broadly across all these missions and it’s
causing a lot of changed a lot of technology adoption challenges because
of all the change and a tremendous amount of opportunity as well yeah well
in that and we’ll we’ll talk a lot more about taking advantage of that kind of
opportunity because I know when we when we spoke last week we talked a little
bit about this increasing digitization of the processes the adoption of
practices the business processes products that how all of that is
proceeding probably at a higher rate of speed than it did in the past oh no
question yeah all universities are using modern local
enterprise systems ERP systems in fact we have many pieces of software to
handle our various business processes but even something as simple as you know
when you graduate a university and you have a transcript and later in life you
want to live for a master’s degree you call us and say I want my transcript
sent over yeah well that’s now getting digitized and probably in the near
future will be a subject to blockchain technology yeah in which much of that
gets automated so yes we’re seeing that continual it’s like the waves coming to
shore every period of time there’s another thing another process to opt to
optimize and improve we have one wrinkle in higher ed we are the land of complex
operations so we have a lot of processes many of our processes handle a smaller
number of transactions which is very different than a larger corporation
which might have fewer processes and a very large number of transactions and as
an example our philosophy department may hire a faculty or so every few years so
it’s a process they have to execute but not very frequently we got a lot of like
that in higher education mmm-hmm now has the the proliferation of
all the tools and technologies how much has that changed the classroom
experience for the students at both at UC San Diego and the other universities
that you’ve seen because you’re very active in the in the education community
well then that’s kind of a bipolar answer on one side you can walk into
most University and still see students sitting in seats much as they did a
hundred years ago and you still see the primacy of the face-to-face interaction
yeah but what’s been going on in some cases quietly but in some cases with a
lot of public fanfare is a lot of use of internet video and audio streaming hmm
lecture capture interaction devices within the classroom and outside the
classroom to enrich the learning experience digitally and every major
university is very focused on that as are we yeah do you think is it like
when you look ahead and think about the next five to ten years is it likely that
the major universities will all have a hugely significant online presence like
that they may actually end up with more students online than they do in the
classroom are we heading that way quickly in the five year window no in
the 10 year window we will probably grow our digital interactions in the areas of
what we call real earners adult learners who are coming back multiple times
throughout their career and that’s more likely to the case where we’ll see more
online at that 18 to 20 to 23 year old range I think we’re still likely to see
a lot of face to face on-premise education because more than just
education occurs at the University in many ways the students are are trying
out their independence from their families for the very first time yeah
and universities have that role too mm-hmm well and one of the things that
we talked about previously which I thought was a very interesting take on
it was the idea that human beings shaped technology more than the opposite and
the view today seems to be that technology is changing our brains and
that children exposed to screens at the age of 2 years old that their brains are
rewiring and all but you have a different take on that yeah I do it
certainly informed by my PhD work in the area of cognitive psychology and
learning and while there is some measure of neuroplasticity in the brain the
brain is structured in such a way to process information in a very peculiar
and human way and so III flip it around and I say rather than think about how
technology may be changing us let’s flip it around and see how do humans shape
the technology to suit their goal and you know I I was speaking at a few years
back at a distance learning conference in Florida and I started the very first
sentence of my presentation was I was at this distance learning conference in
Florida when I had an epiphany mm applause to see if the
audience would get in the epiphany was why are we here in Florida face to face
at a distance learning conference talking about distance learning yeah why
aren’t we doing this all at a distance at a distance and my point has been that
when higher education goes completely virtual and learning is actually
superior in a virtual environment than any face-to-face environment then so too
will be many other human experiences mm-hmm and so at that point Society
would have been massively reshaped and the question I would ask myself is
whether I should take the red pill or the blue pill a reference to matrix so I
kind of invoke what I call the war feein principle which is really borrowing from
Star Trek and Worf when asked by the Borg to embrace assimilation into the
morgue Worf responds no thank you I like my species the way it is yeah
and many human beings like the face to face they like the personal contact they
like the interaction with facilities and in an environment and when the
artificial world becomes equivalent to that that’s a pretty scary place and for
the next times ten years that’s not gonna be an issue yeah that’s why I
think we’re gonna end up in a balanced space between on-premise textu things
and use of online and I think we’re already saving the contours of that line
being drawn here pretty well well and as we talked about this is your war fee in
principle is actually fairly good news for my business when in the face-to-face
conferences that we do with CIOs because we haven’t seen those are continuing to
be very well populated and profitable for the business whereas so many other
forms especially in publishing have been overtaken by digital but not the
face-to-face conferences those still those still matter that ability to get
together and talk with each other yeah and human beings have been doing this to
dawn of civilization so it’ll be very hard to unravel that yeah well let’s
talk a little bit about the disruption going on in your industry and the chain
customer demands cuz I tend to think that any business public or public
university or private dealing with the 18 to 23 year old population is going to
be dealing with a lot of expectations about technology advances and so forth
so talk about the way disruption itself is changing your incoming customers and
how Higher Ed is responding to that yeah I think for our students they’re coming
in with a great expectation for how the universities can fulfill upon an
education experience that’s enriched with all of this technology I think that
that’s one pressure we’re getting another pressure we’re getting is from
what I call our citizen stakeholders and federal governments and state
governments to find ways to make to ensure that higher education is cost
effective so we have a lot of external demands to say hey can you use
technology to lower your cost structure and keep your costs in line so we got
pressure from both sides here both from the student in rich the environment that
they’re in and then from our citizens stakeholders
use technology to be efficient so it’s kind of a double-edged sword there okay
well and how do you when you think about the well diversifying markets that are
bringing more of their education products online
I was interesting the observation that you made when we talked earlier was that
the Internet one the online universities when they first showed up that as a big
disruptive force that didn’t really take root I explained that a little bit yeah
I mean when we go back to the 90s late 90s in the early notes when some of the
for-profit universities come out and really push online learning a lot of
what you saw or what I saw was what I call Model T type engineering which is
one class now big done even larger so a very tightly controlled bit of content
and a very scalable sort of delivery function so basically a bigger mass
manufacturing floor and obviously those models as we look at and today did not
stick for a couple reasons one I think they were trying to
cover up new markets for which the cost-effectiveness ratio wasn’t so high
and in fact the ballooning debt of students was born more than half by
students who attended those types of universities but I think what we’re
seeing coming up now is a little different even from some of the
for-profits which is trying to be extremely cost effective and a little
more tailored a little more personalized for the learner mm-hmm
so you get a little startup like Minerva which is doing using technology in a
great way for a very small population of students right now a universal ed
governor Western University which has been quietly making inroads at this
cost-effectiveness and digital realm so we’re starting to see those continued to
grow but we’re also seeing the elites the Harvard’s the MIT s even
universities like us that are now really jumping in and trying to master the
digital education realm mm-hmm what’s give us an example of something that UC
San Diego has done in the last year in that digital realm something that
students and the outside world would notice well first of all we’ve got a
fair number of content and courses up in Coursera and we’ve been doing that for a
while now and we’re coming out with some Masters of Science degrees in data
science you know in the EDX environment that’ll be coming in the next year so
where we’ve already been in kind of in the the certificate realm meaning non
degreed in Coursera but now we’re starting to move some of our degrade
programs right up to a tax okay and who’s our friend who’s joining us for
this yeah really is it just one he’s noisy yeah I have two miniature
dachshunds and they think that they’re Rottweilers and so when they bark and
I’m on the phone it’s you can hear them all over the house
let me see back to and you had mentioned to the about how much the market is
diversifying how Arizona State for instance is getting massively big yes
Arizona State’s been making great inroads and
and expanding their digital realm and increasing their enrollment their
strategy is to try to serve more of their constituents in a bigger way yeah
and I think that’s a very interesting and good strategy for higher education
and you’re seeing in the East Coast in in New Hampshire the University there
that’s been very successful in trying to grow its online I think some things Ohio
State did to provide blended learning activities a few years back is is
exemplary so we’re you’re seeing a number of
universities take initiatives yeah differently and so I think this
diversity of approach is exactly what is in order for the market that’s great
well because one of the observations you made is that the big brands need to get
bigger but the small brands have to do that as well and they’ll probably have
it in different ways yeah in the online space here it’s really about brand
warfare and how brands then compete with each other across a larger geography
most universities are very geographically driven when you go to the
online space you can now go global but when you do go global you are now
falling into what I call brand warfare 101 yeah and so you really have to
enhance your brand and bring it forward and so the bigger but highly branded
universities certainly have an advantage and the smaller universities have to
carve out their niche and build their brand mm-hmm and doesn’t it require a
very different a deeper understanding of the markets you’re serving when you go
yes absolutely international even across United States
you you really have to do good market analysis and market research we’re
trying to do that here in San Diego with our digital offerings and you really
have to meet the market now yeah yep in the past universities would build some
buildings and attract audiences from the from the local and geography and the
digital realm it looks much more like conventional digital business okay
interesting well and that it kind of naturally brings us in to talking a
little bit more about data science and you mentioned you’ve got a master’s
degree program coming up in that that will be
offered in a digital realm in data science and that you’ve got a lot of
kids that are rushing to get degrees in data science talk a little bit more
about that because I know that this is a trend well AI and machine learning and
digital science that you’re very bullish on over the next decade yeah absolutely
data continues to grow both its diversity its volume and in the speed
with which it’s coming so that’s continuing we’re finding all sorts of
uses for that data in driving value in different ways the problem is in a land
of complex interactions or complex processes it’s not like you’re gonna
have one algorithm that will control everything you’re gonna have hundreds
and hundreds of different approaches what we call analytical approaches based
upon the particular problem and that’s the land of data science how do you
design an environment that can handle a lot of different machine learning AI and
conventional bi sort of analytics going on to support what the university is
trying to do this is occurring in industry in a big way as we know data
the term data Lake has grown up to refer to a larger collection of data that
could be you know tapped for usage later and so we’re doing that as well as many
universities are and responding to it I think this is a trend that is to me this
is the analytical trend is much more significant and much more serious it’s
probably not quite as big as Internet 1.0 but but nearly and that’s gonna last
over the next 10 to 20 years a lot of insight and the research that we’re
getting how to design and and make new things at nano scale or new medical
techniques and technologies are driven by exotic forms of analytics and this is
going to become much more common a big reason it’s getting complex is silicon
is kind of tapped out in terms of its power and hence we have to speciate or
diversify the approaches we take in order to can
you handle the large increase of data coming at us okay so I think this is a
huge area for the next decade I would tell all students you know just like in
the movie the graduates my boy yeah I would say science data science data
science well I’ve been and whenever you know anybody who is a young person
seeking advice which usually they never do
but I’m always saying go into technology or healthcare because I feel like those
two industries are going to rule the earth yeah I mean and healthcare is it’s
certainly got a strong demographic component because here United States we
have end-of-life care mm-hmm for the baby boom generation which is
driving a lot of this so it will have kind of an ebb and flow to it as well
but I think this data realm is a permanent feature of the economy and
that permit but a feature of this economy for next 20 years yeah well
let’s talk more specifically about the way you have the big projects the
business and technology initiatives that are leading for you at UC San Diego and
I believe the top one you mentioned to me is that you’re modernizing all the
transactional systems and then now your data warehouse is essentially it’s it’s
a machine learning platform now it talked a little bit more about that and
explained yeah absolutely first we’re right in the middle of replacing our
ancient COBOL systems which we actually have still today driving our business
processes of finance and payroll etc with modern ERP but as part of that
we’re also completely transforming our data warehouse environment so we’re
using in-memory analytics from sa P HANA and we’re bringing all that data into
that environment and then we’re using that environment as kind of the nucleus
of a machine learning platform where we can put advanced analytics of a variety
of sorts on top of that data like I’ve been dealing and use that to drive all
sorts of interesting things we might want to do in the university setting
yeah what sort of when I
when I think about data lakes especially versus data warehousing I think of de
lakes as having more diverse and structured and unstructured data in them
am I correct in that yes I do I think you are correct structured and
unstructured but structured is a continuum so you know you can have
lightly structured data heavily structured data the reality is most
places both businesses and universities have still not tapped they’re structured
data well enough okay and when you enter the machine learning world in the AI
world while it’s very good at unstructured data wherever there is
structure that even enriches the models more so so we’re taking kind of a
both/and approach we’re trying to enrich our structured our sets of the structure
of our data in this very clearly articulated local activity hub design as
well as enable unstructured analytics as well so I think it’s a bulb and it’s not
either/or all right the can you give me an idea of
the size and the scope of your data like how much how much data is in your like
oh how fast is it growing how many people have to tend to it yeah we’ve got
a team about 15 in our bi team and and you know and in did warehousing team
that attend to the data so it’s it’s generous team baha’i res standards but
not a huge team and not a big team at all the amount of data we have for
University on the structured side you know it’s comprising our finance system
our HR system our payroll systems our student systems etc with 10-15 years of
data so we’re gonna you know we’re not going to be in this 30 40 50 terabyte
range but it will be pretty close to that when we’re done now that’s all in
memory it’s highly compressed so it ends up being even smaller than you’d realize
it’s the unstructured round that actually that you point out that’s
that’s where it gets very big quick for example we’re going to be ingesting
learning events from our LMS or learning management system
and these are the interactions and instructors and students will have in
the LMS that gives us very good clues as to what’s working in the LMS what’s not
yeah and how to improve the educational experience for the student
well that’s capable of throwing off millions of rows per week and we can get
into the billions of rows with just a few years so with that in mind we’re
also pairing up our in-memory analytics with a serverless head Abed of scale had
a bite scale type data Lake environment as well okay now is a learning
management system is that the higher ed equivalent of an ERP system no it’s it’s
Minh higher ed incorporations it’s a place where students go in to get their
course material interact or actually have their course content delivered oh
good video streaming for example if you were to record what we’re doing here
today as one big video stream we can put that up into learning management system
and students who are in the class could replay this to their heart’s content
over and over again I would hope they’d want to to find out what their CIO is up
to yeah but there’s very interesting use cases that come out of this for example
as we’re talking here I might use a phrase that the listener might not know
and they’re watching this replaying it at night and if they’re searching three
or four times for this peculiar phrase we’ll call it digital transformation we
can have two hypotheses about that activity one they’re very confused or
two they’re very interested yeah with the assumption they’re probably confused
well imagine the technology suddenly alerts an expert who says oh are you
listening to Mary Fran and Vince talk about digital transformation no here’s
what they mean and that person call them up on their cell phone right in the
middle of mm-hmm it sounds creepy but if you turn it into
a value-add opt-in service where you can get just-in-time tutoring while you’re
interacting with your course material that’s not a bad example of how the
technology can enrich the environment or even just simpler things like the
technology inserting some content relevant to the discussion that’s going
on automatically for the learner okay well considering the enormous
modernization system you have going on and I think you said one way to think
about it is that not a single part of I T will be unscathed that everything is
getting changed this is a process that you started when you got there about two
years ago right tell me what sort of structural type
changes you’ve made in the IT group talk a little bit about the size and scope of
it and how IT is organized differently now to deliver all of this change that
you have going on yeah we’re about 400 IT staff servicing the institution at
the central level we have a another IT group that handles our healthcare side
of life with a separate CIO so I’m going to set them aside and then we’ve got
probably an equivalent number of IT people sprinkled across the university
mainly in the area of researcher support and faculty support our research
business is a 1.2 billion dollar business just by itself so we got 400
staff here we’ve had – what we’ve done in the last year is we’ve stood up an
enterprise architecture function mm-hmm it has about seven our enterprise
architects in it we’ve stood up a project management function with a very
strong discipline around project management we’ve stood up a total
quality management function that handles the continued education of ITM Lean Six
Sigma or a Lean Six Sigma shop we put all 400 employees for Lean Six Sigma
yell about training we’ve got about 15 plus who are Green Belt certified and
probably have three or four black belt level mm-hmm the training that we did in
this of all 400 people getting some process training and Lean Six Sigma has
resulted in 1800 employees total now at the University have been through Lean
Six Sigma training more coming I wondered if it extended beyond IT people
if they’re also an extended bottom up yes we’ve added some of those pieces to
our structure and then the bigger changes are gonna occur when
we start to empty our data centers one data center is empty we’re gonna empty
out the one in the next two years and then we’ll be pretty much 100% cloud or
90 percent cloud with some older systems that don’t lend themselves to the cloud
still being run on prim but in a Colo facility versus within a data center
that we’re running okay and you’re also in the process of I think standing up a
data Sciences Operations Group yes as part of it we’re looking at how do we
support all the analytical work that’s going to need to happen and so we’re
looking at a data science operations group which has two main functions one
of them is to handle data logistics mm-hmm how to move data in and out of
these environments hopefully real-time and incremental via modern technologies
in the cloud and then the second case is how do you design the different forms of
analysis needed from data architecture right to designing a machine learning
approach to tackling an analytical puzzle interesting well and you had
mentioned too that what you’re doing you don’t consider it DevOps or even data
ops but des ops data science ops yes so that’s gonna be the next new thing after
DevOps well I you know when you go to the cloud you know software’s a service
solution where you’re now kind of out of a software engineering game which I
think it’s appropriate because software engineering is what I call the La Brea
Tar Pits for the naively over-optimistic everybody jumps in thinking they can do
software and then when they write a bunch of software seven years later they
got to rewrite it and now they’re looking just like any other big software
houses face with rewriting their software yeah and we often don’t include
those costs when we go to the cloud software as a service that activity
drops down rather significantly what doesn’t change is a need to integrate
data between various systems while we’re going to have an ERP system we have
another 15 20 systems around that that comprise to make up the various pieces
of software we need to run our biz here that data has to get moved in and
out of those and into our analytical environment so there’s this data
movement piece that has to get tackled and then the so the the development
activity now will be how to create quick integration points very quickly when new
software comes onboard or changes and then secondly how to create data science
packages and workloads and get them working in the environment so
development instead of being DevOps meaning we’re developing software and
then moving into operations and improving that cycle now we’re trying to
bring out stores of data get them integrated and get the analytical
routines built quickly so that’s what I call data science apps do you sobs it’s
it’s cool it sounds like it’s very much the next steps that a lot of beginner
prizes will be encountering I think that’s where we should be I mean it is
at the core of competitiveness for human beings and businesses so yeah we should
do everything we can to shore that up mm-hmm well and with the four books
you’ve written on database technology it looks like you picked a really good part
of IT to have your expertise in yeah yeah I torture my staff with my
questions I was wondering I was wondering how hands-on you get with the
DES Ops teams whether they hide when they see you coming in some areas I’m
deeply in touch with some details but they’re all very skilled very capable
people and they’re very good at telling me when I’m all wrong yeah well let me
see another you mentioned the Lean Six Sigma and the training around that is
that something that you that came with you when you joined UC San Diego was
that new too or was that already underway when you got there it was new
to the organization University of California San Diego has been doing Lean
Six Sigma training to the outside world yeah
through our extension group and we have an internal I think it was a a small
internal consulting group called our office of strategic initiatives where
they’ve been doing some Lean Six Sigma training I’m a big believer in total
quality management and preface thinking yeah and so that I
think it’s very skilled in that and when I came in I said wow I’ve got these
capabilities here let’s use them to train us how to do Lean Six Sigma so yes
yes I brought that in I’ve been doing that my whole career everywhere I go so
mm-hmm and that started back for my oil and gas
days yeah well it sounds like a like you were essentially resolving a shoemaker’s
children issue you know where there was honey there was Lean Six Sigma training
going on but not targeted inwardly yeah that’s correct all right one of the
other things we talked about was the way the the the types of vendors and the
relationships with vendors how that’s changing as you go more toward the cloud
and you mentioned that you’re you’re basically working with the big three
with Microsoft Google and Amazon how has this changed your role as the CIO or do
you see any difference in between working with you know the famous
well-known on-prem vendors and then as you move more to cloud vendors what sort
of differences do you see yeah I think that the biggest change for me is we
move to the cloud as I get much more involved in contracting issues and
contracting terms and service level agreements and limits of liability
fortunately I got some background running and buying and selling
businesses in the past at least I have some a little bit of knowledge there but
I spent way more time knifing into those issues and serving as
a negotiator on behalf of the institution for those vendors yes and
then trying to figure out solutions to that contracting puzzle mm-hmm
because many of the we’ll call the hyper scale vendors want to give you a
standard click-through agreement that isn’t very customized and most bigger
enterprises do not like doing that so we end up having to talk I also spend a
fair bit more time trying to make sure I understand the each of those vendors
product strategies where they’re going the roadmaps very important yeah they’re
coming up with lots of tools and technologies very quick Amazon’s been
setting the way there with new products you know a pace of new product
that’s been very fast you got surveillance technology coming in you’ve
got FPGA field point field programmable gate arrays you’ve got TP use tensor
flows and other things that these vendors are coming out with quickly so I
spend much more time trying to understand their product roadmaps than I
had done in the past yeah and to figure out what you’re entitled to without
extra charges and your contracts absolutely I’m maximizing the contract
yeah we’ve been doing a new session for the last few months at my CIO
perspective series and we call it the trouble with cloud contracts and we have
an ite an IT attorney who joins me on that discussion and I get a couple of
CIOs who are in various stages of negotiation with cloud vendors and then
we do a workshop around and people arc it’s been very popular because everybody
is finding out how different it is yeah there’s been a I started working several
years ago with a firm called strategic blue out of the UK which had started
very early with the birth of Amazon Web Services on cloud brokerage and cloud
reselling but this particular firm takes a different look at it they take a look
at it that’s coming from other commodity industries like the energy business and
how deals and contracts get structured there and strategic Blue has been
analyzing this concept of cloud sprawl meaning you have all your workloads in
the cloud and you think you’re cheaper but the reality is you’re consuming the
cloud in such a way that you’re probably spending twice what you should be in
addition you got these undemanding over tsa’s these pre purchased or reserved
instance workloads and Amazon terms that has significant price differences and
how to take advantage wherever you can the lowest cost reserved instances and
essentially pre committing your ears your spend all of that is very complex
in these environments now yeah it’s computationally it’s actually a big data
science problem – it is well I was just thinking that so many CIOs at some point
in their career path have gone back to business school to get an MBA and I
wonder I wonder at what point they will start going to
law school and making sure they have a juris doctor to go along with their
qualifications I think our future is going to be much more in the realm of
supply chain expert mm-hmm how to and and and the other thing I do in the
cloud now when you go to the cloud I actually have to understand regional
networking and how do the clouds connect to each other across the world what’s
their redundancy strategy so I’m very involved Vince can you hear me we lost your sound
there for a second can you hear me sorry about that
there you are you’re back yep okay yes I think I think our future is gonna be in
the realm of of looking at the supply chain for data and technology and
working out all of the logistic price contractual issues okay fair enough well
in when we were talking earlier about your top technology your top business
issues when I asked you about the top business issue you mentioned how
important it is for university to grow the digital education products is that
is that your number one kind of the business goal that you’re focused on
it’s one of them we have a couple of we have a couple of key goals and certainly
we’ve got an initiative here in San Diego called our strategic academic
program development initiative which is looking at ways of mixing on-premise and
digital learning experiences cleverly together yes and it’s reaching out to
our faculty under the guidance of our EVC Elizabeth Simmons and the faculty
are coming up with a number of proposals what we’re doing in technology is making
sure that all of our core content can be distributed across a variety of channels
distribution channels okay and so we’re trying to adopt a more modern sort of
web based distribution approach to our content interesting and so that’s
happening now and we want to grow that significantly over the next five years
mmm-hmm does that lead you into hiring in different skill sets and talents into
the IT group then you have needed in the past or is all that’s going to be
valving it’s it’s more of an evolution we’ve always needed what we call
instructional designers and instructional designer technologists
people who are very familiar with the technology around instruction and the
techniques for doing so we just now have to do a hire a few more of them to
handle this particular work I think the analytics side is is much
more interesting here because all these and tools have data and there’s a need
for faculty others to analyze that data to look at
how well the students are doing and so to me that’s creating a need for
learning data scientists this I just was learning dairy and how to apply the
theory of learning in to analyzing the data okay when you think about the way
the IT organization is evolving your own there at UC San Diego and also what you
hear about when you get together with other higher ed CIOs how is it changing
what are some of the near-term skill ships and and talent challenges that
higher ed specifically is facing over the next few years
hmm from an IT standpoint the biggest one right now that we’re all harping on
his security yeah yeah we we haven’t you know security professionals are in such
hot man if they’re good they can leave quickly for better opportunities in
industry so in higher ed we have a harder time trying to keep them and
that’s obviously one key area I think this realm of workers who are
extremely shrewd in different forms of data design data architecture and data
analytics and machine learning that’s the next one okay that’s a scarce skill
set that’s hard to get ahold of yeah and so those are probably the top two
obviously project management looms larger and this and in this sort of data
science ops world and use of cloud providers where we’re structuring
projects to deliver new products so sometimes that the skill set but it’s
not necessarily the highway I think the two biggest ones are security and data
right that’s okay yeah that would make sense is the university doing anything
either with a plan digital offering I you know makes sense that you’re trying
to develop more data scientist you also have cyber security course offerings or
we have some at the University here that’s not necessarily a big focus area
for the university but we have within our engineering school ability to take
courses in that area and so at our university not so much but
there are other universities that have very strong security training and
courses available vendors have a bunch to their certification you can get in
security independent of university yeah so I don’t think the shortage is so much
of educational opportunities it’s just shortage of people taking advantage of
them as this demand is growing so quickly yeah well a lot of the CIOs that
I talked with we always especially when we start talking about cybersecurity we
always talk about the talent challenges and so many of them have had to fall
back on developing their own you know role basically growing and rolling your
own security people and a lot of times they come out of data center and
engineering areas yes that’s correct and we’re starting to adopt that approach
here by ramping up our use of student interns and recent student graduates
mm-hmm they can’t stay with university long term we want to at least take
advantage of them as long as we can yeah yeah every bit of experience helps
doesn’t it I want to talk more about you would mention the projects that are
producing products that’s you and I talked a little bit about that I’ve run
into some CIOs and certain kinds of companies where IT has been reorganized
to think more like product teams than just project managers and often that
there is a lot of agile development going on there’s a lot of collaboration
and business people in fact sometimes the product managers are business people
that are part of a particular team and you’re in an interesting reaction to
that that you’ve got product areas but you’ve also got a lot of service areas
so for UC San Diego that doesn’t necessarily make sense no I mean if
you’re gonna create product in a development environment yeah DevOps
environment yes you’re gonna have an approach both on the project management
side and on the sales side of how to create that product kind of market it
how to bring it to market but as soon as you get to
now having a large number of customers consuming that product you’re probably
not going to use the exact same product function that created it to service it
and most large software vendors don’t ok the servicing the customers servicing
comes in a different way and so in higher ed most higher ed shops in IT are
about 80% services not you know mandatory services we have to deliver
20% of our work is in what we call product development of projects
so we’re largely a service based it requires a different structure that I
think is optimized for handling the call the request optimising the phone
optimizing email inquiries and web increase and then proactively
identifying where the improvement areas are I think the reason everybody’s
spinning over to product is you know product management is many of the
software big software houses since the 80s have been doing that and so the
product managers defined role I certainly was to find it Microsoft long
ago and other places in industry is starting to adopt that mm-hmm I think
they’re also adopting it because of the failure of the project management
discipline to really deliver on its promise mm-hmm and so to me we’re
certainly bringing in a flavor of product management to my unit but we’re
also very much beefing up what we’re doing in terms of project management as
well yeah because the reality is a product manager uses project managers in
order to deliver the product of course of course well in a few of the places
that have switched over to thinking about it more in terms of products and
products part teams talk about how differently the IT people start think
about the work that they’re doing it’s not just a you know get in there and get
it done and move on to the next thing it’s more involvement I guess over the
lifespan yeah yeah that makes a difference that’s attitudinally a big
difference it does and the IT worker then gets committed to building a
product and releasing it although in many cases in higher ed we’re
our teams are divided up by product definitions anyway yeah so for example
I’ve got a team focused on students our student system and that’s their product
that’s their baby they’re very good mm-hmm so I think if
you if you’re using product management to solve a motivational issue that’s not
the only tool in your arsenal you got other tools you want to okay
give me it for instance what other tools would you use well one that I’ve
continued to do to this day that I’ve always believed in is I like my staff to
develop their own passion inventory ah so and then I like to see where we have
training or what learning opportunities for them that it’s aligned for their
passion uh-huh so I always keep talking tonight I’m a senior managers like and
the next layer down is what we do here as we align passion to mission so you
have to in some employees the passion accept they’re passionate they
absolutely want to do it and they tell you about it some employees are not that
way they’re a little more quiet or they’re not certain what their passion
is yeah what we have to do with every employee is reach them and find out
where their passion is make sure it’s in a place of most premise for them meaning
something they can actually do yeah you can get them on it
now if it’s taking them out of their current life to work I better do it
because if I don’t they will do that yeah all good employees will follow
their passion regardless of the job you’ve given them I don’t think I’ve
ever heard of a passion inventory is that like a a bucket list for work
projects that I love yeah or you could think it was a little bit broader what
is why am I here in this earth what do I want to accomplish counterintuitive one
years ago and when I was CIO at DePaul I talked to an employee about his passion
he said well my passion is music I have this computer job so I can get money to
do my passion oh okay I said okay how can I help you get on your passion he
said well if I could have a slightly more flex
schedule that would really help me mm-hmm I said great I think we can
accommodate that there we go you gave him practice time yeah meaning
I can he was in a row worked easily we can easily put him in some flex time
yeah and and slide his schedule around actually was beneficial for us he wasn’t
in a chemo called field support role mm-hmm where that makes great sense
especially seasonally yeah yeah win no wouldn’t have come up if I hadn’t asked
what’s your real passion here right right yeah a lot of us are afraid to do
that but I feel like they just won’t tell you yeah that’s a good point
they’re gonna know what their passion points are it’s whether or not they have
the level of trust with you that they will share it well that’s the key yeah
that’s exactly right so when we start to do organizational restructuring mm-hm
and terms like product management etc as kind of a way of getting at that basic
trust and passion alignment just cut through that just go right to the pit to
the tension and the trust yeah when you got strong past and strong trust any
structure will do mm-hmm that’s a great point I want to circle back on one thing
and ask you to talk a little bit about the approach you do take to project
management because you’ve been deploying and developed and deploying a
statistical project management approach and I had one I had not heard anyone
talk about it in this kind of level of detail before so tell me about the
project manager role that you have at UC San Diego and how it’s different from
what you might think of as a run-of-the-mill project manager role
right and the difference in the role for that we’re trying to define here at San
Diego and having to find and I’ve started a deploy is the project manager
is looking broadly at the level of volatility or difficulty of the project
versus trying to understand all the dependencies of the project
so I’m gonna go to the heart of this matter and the project management
discipline there’s a lot of discussion and in the training on how to estimate
and then how to capture when values being delivered a lot of it is through
modeling the dependencies carefully in modeling the resources aligned carefully
well those are two very difficult things and you start to model dependencies and
you start to change I mean you suddenly see wild shifts in the project budget
and duration which project managers that hunt down and track the reality is
especially in an agile product world the date is fixed so the date is sat the
work is done to hit that date so in our approach rather than try to model
dependencies instead we just define a project or product as having things in
it that the user is getting we call those objects an object is meant to be
tangible concrete two or three independent observers can look at it and
say I know what that is but I think that’s a simple cut object an example
might be in in a analytical environment we’re going to deliver a tableau
workbook with seven pages on it yeah any changes gonna have a different visual
that’s an object that I can get my arm around then what we do is we build the
project plan we get time entry for everyone working on all projects being
occurring on a daily basis and then the project manager is looking at how well
the teams are delivering on the estimate for creation of that object and that’s
now getting in this realm of statistics mm-hmm so the goal here is to have a
large number of tasks small number of hours per test roughly about 12 hours
per task a high closure rate on tasks as we each week goes by following more of
an agile approach and a very quick retrospective it says hey have the 30
tests we just closed off where we over-and-under much worked out certainly
all the numbers for the over-and-under component but also different forms of
bullet ility our ability to hit the estimate how
frequently were Resta mating well procrastination are the team’s
delaying work until the last minute and all that gives the project manager
what’s going on with the project and more importantly listen pinpoint where
in the project with their effort and in a large portfolio of projects which
projects are the ones that are problematic okay yeah doesn’t need to
know deeply the technology in it right and it sounds almost like the kind of
approach that a data scientist would take to project management yes that that
stuff is sneaking in everywhere isn’t it yeah Vince your sound quality is a
little bit shaky I’m wondering have you let me try this
there you go stay close to your machine last thing I wanted in the last few
minutes I wanted to wrap up talking about how you approach and support
innovation inside of IT I mean there’s it’s always I find CIOs usually fall
into either a structured approach to it or more unstructured but it’s one of
those topics where if you’re not encouraging and talking about innovation
it’s hard to identify it you know yeah you I suppose people know it when they
see it but most CIOs have an approach to it so how do you do that I would call it
semi structured ok we have for example where we did an innovation on this cloud
optimization cloud brokering peace but we deliberately are putting it through
this stage gate methodology where the idea has to prove itself out at
different stages mm-hmm so that’s a more structured approach in the area of
learning analytics we’re going to go out to the faculty with their innovations
and that’ll be a little bit less structured in that way so I think the
approach we take here is you know depending on the context I think if you
get overly structured in innovation it probably isn’t innovation innovation can
be very messy ya can say you gotta give it enough room and enough protection so
that it can go through its messy birthing phase yeah there has to be a
lot of failure with innovation because you have to be able to try things
absolutely and the people in it twice hard to do innovation inside an
enterprise because people are very risk-averse inside an enterprise that’s
why they’re in the enterprise they’re not out being their own entrepreneur so
they’re afraid to get on a venture that might be a failure so you got to give
them protection as well mm-hmm so you know you have to think very hard about
how to do the innovation internally yeah and some of the innovation can occur in
partnership with a vendor so I’m a big believer in that and to bring some
perspective and some skin in the game and some rigor to it as well yeah well
and I think that’s always that always tends to turn a vendor relationship into
more of a partnership yep well and you mentioned too that in a university
setting you can use the research domain as an incubation ecosystem how do you do
that at UC San Diego well in fact with with our with our analytics environment
we’re about to do that we’re about to go out to the faculty and say we have these
large collections of data that we certainly want to use from an
administrative standpoint but in your research domain you might have insight
into how to tackle this and so I’m sitting down with our teaching and
learning center director Gabriel Dean housing and she’s putting together her
or learning data scientist positions and the purpose for that is to then work
with the faculty on the data were collecting on innovative uses of that
data within their teaching and instruction and so I think that’s one
way we’re trying to tackle that so I look at the faculty is kind of a
crowdsourced environment so to speak yes community sourced mm-hmm so I T doesn’t
be the font of all wisdom it can community source things out we’re doing
that with analytics writ large we’re trying to say IT cannot tackle all the
and analytics we’ve got to get everybody engaged so we’re adopting is what I call
community sourced model with a community practice manager
I like that terminology about our actually community source crowdsourcing
always sounds like something on the edge of a riot to me yeah you know chaotic
one of the things you mentioned was that you’ve got a performance evaluation tool
that started out as research and a pretty cool idea and is now something
used widely yeah it’s it started out as an innovation we’re in one of our
academic colleges divisions and got popular there and got used throughout
the university and then just recently we’ve raised it to the level we call an
enterprise application and they’re hardening it a little bit more and then
bringing it forward and that’s an example of what I call community source
software development in fact in our new enterprise system and data warehousing
environment we got a robust API strategy because we want to have an API economy
fueling this innovation potential where people can get at the core
administrative data safely but do their innovations okay excellent well and as
we we wrap up here we are at our one hour mark I’m always so amazed at how
fast the hour goes by I always like I like to give people an opportunity to
just give a parting bit of advice to other CIOs maybe who’ve been listening
to the kind of issues you’re dealing with and things you’re talking about
what are what is a piece of advice for CIOs who want to encourage more
innovation who want to get their enterprises moving more quickly toward
data science and toward the future what do you advise oh my goodness gracious it’s a multi-level plan levels that have
been well orchestrated like 3d chess game and then you need a lot of good
people to help drive it and for all the good people who might be listening to
this too there is no better time to be in technology than now I’ve been in it
my whole adult career and that’s been the most wild and fast
dating right now yeah yes it is wonderful and it’s been wonderful having
you with us here today thank you thank you thank you I’m afraid so yes yes but
though they’re gonna kick me out of the studio here so we will have to rip up
thank you so much for spending the time with us today Vince now if you joined us
late and you can still watch the full episode later today on cio.com
or you can listen to an audio podcast of my conversation with Vince wherever you
get your podcasts and I wanted to invite you also to join us for our next episode
on Tuesday December 11th at 2:00 p.m. Eastern I’ll be joined by CIO Elizabeth
hakonsen who is with Schneider Electric and has in the past worked at AES
corporation so we thank you very much for joining us today at CIO leadership
live and I’ll see you the next time take care