Transcript of a discussion on how WWT has reached deep into its applications data and content to rapidly and efficiently create a powerful Google like pan-enterprise search capability.

1. How WWT Took an Enterprise Tower of Babel and
Delivered Intelligent Search from Across Myriad Apps and
Content Sources
Transcript of a discussion on how WWT has reached deep into its applications data and content
to rapidly and efficiently create a powerful Google like pan-enterprise search capability.
Listen to the podcast. Find it on iTunes. Get the mobile app. Download the
transcript. Sponsor: Hewlett Packard Enterprise.
Dana Gardner: Hello, and welcome to the next edition to the Hewlett Packard Enterprise
(HPE) Voice of the Customer podcast series. I’m Dana Gardner, Principal Analyst at Interarbor
Solutions, your host and moderator for this ongoing discussion on digital
transformation. Stay with us now to learn how agile companies are fending off
disruption in favor of innovation.
Our next enterprise case study highlights how World Wide Technology, known
as WWT, in Saint Louis found itself with a very serious yet somehow very
common problem -- users simply couldn’t find relevant company content.
We'll explore how WWT reached deep into its applications, data, and content to rapidly and
efficiently create a powerful Google-like pan-enterprise search capability. Not only does it search
better and power users, it sets the stage for expanded capabilities using advanced analytics from
machine learning and augmented intelligence to a more productive and proactive digital business
culture.
Here to describe how WWT took an enterprise "Tower of Babel" and delivered cross-
applications intelligent search, we’re joined by James Nippert, Enterprise Search Project
Manager at World Wide Technology. Welcome, James.
James Nippert: Hello, thank you for having me.
How HPE IDOL
Humanizes Machine Learning
For Big Data Success
Gardner: We're also here with Susan Crincoli Manager of Enterprise Content at World Wide
Technology. Welcome, Susan.
Susan Crincoli: Good afternoon.
Gardner: Let’s think about some of the trends It seems pretty evident that the better search you
have in an organization, the better people are going to find what they need as they need it, when
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Gardner

2. they want it, but there are some other trends afoot here. I’m thinking about behavior,
expectations, and heightened ability for businesses to behave like what people are used to when
they're in consumer’s spheres. Is that part of things, James?
Nippert: It’s kind of the understanding, because it’s the way things have always been. You just
had to drill down from the top level. You go to your Exchange, your email, and start there. Did
you save a file here? No, I think I saved it on my SharePoint site, and you try to
find it there, or maybe it was in a file directory.
Those are the steps that people have been used to because it’s how they've been
doing it their entire lives, and it's the nature of beast as we bring more and more
enterprise applications into the fold. You have enterprises with a hundred or two
hundred applications, and each of those has its own unique data silos. So, users
have to try to juggle all of these different content sources where stuff could be
saved. They're just used to having to dig through each one of those to try to find
whatever they’re looking for.
Gardner: And we’ve all become accustomed to instant gratification. If we want something, we
want it right away. So, if you have to tag something, or you have to jump through some hoops, it
doesn’t seem to be part of what people want. Susan, are there any other behavioral parts of this
that we missed?
Find the world
Crincoli: No. We, as consumers, are getting used to the Google-like searching. We want to go
to one place and find the world. In the information age, we want to go to one place and be able to
find whatever it is we’re looking for. That easily transfers into business
problems. As we store data in myriad different places, the business user also
wants the same kind of an interface.
Gardner: I suppose certain tools that can only look at a certain format or can
only deal with certain tags or taxonomy are strong, but we want to be
comprehensive. We don’t want to leave any potentially powerful crumbs out
there not brought to bear on a problem. What’s been the challenge when it
comes to getting at all the data, structured, unstructured, in various formats,
James?
Nippert: Traditional search tools are built off of document metadata It’s those tags that go along
with records, whether it’s the user who uploaded it, the title, or the date it was uploaded.
Companies have tried for a long time to get users to tag with additional metadata that will make
documents easier to search for. Maybe it’s by department, so you can look for everything in the
HR Department.
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Nippert
Crincoli

3. At the same time, users don’t want to spend half an hour tagging a document; they just want to
load it and move on with their day. Take pictures, for example. Most enterprises have hundreds
of thousands of pictures that are stored, but they’re all named whatever number the camera gave,
and they will name it DC0001. If you have a thousand pictures named that, you can't have a
successful search, because no search engine will be able to tell just by that title and nothing else
what they want to find.
Gardner: So, we have a situation where the need is large and the paybacks could be large, but
the task and the challenge are daunting. Tell us about your journey. What did you do in
order to find a solution?
Nippert: We originally recognized a problem with our on-premises
SharePoint environment. We were using an older version of SharePoint
that was running mostly on metadata, and our users weren’t uploading any
metadata along with their internet content.
We originally set out to solve that issue, but then, as we began interviewing business users, we
understood very quickly that this is an enterprise-scale problem. Scaling out even further, we
found out it’s been reported that as much as 10 percent of staffing costs can be lost directly to
employees not being able to find what they're looking for. Your average employee can spend over
an entire work week per year searching for information or documentation that they need to get
their job done.
So it’s a very real problem. WWT noticed it over the last couple of years, but as there is the
velocity in volume of data increase, it’s only going to become more apparent. With that in mind,
we set out to start an RFI process for all the enterprise search leaders. We used the Gartner Magic
Quadrants and started talks with all of the Magic Quadrant leaders. Then, through a down-
selection process, we eventually landed on HPE.
We have a wonderful strategic partnership with them, Susan can talk more about that, but it
wound up being that we went with the HPE IDOL tool, which has been one of the leaders in
enterprise search, as well as big data analytics, for well over a decade now, because it has very
extensible platform, something that you can really scale out and customize and build on top of. It
doesn’t just do one thing.
Gardner: And it’s one solution to let people find what they're looking for, but when you're
comprehensive and you can get all kinds of data in all sorts of apps, silos and nooks and
crannies, you can start to deliver people results that they didn’t know were there. They can be
perhaps more powerful than they were originally expecting in terms of their results.
Susan, any thoughts about a culture, a digital transformation benefit, when you can provide that
democratization of search capability, but maybe extended into almost analytics or some larger
big-data type of benefit?
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4. Multiple departments
Crincoli: We're working across multiple departments and we have a lot of different internal
customers that we need to serve. We have a sales team, business development practices, and
professional services. We have all these different departments that are searching for different
things to help them satisfy our customers’ needs.
With HPE being a partner, where their customers are our customers, we have this great
relationship with them. It helps us to see the value across all the different things that we can
bring to bear to get all this data, and then, as we move forward, what we are looking forward to
is helping people build more relevant results.
If something is searched for one time, versus a hundred times, then that’s going to bubble up to
the top. That means that we're getting the best information to the right people in the right amount
of time. I'm looking forward to extending this platform and to looking at analytics and into other
platforms.
Gardner: That’s why they call it "intelligent search." It learns as you go.
Nippert: The concept behind intelligent search is really two-fold. It first focuses on business
empowerment, which is letting your users find whatever it is specifically that they're looking for,
but then, when you talk about business enablement, it’s also giving users the intelligent
conceptual search experience to find information that they didn’t even know they should be
looking for.
If I'm a sales rep and I'm searching for company ‘X’, I need to find any of the Salesforce data on
that, but maybe I also need to find the account manager, maybe I need to find professional
services’ engineers who have worked on that, or maybe I'm looking for documentation on a past
project. As Susan said, that Google-like experience is bringing that all under one roof for
someone, so they don’t have to go around to all these different places; it's presented right to
them.
Gardner: For the benefit of our listeners and readers, tell us about World Wide Technology, so
we understand why having this capability is going to be beneficial to your large, complex
organization?
How HPE IDOL
Humanizes Machine Learning
For Big Data Success
Crincoli: We're a $7-billion organization and we have strategic partnerships with Cisco, HPE,
EMC, and NetApp, etc. We have a lot of solutions that we bring to market. We're a solution
integrator and we're also a reseller. So, when you're an account manager and you're looking
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5. across all of the various solutions that we can provide to solve the customer’s problems, you
need to be able to find all of the relevant information.
You probably need to find people as well. Not only do I need to find how we can solve this
customer’s problem, but also who has helped us to solve this customer’s problem before. So, let
me find the right person, the right pre-sales engineer or the right post-sales engineer. Or maybe
there's somebody in professional services. Maybe I want the person who implemented it the last
time. All these different people, as well as solutions that we can bring in help give that sales team
the information they need right at their fingertips.
It’s very powerful for us to think about the struggles that a sales manager might have, because we
have so many different ways that we can help our customer solve those problems. We're giving
them that data at their fingertips, whether that’s from Salesforce, all the way through to
SharePoint or something in an email that they can’t find from last year. They know they have
talked to somebody about this before, or they want to know who helped me. Pulling all of that
information together is so powerful.
We don’t want them to waste their time when they're sitting in front of a customer trying to
remember what it was that they wanted to talk about.
Gardner: It really amounts to customer service benefits in a big way, but I'm also thinking this is
a great example of how, when you architect and deploy and integrate properly on the core, on the
back end, that you can get great benefits delivered to the edge. What is the interface that people
tend to use? Is there anything we can discuss about ease of use in terms of that front-end query?
Simple and intelligent
Nippert: As far as ease of use goes, it’s simplicity. If you're a sales rep or an engineer in the
field, you need to be able to pull something up quickly. You don’t want to have to go through
layers and layers of filtering and drilling down to find what you're looking for. It needs to be
intelligent enough that, even if you can’t remember the name of a document or the title of a
document, you ought to be able to search for a string of text inside the document and it still
comes back to the top. That’s part of the intelligent search; that’s one of the features of HPE
IDOL.
Whenever you're talking about front end, it should be something light and something fast. Again,
it’s synonymous with what users are used to on the consumer edge, which is Google. There are
very few search platforms out there that can do it better. Look at the Google home page. It’s a
search bar and two buttons; that’s all it is. When users are used to that at home and they come to
work, they don’t want a cluttered, clumsy, heavy interface. They just need to be able to find what
they're looking for as quickly and simply as possible.
5

6. Gardner: Well, it’s great to discuss things, but it’s even better when you can show. Do you have
any examples where you can qualify or quantify the benefit of this technology and this approach
that will illustrate why it’s important?
Nippert: We actually did a couple surveys, pre- and post-implementation. As I had mentioned
earlier, it was very well known that our search demands weren't being met. The feedback that we
heard over and over again was "search sucks." People would say that all the time. So, we tried to
get a little more quantification around that with some surveys before and after the
implementation of IDOL search for the enterprise. We got a couple of really great numbers out of
it. We saw that people’s satisfaction with search went up by about 30 percent with overall
satisfaction. Before, it was right in the middle, half of them were happy, half of them weren’t.
Now, we're well over 80 percent that have overall satisfaction with search. It’s gotten better at
finding everything from documents to records to web pages across the board; it’s improving on
all of those. As far as the specifics go, the thing we really cared about going into this was, "Can I
find it on the first page?" How often do you ever go to the second page of search results.
With our pre surveys, we found that under five percent of people were finding it on the first page.
They had to go to second or third page or 4 through 10. Most of the users just gave up if it wasn’t
on the first page. Now, over 50 percent of users are able to find what they're looking for on the
very first page, and if not, then definitely the second or third page.
We've gone from a completely unsuccessful search experience to a valid successful search
experience that we can continue to enhance on.
Gardner: Great. Susan, anything to offer on the proof of the pudding is in the eating?
Crincoli: I agree with James. When I came to the company, I felt that way too -- search sucks. I
couldn’t find what I was looking for. What’s really cool with what we've been able to do is also
review what people are searching for. Then, as we go back and look at those analytics, we can
make those the best bets.
If we see hundreds of people are searching for the same thing or through different contexts, then
we can make those the best bets. They're at the top and you can separate those things out. These
are things like the handbook or PTO request forms that people are always searching for.
Gardner: I'm going to just imagine that if I were in the healthcare, pharma, or financial sectors,
I'd want to give my employees this capability, but I'd also be concerned about proprietary
information and protection of data assets. Maybe you're not doing this, but wonder what you
know about allowing for the best of search, but also with protection, warnings, and some sort of
governance and oversight.
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7. Governance suite
Nippert: There is a full governance suite built in and it comes through a couple of different
features. One of the main ones is induction, where as IDOL scans through every single line of a
document or a PowerPoint slide of a spreadsheet whatever it is, it can recognize credit card
numbers, Social Security numbers anything that’s personally identifiable information (PII) and
either pull that out, delete it, send alerts, whatever.
You have that full governance suite built in to anything that you've indexed. It also has a mapped
security engine built in called Omni Group, so it can map the security of any content source. For
example, in SharePoint, if you have access to a file and I don’t and if we each ran a search, you
would see a comeback in the results and I wouldn’t. So, it can honor any content’s security.
Gardner: Your policies and your rules are what’s implemented and that’s how it goes.
Nippert: Exactly. It is up to as the search team or working with your compliance or governance
team to make sure that that does happen.
Gardner: As we think about the future and the availability for other datasets to be perhaps
brought in, that search is a great tool for access to more than just corporate data, enterprise data
and content, but maybe also the frontend for some advanced querying analytics, business
intelligence (BI), has there been any talk about how to take what you are doing in enterprise
search and munge that, for lack of a better word, with analytics BI and some of the other big data
capabilities.
Nippert: Absolutely. So HPE has just recently released BI for Human Intelligence (BIFHI),
which is their new front end for IDOL and that has a ton of analytics capabilities built into it that
really excited to start looking at a lot of rich text, rich media analytics that can pull the words
right off the transcript of an MP4 raw video and transcribe it at the same time. But more than
that, it is going to be something that we can continue to build on top of, as well and come up
with our own unique analytic solutions.
Gardner: So talk about empowering your employees. Everybody can become a data scientist
eventually, right, Susan?
Crincoli: That’s right. If you think about all of the various contexts, we started out with just a
few sources, but we also have some excitement because we built custom applications, both for
our customers and for our internal work. We're taking that to the next level with building an API
and pulling that data into the enterprise search that just makes it even more extensible to our
enterprise.
Gardner: I suppose the next step might be the natural language audio request where you would
talk to your PC, your handheld device, and say, "World Wide Technology feed me this," and it
will come back, right?
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8. Nippert: Absolutely. You won’t even have to lift a finger anymore.
Cool things
Crincoli: It would be interesting to loop in what they are doing with Cortana at Microsoft and
some of the machine learning and some of the different analytics behind Cortana. I'd love to see
how we could loop that together. But those are all really cool things that we would love to
explore.
Gardner: But you can’t get there until you solve the initial blocking and tackling around content
and unstructured data synthesized into a usable format and capability.
Nippert: Absolutely. The flip side of controlling your data sources, as we're learing, is that there
are a lot of important data sources out there that aren’t good candidates for enterprise search
whatsoever. When you look at a couple of terabytes or petabytes of MongoDB that’s completely
unstructured and it’s just binaries, that’s enterprise data, but it’s not something that anyone is
looking for.
So even though our original knee jerk is to index everything, get everything to search, you want
to able to search across everything, but you also have to take it with a grain of salt. A new
content source could be hundreds or thousands of results that could potentially clutter the
accuracy of results. Sometimes, it’s actually knowing when not to search something.
Gardner: That would be the "not too intelligent" search, right?
Nippert: Exactly.
Gardner: It sounds like this is an essential part of any organization to become a digital company
data driven, but intelligent and fit for purpose approach to gathering that assets wherever they
are.
How HPE IDOL
Humanizes Machine Learning
For Big Data Success
I want to thank our guests. We've been exploring with World Wide Technology how a very
serious and somehow difficult problem of users simply finding relevant content can be solved.
We've seen how WWT has reached deep into its applications data and content to rapidly and
efficiently create a powerful Google like pan-enterprise search capability.
So, please join me in thanking our guests. We have been here with James Nippert, the Enterprise
Search Project Manager at World Wide Technology. Thanks, James.
8

9. Nippert: Thank you very much for having me.
Gardner: And we've also been joined by Susan Crincoli. She's the Manager of Enterprise
Content at World Wide Technology. Thank you, Susan.
Crincoli: Thanks, Dana, I appreciate it.
Gardner: And a big thank you as well to our audience for joining us for this Hewlett-Packard
Enterprise Voice of the Customer Digital Transformation Discussion.
I'm Dana Gardner, Principal Analyst at Interarbor Solutions, your host for this ongoing series of
HPE sponsored interviews. Thanks again for listening, and please do come back next time.
Listen to the podcast. Find it on iTunes. Get the mobile app. Download the
transcript. Sponsor: Hewlett Packard Enterprise.
Transcript of a discussion on how WWT has reached deep into its applications data and content
to rapidly and efficiently create a powerful Google like pan-enterprise search capability.
Copyright Interarbor Solutions, LLC, 2005-2016. All rights reserved.
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