moderator: walt ellenberger iii april 10, 2018 12:01:18 … in healthcare consortium... · name is...

SAP SE/AUDIO NAM Moderator: Walt Ellenberger III

04-10-18/12:01:18 p.m. CT Confirmation # 659830208

HANA IN HEALTHCARE CONSORTIUM APRIL UPDATE

Moderator: Walt Ellenberger III April 10, 2018

12:01:18 p.m. CT

Walt Ellenberger:

I'd like to welcome everybody to the April update call of the HANA healthcare consortium. My

name is Walt Ellenberger, I head up business development, strategic alliances for SAP regulated

industry to healthcare interest. I will be helping facilitate the call today.

Just from a logistic perspective, during the call everybody is going to be on mute and we will save

time at the end 30 minutes after the main body of the agenda is completed to field questions.

You'll have to hit star 6 to do that.

In the meantime, feel free to enter online questions, we'll queue those up and get to them. This

session will be recorded and made available to everybody for rebroadcast and the presentations

will be packaged up and sent your way also. So with that, I am going to turn the floor over to you

Jon.

Jon McManus: Good morning or good afternoon everyone depending on where you are. My name is Jon

McManus and I have the pleasure of chairing this advanced analytics healthcare consortium that

SAP helped sponsor for us. So we have a lot of exciting content for April.



I know there's a ton of busy projects and efforts on the analytics domain of Parkland. Walt has

the agenda up for today so I'm just going to kind of go through the cadence of that, walk through

some of the subject matter and then we've got a few demonstrations slated for today.

And as Walt pointed out, one change that we're introducing this call and in the calls proceeding

this is that we're going to have 30 minutes of Q&A so the consortium call itself should last just

under or at a hour.

So at 1 o'clock Central Time that will really conclude the content for today's consortium call but I

will stay on and some of the other leadership council members will stay on for Q&A.

So if any participants, members, observers on the call do have any questions or if you'd like to

ask anything deeper based on the content we present or anything else, I'll be around to answer

those questions and we'll see if any of the other leaders can as well.

So the agenda for today is just some welcoming comments from me. We've got some updates

on the new leadership council. I'm going to spend a little time talking today about data literacy

and them my leadership council colleagues are also going to have a few comments on that.

Parkland's going to do a brief demo today on our (Realogy) dashboard and understanding kind of

how we tie that with contextual awareness to tie in with the data literacy concept.

And then (Tracy) from the Analytics Center of Excellence from SAP is going to give us an

overview and demonstration of the SAP Analytics Hub which is a new tool that has Parkland's

attention for sure and I think it's going to be interesting to hear your thoughts and opinions when

you guys get a chance to understand what its role will be and what some of the use cases are.



And then turn it back over to Walt for a few upcoming events and announcements proceeded by

the Q&A session that we discussed. So Walt, if you can go ahead and go to the next slide. So

with great pleasure I get to introduce the new leadership council. I will have to figure out where

Jamie gets his headshots from because his is far superior than some of ours.

However, I have the pleasure of introducing Jamie Oswald who is the manager of information

delivery at Mercy and he has agreed to continue in Mercy's longstanding role as a leadership

council member organization for this consortium.

I have the pleasure of introducing Vijay who is the senior vice president and chief data officer at

Providence St. Joseph Health. Vijay brings a wealth of experience to the consortium and we're

very excited to have him. He's also ran several analytic programs in multiple organizations so he

has lots of depth of experience to bring to bear.

I have the pleasure of introducing Patrick Farrell, he's the senior director of data analytics at the

Data Analytics Center Corporate Information Services at Penn Medicine. Pat is no stranger to

the consortium call but stepping up into a leadership role we're very excited to have him be a part

of that and I look forward to his insight.

And then finally I have the pleasure of introducing Neil Gomes who is the chief digital officer at

Jefferson Health. And I believe Pat and Neil are only a few minutes from each other regionally

where their organizations are located but again lots of breadth of knowledge and we're excited to

have them be a part of it.

So that rounds up our newly formed leadership council. I look forward to hearing from them a

little bit later on in the call.



And we will be kind of doing round robin rotations for the remainder of these consortium meetings

over the next six, eight, 12 months where we'll each be taking turns talking about things going on

at our organizations, things we're having success with, questions we have and then we'll be able

to have that roundtable each time we get together. So Walt next slide please.

And the other thing that I think we're going to do a little differently now is we as a leadership

council have gotten together and started to roadmap out some of the concepts we want for future

consortium meetings.

So we started going six months out through September and you can see some of the thematic

points that we wanted to touch around on scaling, self service, visual based discovery,

augmented analytics and machine learning, data science and then geo-mapping NLP, NLG.

But the subject matter, so today is April's consortium call so the focus is going to be on data

literacy and the Analytics Hub.

For May we're still finalizing it, this is just a draft but we're thinking about getting into the concept

of no more ETL and HANA Live connections and then potentially having a demo from our

colleagues over at UPenn and a demo from SAP's thought leadership on ELT different from ETL

and concepts of dynamic tiering et cetera.

And then moving forward through June, July, August and September you guys can see some of

the subject matter we have in mind. I will be trying to finalize this with the leadership council and

have this posted on the consortium website.

And my hope is one, it helps us as a leadership council get organized about when we're going to

be demoing and kind of the content subject matter we'll be getting into so we can make sure

we're prepared to speak to it on these calls.



But also you as members and observers and other colleagues will be able to see kind of what the

roadmap looks like so that you can know when we're going to be touching on certain subject

matter, if there's additional people from your organizations that you'd like to attend the call, or if

you really want to make sure that's the one meeting you do attend if you have scheduling

conflicts.

So we hope that will be helpful to kind of have the roadmap out there and then once we get into

June, July we will probably start to work on the next six months out so we always have at least a

six month roadmap for what content we're planning to present on. So I'm excited to have that

work in progress.

You can see the draft form we have here, this is certainly subject to change and I will be working

with my colleagues from the leadership council to get this finalized and posted on the consortium

site hopefully before the next time we get together in May. Walt, if you go to the next slide

please. Thank you Walt.

OK, so with that I'm going to do my best to get into the topic of data literacy. If anyone has been

keeping tabs on some of the more recent literature around the core business drivers for

healthcare analytics, data literacy is listed across those domains. So it is not only a barrier to a

successful analytics strategy, it is also a driver that that needs to be improved for business

outcomes.

And it's something that I think a lot of us have not really paid a ton of attention to as we have

struggled to really get our technology platforms off the ground and scaled, as well as trying to

meet you know key deliverables and fire drills from our organizations by getting a dashboard built

or getting a deliverable met, not necessarily thinking about as we deploy that deliverable are the

folks who are consuming it really in a position to be successful?



So I have a few slides that I want to touch on this and then I look forward to hearing from my

colleagues on the leadership council about some of their thoughts on this subject matter. So you

know the way to start this off real quickly is you know technology and people are frequently seen

as the two keys to unlocking the power of data really in any organization.

And I think as many of us have sought to hire more data specialists, you know we've all been

focused in turning our attention to self service analytics trying to extend the influence of data

across our various departments and teams.

You know democratizing data throughout a company, you know the idea is that helps everyone to

do their jobs faster, better, smarter. But I think what most companies are starting to recognize is

that data in the hands of a few data experts can be powerful, but data at the fingertips of many is

what's truly transformational and I think what a lot of us are trying to get at.

And there's also the risk of having data in the hands of just a few because they can misinterpret

or we can start to have bottlenecks within our organizations.

So you know as organizations look to increase data access you know for our managers, our

employees there's always this implied expectation that they'll know what to do with the data once

it's shared with them.

And you know at least at Parkland what we're finding is that's not necessarily the case you know

and we're really discovering that simply making data more pervasive and accessible which we're

having that success with the technology strategies we've put into place, it doesn't necessarily

mean that that's enough you know.



And the example I like to use is you know imagine you assembled an extensive library of

(content) that comprised of the finest literary works in the world, how valuable would it be to

someone who's illiterate who can't read? Until they can read and appreciate it the library remains

just a useless collection of inked paper you know.

Similarly, all of the rich data visualizations and intelligence built you know in all of our

organizations particularly around self service you know can be negated by the simple deficiency

in data literacy you know which can be defined as the ability to understand, ease and

communicate data use and communicate data effectively you know.

So on the slide deck here from Walt's standpoint, I grabbed a few definitions. You know the

prevalence of data and analytic capabilities including artificial intelligence requires creators and

consumers to speak data as a common language.

And then Gartner defines data literacy as the ability to read, write and communicate data in

context. And you know I think the concern is that there really may not be that level of

preparedness in an organization to consume all of the content we're starting to create much

faster. Next slide Walt please.

So you know a lot of us sometimes feel that technology should be able to sufficiently address the

issue and foster data literacy improvement on its own. Walt, can you go to the next slide please?

Thank you.

But what I think is happening is most of the automation, the mundane manual manipulation of you

know time consuming tasks to wrangle data together, it bogs down our experts and the tools

really don't come with automated ways to support this.



And I call your attention to this slide I got from Gartner which poor data literacy was the second

largest roadblock to a successful chief data officer you know office establishment i.e. a data

strategy.

And you know I think the – if you go to the next slide Walt, the thing to think about what to do it's

you know Gartner starts to break down you know how do you enable data literacy for a digital

society?

They talk about do you have a base vocabulary? Do you have a set of dialects that transform

across the IT vertical to the business vertical? Do you have levels of proficiency? Are you

grading your organizational consumers about their ability to interpret data effectively?

And then what's language development look like? How are you, you know your development

pipeline for cultivating that dialect and language of data how is that shaped up and is it

repeatable?

I think you know there's really four domains that most of us you know try to break this into. Data

knowledge, you know what is my company's knowledge of data? You know in healthcare it's

healthcare but we have a big vertical in finance and HR and supply chain.

You know the more employees understand that that's good but also are they understanding the

way the information's being presented to them? You know the next vertical we always look at is

data assimilate – excuse me, data assimilation.

When you're presented with new data for interpretation are you adept at orienting yourself to

unfamiliar data before consuming it? Do people have a repeatable plan?



You know I think the problem with Excel is its biggest strength; it's wide open but everyone

seems to go to spreadsheets and pivot tables and VLOOKUPs but you know is that a repeatable

strategy? How do people handle titles and tables, timeframes, data sources, units of measure,

calculated measures, dimensions, filters, sorting, targets?

These are all the types of things that you know if you're not asking your organization to really

think through them, you know you might find you have a serious gap and it doesn't matter how

good your dashboard is, you may have a lot of people misuse it you know and that gets into data

interpretation.

Does your common consumer understand trends, patterns, gaps, clusters, skewness, outliers,

focus, (anomalies)? Do they understand what those things are? Do they have the same

definition?

You know is there some artifact from your business intelligence group whether you're

representing IT or the organization that even defines cluster versus skewness versus outlier so

there's a common lexicon that people are using?

You know and then finally I think it's data skepticism and curiosity, the concept of what's value,

what's context, what's bias? You know how are you determining significance? You know and

again is there a repeatable way?

So Walt, can you go to the next slide for me? I think I beat that on the drum a little bit. So I won't

read all through this but I put a few things that you know lot of the literature kind of points to

these four things that you should be doing to foster better data literacy.



Make sure there's someone in your organization acting as a visible champion for data literacy,

cultivate it as a second language across business and IT stakeholders by figuring out what your

base vocabulary should be.

And if a lot of you are at the customers you know, clarity only gets you a little bit of the way so

you want to look at Epic's data dictionary material and that goes for any other vendor. Try to start

tying those information sets together.

You want to try and drive and sustain improvements to the organization's data literacy by

identifying areas where data is spoken fluently and where do you have gaps and try and

proliferate the things, the groups that speak it fluently are doing well. A lot of organizations that

occurs in finance.

Talk to your finance people about how do they understand financial information, how to interpret it

and then you know change the way you interact with your leaders and stakeholders by speaking

data in a uniform way? Next slide Walt.

So last thing I wanted to touch on is you know this is screenshots from Parkland's actual strategic

plan going through 2020 just around analytics. And you'll see at the bottom there one of the

program components that Parkland chose is data literacy. And I literally pasted in Gartner's

definition of it because that's how define it as well. Next slide Walt.

And to that point, we went and did a full on SWOT analysis that I'll be sharing with all of you. You

know we looked at what are our current strengths around data literacy? What are our

weaknesses?

Many dialects, workforce training and development, lack of consumer training as deliverable and

focused, overlapping functionality with existing data stewards.



Even though we're trying to standardize our (outer) analytic toolset, people still kind of go rogue a

little bit and we can have trouble bringing them back to center. Lack of full adoption of all

identified departments.

Moving into opportunities, you know one of the things that Parkland's going to be thinking about is

developing a driver's license for organizational analytics and not just for the developers. The idea

that you get your license to have the right to interpret and make decisions on reports.

Maybe there's a learner's permit for those getting started and then there's the full blown driver's

license for you know anyone who's directors and above so that they can have the same training

and foundation to interpret their information.

And then what are the press? So I share that with all of you transparently so you can understand

what's Parkland really thinking about as we look at data literacy across the 360? Next slide Walt.

And then finally from our strategic plan, these are some of the things from initiatives that we're

pursuing at Parkland to try and do something about it. We're trying to get a driver's license for

analytics initiative off the ground.

We're trying to start thinking about the concept of data asset watermarking. Can we start to

certify information that has a certain level of validation and integrity behind it different from ad hoc

reports that may not have had that same level of validation?

Do we need an enterprise seal that we put on those reports? Do we have data context focused

training for consumers not just developers? And you know are we formalizing the concept of the

chief data officer role and office appropriately?



So that's where I'm going to kind of conclude my tirade on data literacy, I think it's absolutely

critical. But I wanted to take a moment and pause and reach out to my colleagues on the

leadership council so Jamie, Pat, Vijay or Neil I would love to hear some of your thoughts on the

concept of data literacy.

Vijay Venkatesan: Hey Jon, this is Vijay. Again excellent presentation as always and sometimes I feel

like I can listen to you forever on this topic.

I appreciate that. I think, I think you know there are a couple of key touch points you have and

one touch point was really around this idea that data literacy is not something you do in a

vacuum, right.

You've got to have both what I call the you know data organization or the semantic layer of data

organized in a way that makes easy for people to know what data exists and what can be – or

how it can be used and what can it be used for?

And then the other portion of that is really then goes to your point about learner's permit, driver's

license. So it's almost like you have to take steps and make sure that the right steps are in place.

And the first step in my mind at least is really how to organize the information to make it useable

first so people know what exists and then what can they do with it.

And that's been our approach is to kind of build that you know I'm going to use the term semantic

layer creation, but what is the right semantic layer to build so we know what catalog of data exists

where and what can be used for?

So I call it my app store of data for others to consume via any means necessary once they have

the learner's permit and the driver's license. I really like your model there and again open to other

comments and suggestions. Thank you.



Jon McManus: Thank you Vijay. Jamie and Pat?

Jamie Oswald: So this is Jamie and I think it's just widely important, right. I mean I think you nailed it

upfront when you said you know that if you don't have this in place all the stuff that you're building

is not getting used to its fullest potential, right.

And especially in healthcare where we have to prioritize everything, we have to be aware of our

resources, investing in building the analytics but not in educating them and you know really

empowering your end users is it's not a total waste but it's a pretty big one.

Patrick Farrell: And this is Pat. I think the only thing I'd probably add it's I mean a really great topic is the

challenge I see and perspective you know I'm a technology shop, IT shop, I think maybe most

people on the call are and maybe it's a mix but you know where does initiative start from to help

with data literacy?

It's really got to be a partnership. So you take initiative to try and get people there but I don't

know that you'd necessarily want the technology shop to drive that conversation of how to make

data literacy happen.

And I'm curious about other people's experiences if sometimes these conversations focus too

much on lack of data literacy being a technology problem versus when it comes to you know,

sometimes comes down to people and process being in place to help make this happen so. But

I'm sure it's a challenge we're all kind of walk through right now so.

Jon McManus: I think that's a great point Pat. I mean you know at Parkland we really try and walk that

line with operational partnerships so that – I'll give you an example.



We have a data usage and standards committee that IT does not share even though you know IT

really drove a lot of the creation or the reason to create it and it sits under our executive

compliance committee so it's on the compliance, ethics, lawyer legal wing of the house.

The whole role of that committee is not like a traditional data governance committee or a data

steering committee, it's data usage and standardization. What that means is, that's where we

take things to determine is it right to do this?

You know like the CDC wants data from us or some university wants public health data from

Parkland which happens quite frequently and they want like 10 years of it, is it OK for us to do

that?

You know so we have a group of multidisciplinary leaders to be able to have that conversation.

But to your point Pat, we really sat down and said is you know is technology really the driver of

that? We should just be a participant.

So I was able to coax, beg and plead to have my chief privacy officer actually chair that. And to

be honest I had some of my IT personnel help do the administration of that meeting to help keep

it going, do the agenda, the minutes, the kind of legwork but all of that is with the understanding

that IT is not in the chairmanship role.

And we've had a lot of success that way and I think data literacy is the same type of topic that I

think there's a lot of common sense but it's pretty nebulous until you get into some of the

specifics, and maybe even some of those slides can help you with some of the specific initiatives

you can start to put on your roadmaps as organizations.

Because I think if you don't have data literacy as a core focus and if you're not thinking about your

consumer base the people who use these dashboards and reports, are they being trained and



prepared like anything else they go through credentialing on to interpret that information

correctly?

I think you're going to start finding that that's a bigger and bigger gap as the tools get faster, the

ability to create data gets faster and infinitely more complex.

Do we have Neil on the line just one more leader to touch base with? OK, he had said he might

not be able to make it so that's OK. So I'm going to say one more thing and then I want to turn it

over to our customer showcase demo and then the demo from our colleagues over at SAP.

There's a reason that we bundled the SAP Analytics Hub today with the concept and topic of data

literacy. And the tie in for that is the other part of data literacy I find really important is are you

controlling the entry point to information?

You know at Parkland we have traditional business objects, we have SAP Analytics Cloud and

we have lots of content in Digital Boardroom, we have lots of content in business objects in WebI,

Crystal, Lumira, I have we have some dash of Xcelsius left but we're just finally getting that out of

the picture.

But you know what, I've got 15 other vendors that have a significant amount of analytics stuff like

Kaufman Hall for financial decision support, Lawson for supply chain, PeopleSoft for HR where a

lot of my organizational leadership go to those places for content and reports.

And to be honest, I would say email is another portal. I mean how much reporting goes and gets

blasted out to people's inboxes? We have a whole waterfall of that every night and I'm sure a lot

of you do.



And I think one of the challenges for data literacy is if we have so many entry points where data's

actually rendered and presented to our target audience, getting the lexicon standardized can be

challenging.

So one of the things that I will call all of your attention to when SAP presents in a few moments,

the Analytics Hub separate from SAP as a vendor is a concept that I think is going to have

tremendous growth over the next three years. All of the leading vendors are going to be doing an

Analytics Hub.

And it's the idea that not only can you have a central repository to present on prem content i.e.

business objects derived and cloud content i.e. Digital Boardroom and SAP Analytics Cloud in our

context but also third party vendors.

So one of the things that I think is critical is can you start to have a one stop shop to launch

content? And that's what SAP Analytics Hub is really stands out to Parkland the main feature

where I can actually sunset business objects from a customer going to the nested boulder

structure perspective.

I will keep business objects alive architecture and all of the content and house it, but I'll never

have someone go to business objects frontend again. I will have them go to the Analytics Hub to

launch business objects content. But you know what's also in the hub, Digital Boardroom

content.

They won't have to separately go to the Digital Boardroom cloud analytics portal. And I'm also

going to put in Kaufman Hall content so they don't have to go to kaufmanhall.com with Parkland's

log in.



So that's why we tied the two together because I think that that's an important decision point and

that's the way Parkland's thinking about it. I look forward in the Q&A session or in follow up after

the meeting to hear how all you think about it but that's the tie in.

And I'm going to turn the ball over to Clay Townsend who's one of my most senior enterprise data

architects at Parkland to talk about just a deliverable that's you know HANA powered, built in

Lumira and walk through that.

But also how we're understanding that data and context so when we create a dashboard we don't

just give the dashboard, we give some contextual information to try and help with the data literacy

piece.

And by all means we're not perfect, we're not where we want to be but just an example of where

you can start to take that extra step and the dashboards you create. So with that, Clay I'm going

to turn it over to you.

Clay Townsend: Hi everyone. So I wanted to start this today just with the HANA model itself. So I think

this is something most of us are familiar with. This is a HANA model on top of imaging orders

here at Parkland.

And this is a pretty wide open model, it has all of our imaging orders and we have quite a few

measures and dimensions here for users to use intel service that we also use to generate content

ourselves.

And you know we do a lot of work to try and make our label easy to read familiar concepts but

there's a lot behind the scenes that users are going to want to understand as well. Not just what

they mean, what calculations go into the measures but maybe the time period and how we

actually generate these data sets.



So we do a couple of things, one of those is we always try to generate a just basic high level data

set for the user to consume in Lumira. And this gives them a feel for the time period of the data

set, just some general accounts on their dimensions but just to give them a scope and to get

them used to what they're looking at.

But what really kind of I think ties this into the data literacy is how do we start sharing all the

information that's not just on this front page here with the users? How do they want to interact

with the data set?

And so we have here at Parkland a wiki that we're standing up, and we are integrating it into the

Lumira chart itself. So with a hyperlink we can click on this and launch into the wiki.

You'll see our high level data set up here, we're looking at the radiology order utilization one. And

you know just moving fully down this page, we get a nice overview of what are we looking at as

the user? So I have attributes around the imaging orders place department over a 13 month

period so I know the time period for this specific data set itself.

And I know that what I want to do is I want to look at how this is going to impact the quality of care

here at Parkland, right? That's the ultimate goal for a lot of these.

So additional details just so that I understand further who can I reach out to at the organization?

Who's our business owner for this, who's our IT owner? The scope of the data, so it's 13 months

worth of data.

And not all users are going to appreciate everything on here but some will, right. So I know that

the lowest level of data in the data set, I can get down to the individual order line.



I know that I'm looking at all orders of type imaging, I know that it's coming from Clarity for users

that are familiar with that and I can even launch the data set itself from my wiki page just like I can

get from the data set over here. It'll use an open document link, I think most of us are familiar

with that. It's pretty nice for moving back and forth between various places.

Now everything in here, everything that we've built in that data model is again listed on the wiki

page except with a nice longer description so it's easier to search through and we can put

additional information there for the users.

So if we scroll down here, not only do we have what it is in the source system that we brought

into from you know ((inaudible)) or Clarity into HANA, what it is listed as and the data set it's in

our description here. And as we move down and where this really starts to become handy is

when we're calculating these measures.

So if I want to calculate a ratio and I want to make this available for the users in the data set they

need to understand what it is. So it's that order count, right. This is the count of orders where

this is true and this is true or a ratio.

Well it's these times divided by these times where this is true ((inaudible)) down the line so that

they can continue to operate it here. Now this right here, this gives you a feel, right for what the

data set is. And with this I'm probably going to be more comfortable generating a report.

If we keep moving down here, when we started to kick this off there were some end goals. There

were projects that we wanted to support with this, I mean otherwise why would you just (us going)

out there?

And the two that I'm going to talk about just very quickly give a high level overview is there was a

concern that we may be placing too many urgent and stat orders and that was to get these orders



through and this would diminish the capacity for truly urgent and stat imaging orders to come and

actually be processed in time.

We know that there are national guidelines around the percentages for urgent and stat orders and

so we wanted to look at that. And we just dropped a real quick chart in here and we can see just

a very slight increase over time of our (stat) ratio. Here are the KPIs that are in the data set itself

that are providing these charts. Another one we want to go look at, so ED dwell time.

Our patients sitting in the ED waiting on their imaging results and is that causing their link to stay

in ED to be extended? This is another project that we wanted to track in this. The other nice

thing about the wiki, so you don't have to have an account on the wiki; it works just like Wikipedia

itself, it's also very easy to edit.

I come up here if I have an account so I'm IT, I can edit this, I can type whatever I want in here

and then I can save it. It's very nice for documentation purposes. It's easy to share, it's easy to

see. I might discard that, no one needs to see that. And like I said just to kind of finish this off,

we can go back over to imaging analysis.

And I guess to give one more quick actually use case of how to use it, I find a lot that patients or

not patients, providers just want to get a feel for how many orders are inpatients versus

outpatients?

And I think this is a good one because when you look in a lot of the Epic's documentation they

talk about ordering modes inpatient versus outpatient.

But you wouldn't necessarily think order mode for inpatient, outpatient. So if I wanted to do that

in this data set and I went over to visualize I wanted to create a new one today, I might search for

inpatient, outpatient I wouldn't find anything.



But because I have this documentation I can search inpatient, oh and look it's order mode. And

so it's very easy for me to come back into my data set and find order mode now and now I have

my accounts that I was after.

So I was able to answer my own question without reaching out and not knowing exactly what I'm

looking for. And I can feel more confident in these numbers because I have the documentation

behind it, I know it's 1 months et cetera, et cetera. I think that about wraps it up for me.

Jon McManus: OK. Clay, thank you very much. Obviously I am very blessed at Parkland to have some

pretty tremendous talent over here.

And I see some questions are coming into the QA box, we will go back and answer those

questions at the end of the hour for that extra half hour. And if anyone has to drop, I will be

happy to respond back via email. Walt I'm sure will be gracious not to log those questions.

So just to keep us moving along, we've got about 20 minutes left and I want to make sure there's

enough time for (Tracy) and SAP to talk about the SAP Analytics Hub.

But I just wanted to point out that regardless of what your strategy is for data literacy and what

your strategy is for trying to have you know good documentation for the deliverables that you

create, you're going to find that you're going to have some really critical decisions over the next

12, 16, 18 months.

You know do you try and fix your data literacy problem with a vendor or a software solution? Do

you try and fix it with a feature that is available for your existing investments, for example if you're

already an SAP customer like most of the folks on this call? Or are you going to address it

through your organization contacts and try and have it be more of an organizational initiative?



You know and I think if you talk to your chief medical information officer, you'd find an ally in the

concept of data literacy and probably someone who would very quickly self admit that they may

not be the best at always interpreting all of the reports and dashboards that they ask for.

And I would lobby and recommend this to all that I think you have to do all of them. And I think

you got to really take a step back and think about we're so focused on trying to get the right tools

and be able to create data fast and do this concept of self service, but self service tends to fail

when the people trying to use self service can't operate the kiosk. They can't even know the

difference between what the kiosk looks like and something else.

You know I always imagine when I walk into an airport and you know I'm not – sometimes there

are different kiosks now for when, they're not all just check-in and print your boarding pass and

I'm thinking oh geez, which one do I use?

If you can't just wing it and be successful, that's probably all anyone's doing so that's where your

failure rates are coming from. So anyway, just some thought provoking commentary there. And

with that (Tracy), I'd love to be able to pass the ball over to you to walk us through the Analytics

Hub for our remaining 20 minutes if that's OK.

(Tracy): All right perfect, thanks Jon.

Jon McManus: You're welcome.

(Tracy): All right, so thanks everyone. Again (Tracy Irwin) from SAP and part of the North America center

of excellence and we're going to cover just quickly the Analytics Hub. So this is a relatively new

product from SAP.



We actually use this internally, it's been around in SAP for about two years and we actually as our

transition to the cloud we have a lot of legacy content that's built in business objects whether it be

Explorer, WebI reports, Crystal reports.

And mostly this was used by our sales force globally. So if you think about how many sales

people we have at SAP, we probably have about 20,000 salespeople that are trying to get to their

information multiple times a day.

And a lot of it we started this initiative to really kind of harmonize and centralize the information

but we found that a lot of people really couldn't figure out where to find their information

sometimes even though we were starting this transformation. And we talked to a lot of our

customers.

We know that as much as we would like SAP BusinessObjects to be the primary reporting tool,

we know that customers have multiple BI tools in their environment and several different

applications.

We found that really a lot of their users were trying to figure out where was their content, were

they reproducing content that was probably produced in another tool?

So it's really not efficient and even as people are producing self service or leveraging self service,

you start this proliferation of content, duplicate content and as you know as an IT department it

can get a little bit hairy trying to manage all of this.

So SAP wanted to actually put this product in part of our solution that we leverage with our

customers and this is a very, very new product. It (went GA) I believe in September of 2017 so

it's only been out for a few months. So this is what we find a lot of our customers are looking for.



They're trying to do it on their own. We found that this was an easy way for our customers to help

harmonize and centralize all of their analytics content whether it be in the cloud or on premise.

So again this is part of the SAP Analytics Cloud portfolio so it's part of the solution but it could

stand alone separately.

And really I'll jump into the demo just really quick but it does allow you as Jon mentioned to

harmonize or bring together not only your business objects content on premise but also any

content in Analytics Cloud or Digital Boardroom and also third party content.

So I'll show you how we actually can pull that information in. And I'm going to actually skip past

these slides so that I can jump into the demo. You guys will get a copy of this as well as Walt

mentioned.

So let's go ahead and jump over to (Image Club). So for those of you that have seen it, this is

your initial launch page to get into SAP Analytics Cloud and you'll just go browse Analytics Hub

and there's really not a lot to it.

Actually let me jump over to the screen. So as an end user you're going to have a view just for

you. You'll have – I'm sorry, this is the custom one.

You'll have your own view, you can actually create favorites if you wanted. You can have your

favorites, you can have content that's picked just for you based on your history, you also have

most viewed, you can also look at all of the assets that are available to you.

You can also search the content. So you see that some of these actually have tags in them so if

you wanted to find everything that was reported to or applicable to sales, you can actually search

that and it brings up everything relevant to sales.



You can also create your own favorites, so all of these in here have little stars so you can actually

go into those assets and just quickly create your own view of reports that you frequently access.

Now, keep in mind this is something that not everyone is going to publish content to. This is

really controlled by a small group of people that have certified this content as part of the

enterprise analytics catalog. So this is really it's not anything new, it's a catalog of content.

So if you wanted to create something, certain people will have edit rights or create mode so you'll

go in and create a new asset. You can create the draft, you can – it's actually just links to URLs

so you're not actually storing any content as part of this.

You can add links to wherever those reports live, you can also tag it if you had reports around

radiology or inpatient processing. So you can add different tags in here, makes it very easy to

create that content.

If you wanted to go and append something, you can also edit that content as well. So you can go

in here and edit the content very quickly if you wanted to add additional links. These images are

actually not linked to the report itself, you actually need to embed those images.

So again Analytics Hub doesn't store any of the data of these reports, it actually just serves as a

catalog for all of your analytics content. As you see we actually have a Tableau dashboard in

here as well, so again because we're leveraging basically a URL we're not storing any of this

content in any of our servers, we're just storing the link out.

So this will allow the user if they have access to it to quickly jump to that report and you can also

leverage same authentication so that your users have a seamless experience as they're logging

in to the Analytics Hub and looking for their content. All right, any questions Walt?



Jon McManus: And (Tracy) we'll get to those questions, this is Jon. You know and I think for the group

you know, the simplicity of this is one of the things that Parkland like.

We already kind of told SAP that we'd like to have a little bit more organizational structure to this

not necessarily (poured over) in nested folders, but the idea that we can better group content so if

like my CFO logs in to a tool like this we can really kind of not necessarily let the pitch for you

thing automatically pull stuff that probably won't be the exact reports the CFO wants. But we can

help better organize that information for them so that the CFO doesn't have to go and make all

their favorites.

But I think what's really important and this is a bit of a departure for SAP more along the lines of

that concept of open SAP, is that you know think hard about the opportunity to have one browser

that you can embed as an application within your internal intranet or anything where you can

have a single launch point to start to bring together the federated analytic tools your

organization's using. You know that's where I think the simplicity of this you know just calling out

to URLs makes a lot of sense.

So you're still doing your cloud development in Digital Boardroom, you're still doing your on prem

builds in Crystal and Lumira and Web Intelligence and BusinessObjects and you can all of a

sudden go across the hall to finance and say hey, that you know Allscripts EPSi thing you're

using over there can we you know start pulling some of your content into the enterprise you know

content delivery portal or whatever you want to call it?

I think that that's a big step forward for some of us who struggle with the concept of a one stop

shop for certified information if you have some competing departments.

So anyway, it's something that I think really stood out to us and Parkland's very interested in how

we can make this fit particularly because we're building so fast in both the cloud platform and still



on prem that I'm really looking for something to essentially simplify the presentation layer

between those two very different environments.

And before I turn it over to Walt for just a few minutes of closing and we will turn our attention to

the Q&A after that, I just want to open it up again to my colleagues. And sincere thank you to

Clay and (Tracy) both tremendous, thank you so much. Jamie, Pat, Vijay any comments on the

hub or Clay's presentation?

Patrick Farrell: This is Pat. Definitely the challenge for us here at Penn feedback from more the

executive level and others about going through the folder structure being cumbersome to go

through and how many clicks it takes to just get the content you want.

So definitely looking at this, I have some hope that that could help make things less simpler for

people to find what they need and also irregardless of what platform they're trying to find it on.

Jon McManus: Thanks Pat. Jamie, Vijay?

Jamie Oswald: So I think it's interesting, right. I really think that it's a good idea, I really want to see how

it develops, right. So I'm not – I just I want to see where it gets to especially as we're evaluating

the SAP Analytics Cloud so.

Jon McManus: Right. And you know a quick departure just from SAP, you know I think a lot of – if there's

one takeaway from this, I think one of the things we all need to add to our research plate, you

know previous years it was the concept of data virtualization what is that, what is distributed

processing, you know what's going on in the Hadoop space?

You got to be somewhat aware what modern BU versus traditional BI. But I think the new thing

has to be this concept of an analytic hub.



And I was just at Gartner's seminar up in Grapevine their big data analytics summit it was the

same week that (HIMSS) was going on and literally (Laura Craft) who's a colleague of mine and

she works for Gartner and she's the vice president for their healthcare analytics research wing,

incredibly smart lady, she had a whole brief just on the concept of an analytics hub vendor

agnostic of course.

So I think that it is something that a lot of us really need to put some thought into about potentially

being an important technology decision point really with the intent of simplifying the content

accessibility. But anyway, just the way Parkland's thinking about it.

So Walt with that, let me go ahead and let you close out for the next few minutes and then some

of us will be handing around for the Q&A section. And I just wanted to say a sincere thank you.

I just glanced at the attendee list and it is 74 strong, so I'm overwhelmed by the continued

attendance and I'm very thankful for everyone's participation and I look forward to speaking with

you all after and thank you to my leadership colleagues. So Walt, I'll turn it over to you.

Walt Ellenberger: Very good and I'll bring everybody through the home stretch. You know once again,

thank you Jon. We actually started out with 83, probably had some people that had conflicts but

great size group. Great change in approach more education oriented, leadership council, (Tracy),

Clay all good.

So I'm going to just walk you through a high level. A lot of this content we're going to provide you

in retrospect so you'll have it hard copy and it's going to be on the collaborative website.

If you have any questions on how you access that feel free to reach out to me. Coming out of

(HIMSS) and the Gartner summit we had a lot of good press.



Here are some examples of those articles that are made available to you, a lot of highlights as

relates to some of the work that Mercy has been doing and Providence, I think Parkland's got

some good press in there.

Overall we've had a great session with the ask the experts where we had Parkland and Jefferson

and you know some of our partners Esri and Samsung – I'm trying to think who I missed in the

equation – and Providence you know all speak and provide a forum for people to ask questions

directly, so that was much appreciated.

I had some content to share there too. Just kind of continuing down the list of some post game

articles picked up by the analysts and press we'll share with everybody. I'm going to do a

shameless plug for (Dan Exely).

I'm turning into his biggest marketing fan just with the talent that he brings now to the marketplace

in the form of consulting services really looking at strategy in you know an existing ((inaudible))

environment or a HANA environment we're starting to use him to help folks that are looking to you

know optimize what they've already invested in, figure out a migration path to a hybrid model,

figure out how to facilitate greater exposure with the HANA environment. You know (Dan's) the

guy and he has you know access to a lot of other great talent out in the partner channel.

So the big event that's coming up next, if you want to see Parkland live and in person, Jon and

his team have been kind enough to host an event on site, this is next Thursday in Dallas, Texas.

There you'll see a full day of looking at the technical underpinnings a logical data warehouse, a

hybrid model and using on prem assets in the analytics and how that's been visualized and

leveraged with the C-suite and a lot of operation managers in daily use now at Parkland itself.



So this is a must see opportunity, you have to register to get plugged in, we'll provide information.

SAP's going to sponsor dinner the night before and we'll have a full day the following day, a lot of

prep that's available out there.

If you haven't heard of this please get plugged in with the AEs in the field and you have to see

Parkland in action. It's a live version of a webinar so we can't push this opportunity enough. And

then coming up with things coming down the line, obviously talked about the Parkland showcase

next week.

We actually are going to participate as a table top vendor at the (XGM) the following the 24th

through 26th in Verona. Jamie I don't know if you want to plug in, and you're going to be there

the following week if you want to say something about?

Jamie Oswald: Right. So I'll be at the second week of (XGM) for the analytics roundtable and would be

very, very interested in meeting up with everybody.

I think we're working on maybe setting up and a place which I'm sure Walt will be happy to

communicate. And if not if you just want my contact information, you can reach out to Walt or

whoever and I'm happy to share that and try to meet up.

Jon McManus: Yes Walt this Jon, if I could – and Jamie, I had forgotten to bring this up. So I already

reached out to Tom Yosick over at Epic to try and get a room reserved and a time for Jamie to

host a roundtable, and we'll have Walt send out that detail.

So if any of you are having anyone from your organization or yourselves attend (XGM), Parkland

one of my data scientists will be there, I won't be there myself neither will Clay, but we'll have her

be at that roundtable with Jamie as well.



So if anyone is interested, we will certainly have a consortium presence during that time and

Jamie will work on the logistics with you and Walt will send that out.

Walt Ellenberger: Very good. And then just real quick, we have a couple of other webinars that are

coming up. They're not specific to the consortium here but obviously invited, a lot of interesting

work we're doing with Esri in looking at the opiate problem not just from a reactive way but really

moving it to the front line from a practice front line perspective.

And the work that we are gaining momentum on in the U.S. that we've established a nice track

record with from a medical research, clinical management perspective abroad and now moving

that capability into the U.S. marketplace, we're going to be featuring that webinar in the May

timeframe.

Our big event is June 5th through the 8th that's SAPPHIRE along with our big user group

meeting. I know we had a lot of submissions for the HANA Innovation Award, we're anticipating

that we'll get some winners out that group, we have a nice track record to that end. And we have

several different events to showcase there not the least of which will be Providence and Mercy.

You know Mercy's kind of an interesting scenario kind of jointly talking about collaborative

analytics we are doing with Medtronic and looking at outcomes, assessments and things along

that nature. So stay tuned, a lot of details to follow on that front.

And then we're actually going to move the next consortium update call into the May timeframe

originally slated for June but we're going to move it up. We have a healthy agenda, a lot of the

education oriented details that Jon outlined here. We're going to do a little more showcase

feature as it relates to some of the work Pat is doing at Penn Medicine.



And then we are in the process of getting education series scheduled for the consortium as it

relates to our overall advanced analytics strategy, a lot of interest, a lot of change, a lot of

opportunity.

And then just kind of a specific event around HANA 2.0 we're going to talk a little more about that

and then working with Vijay and doing a webinar showcase with some of the great work he's

doing with rev cycle in the HANA environment in Providence St. Joe's.

The other plug I'll put in in the last couple of minutes here is if you're not aware, there's a lot of

great information available through the blogs and live expert sessions that we have set up.

Once again I'll get you this detail so you can have these hyperlinks to you know register but a lot

of new content, a lot of exciting enhancements broken down into specific you know focus areas

as it relates to HANA 2.0, so I just wanted to bring that to the group.

And with that I think we're one minute over, apologize for that. That will be a wrap for the main

body of the discussion today, and if anybody wants to hang on we'll kind of move in to Q&A from

there. So, I'll turn it back over to you Jon.

Jon McManus: Thank you Walt. So that concludes the consortium call for April, thank you all for

participating. Feel free to sign off and if you want to hang around for the Q&A we will – I will stay

on the phone between now and 1:30 until the questions stop.

So with that, I think we will – Walt how do you want to do this? You want to read the questions off

in the chat or do you want to have people unmute themselves?

Walt Ellenberger: Yes. I think why don't we start with the questions in the chat and then if anybody wants

to you know add to those or questions after the questions are answered you can hit star 6 and



we're good to go. So why don't we just start with the questions in the chat. Can you see those all

right Jon or you want me to read those too?

Jon McManus: No I can see them. OK Walt. So the first question's from HD, so HD if you want to

quickly star 6 unmute yourself I'd love to hear who you are and feel free to ask your question.

Going once, OK. So the question HD asked is how much effort is in creating wiki pages like the

radiology order? How many pages are there at Parkland?

So there's a bit of effort. So I think we have done that for our more reusable self service focused

enterprise validated assets, I know it's a mouthful but. So we try and use that for those self

service tools that typically we're provisioning in either Lumira or Digital Boardroom that have a

heavy amount of reused and self service.

And you know a lot of those things like the radiology one, we have another one that covers like all

lab orders for the last 13 months, we got another one for medications, the real – and another one

for like best practice alerts or decision support alerts if you're Epic savvy. Those are the kind of

things that we tend to have that level of documentation around.

So I want to say we're in the teens on the counts of those actual pages that are that level. You

can use the universe to extract metadata from BusinessObjects, you can also use information

from the design tool to extract objects from the universe to help you get the you know kind of

semantic materials.

But as far as the business friendly nomenclature, you know that is something that we

administratively take on. So I have a few staff within my division that are more in the data

coordination role.



They do kind of business and analyst work, they gather requirements for report requests, they

help with validation and work with customers and we typically charter those individuals.

And these are more you know a lot of times they're more junior members of my staff working on

up skilling so they can grow into more professional technologists at more senior levels.

We'll ask them to do kind of the data dictionary documentation and quarterly updating and things

like that. So, we typically ask those folks to try and do that documentation and our internal wiki is

very much a work in progress. Clay do you have any – are you still on? Do you have anything

you want to add to that?

Clay Townsend: Can you hear me?

Jon McManus: Yes, yes go ahead.

Clay Townsend: It looks like I'm unmuted. OK. As far as the amount of effort it takes, yes you have to sit

there and document all that material, work with your customers and everything.

But the actual tool itself working inside the wiki I think is a great tool, it's just simply editing a word

document and then instantly shared and you take advantage of that kind of crowd sourcing or at

least you can because it's shared like that.

Jon McManus: Right. And I think the sweet spot we're trying to find at Parkland, the reason you know

Clay convinced me to have the wiki was a good idea is we're trying to look for those tools that just

have that innate understanding of how to navigate, we don't have to really retrain people on.

So Wikipedia is something a lot of us are familiar with you get the concept, so when you see that

type of interface deployed internally to an organization, people just get how to navigate it; they get



how to use it, they get how to search it, they understand that the links will let you go different

places.

And you know we've had pretty good success with it but I think we really want to ramp up how

much we're documenting in there and make sure that if we start to really continue the congealing

of enterprise content and watermarking it and labeling it, every enterprise asset has that level of

documentation to go with it, and I think we have a really good start.

The reason I thought it was important to share that was give everyone a sense of how you can

approach giving your deliverables in context, not just give the deliverable. So HD, I hope that

answers your question.

The next one's from (Michael Cabarel) and the question is, what is the mechanism process used

to control the wiki content? So (Michael), do you want to unmute yourself and introduce yourself?

OK we either have people who like to drop questions and run or they're shy. So the mechanism

our self is we're just using media wiki, the same thing that you can download from an open

source standpoint.

We did deploy an internal server to house it and then we have an internal and external view of

those pages. And when I say external I mean to my internal organization outside of our IT

department. Clay, you got anything you want to add on that? I know it's your baby.

Clay Townsend: So yes, exactly like what Jon said. If we have (production) information you don't want to

share not necessarily with everyone it's going to go on the internal side, otherwise it's all

externally facing content.



Users are created and if you have a user account you can edit but you're not necessarily going to

give everyone a user account to edit those pages. It is editable just like traditional Wikipedia.

Jon McManus: OK. Next question is from (Christy Jones). (Christy), do you want to unmute yourself and

introduce yourself? And it's star 6 to unmute yourself in case.

(Christy Jones): Hey this is (Christy), can you hear me now?

Jon McManus: Ah, someone's still on. Hi (Christy), how are you?

(Christy Jones): Hey, I'm good. How are you? Sorry about that.

Jon McManus: No problem. So if you just want to introduce yourself, your organization real quick and

then we can tackle your question.

(Christy Jones): Sure, sounds good. So this is (Christy Jones) at Sanford Health. My question is really

around we have some data governance software and we're going to start pulling in basically a lot

of the same stuff that wiki had shown and we can attach it to reports and you know look to

((inaudible)) column or something, we can look to see where you know that lineage goes. So do

you guys have any governance software? If so, how do you use that in conjunction with the wiki?

Jon McManus: Yes, no that's a great question. So we actually do not so I have not gone and bought

Collibra or some derivative. We have chosen to do really three things for a data governance

standpoint.

The first is we really just did a ton of manual interviewing and building up an enterprise data

dictionary and enterprise data catalog like a J.C. Penney catalog for reports and we're trying to

keep that updated quarterly.



And you know that's had tremendous success and a lot of input. And that really is I would say

that's 85% accurate for our overall inventory not including ad hoc analysis one time things.

You know we have a logical data warehouse at Parkland that you know has a lot of SAP

foundation but there's other technologies at play like TIBCO for data virtualization and we have

Hortonworks with Hadoop, and there's you know between Clarity and Kaboodle and Epic's

((inaudible)) portfolio, there's a ton of data lineage tool sets that come with those products. So for

a lot of the metadata management we're relying on a combination of the vendor data dictionaries.

And you know Parkland has close 150 different data sources that we have to tap into Epic is

Clarity number one, (EDW) number two they're big but then I've got 148 other things that have

you know, that are either named vendors or they're flat files coming from somewhere or

something. So, we have a lot of that captured and documented.

And the reality is I have really not found data governance software as a standalone to really bring

me the automation and value without the legwork. And if I was going to have to do the legwork

anyway, I didn't see the value of paying for software to help organize it when we could just do that

ourselves.

And where I'm about to change my tune is the next big thing that I have my eye on is the concept

of – Clay mentioned this briefly because he and I have had a lot of conversations about this,

crowd sourcing metadata and data governance.

And there's some vendors out there now that are starting to tap into the concept of social media

with data governance. And what I mean by that is imagine a software that can introspect

automatically all of your tables of value whether that's Oracle, SQL, DB2 whatever?



And then they create a Facebook like page – not Facebook but it looks like Facebook – for each

table so you developers, you data stewards can go in and like a table and say hey, you know

watch out for this drawing or use this index when you're in here like alert, alert.

That's where I think we can really start to get value out of a software partner in data governance.

Instead of it being top down and centrally pushed out, really start to put a framework in where we

can have a lot of the people doing the content development particularly as we push more and

more of that out to the business, so that we build an ecosystem that they can collaborate on.

And if certain vendors out there and I can – we can have a follow up call if you want to know what

vendor I'm talking about and kind of the ways we're looking at it.

But those are some of the things I think that are exciting that may warrant a data governance

software. But I unlike many of my peers have not really put a ton of value in the vendors going

back three, four years to make that investment at Parkland.

That's a long winded way of saying no but that's some of the context around it. And if Jamie or

Pat or anyone are still on the line Vijay, if you guys have anything to help with (Christy's)

comments by all means.

Jamie Oswald: So we're in that process where we're evaluating all of those tools as well and seeing if it's

time to move to that.

So we've used a similar wiki for several years now and are kind of at the – and it's provided a

tremendous amount of value for us, but we're starting to look at that next step. So happy to have

a conversation about what we found and what you found as well.



Patrick Farrell: And similar here, this is Pat. We're also going through a similar exercise but we've built a

custom website. So you know, maybe there's some room to leverage some of the solutions that

SAP show now.

But our part not really the technology again, it's more about what exactly is the information you

need a wrap around the assets you have, dashboards, reports whatnot, what metadata (help)

people find what's out there. So hopefully we encourage reuse and we talked about data literacy

earlier so hopefully encourage that too.

Jon McManus: Yes and I'll just give a shameless plug. I've seen Pat's website from a Penn Medicine

standpoint, it's pretty fantastic if you're looking for like a front page to your analytics program.

They did a really nice job over there. But (Christy) if you go to the consortium website and Walt

can connect you, you can find our contact information and it sounds like a lot of us can have

offline conversation with you.

But I think this is something that we all share in common that the time and place for a data

governance strategy really needed to come when you had your act together, and it's taken at

least us on the leadership council a few years to do that.

So I think we're all at the point now we're really starting to look at that. But we've done things to

handle the blocking and tackling, just not by a named vendor.

(Christy Jones): OK. No, that sounds great because you're absolutely right when you said I mean it's a

lot of legwork to get that up and going. And so as we go down this path I had a lot of maybe red

flags if you'll call them and moving forward. So yes, that's really helpful.



Jon McManus: And you know what sustaining it too I mean that's the other big (got you). You do all this

legwork to get it up and then you've got a team of centralized data governance experts trying to

sustain it, and if you don't have the incentives out in the organization where more and more of the

content development decisions are happening in the business, keeping it updated becomes the

next problem.

So you know I think you know (Christy) one thing you may want to do some research from an

academic standpoint on is this concept of crowd sourcing data governance.

And there's a few vendors out there doing some interesting things like I just described that may

actually start to incentivize getting the business to contribute better if you tap into that willingness

to participate. Like the reason we chose wiki is because it's easy to use and people get it

already.

Well if people start to have like a Facebook like experience for data governance and table and

drawing documentation, maybe you'll have some more success. At least that's what we're

thinking.

(Christy Jones): Yes, makes sense. Thank you guys.

Jon McManus: OK. All right, you're welcome. Next we have two more questions, next one was from

(Susan Pena). (Susan) can you star 6 and introduce yourself?

(Susan Pena): Yes. Hi, this is (Susan Pena) and I'm with MultiCare in Washington State and we've been

…

Jon McManus: (Susan).



(Susan Pena): Hi. Yes, we've been looking at building our own version of the Analytics Hub and we kind

of are struggling with we have a ton of reports and really we need to whittle it down instead of,

nobody needs to know that we send a flat file to some vendor somewhere, right?

Jon McManus: Right.

(Susan Pena): But we also are finding that we've built a lot of Crystal reports that are basically duplicates

of a Reporting Workbench report that we just didn't know was there. So we were wondering if, I

was wondering if you guys show your Reporting Workbench reports on your hub as well as your

reporting content.

Jon McManus: Well just yes, no great question. Parkland's not implemented the Analytics Hub yet. We

are a eager, interested, potential consumer like the rest of you.

I just got I guess the little bit more early preview, which is why we wanted to bring it to the

consortium as early as we could so you all could see it too and think through what it could mean

and if that could help you or not.

Because the real pain point is if you start doing cloud development in addition to on prem, then

you're really going to have stuff all over the place like we do now so I think it's important.

But if you've seen Epic's new 2018 version roadmap, you will notice that they have a content

catalog in hyperspace that looks a lot like the Analytic Hub.

(Susan Pena): Yes, we've seen that too.



Jon McManus: Yes. So we've got our eye on that. Parkland's not going to upgrade to 2018 until spring

next year although we have 2018 in our test environment already live and on prem so our guys

are already looking at it.

I think the thing we're thinking is – and I've spoken to Epic's leadership about this and they can

always again, sometimes the things I say they are subject to change. But Epic's thinking is this,

they need to organize a lot of their own stuff, so they are pursuing a concept of a easy to use

aesthetically pleasing catalog in hyperspace.

And really the driver for that is and I don't know how much you know about Project Telescope

with them, but that's where they're taking SlicerDicer and they're really going to you know put it

on steroids starting in version 2018 and then the next version of Epic which will be a much, much

bigger where SlicerDicer will become the self service tool that end users in Epic use to create

content instead of Workbench.

And then SlicerDicer will have settings after a user creates a visualization say how would you like

this to be run in perpetuity? And that's where they can start to reuse some of the Workbench

settings.

So they're going to absorb Reporting Workbench into SlicerDicer and then SlicerDicer is how you

create the widget that you push to a Radar dashboard. So they're starting to tile that together so

they need the ability to organize all those reports internal to Epic.

I have already spoken to Epic about what would their ability be to link to an Analytic Hub? And I

think what's going to happen is they're also moving Radar to the browser so to serve executives

who never log into hyperspace, and then what happens is it just becomes a URL.



So our thinking is if we can land on an Analytic Hub that offers the third party redirects as simply

as URLs like SAP's pursuing, and we got to learn more about SAP to be sold on it but we're very

interested, potentially then I just launch out to the browser domain that provides Epic i.e.

Reporting Workbench, Radar or SlicerDicer.

So that's you know and again all that would happen is I click the tile from Anlaytics Hub and it

launches hyperspace and I'd have my log in credentials port over there. So I think that's the way

we're thinking about it if that helps (Susan).

(Susan Pena): Yes that definitely helps, thanks.

Jon McManus: No problem. And then last question (Serang)? (Serang) can you unmute yourself and

introduce yourself?

(Serang): Yes, hi. This is (Serang Vishwan) I'm with (Unity Medical Center) out in Fresno, California.

And I believe my question was already answered earlier about any event or meetings planned at

(XGM) week two for the analytics council, so I'll be there and I know Jamie well. So I think you

know unless I hear anything from Walt, we'll make sure to set up at least an informal

conversation.

Jon McManus: Yes, no great. Jamie will be waving the flag for the consortium and I will be working

behind the scenes with Epic and Walt to make sure there's a room, there's a time.

Epic's been gracious enough to – they know all about the consortium and are very supportive of it

and always interested in the meeting minutes and they read them. So they have made

accommodations in the past for (Dan) and I'm sure they'll do the same again. So I will just get

those logistics sorted with Jamie and we'll get that sent out.



(Serang): Awesome, thank you.

Jon McManus: OK, well that's all the questions everyone. So I just want to thank everyone again for a

great April consortium call. I look forward to hopefully having many of you join again in (front with

us) in May, we got some exciting content.

And I'll be working hard with the leadership council in between to try and make sure that we

continue to have really action packed sessions and a big thank you to Walt and SAP. So with

that, we'll end the call. Thank you guys so much and I hope everyone has a great remainder of

their Tuesday. Thanks a lot.

Walt Ellenberger: Thanks Jon.

Operator: The leader has dropped from the call and if the leader doesn't dial back in and rejoin …

END

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