>> Announcer: From San Francisco, it's theCUBE!
Covering OSIsoft PIWorld 2018.
Brought to you by OSIsoft.
>> Hey welcome back everybody Jeff Frick here with theCUBE.
We're at OSIsoft's PIWorld 2018 in downtown San Francisco,
they've been at it for decades and decades and decades
talking really about OT and efficiency.
And we're excited to be here it's our first time,
and really want to talk to a customer,
excited to have our next customer CJ Smith,
She's a Project Manager for the city of Riverside
CJ great to see you.
>> Thank you, hi!
>> So you represent a whole slew of mid-sized US cities,
so how big is Riverside for people that aren't familiar?
>> We serve 120,000 customers so we're not too small,
but we're definitely not as big as some of the other cities.
>> Right and then as we said before we turned on the cameras,
you guys have a whole department for utilities,
you have your own utility as well.
>> Yes we do have a public utility division within the city,
also an IT and public works,
parks and recs like other cities as well.
But we do have the utility,
which is different than some of the stand along utilities,
like LADWP for example.
>> Right but it's good you were saying off camera
that that gives you guys a nice revenue source,
so it's a nice asset for the city to have.
>> Yeah the utility is revenue generating department.
>> Okay so what are you doing here at PIWorld,
how are you guys using OSI software?
>> So we started down PI back in August 2016,
as an enterprise agreement customer,
and at that time we really lacked visibility
into our system so we needed something to help us
gather the data and make sense of it,
because we had data all over the place,
and it was hard to answer simple questions
it was hard to find simple data.
And so we started down the PI journey at that time,
and we basically used it like a data hub to aggregate data,
turn that data into information,
and then we disseminate it using dashboards.
So PI Vision dashboards which used to be PI Coresight,
as well as reports.
>> So what were some of the early
data sources that you leveraged,
that you saw the biggest opportunity to get started,
or yet even more importantly your earliest successes
where'd your early success come from?
>> So our very first work group that we worked with
was our Water Operations and our Water SCADA team.
>> Seems to be a pattern here
a lot of water talk here at OSIsoft.
>> Yeah I'll talk about electricity too.
But we started on water and the first thing
we did was implement their data,
it was called a Water Operations dashboard,
and they were doing it manually in Excel,
and it would take a staff person
over eight hours to do it.
And they would do it the next day
for the previous day data.
So imagine how opposite of real time that is right?
So we integrated that data with PI.
>> And how many data elements?
How big is the spreadsheet this poor person is working on?
>> So the Water SCADA tags that
we brought in were near 1500 tags,
so you imagine that much data and calculations
with over 1500 calculations behind it.
So it was a ton of effort.
>> Right.
>> And a huge quick win for them!
So it's saved staff time,
they now have actual intelligence, real time data,
the managers get alerts to their phones
about the status of wells,
and so it was really helpful to that work group.
So that one was one of our first
and earliest wins on PI.
>> Was it a hard sell?
To those people to use it?
It wasn't because we did find a champion in that group,
someone that would help us.
Actually the manager he was very interested
in technology and automation.
And they understood that even though
it would be a time investment up front,
it would save them a ton of time in the long run,
for the rest of the year.
And so one of the things that helped us get buy-in
early on is that we used an Agile approach.
So we would tell the manager,
I only need you for five weeks.
I need you and your staff for five weeks,
and then you don't have to talk to us anymore.
We will deliver the product in five weeks,
we will do all the work,
but if you could give us five weeks of your time,
then you could have all your time back the rest of the year.
And that helped us get buy-in
from the managers and a commitment,
because they can identify with okay just five weeks.
>> Right so those were probably the operational folks,
what about on the IT folks how was
getting buy-in from the IT folks?
>> The funny thing is and the thing we did different is,
we have a great relationship with IT,
and we really forged a partnership with them early on,
even from the very beginning when we
were just reviewing the agreement.
We got their buy-in early on to say okay,
this is what we're thinking about doing,
we want you to be part of the team,
and we really built a partnership with this project
so that it could be successful.
So they work hand in hand with our
PI implementation team every step of the way.
They've been on this journey every step
of the way with us.
So we don't have some of the challenges
that other companies that I hear
are talking a lot about here with IT
and it kind of being a bottleneck,
we didn't have that same experience
because we really worked hard
up front to have the buy-in with them
and really build a partnership with them,
so that they're implementing PI with us.
And another selling point with that is,
we're using PI as a data hub or like a bus,
a data bus essentially.
So for them it's good because we're saying
look we're only going to have this point to point system,
instead of having all of these individual points
we're only going to connect to one system,
which will be easier for them to manage and maintain,
and we'll instruct staff to go to PI to get the data.
So that's a selling point for IT
it's more secure, it's more manageable.
>> And did you use an outside integrator,
or did you guys do it all in house?
>> Our implementation team is a combination
of in house staff and a consulting firm as well.
>> And then it's curious 'cause then you said
once you add all the data it's kind of a data bus,
how long did it take for somebody to figure out
hmmm this is pretty cool maybe there's data set number two,
data set number three, data set number four?
>> So right after our first six week implementation,
we rolled out a new implementation every four to six weeks.
>> Every four to six weeks?
>> Yeah so we did a sprint cycle the whole first year,
and actually the whole second year
we're currently in right now,
and so we touched a different work group every single time,
delivering a new solution to them.
So we picked up a lot of traction so much that now,
other departments in the city want it,
public works is asking for it,
the city manager's office so it's really
picking up some good buzz,
and we're kind of working our way down
discussion of smart city talks,
and seeing how PI can support smart city,
big data advanced analytic initiatives at the city.
>> So what are some of the favorite
examples of efficiency gains,
or savings that department A got that now
department B sees and they want to get a piece of that
what are some of your favorite success stories?
>> I would say two of mine,
I shared one on the big stage yesterday about the superpower
I talked about our operations manager,
who started receiving actionable intelligence overnight.
And he got an alert around midnight,
and he called his operator and said hey,
what's going on with that well?
And the operator said very puzzled,
how do you know that there's something
going on with this well?
And he replied and said because I have superpowers.
And so his superpower was PI,
and that's one of my favorite stories because
it's just simple and it resonates with people,
because he is receiving alerts and push notifications
that he never had before to his mobile device at home.
So that's a huge win.
>> Was the operator tied in to that same notification,
or did that person know before the operator?
>> The manager knew before the operator.
So the operator didn't know about PI at the time
and we had just rolled it out.
And so the manager was just kind of
testing it and adopting it,
and so it was kind of like he had a leg up a little bit
and they were confused like how do you know you're at home?
>> Man: Right.
>> He's like I have superpowers.
(laughing)
It's probably my funniest and best story,
and one that I always tell because it helps everyone,
no matter if it's an executive to a field person,
really understand the power behind PI.
I think another one
if I had to pick another example of a win
that I think was powerful is,
our work order and field map.
So we have our field crews right now that have a map,
that's powered from our work order and asset management
system pushing data to PI,
which then pushes it to Esri through the PI integrator,
and they're out using it in the field
and it helps them route their work,
they can see where their workers are,
they can see customer information.
And that map is really changing
the way the field crews work.
So imagine a day before this system where,
they would go in and have to print
every work order from the system.
And not all asset management systems
are really user friendly.
They're kind of archaic a little clunky,
so I won't say the name of our system.
>> And doesn't work well if there's a change right?
>> Yeah and they're not really mobile friendly.
So that's part of the challenge,
but because of that now public works wants that map,
parks and rec every department that has field forces,
they want something similar so that
they can get all the data from all the other systems
in one app in one location on their device.
>> And do you find that's kind of a system pattern,
where often department A needs very similar to what
department B needed with just a slight twist?
So it's pretty easy to make minor modifications
to leverage work across a bunch of different departments?
>> Absolutely a lot of work groups are similar,
maybe a little different like you said,
but especially those that have field forces.
Sometimes it makes it easy to sell it to the next group,
it's like look this is what we've done,
is this something that you kind of need?
Or what would you need differently?
Like we've developed field collection tools.
That's easy to replicate.
Once you see it it's easy to say
you know what that works but I need it to
say this and I need it to say this.
If you just show them a white paper,
it's hard for them to say this is what I need.
Most people just don't know,
but it's easy once you see a suit to say
oh I don't like that tie I don't like that shirt,
I don't like those pants.
>> But something close.
>> Yeah but something like that right?
So that's the benefit once you start having a solution
to easily modify and reproduce.
And then the good thing about Agile,
you're running sprints so you're learning every sprint.
You're kind of learning as you go,
and you're able to refine it and refine it
and make the process that much better.
>> Right.
On the superpower thing employee retention is a challenge,
getting good people is a challenge,
I'm just curious how that impacts the folks working for you,
that now suddenly they do have this new tool
that does allow them to do their job better,
and it's not just talk it's actually real
and gave that person a head up on the actual operation
person sitting on the monitor devices.
So as it proliferates what is the impact on morale,
and are more people rising up to say hey,
I want to use it for this I want to use it for that.
>> Yeah we are getting a lot of interest,
and I think the challenge is,
and I talked about this a little bit during my session,
is change management and culture.
Some people see automation and technology
as sometimes a threat because of job security,
or the I've always done it this way type of mentality.
>> Man: Never a good answer.
>> Right but once you kind of get them to see that
we're just automating your process to make it better
so that you can do cooler and better things,
so that you can actually analyze the data
instead of inputting data.
So you can actually solve problems versus
spending all your time trying to
identify the data and collect information.
So staff are starting to see the value,
and after the first year and a half,
we've gotten a lot of traction.
I don't really have to sell it as much,
it's now such a huge part of our culture that
the first question when we want to implement a new
system is does that integrate with PI?
I don't even have to ask them.
Everyone else is asking well have you
thought about using PI for that?
So we always kind of look to PI first to say,
can we create this solution in PI?
And then if not we look at other solutions
and if we're looking at other solutions we say,
does that solution integrate with PI?
So that's become part of our norm to make sure
that it plays nice with what we're calling
our foundational technology which is PI.
>> Right so you talked a lot about departments.
Is there kind of a cross-department city level play
that you're rolling data and or dashboards into
something that's a higher level
than just the department level?
>> Yeah so far the only thing that we have done
that's kind of cross divisional not just in one division,
is our overtime dashboards.
So we recently created overtime dashboards throughout
the entire city so that executive level department heads
have visibility into overtime,
which just gives them trends so that they can know
what departments are receiving the most overtime?
Is that overtime associated with what type of cause?
Was it something outside of our control?
Was it a planned overtime?
And then most importantly where we're trending.
Where are we on track to be by the end of the year,
given our current rate so that they
can be proactive in making changes.
Do we need to do something different?
Do we need to hire more people in this department?
Do we have too many people in this department?
Can we make shifts?
So it's giving that level of visibility,
and that's a new rollout that we just have completed,
but it's something that we're already seeing a lot
of interest in doing more of.
Cross divisional things so that the city manager's
office and that level has more view into the whole city.
>> Right well CJ it sounds like you're doing
a lot of fun stuff down at Riverside.
>> Woman: We are we are!
>> And you can never save enough water in California,
so that's very valuable work.
>> Woman: That's true!
>> Well thanks for taking a minute and sharing your story,
I really enjoyed it.
>> Thank you for having me.
>> Absolutely she's CJ Smith I'm Jeff Frick,
you're watching theCUBE from OSIsoft PIWorld 2018
in San Francisco, thanks for watching.
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