Planning Makes Perfect: How Preparation Led to a Smashingly Successful Data Transformation

Transcript

Jess Carter: The power of data is undeniable and unharnessed, it's nothing but chaos.

Speaker 2: The amount of data was crazy.

Speaker 3: Can I trust it?

Speaker 4: You will waste money.

Speaker 5: Held together with duct tape.

Speaker 6: Dream defier.

Jess Carter: This season we're solving problems in real time to reveal the art of the possible, making data your ally, using it to lead with confidence and clarity, helping communities and people thrive. This is Data Driven Leadership, a show by Resultant.

Hey guys, welcome back. I'm your host Jess Carter, and on this episode of Data Driven Leadership, we're diving into developing a successful data strategy. We'll kick off this episode with our solution on the spot segment, where we bring in thought leaders and put them on the spot for some solutions that are relevant to today's data challenges. Specifically, we're looking at the issue of, what is a good data strategy and how do you get one. To help me solution on the spot today, we'd welcome John Roach, the President of Resultant. For those who don't know you and just see the title, tell us a little bit about John Roach and why is John the guy to talk to about data strategy.

John Roach: I've been a consultant now for the last 11 years. Before that, I worked in aerospace defense in very heavily data driven roles there. In the consulting world, I spent the first couple years as a general management consultant dealing with all things organizational strategy. I pivoted after that and started and built our data analytics practice from me to about 60 people. But throughout the course of that I've probably run, gosh conservatively, four dozen data strategy projects and helped I would guess, over a hundred organizations, align their technology strategy and data strategy to their organization's mission.

Jess Carter: For this solution on the spot, what we're going to focus on is you've met a client, they're talking to you, you're getting familiar with them, and you ask them about their data strategy and they say, "What is that? Why do I need one?" What do you do?

John Roach: If they said, "Yeah, we don't really have a data strategy," that's really common, so if you're in that position, I wouldn't worry about it. What's honestly much more common is we'll get a call to come in and help an organization with their data strategy. Turns out they have no idea what their actual strategy is, as an organization. And in the course of assembling their data strategy, we often have to sort of suss out what's your mission as an organization? How do you differentiate in the market? What are the three or four things you have to do extraordinarily well as an organization to be able to accomplish your mission? And then we build the data strategy under that, supporting those three or four things that they have to do extraordinarily well.

Jess Carter: Does everybody need a data strategy? Does every company need one, every market, every industry?

John Roach: No, of course not. But if you want to be able to compete with your competitors, I think you do. Lots of smart people have done research on this and concluded various numbers. Roughly, you'll be 10% more efficient and 10% more effective in your market, if you are using data as a strategic asset.

Jess Carter: Let me ask you this, maybe somebody does have a draft data strategy. How do you evaluate if it's any good? How do you evaluate the efficacy of a data strategy?

John Roach: If it starts with technology, it's not good. If it isn't very, very closely tied to the organization's mission, it's not good. And if they haven't contemplated organizational and cultural adoption of what they're doing, it's not good. I'll say that in a much more positive way. Getting the data and technology stuff right is table stakes. You have to do that. Catering for the sensitivity of the data and ensuring that you are complying with all of the regulations around governing that data effectively and ensuring that you are appropriately using it, so given that all that stuff has to be done incredibly well and you, you've got to be able to check all those boxes.

What we've seen is the difference between a good data strategy and a not so good data strategy is, a good data strategy is about the business. It's really about how do I leverage the data assets that I have or I can go get, to help the business accomplish its mission. If that's not the first three pages of a data strategy, if they're about the tools or if they're about the architecture, they really are going to have a hard time gaining long term adoption of what they're trying to do across the organization. It will not get integrated in the business in a way that could create the transformation and improvement that it could and should across the business.

Jess Carter: Maybe I'm a client that we've been having this conversation. I went back and I tied it to my business strategy that didn't exist, but I created one because of that great advice and then I made sure that it was a good one, it wasn't just based on technology. My business and my leadership are still not buying it. What are some suggestions you have about forcing functions to get my company to buy into my data strategy?

John Roach: This mindset shift in the role that data and technology should play in organizations, is relatively new. The problem you're describing isn't rare. What we found is its impossible to get a data strategy right, before you start building something. So to say that another way, we found that iteratively building both the strategy and I'll just say, physical assets inside of the organization, you can't write down a 50 page plan of your data strategy and then go execute it and expect that you're going to be able to build what you wrote down on paper. The reality is, stuff you assumed will be one way, will be a different way.

The ways people will react to, respond to, what you build will be different than you thought. The pace of adoption across the organization will be different than what you thought. Almost never have we seen the data not inform the organization's mission as well. Building out and driving insight from the data, we've almost always seen inform, if not the organization's mission, all of the tactics underneath how they're accomplishing that mission. Those get transformed and formed by the data and vice versa. It should be this reciprocal cycle where you learn new things in the data, it changes how you think about the business. Because you've changed your thought about the business, it changes how you want to look at the data, on and on and on.

Jess Carter: Okay, I got one more for you and it should be a little bit fun. What are the pitfalls? You've done a bunch of these, everybody trips up at this point. I constantly have clients come to me and say, "Oh no, we're in this situation. What do we do?" Walk me through some of those pitfalls.

John Roach: The most common, least spoken about pitfall we've seen is you have an organization adopting data, getting really excited about the strategic use of data in the organization. They get some wins under their belt, they get people really excited about it. They get people using, name your favorite BI tool, and they get what we call, dashboard sprawl, so they'll be really thoughtful, about four or five visualizations or ways of extracting insight out of the data that inform the business unit or the business as a whole. Everyone gets really excited about those. They empower users, which I think is a great thing. They empower users to drive their own insight out of the data and pretty soon, instead of 5 or 15 dashboards that are thoughtful, that enables people to understand what's going on in the business, you have 2000 and 2000 dashboards is just as bad as zero.

I think the trick is, empowering the business to really move toward a self-service model with trusted data underneath it, with data that is simple but detailed and specific enough that people can be creative with it and drive answers to their questions. But put a layer of governance around what they're doing, such that you don't end up with a gajillion dashboards in production, that all look at things from a slightly different angle, get different answers about what was my revenue in quarter one, because that will happen.

I think it is the very last bit after you've done the really challenging parts of gaining cultural adoption of data as a strategic asset, is putting some governance around push to production or productionization process of the data assets, such that you don't end up with just unwieldy amounts of dashboards. The other main, I'd say failure mode we've seen is data can and should drive insight for users. A dashboard is not always the best mechanism to drive that insight. I think thinking about ways to meet business users or customers, kind of where they are, and the best mechanism for them to use that insight at the time they need it, that always isn't a dashboard.

It could be completely obfuscated from them. It could be just transforming a workflow on demand based on the situation. It could be embedded inside of an application. I think giving a nod toward and sort of critically thinking about, "Hey, if I were this person or ask this person or test some things out, what's the best way for me to understand and act on the insight, at the time when I need it?" And then build the underlying mechanism such that you are giving them that insight in the way that they're going to most effectively consume it.

Jess Carter: The irk thing, I love the irk thing because you're right, if you walk around any business, somebody's wishing they had data to drive a strategic decision or to go drive their behavioral change and they don't have it, and if you can just scratch that itch, huge buy-in. And then even on the dashboard sprawl, you're excited because everyone bought in, but we got a little bit narrow, everyone just got really excited about the dashboards. And to your point, to think about, how do we drive and improve workflow? How do we drive reduction in waste? How do we drive insights to the business of how we should adapt or change in the next 18 months? What our product should look like in two years, in our industry based on our competitors and the need to change? And so if you think the outcome of a data strategy is just dashboards, we've limited ourselves immediately. It's not a problem, but there's more to it than that.

John Roach: Exactly.

Jess Carter: How hard is this?

John Roach: It sort of depends on the continuum organization that I laid out. To make dramatic improvements is really easy. To get it perfect, is impossible. It depends on that continuum organization that I laid out. In the latter case where you've got a large complex organization with lots of legacy systems and forgive the description, but lots of legacy mindsets. To transform the entire organizational culture to be data driven, is really hard and it's going to take a long time and you've got to be very thoughtful about how you want to do that. And frankly, you've got to be very thoughtful about the ROI you're going to be able to drive from that. There may be parts of the business that it might not be worth the lift. In parts of the business that is absolutely, 100% worth the lift. In that scenario, I would think about tracing way back to the tactics that drive the organization's mission.

I would ask, "Hey, of those three or four things that your organization has to do extraordinarily well, how well are you doing those things and how can and should data play a role in you doing those things better?" And if the answer is, "Hey, we're doing these things, doing one of these things really, really, really well," and I don't think data can help very much, I wouldn't focus your efforts there.

If the answer on the other hand is, "Hey, there's this other thing we really don't have our hands around it and I think if we had this insight at this point and this insight at this point, we could do this thing dramatically better and it's really important to our business," focus efforts there. And sometimes those things are pretty darn easy to do. Sometimes they're harder. Don't think of data strategy as a discrete starting point and end point. Your data strategy needs to be a living thing that evolves with your business, with the industry, with technology, with all of those things. It just needs to be one of the things you continue to maintain, monitor, enhance as you are doing that with your business.

Jess Carter: Thank you so much for your time today, John.

John Roach: Thank you Jess, really enjoyed it.

Jess Carter: Now for the deep dive on developing a sound data strategy, the two experts that you guys are going to hear from are Will Grey, the VP of Data Services at Resultant, and Lori Hotzel, the CIO of the Children's Hospital Association. In their conversation, they're going to discuss the importance of having a sound strategy and the different elements and approaches needed in order to do that.

Lori Hotzel: We are a complex organization, but our mission is pretty simple. We work with our hospitals as champions of children's health, with this pretty strong focus on improving delivery of care. And we do that in multiple ways. We do that through analytics, research, quality of care, education. We have over 65 different programs and products that we work with our children's hospitals to help improving that delivery of care. Currently we have about 220, maybe a little over 220 children's hospitals that we work with in the US and we also have an advocacy and policy arm in our office in Washington DC. A little bit about me, so I've been with CHA for three and a half plus years. I lead the IT Department here. Prior to that, I worked for a large private, for profit organization, they were similar in size to a Fortune 100 company.

Will Grey: I think that's one of the unique things that you really bring to the table is you've worked in almost all sectors and I've really enjoyed getting to hear your stories behind the scenes. Working in a for profit business, you've worked in local government and then you've also worked in nonprofit. Now when I dig into how you realized to start with strategy, when you took on the data analytics program and how you took that to the next level, what were some of the challenges and indicators you saw within the organization that led to you stepping back and ensuring you had the right strategy before you really dived into your initiatives?

Lori Hotzel: Really it kind of started out when I started at CHA, the analytics business lead had a vision of taking and wanting to take their analytics to the next level with some new data visualization capabilities and wanting to get data to our customers faster than we do today, so really in order to see trends, you need to get that data out there too them quicker. This was a great vision and I was really excited when I started to see that they did have that vision coming into CHA, based on my background and knowledge and things that I've put in place before. But, I quickly realized our data infrastructure was pretty dated and probably wouldn't play nice with the new data visualization tools, as you can imagine. That's really where our journey began and defining a new data warehouse strategy was key.

Will Grey: I really love that word journey because it truly is a journey and it's not something that can be achieved overnight and taking a step back and realizing, you looked down the road a few steps and realized, we can't get there with our current infrastructure. How do we achieve this? How do we do this through the nonprofit lens? What were some of the deciding factors of bringing in a third party and leveraging the tool like the SDA to help you define that strategy?

Lori Hotzel: We really recognized we had gaps in knowledge, on the IT as well as on the business side, which is our data owners, so I knew we were going to need assistance in really putting together what I would call a true transformation build out of our new technology foundation that would work with our visualization tool, be secured, flexible, and very high performing in delivering the data to our customers. Moving to the cloud was a bit of a barrier in the past for CHA, just because of concerns around security. We house a ton of sensitive data for our hospitals, so bringing in a third party to help bridge that level of knowledge around security and alleviate those fears, was another thing we thought about. But also sometimes hearing from a vendor that's been there done that, a little tried and true, can make a huge impact on gaining buy-in and we knew we were going to need that going into this.

The SDA also helped in bringing all the parties to the table and defining a more detail of our gaps and our needs and where we wanted to go with the future and our outcomes. But the part I liked the best, it was the technology stack, that the process kind of drove. It was defined in a way that we could be flexible and scalable. We didn't have to go big bang out of the gate and we could introduce new technology as we grow. And as you can imagine with a not for profit, making sure we're not tapping into our pocketbook that hard and heavy from the get go, makes a huge difference.

Will Grey: I love that and I love the intentionality and being a father, our children have been to a children's hospital here locally and just seeing the sensitive and care that you've taken with PHI and PII data, and how intentional you are in making sure you make the right steps around security, and how that's kind of at the core, really makes me feel good. I want to pivot a little bit because you talked about execution. I think strategy informs that execution and the stack we put together really allowed it to I think scale beyond where you originally were wanting to point. And so I think there's a lot of different possibilities out there, but when we focused about how we ensured that the data was right, we built trust in the data, it got some early wins. Could you give us some thoughts on how you laid out that execution plan and maybe a little bit of the why behind it?

Lori Hotzel: The first part, as you mentioned, we really needed to get our data right. We have stakeholders in our organization that have spent years and years, really getting our data to a trusted state and we wanted to make sure we didn't compromise that trust in a new environment. I knew we'd have to continue to make sure that that was a priority and focus on the trust of the data and the components. But if you don't focus on that, then the rest doesn't matter. It doesn't matter that you've got technology up and running, if people don't trust in the data, so that had to be a first focus.

The second part came a little fast and furious, faster than we thought. But the good news was, because we spent so much time up front, our analytics business leader was very confident in the technology and created a new initiative to move data processing, which was previously done by a third party to us processing it in house, which is a lot of data that we run through our system on a quarterly basis, as I mentioned, and soon to be monthly.

We were going to do a smaller proof of concept to start. Obviously that's where you want to start and make sure it's right, but we had some financial drivers that really move this to the top of our list to focus on. We spent a lot of time up front, coming up with a strategy, what our methods were, what our outcomes were. Because we spent so much time on that upfront, we were able to gain buy in on doing such a large initiative out of the gate. It really allowed us to move very quickly through the implementation phase for something that level of initiative.

But the third part is around how we move from our old analytics to our new platform. Again, we wanted to make sure that the platform was flexible enough that we could do that because we've spent years filling out these reports and not everything make sense to go into a data visualization tool, and it's a bit of a paradigm shift that you really want to think about. Again, the plan has really made it to where we can evolve and move things as we need to and want to in the new environment while maintaining our current customer base.

Will Grey: It's been great to watch that execution unfold and in how the organization's matured in the capabilities throughout that. Organizations measure success in different ways. Can you share with the audience a couple of the successes that resulted from the journey CHA has been on?

Lori Hotzel: We saw some gaps in the knowledge going into this. I have, and you mentioned this, a great, very smart database team that has been able to execute on our plans and initiatives very quickly, and this was new to them. But again, as you mentioned, we've been able to do this in two years and it's been a lot in a short amount of time. Just as a reminder, having very smart and capable staff is really key to all of this as well.

But overall related to the SDA process, it set us up for success because we took the time to lay out the strategy and then the results really drove more than we were expecting. Not only improved data processing, but it created a better user experience for our data submission from our hospitals. They really love how easy it is, how they can follow it through the process and basically can then just walk away. This also set us up to move to the monthly. I think I mentioned we wanted to get data out to our customers quicker, so it allowed us to move monthly data refreshes versus quarterly. Obviously, the more frequent you have data, the better you are at seeing trends and driving quality of care.

Speaker 10: One question that we do have is, is it sometimes hard to show ROI and time to value? What does the exec team think about the progress so far?

Lori Hotzel: Yeah, that's a great question and that's always foremost in my mind is, how do we show our ROI and how do we show it quickly? Again, when we're spending financial investments, we want to show that ROI very quickly. It's a bit challenging, but I would say because we put together the strategy, people could connect to it very easily. And like I said, we spent a lot of time getting the business buy-in, the data owner buy-in. They were excited about it, so it wasn't just coming from IT saying, "Hey, we need to do this, we need to spend this money to stand up a data warehouse and trust me, all of these wonderful things are going to happen."

I would say definitely the buy-in, it wasn't just the financial component of it, but it was we showed how we were going to create more value for our hospitals and how they were going to make better decisions as well as getting the data to them quicker. We had some pretty strong, I would say use cases to share with our executives to get them bought into the vision and the mission and they're very excited. In fact its, can you go faster, as it always is. What we're continuing to work on is how do we get some of this stuff out faster?

Will Grey: Just to add to that, ROI, I find can be one of the most difficult calculations to really get because you don't know, you implement something like a data warehouse or a data process and then all of a sudden you don't know who's picking up the data or where. And it's very hard to collect those use cases where it made an immediate impact. And so the excitement of, I want more and more, often tells you the value is exponential to what you've put in, but it's really hard to see that. And I know your hospitals have been very excited about the work you've done and especially bringing in the process in house. I think you've had some pretty tangible ROI though just from a savings standpoint as well.

Lori Hotzel: We didn't realize it going into it, but once we started that initiative, moving the data processing in house, that was a $2 million savings. Again, we did have some pretty good use cases to get buy-in from our executives to move forward.

Speaker 10: Did you have to build a business case to bring in a consultant? Any advice on how you build that case?

Lori Hotzel: Yes. We had to have a business case. There had to be a why behind it. Like I said, the biggest part of the business case was defining those use cases. What are we going to do? Why are we doing this? Why are we spending money on this? Why are we spending money on it now versus later? I really wanted to focus a strategy on not just a big bang, how can we evolve this and grow and show them that we just want to start with this, but we are thinking about the future.

That was a big part in the business case, that the executives really appreciated was I wasn't looking at it just at a big bang, that I was looking about, here's where we are today, here's the next step, here's where we want to be in the future. Again, it wasn't such a huge hit on the pocketbook from the get go, but obviously they want it done right, so they also wanted to make sure we were thinking about it in the future, so really laying that out as well as the business cases. I'm fortunate in that our executives work closely with the hospitals so they hear a lot of what our hospitals are wanting from us in our data analytics space, so it was kind of easy to get that buy in, of moving in that direction for that purpose.

Will Grey: One thing that I think is, it was very interesting and it really kind of clicked for me is, you had a clear value proposition and you had a unique approach to how you wanted to achieve that. And I think you were willing to make some clear trade offs. There was things that you were able to deliver today that you are not sure you could deliver at the same level that you were used to, but the trade offs of what a modern BI system gets you, you saw that and you were able to convince people that, it's worth getting on board because it's going to allow us to do X, Y, or Z that we can't do today. But you have to change the way you shift your mindset around that and you're continually thinking about how to improve on what you're doing, hence how you have implemented the hub from a table visualization standpoint. And so I love how that strategy is continuing just to come together and really push that to the next level.

Speaker 10: Another question is, how soon were you able to see the impact of your new strategy?

Lori Hotzel: Really pretty quickly. Obviously it takes time to implement the technology and get that stood up and get the data formatted into the new environment. But, within the first year we were seeing benefits, especially when we went with that initiative to move the data processing in house. I know it doesn't sound big, but it's a lot of data. Getting unique IDs to line up is really a tough job in the hospital space because each hospital's very different. Even though it took us a year to implement, really considering where we've been in the past, to be able to do that, at that level, that quickly, our executives were very impressed with.

Will Grey: And just to piggyback on that, I think what was really amazing is the system that you were replacing, had been used for 15 or 20 years and so it had such a longstanding history. To replace that process in a year, it's a monumental achievement and I thought that was really cool and it had such a clear value proposition to it, to make sure it was very deadline focused. I know both teams had some late nights getting that across the finish line, but it's really fun to look back and see the success that was created from it.

Speaker 10: What were some of the biggest hurdles you faced with your data transformation? Did your strategy help you overcome them?

Lori Hotzel: I'm not sure the data strategy helped us get through the challenges. I would say the data strategy made sure we thought through most of what our challenges would be, but obviously when you get into implementation, there's more challenges that you just can't think of, that we had to face. Some of that being we're bringing over this data processing and moving it to monthly, Well, there's a lot of business processes that have to change along with the technology.

And so there was some challenges and timing of that, so you've got the technology and then now we've got focus on the business process side of it, so there was some challenges there. And then just understanding how our vendor was processing the data, how are we going to process the data and learn from that. There was no documentation to go from. You can't ever predict that in a strategy, that you pretty much know going in, there's going to be limited documentation. But the fact that it was really limited documentation, was a pretty big strategy hurdle we had to get over.

Will Grey: And you assigned a really strong project manager from your end to it, and I think they did a...

Lori Hotzel: Strong is a great word, Will, really.

Will Grey: But, they did a really good job documenting risk or ensuring at least pointing out, I hear this in a meeting, that's a risk, and then chasing down what is. If that comes true, what is the mitigation strategy, we're going to use that. And I think that part of execution is very crucial in making sure that you have the right teams and having strong internal project management to work with a third party vendor's project leadership, to ensure that that gets brought to fruition, is key. And that person was successful in chasing down the right people on your side, that maybe doesn't always have the time to answer or respond, to getting the right answers, because everybody's so busy and if you're not on the core project team, it's not always the core focus.

Lori Hotzel: That's a huge challenge. You've got an internal team that's still focusing on their day to day jobs and maintaining. You're right, you got to have a great project manager and in our case, we were lucky, we didn't have just a project manager, we had a project leader and somebody that wasn't afraid to hold people accountable to getting their tasks done on time.

Jess Carter: Thank you for listening. I'm your host Jess Carter, and don't forget to follow the data driven leadership wherever you get your podcasts. And rate and review us to let us know how the data topics are transforming your business. We can't wait for you to join us for the next episode.