Data and analytics offer tremendous opportunities to deliver high-quality customer experience and drive business success. However, enterprises must navigate numerous challenges to unlock their value, from ensuring data quality and consistency across multiple sources to finding skilled talent and implementing effective data governance. Several hurdles must be overcome, including technical infrastructure, data privacy and security, resistance to change, and measuring and demonstrating value.

So, how are enterprise leaders measuring and demonstrating the value of data-driven initiatives and realizing strategies for overcoming these obstacles to leverage data and analytics to empower high-quality customer experience effectively?

Watch this webinar to get answers to the pressing questions, including:

• How to measure and demonstrate the value of data analytics to stakeholders?
• How to overcome resistance to change and cultural barriers hindering the adoption of data-driven approaches?
• How to determine data storage and processing power requirements for analyzing large datasets?
• How to ensure data quality and consistency across multiple sources?
• How to find and retain skilled talent in data science, machine learning, and artificial intelligence?
• How to effectively integrate data analytics with business processes?
• How to implement effective data governance processes and policies?
• How to safeguard data privacy and security while adopting data and analytics?

Contributors

• • Abhi Seth, Chief Data Officer, TE Connectivity
  • Shawnna DelHierro, Chief Information Technology Officer, Sportsman’s Warehouse
  • Sha Edathumparampil, VP Digital Tech/Chief Data Officer, Baptist Health South Florida

Transcript

Sanjog Aul [00:00:28]:
Hello and welcome to the CTN webinar. The topic for today’s discussion is empowering high quality customer experience with data and analytics. And thanks to Luminar who have made this webinar possible. My name is Sanjo Gaul. I will be your host and moderator for this webinar. Now, quick housekeeping. Please keep your microphones muted currently to help minimize any background noise. Who server is speaking when they’re not speaking, that that’s what they should do.

Sanjog Aul [00:01:01]:
And that’s for panelists. And sometimes even the attendees would also be unmuted to provide their inputs. And then at the end of the webinar, since we will try to all work hard to make this valuable, please share your experience by completing the feedback form which will pop up. Now, before we get started on the beautiful journey of how you create customer experience during the user, the data and analytics, let me ask very simple question. By show of hands, how many of you like ice cream? All right. My God, I got almost everybody saying I like ice cream. All right. Awesome, awesome, awesome.

Sanjog Aul [00:01:42]:
So now the second question, I’ll try to connect the dots. So imagine if you had your favorite customer experience and it was supposed to be mapped to your favorite ice cream flavor, or it was to be seen as an ice cream flavor. Which flavor would you pick and why? Just share with us on chat so that’ll help. And then that is what we would like to talk about. And while you’re sharing your insight, I’ll tell you. Why am I even saying this? Because, see, like with ice cream flavors, each of us as customers have our own preferences when it comes to our experiences. So how does one understand that you as a customer, needs to be offered that unique experience or that key ingredient or set of ingredients which will make that experience most unique and enjoyable? Well, you can use data and analytics to be able to do some churning and figure that out. But then, is that enough? After you having that data and or insights pulled out, what do you do with it? How do you get your people, process, policy, pocketbook, budget, culture, leadership and tech all come together to deliver that experience? And frankly, the way we have heard and all seen customer experiences is a living organism.

Sanjog Aul [00:03:16]:
And you cannot claim that today you gave an amazing experience. Tomorrow is going to be the same. So what do you do to come as close to giving a good, consistent experience? Showing them a movie of good experience versus a snapshot of wow and then a dud? That’s not what is called good customer experience. But how do you do that? How do you keep it consistent? How do you use data and analytics, and how do you empower this whole journey of customer experience using data and analytics and many other elements that I spoke about? Well, I have three ice cream artisans with you. Okay. They have got a great capability, great background who are going to help discuss. And frankly, we will also be inviting a lot of people from the audience members to join in. So I have Abhish Sheth, who is the chief data officer with te connectivity.

Sanjog Aul [00:04:08]:
Hey, Abhi, how are you? Awesome. And we have Shawna Delhiro, chief information technology officer with sportsman Warehouse. Hey, Shauna, how’s life?

Shawnna DelHierro [00:04:21]:
Hi there. Very well. Thank you for having me today.

Sanjog Aul [00:04:23]:
And we have Shah Adatum Parampil, who’s the vp of digital tech and chief data officer with Baptist Health, South Florida. How are you, sir?

Sha Edathumparampi [00:04:34]:
Very good. Great to be here, Sanjay.

Sanjog Aul [00:04:36]:
Great. So what we will do is, of course, as a format, what we’re going to start doing is going to start with a challenge inventory. Let me explain what that is. Our goal is to have the panelists and also the audience members share their top challenge. You may have many, but just your top challenge, which holds you back from delivering amazing customer experience and consistent one while leveraging data and analytics and even other elements. So we will start with that. And once we have spoken about that set of challenges, then we will not talk challenges anymore. We will switch to the brainstorming and solutioning mode to see what has been done to solve, to solve those problems that are considered to be the top challenges by each person who reports it, and then what is making it still a problem.

Sanjog Aul [00:05:31]:
And if that’s a snag that they’re hitting, we got to all step up and share our suggestions to help move forward in solving that problem a little more. So, if this is going to be a great format for us to create some actionable insights and meaningful takeaways, my request will be for all of us, our panelists and the audience members to please actively engage. Now, with that said, let’s get started. So, Shauna, why not we start with you. Give us a quick background about yourself and your organization so people understand the context, and then share your top challenge, which is giving you the most heartburn in the context I just explained.

Shawnna DelHierro [00:06:13]:
Sure.

Shawnna DelHierro [00:06:14]:
So, hello, everyone. Again, thank you for having me today. I’m excited to share a bit of what is going on in my world. As mentioned, I’m with Sportsman’s warehouse. Sportsman’s warehouse is an outdoor retailer. We focus on hunt and camp, outdoor activities, fish, hike, etcetera. We have 136 retail stores across the US and growing excited that we have a lot of challenges. I think for all of us, I think everyone on the call would agree that some of that breeds job security and some of it’s just exciting to see times changing.

Shawnna DelHierro [00:06:55]:
I think for sportsmen, having been an organization that has grown pretty quickly and then lived through Covid and then it’s been kind of a soft year in retail. I think much like a number of others, we have this goodness of data, but it’s pocketed and we have where it sits, whether it’s in our retail store or it’s in an e comm database, or it’s in some loyalty or some warranty information. But bringing those together, I think is probably one of our greatest opportunities and challenges. With that, there’s also the need to further explore and vet out where we’ve got some tech debt and some back office systems that haven’t been given the time, resources or attention to really bring them the course of where we need to be today. So addressing those things, getting the first things first lined out in an order, and really seeking to understand what it is that our customer expects of us and how we can best serve them by aggregating their data effectively and having that at a point where we can be good stewards and good customer service agents.

Sanjog Aul [00:08:03]:
Shah, what’s your. Give us your background, of course, and love to hear about your top challenge.

Sha Edathumparampi [00:08:10]:
Once again, thank you. It’s wonderful to be here and to meet you all. I have Shahida Kumar. I work for Baptist Health, which is a hospital system, healthcare system in south Florida, and we operate about eleven hospitals and well above 100 urgent care locations and so on. From a challenge perspective, taking a step back, today’s consumer is really spoiled. If you look at the ecosystem, there are some truly great consumer experiences out there. Amazon, Apple, you can name quite a few of these. But when you think about healthcare or your last doctoral visit, chances are that experience does not align with the experience that you have seen elsewhere in other industries, such as the ones that I.

Sha Edathumparampi [00:09:01]:
Some of the names that I mentioned, and there are lots of reasons for it, but a big part of it is the lack of focus and investment, perhaps into building the capabilities, technology and digital is one part of it. But just being able to focus on consumer experience and building the right solutions and features for them I think has been a challenge for us. Now, underlying that is obviously needing the right infrastructure, processes, practices, strategy, leadership, funding, all of that. Specifically from a data perspective, healthcare tends to suffer from, and this is true for practically every system out there. Suffer from not having the right data culture, which is for people making decisions based on opinions and as opposed to data. And they’ve done that for decades and decades. So it’s a hard sort of shift, if you will, in mindset to move from that to being data focused, focusing on consumer, being consumer focused and having a data oriented culture and everything that is necessary to build that. I think those are sort of the challenges that I see in healthcare today.

Abhi Sheth [00:10:21]:
Abhi hey, thank you for having me here. Sanjuk, and really, really happy to be able to speak today on this topic. My name is Abhi Seth and I am the chief data officer for Te connectivity. TE is a $16 billion company, global company. We serve across many different industries, all the way from automotive to sensors to appliances. A Te sensor, you can find it all the way from a coffee maker to the JM telescope that went up and all kinds of electric vehicles. So we are everywhere. And as a matter of fact, I think as we look at the diversity of industries we serve in, we are serving multibillion dollar customers.

Abhi Sheth [00:11:08]:
And then we are working with Diyev, individual startups that are actually trying to get some of these electronic components and build the next new product, next Apple Watch or next iPod or whatever that might be. How do we make sure that we are able to partner with them and understand their very different needs in terms of the skill at which they need the product, the innovation that they need, the application, really, truly a very different variety of application that they need. And it’s really understanding that and being able to respond to that. Plus the other interesting thing we do is we have a lot of better customers and then we sell directly to customers and through distribution. And that makes it even more difficult for us to. How do we have different layers of customer interfaces? I would say so in terms of the biggest challenges, I think. I would say the big challenge for us is really getting into that holistic record of the customer. I think being able to talk about, I think Shawna mentioned some of the technology dead side.

Abhi Sheth [00:12:16]:
I think we are getting into, it’s an interesting time for everybody in data and digital because we are all starting with everybody has an oracle or a SQL server somewhere and a lot of the stuff still happening on Excel. And then we are getting into generative AI and everybody wants to, wants to talk to a chatbot and get all the insights on their fingertips. And I think it’s really about trying to educate the masses that, hey, you can have generative AI, but if you don’t fix your data foundation, you might get five different answers to the same question. And it’s really more and more important, because if we want it or not, we’ll get pushed into this not just predictive, but generative AI space. And at some point, I feel like the time to fix the data and the stuff we have been talking about for the last ten years, you know, it’s going to be behind us.

Sha Edathumparampi [00:13:04]:
Right.

Abhi Sheth [00:13:04]:
I think it’s time to move on to the next generation of AI. And for that, we really do need to address the technology there. The other aspect, I would say, is really, I think there is a lack of understanding. You know, I think, Shah, you mentioned data culture and medical, and I understand that, but there is a lack of understanding who owns the data? You know, I think everybody wants to use the data, but I think very few people is like, data and environment. I kind of feel like the same thing. Everybody wants us to be green and everything to be clean, but who owns the responsibility to, you know, pick up the mess, right. And understand what their contribution is in sustainability? Are you throwing the right box in the recycle bin, you know, or not? And I think that’s kind of where it starts, is educating, making sure that not just the technology side of that data foundation, but also the process side and the people side is really addressed and matured. And I think the good news there is, I think I can tell you about Ted.

Abhi Sheth [00:13:59]:
I’ve been here three and a half years, and the amount of momentum and pull around data has exponentially changed. And the amount of awareness in the top business leaders and functional leaders understanding of how data is really the root cause and we must invest in fixing it is also changing rapidly.

Sanjog Aul [00:14:22]:
Thank you so much. Our panelists have spoken about their respective challenges and given a background, but I would love for audience members who would like to also share their top challenges. Please raise your hand so I can invite you to talk and share about your challenges first. And as you share those challenges, also type in in the q and a box so that we also have a record of what your top challenges are. So who would like to volunteer from the audience members who have top challenges and they would like to articulate. All right, I’m going to have Shravan Ericola. So, Shravan, you are unmuted. You can go ahead.

Sravan Erukula [00:15:08]:
Okay. Hello. Can you guys see me?

Sanjog Aul [00:15:12]:
Yes, we can. Thank you.

Sravan Erukula [00:15:15]:
Hey, so my name is Shravan, and I’m the director working in Nehman markers. For those of you who don’t know much, it is a luxury retailer company that has over $3 billion operating income and revenue. And so one of the things where I kind of manage is customer data platforms, building a golden card. We are talking about, you know, different, different people talking about some other, you know, disparate systems and siloed systems managing their own data. And we are kind of focusing on building the centralized solution for all the customer data that is coming through the different source system. And at the same time, I am kind of focusing on building a customer 360 view, essentially anything and everything that we need to know about the customer. And the third part of that is leveraging the data analytics and insight to power customer client engagements. So that is something, you know, we’ve been trying to do that through the personalization, and we are using a lot of those AI ML, some of those algorithms to kind of power some of those recommendations.

Sravan Erukula [00:16:40]:
But one of the challenge where, you know, having trouble is how to scale the personalization, how to kind of connect with the customers seamlessly across channels and at a faster pace. So again, if you guys look into the experiences, there are different, different teams work together to make that happen. We have front end teams, we have some of the middleware teams, and then the back end teams where I’m having, you know, there’ll be challenges. How can I, you know, build a scalable personalization solution that could be expanded to any channels. It could be call center, it could be, you know, ecommerce site, or it could be, you know, mobile apps, or it could be email wherever. You know, I want to make sure that we are kind of looking at leveraging the data analytics and insight to kind of power those seamless experiences, the clients in a much faster fashion in a larger scale. I think that’s where, you know, I’d like to kind of hear some thoughts in terms of how that is something, you know, if you guys have done anything like this, you know, I’d like to kind of hear your thoughts on that.

Sanjog Aul [00:17:55]:
So we will talk about, thank you so much for sharing the challenge. And Shravan, do me as, do us a favor, put your actual challenge on the chat, like the q and a. So we’ll have a log of that. And of course, we’ll come to it when we are going to go through the solutioning. Cynthia, we’d love to have you share your thoughts.

Sravan Erukula [00:18:13]:
Sure.

Cynthia Barbarino [00:18:13]:
Thank you very much. I am a chief data officer at the University of North Carolina at Charlotte, and I’m tasked with implementing a completely new, fully integrated data and analytics system. As soon as I endeavored on that path, clearly it became a pretty significant task. And the reason I’m saying that is because I’ve been in supply chain, I’ve been in manufacturing, I’ve been financials and built analytic systems that support that activity, customer base, that kind of thing. In higher ed, it’s a very different beast. It’s a different beast because if you’re in a university with multiple colleges, you’ll generally find that each of the colleges operate independently. So unlike a major corporation, or let’s say, what was it, sportsman’s? Was that paradise? All of the stores are pretty much the same in college. They all run differently.

Cynthia Barbarino [00:19:29]:
And so one of the challenges that we’ve had to, or that I’m facing right now is, to the point made earlier, truly not only identifying who owns the data, but more importantly, who’s willing to step up and maintain that data, which is the point that was recently made. We have that issue where today, and it’s been the culture for many, many years, that it takes care of everything. And that’s where the solution that we endeavor to finally select needs to be as much focused on self service as it is on ensuring that we have the proper controls in place behind the scenes and the data governance side. Just getting the buy in that we had to go in that direction has taken, I’ll say, two years just to get the funding and the budgeting and move forward. My quandary, if you will, is that while we’re aware that there are data quality issues, the actual action of having or convincing certain leadership streams to understand that not only do they own the data, but they also are responsible for assisting in improving and measuring the data quality. And it’s that separation of it can give everything that you need in terms of information, but we cannot make your decisions for you. And I think we all have that challenge where it depends on how far our customer wants us to go versus how far we really should go.

Sanjog Aul [00:21:27]:
All right, great. So we also have Rajeet Waratante, who actually shared it over chat. So he said his challenge is that suppliers have to service multiple customers who are on different journeys, on how they can accept data from suppliers, that is, data entry in customer portals to API, and how to influence customers to become more advanced in their journey, or come up with a solution that allows supplier to service all methods of product exchange. All right, now with that, I’m going to take one last challenge from Pramod. Pramod, you’ve been unmuted. Please go ahead and share your challenge. Pramod, are you able to unmute yourself?

Pramod Pillai [00:22:14]:
Sanjoy, good afternoon. Can you hear me?

Sanjog Aul [00:22:16]:
Yes, we can.

Pramod Pillai [00:22:18]:
Yes. Hey, good afternoon, team. My name is Pramod Pillai. I am a director, it director with the professional services firm called infovision. And my question, or some of the challenges that when we go do some of these data implementations are around data duplicates, right? So whether in retail, you have, like, customer data duplicate, and if it is commercial real estate, you know, you have properties, duplicate properties, and over a period of time, 1520 years, there is a lot of these duplicate data. And it’s one of the challenges that I’ve been thinking about, like, how do we. How do we effectively solve for this? I know, of course, we use the different algorithms we can use. There’s AI, ML.

Pramod Pillai [00:22:57]:
But I’m very curious to understand from this team over here, do you have any experience in it comes down to data quality. Do you have any experience in data duplication? What has worked well for you in your scenario? I would love to hear from you guys.

Sanjog Aul [00:23:14]:
All right, good. Thank you so much. These were a lovely set of challenges. Now, coming back, Shauna, to you, let’s go to your own challenge and like to very quickly have you share what specific things that you’ve tried to do, given that it’s your top challenge. So I’m sure you put time, energy, dollars towards it. What all did you try and what worked, what did not work, and where are you truly stuck?

Shawnna DelHierro [00:23:37]:
Yeah. Thank you. And thank you. For those who also shared, as our attendees today, I think it’s interesting to hear the different perspectives and different challenges that existed. Where I would kind of share a bit more is I started here with Sportsman’s at Black Friday. So at a peak period of time, it is absolutely our highest sales volume and our highest store traffic, which coincidentally now has resolved to be our highest in e commerce traffic as well. So, as I look at coming in, and one of the reasons that I came here was to really to kind of lead a transformation journey and to take us from where we’ve been in some data and legacy systems and processes, or the lack thereof and some absence of rigor and operational structure, to get us to a point where we had a more unified position in how we move forward in meeting the customer where they are. I think Shaw had a great point earlier as we were talking.

Shawnna DelHierro [00:24:44]:
We do we have a little bit of spoiling of our customers that we are trying to be the one size fits all. And I think that while that is great by intent, I think it can become incredibly challenging and can become a blocker to even good, let alone great. So for us, as I look at our data landscape, look at our organization and what we have is our enterprise level goals. When we talk about one specifically around grow omnichannel, well, what are the challenges that we have and what are the issues that arise from a data and analytics perspective? Again, going back to the disparate systems, but I think it also comes back to not having a clear measure or clear method for how we collectively as an organization, want to move forward. I appreciate one of the comments earlier about all of these different business models within a higher education model. There’s a different approach, there’s a different methodology, and perhaps even a different need. And I think for us, there’s some of that in the retail space. I think being able to operate despite weather, being able to operate despite other macroeconomic impact or factors, getting to the basics of everyone organizationally, understanding that this is what our roadmap is, socializing, that giving others an opportunity to weigh in so they can more effectively buy in to what we feel as though are the pressing needs from a technology standpoint.

Shawnna DelHierro [00:26:16]:
But also how do we then better expose that data more real time so they understand exactly what’s happening, whether it’s in the customers seat, whether it’s in the associate seat in the retail frontline area, or whether it is within, you know, the more corporate back office system and structure. So I think for us, it was just kind of taking that first step first. And what is it that we can do to present a unified platform and a source of truth for data to be visible, and then really kind of surveying and scouring the landscape to say what, what data is relevant to you? What helps you to be a driver of your business vertical? And then how can we, from a technology standpoint, be more effective in the way that we stand up a system or a platform or an availability, whether it is leveraging an AI solution or a legacy API call for just the data availability, but getting there to where our entire enterprise understands what we’re seeking to achieve and is aligned on what that method is going to be so that we can have something effectively measured.

Sanjog Aul [00:27:22]:
So is there a snag you’re hitting? Or would you say that if you kept doing this and if you did the same webinar a year from now, you’ll say, okay, we are singing Kumbaya, everything is awesome?

Shawnna DelHierro [00:27:32]:
I would love to say that in a year from now that would, that would be the case? I think every day there’s a new, you know, there’s something that comes about that’s new in the way of, you know, opportunity. So I don’t think that that journey is ever quite finished or complete. I think it’s an ongoing evolution. What I would like to say is that if we stay the course with the consistency in the model that we’ve all aligned to, my hope would be that we could have good demonstration of progress and that we’re putting data in the hands of those that can use it to drive us to be better. I think historically, if we were to look back 10, 15, 20 years, there was this idea, especially if I were just to look at where I sit in retail or even where I came from in healthcare, we have these drivers that sit in a big high rise somewhere, and then we have these operators that are expected just to go and to do. And I very much don’t believe that to be the case. I think that we have to engage people end to end throughout our organization, whether it means that you sit in payroll or you sit in distribution or you do sit in the retail space or technology to understand how they are contributing to the overall bottom line, but more importantly, and the efficacy of relationship that we’re driving with that customer that keeps them coming, coming back. And so I think data is critical to that and being able to have that in their hands.

Shawnna DelHierro [00:28:57]:
You know, again, we have systems that are dated. I can’t have them hitting those systems to get real time information, nor do I want them to. I want to give them the data that empowers them. So I believe that, yes, we’re on the right path forward. I think that there are a lot of things that we will mature and that we will shore up as we go. But I definitely think getting, you know, just, you’ve got to start somewhere. So it’s drawing that line in the sand to say, this is the way that we’re going to go forward. Does everyone agree? And then pushing ahead, recognizing that you’re going to have some, you know, some bumps in the road, but staying the course of that without allowing for that to be the big blocker that prohibits you from progress.

Sanjog Aul [00:29:36]:
So, Shah, your journey, of course, somewhat similar and or different flavors, but I know there is always complexity. It’s always like, you know, I use two analogies. One is changing tire off a moving car or building the plane while you’re flying it. Which one is more appropriate for you?

Sha Edathumparampi [00:29:56]:
I think both to some extent, because there is obviously the industry transforming as we are doing it, plus we are transforming within it ourselves. So that brings up some very interesting dynamics.

Sanjog Aul [00:30:11]:
So when you shared your challenge and where you’re stuck and or not stuck, but it’s still a journey. How would you define it? Is it a leave it to God problem or something you can do something about?

Sha Edathumparampi [00:30:22]:
Well, that certainly is not so. Look, so I have a dual role. I’m responsible for building out digital capability, digital consumer capabilities, and I’m also the chief data officer. So in many ways, my teams are, some of my teams are consumers of the data products that the other parts of my organization builds or provides. And I talked earlier about one of the challenges being the culture of data, right? So that really comes from, in my mind, roughly three things. The lack of data oriented culture in an organization comes from, first of all, access to data. Are you able to easily get your data? Second, trust in data. Is this good quality data? And then number three, the usability of that data.

Sha Edathumparampi [00:31:09]:
So if you have to spend hours or call people to understand the data, then there’s a, there’s a problem. So, and I guess this is true for most industries, but others may have had a head start compared to healthcare in terms of solving some of these things. So we set out from a data strategy perspective to address those things. There is obviously a technology element that supports all three of those, which is to have the right technology platform, which is scalable and reliable and performant, and has the ability to plug and play all of these new capabilities as and when those become available, everything from generative AI now to other types of analytics before. So we set out to address those three challenges, or broke the overall challenge down to those three and set out to address this one was we started building this data platform that has, which is obviously new technology, cloud based. It lets people get to the data much more easily in the sense that there are no restrictions in terms of how many users can connect to. So there’s trivial things for addressed and taken out of the way. The other part of access is even knowing where your data is.

Sha Edathumparampi [00:32:24]:
So we have things like, we implemented things like data catalog that makes it easier for folks, anyone within the company, to be able to understand what assets, whether it is just data sets or existing dashboards or workbooks and reports and so on and so forth. So a catalog. So between the platform capabilities and the catalog, we are on the way to on our, we’ve started a well into our journey to address the access issues. The second is the trust aspect of it. So you have to have quality controls implemented as part of your technology platform and framework as and when the data comes in. So you have the ability to understand what the issues are and quickly address those quickly may not be immediate, but at least knowing I various issues are, gives you the option, gives you the ability to go back and address those. So we have automated pipelines, monitoring, alerting with the right users or user representatives, getting involved early on in the cycle, and then having a process to remedy it relatively quickly. So that’s the trust aspect of it.

Sha Edathumparampi [00:33:32]:
There is also another factor which is obviously, we cannot overstate the importance of security, data security. So you have to overlay that aspect also into the trust aspect. But I think, all said and done, the thing that makes the biggest those items are foundational, but the one that makes the most difference in terms of helping people use data, whether it is the consumer or internal stakeholder, is how quickly or how easily, how usable is these systems that you have. For instance, you can have a report that has 100,000 cells or an excel file that has 100,000 cells, or you can visualize the data in a way that is intuitively easy for folks to understand, whoever is looking at the data or the point of use of that data. For instance, let’s say a physician in our environment who uses electronic health record system essentially all day long. If that person then has to switch context and go to a separate reporting system or a dashboarding system, then that causes friction and it prevents or it reduces the level of adoption that you could otherwise achieve. So that last mile of usage or usability for users is critical. We are addressing that by making sure that the data that is trusted and easy to access and so on.

Sha Edathumparampi [00:34:57]:
But it is also presented in a way that is closest to the point of use. So those are some of the things that we’re doing now. Those are still foundational. You also have to change the mindset and the culture. You really have to get them excited about the future. What can you do with all this in place, which is where taking these relatively small but meaningful bets around using new technology, whether it is, I mean, generative AI is all the race now, there are things that you can do, partnering with willing, enabled stakeholders within the organization to prove some of these new and advanced uses of data and show them the benefits in a highly quantified kind of a way. It could be that you reduce the amount of hours someone had to spend filling documentation or amount of time a patient had to wait to get in. We have things like from a consumer experience perspective, we’ve plugged data all the way in to show wait times forecasted and current wait times at our urgent care centers.

Sha Edathumparampi [00:35:58]:
So that aspect of usability making it really, really easy to consume. The data, I think is a big part of our effort. And so far it’s been going really well. We’ve this journey for almost two years now. We have a number of capabilities that are out in the market through digital channels to consumers as well as to internal stakeholders. It seems to be going well.

Sanjog Aul [00:36:21]:
Awesome.

Abhi Sheth [00:36:22]:
Abhi, I would say, I think.

Abhi Sheth [00:36:27]:
To.

Abhi Sheth [00:36:27]:
Your earlier point, I think a mini Kumbaya every day is the goal. I think you can’t have one big one and wait for it for five years. I think that’s the key. Some of the challenges I outlined, I think is really more focused on technology and data. But again, as I said earlier, I think our customers aren’t waiting for us for three years to go fix the data and then come back and get the experience. They’re all to Sha’s point, you know, getting spoiled one way or the other. And they want, you know, they expect that and especially in the digital age. So some of the things, and I’ve been here three and a half years, so some of the key things we have tackled early on is really, you know, simplifying our architecture.

Abhi Sheth [00:37:06]:
I think as we look at, as we look at technology that we all talked about it, I think it’s really about thinking enterprise architecture end to end and then thinking the flow of data from the beginning to the consumption point. Either it’s for the internal stakeholder or for the customer trying to figure out what is your order status or my delivery date is. And how do you make it seamless. And thinking about your systems like SAP, a lot of people are going from SAP, from pr two to s four. Everybody’s going through that journey as we speak. So how do we really use that as an advantage to simplify? Because SAP is such a big element in all of our data journeys that if we, this is kind of one of once in a lifetime golden opportunity to address a lot of those issues as we go do our SAP upgrades. But then at the same time, there is other operational system. So the challenge with the was really more around.

Abhi Sheth [00:38:00]:
We have a lot of analytics teams across ten business units. Everybody’s downloading data from SAP or different core data publication systems, doing their own analysis, taking them to the business leaders, and then suddenly the data doesn’t match right. And then you have this, you know, I don’t know which number is right, and then you get into that debate. So in three years, we have kind of addressed a lot of that by consolidating most of that data into a single cloud platform. So we launched our cloud platform around 18 months ago, right. And then we have actually dragged and we weren’t sure if this is the right way to go, but we knew this is the right thing to do. So we have consolidated, brought in and created a governance team. So similar to what Shah was talking about, really, I think having around 40,000 data elements cataloged, data definitions put in place, master golden records for customer.

Abhi Sheth [00:38:53]:
Again, it’s not holistic and we are not there yet. This is not, again, about Kumbaya, but about getting towards the right direction. What we have seen is, as we launched our cloud platform, you know, we quadrupled our data users, right? And I think a lot of people actually, they were. It’s about make the, make the right way, the easy way, you write. I think that’s kind of the philosophy. So everybody was struggling through getting to the right sorts of data, building this report, and there was no visibility. We’re trying to solve the same problem ten different times now. We are, with this cloud platform, we are able to have multiple business unit teams, you know, solve the problem, and then we are using reusable architecture.

Abhi Sheth [00:39:33]:
So the cool thing about that is if one business unit solves problem around the cons, receivable or customer attribution or something, we are able to now quickly deploy it to nine other business units. And they can actually, no matter where the innovation comes from, it doesn’t really have to come from the hub team, it can come from anywhere. And then you can actually reuse that innovation across the board, which is pretty cool. So we are able to now scale analytics because of that, we are able to quadruple our users. I would say our data value has gone. So we track data value which is attributed OI, which is approved by finance. So that has actually gone up, I would say, 30 times than what it was four years ago. And so we are definitely doing the right things, and then ultimately, I think, picking the right problems.

Sha Edathumparampi [00:40:22]:
Right.

Abhi Sheth [00:40:22]:
So instead of convincing everybody that this is the right thing to do, we gotta show it, right. And because seeing is believing, at the end of the day, nobody wants to do data or digital, because that’s the right thing to do, because we really want to see the business results. So it’s really being purposeful. So finding the right problems that are the problem of the hour for the business, and it’s sizable and meaningful, and we got the momentum behind it. So I’ll give you a couple examples. And everybody was struggling through delivery during COVID So supply chain problems and being able to deliver on time. You saw across the board how the supply chain disruptions happened in the last two years. We used that opportunity to drive the leverage of the cloud platform we built to drive improvement in shift to request to our customers.

Abhi Sheth [00:41:08]:
That’s a key metric. So we actually did a lot of work in not just the customer acquisition, to your point trailer versus the whole movie, but once you acquire a customer, how do you deliver products on time and deliver them on right quality? So we were able to actually achieve, with analytics, one of the highest in TeS history, you know, shipped request, it’s in the mid nineties, you know, on number, which nobody has ever imagined we could do, and that is through Covid. So as we are coming out of COVID you know, our shift to request is up and a lot. There is not one analytic, but multiple different analytics and process changes that have actually resulted in that. The second example I would give you is really the customer retention piece. So like every customer, every business faces is customer attrition. That happens. So, as that happens, how do we define churn? How do we predict churn? So we were able to predict who’s going to churn, where do we have loss of engagement, and then why do we have it? And I think that second piece is really the key.

Abhi Sheth [00:42:09]:
Why are customers getting disengaged or about to leave? And we were able to provide that information back to our customer support and sales teams, and we were able to actually prevent tens of millions of dollars of loss of revenue from the bottom that actually misses every year. And those are two key examples that kind of resonate and internally and externally recognize for te. And that kind of has moved. Now, have we, have we addressed all of our technology debt? No, not yet. Right. We still have a lot of issues, but I think now we have what we can call a future data home and a platform where we can continue to grow while we address the holdbacks. I would say in our technology that we have had a. So that’s kind of been the approach.

Sanjog Aul [00:42:53]:
Beautiful. So, for the audience members, any questions based on the responses by Shauna Shah and Abhi about what their challenges were and how they tried to solve? Because once we have those questions answered, we can very quickly move on to the challenges posed by the audience as they shared. Anyone, by show of hands? Let me know if you’d like to ask specific questions from the panelists. All right, maybe they got, you gave all the responses that you wanted, right? So, awesome. So let’s. Let’s quickly now do a rapid fire in the sense we’ll ask the question that were posed, and the panelists would be requested to give short, crisp, but what I call as a Friday morning, actionable takeaway type of answers. Okay, so first one came from Srabhan. How do we scale the personalized experiences to engage the customers across channels seamlessly? Anyone? Any of the panelists, please take it away.

Sha Edathumparampi [00:43:59]:
I can go first? You start small. You pick one or two, use cases and pilot it, learn from it, then go to the next one. The big bank absolutely never works, having done this a few times. So start small and scale iteratively.

Shawnna DelHierro [00:44:17]:
All right, I agree with. I agree with Shaw. I think for us, you know, personalization can be so broad, and if you try eating the apple in one bite, he’s absolutely right. I mean, you will. You will fall flat. And so our first approach was, you know, what is the low hanging fruit, and what can we go get as quickly as we can that will drive the greatest impact and show the greatest result? And so if we look at personalization across online store, we went with online. We knew that that was the area that we could really see big bang for our efforts and our endeavors, and it’s been successful. So now we’ll be able to spread that and propagate it across the enterprise.

Sanjog Aul [00:44:58]:
All right, Cynthia, I believe you had a very detailed explanation of the challenge. If you could, in very crisp manner, just speak again and give a very crisp question, pose that question for the audience so they can give a crisp answer back.

Cynthia Barbarino [00:45:16]:
Sure. The greatest challenge is in identifying or convincing the data owners that they do own the data and getting them to agree to ensure it’s meeting current quality standards.

Sanjog Aul [00:45:34]:
Thank you.

Abhi Sheth [00:45:35]:
Yeah, I can. I can probably tackle that a little bit. So the way we have addressed it, and I don’t know if it’s going to work for everybody or not, but this is a common challenge, and I think I. And everybody expects it to provide the perfect data possible. And I think what we, you know, what I’ve probably, you know, done, I would say a fairly good job in the company is really talking about not just you should fix your data, and here is your, you know, here is why you own it. I think we have talked about two things. One is providing a framework on how do you look at data quality and what is data governance? And we are here to help and support. Right.

Abhi Sheth [00:46:07]:
But we can’t solve it. All right. It’s like a small, small, I would say, SWAT unit that can come in and step in. It’s not an army. The second one is really talk about challenges because the data is not fixed, right. And I think business context is really the most important thing here. It’s not about, let’s not talk about data, let’s talk about, because the data isn’t perfect, what issues are we having either? It’s on the customer experience side, it’s our operating margin side, pricing, key levers that are very directly connected to the financial metrics that we track as a company. I think that once the leaders have a common understanding of that, as we roll out our data governance process, we identify, we can do the data definitions piece, but we identify data owners for each data within each business unit.

Abhi Sheth [00:46:56]:
And from an ID perspective, I say, you know, we are, we are kind of really the plumbers, right? So we can do the plumbing, you can get in and get out, and we can actually even give you a filter, you know, so it’s like the label behind the drink. You can see how many calories and water you’re drinking, but you fill the drink and you drink it, right. I think it’s really not, the data doesn’t necessarily belong to belong and owned by the IT systems, but it really flows through the IT systems. We can give you an easy way to track the quality and measure the quality and then tell you how it is trending over time. But it’s your role to go address that quality by addressing those business processes. And if we can pick, there’s a couple of examples where we picked issues which were CEO level attention and we know the data was causing it, or in a couple areas where we had excessive trade and we did not have visibility. Once we figured out what the data quality issues were that were causing it, it got addressed very quickly because it had direct impact on OI or a senior executive metric. It got addressed.

Sha Edathumparampi [00:48:01]:
So I agree with everything, but it may have a slightly controversial sort of take on this. Sunlight is the best disinfectant in many ways. So, so bringing that, making the issues, on the one hand, transparent, I think is important. That could be done in many, many ways. There could be dashboards or reports or whatever that says, hey, this data set has these many issues or whatever. That tends to work to an extent, but I guess that’s part of the, they still need to, to work on it. In addition to that, what we’ve done is we’ve built these from an IT perspective, or in our case, the data team, the central corporate data team has built out these enterprise dashboards as an example for different business units. The data is, there are data owners in the business units but to make that data visible, we have dashboards that are built out.

Sha Edathumparampi [00:49:06]:
We call it the system metrics hub. Now, what happens is, if there are issues in the data, that becomes immediately clear at the system metrics level, because the CEO of a particular hospital is going to say, well, that doesn’t look good. I had 105% occupancy, but this dashboard says it’s only 90%. So bringing that level of visibility both at the low level, the nuts and bolts of these many issues were reported and not resolved over the last two years is helpful. But really elevating the visibility into that data at a much higher level, from a user’s perspective or the consumer’s perspective, I think, has the most impact, because suddenly, then there is visibility and there is investment and focus and attention in terms of getting those issues fixed, because the people who are going to complain about those issues are going to be the leaders who are responsible for the teams that own that data as data owners. So I think that that has, in my opinion, helped in my career.

Sanjog Aul [00:50:07]:
So, Cynthia, we have to move on, but did it give you some semblance of an idea on what you could be doing in your organization?

Cynthia Barbarino [00:50:14]:
Yes, absolutely. And I think that I also came away with some ideas to do things a little bit differently. So I thank the panelists.

Sanjog Aul [00:50:23]:
Absolutely. Thanks so much again for asking the question. Let’s continue. So, we have actually a question came. It’s from Emory University, Peter Barr. He mentioned that they are facing similar challenges in collecting data from a wide range of separate schools and systems. A basic example is that schools will define faculty differently in each school. So basic faculty counts become problematic on a broader scale.

Sanjog Aul [00:50:50]:
Coming to an agreement on data definitions is our big issue. And the other challenge that he mentioned is that they do not have an integrated employee job applicant, new higher listening strategy. So we can. They can report on turnover, recruiting performance, applicant facts, but they still don’t have the. They don’t know the root causes of the results. Well, the good news, at least as reported by Peter, is that they are starting on a listening strategy. So, any specific tips? Crisp tips, actionable tips for Peter?

Sha Edathumparampi [00:51:26]:
Look, master data management comes to mind. I think that is. That won’t solve. That’s not your ultimate cure all, but at the minimum, you need to have that, and that’s each domain. I have somewhat of a similar situation with provider data in a hospital environment, but I think the principles are somewhat similar. So have a master data management strategy as your foundation, and then you can start plugging in whether there is data that you buy from outside vendors, whichever way you can plug that in. But at the very least, you have to have an MDM solution in place.

Sanjog Aul [00:51:58]:
All right, Peter, did you get what you needed? Yeah.

Peter Barr [00:52:06]:
One of the things I’d like to hear about is actually strategies for listening to employees. You know, what technologies would you recommend? I know there’s a lot of kind of, like, word mining and commons mining, but, like, what have you all? I mean, you’re in the customer business. We’re kind of more in the new hire, job applicant student success business. So any. Any technologies or strategies for employee listening or customer listing is really what I’m talking about.

Abhi Sheth [00:52:38]:
I mean, all the interactions we have, you know, we have, you know, call logging technology, you know, as we get any interaction, any questions we get from our customers, we use software that can actually convert voice to text. And then we are able to now generate a lot of insights from that, not just the sentiment, but think about all the responses we are able to give to customers. How can we synthesize? We are starting to use more generative stuff, actually today as we speak on how can we synthesize and make the interactions a lot better, I would say. But you got to understand, as you think about listening to employees, what are the right channels in which you are talking to your employees, and then how do you capture the knowledge in those channels and synthesize that? That’s kind of where I would start.

Sanjog Aul [00:53:26]:
Okay, so now with Rajeet, who had mentioned that they had the suppliers having different. They have to service multiple customers who have their own way of accepting the data from suppliers. So what do you do for a solution so that it allows a supplier to service all methods of product exchange that’s happening between supplier and the customer.

Abhi Sheth [00:53:51]:
APIs and records, you know, that’s really what it is. You know, there is not, you know, it works all the time. It’s been proven. So that’s what I would do. And standardize API and records and mapping.

Sanjog Aul [00:54:04]:
So, Rajiv? Yeah, go ahead.

Rajeet Worthen [00:54:07]:
Thanks, Abhi. I think one thing is, depending on the customer you’re working with, they’re very basic.

Abhi Sheth [00:54:14]:
What’s the word?

Rajeet Worthen [00:54:15]:
They’re behind on the way that they accept data. So they don’t have the capability. You know, you can ask them, we want to create an API feed, but they don’t have that acceptability. Instead, they want you to provide data, like in an excel sheet or provide it into a portal. So that’s where we struggle sometimes. What’s the best way to, you know, come up with one solution that can service menu or how do you influence them to get towards a more advanced part of their journey?

Shawnna DelHierro [00:54:48]:
Sorry, just real quick. I mean, I think that goes back too much like whether you’re talking about your internal customer, your external customer, your vendors, your partners, etcetera. I think developing what the value prop is and sharing that to get the higher rate of adoption and engagement has certainly, I mean, that’s very grassroots and very simplistic, I realize. But for us that was most certainly where we’ve, where we’ve started. So Abhi, I’m sorry, please.

Sha Edathumparampi [00:55:22]:
There is an element of culture and sort of the business dynamic. I don’t know if you have the ability to influence the behavior on the other side, but the portal idea isn’t necessarily bad in the sense that if you’re able to create a single interface where people can slice and dice or create a view and download that data, especially in financial services where you have to provide statements and reports to your client base, that has definitely helped having a portal where people can self service and format, but practically every bank site does it today. Your statements can be filtered in 20 different ways and you can download it in multiple different formats. That if the API level route is not feasible, then I would recommend something like that.

Abhi Sheth [00:56:14]:
Yeah, I think just having flexibility on how you provide the data, because to your point, not everybody is going to be at the data maturity that you would have being able to accept it from an API. But the other thing you can do is, I think what Shawna was talking about is educating them. What are the challenges since they’re not using an API? I’m sure there are challenges if they’re using excel of misinterpretation, wrong data, timeliness integration, there is all kinds of issues with that. And then they cause business disruption one way or the other. Highlighting that and how API can provide a more seamless and almost real time integration into data feeds. I mean, we get data from hundreds of our distributors, from what’s old and what’s their inventory level and who bought it and what part. And we have multi, several million part numbers in dE. We make all these small parts, right? So we manage all that diversity and complexity and managing that point of sale data and then getting it standardized and mapped and understanding.

Abhi Sheth [00:57:20]:
Okay, what’s selling, where it’s selling and why. It did require a lot of work, but it can be done.

Rajeet Worthen [00:57:32]:
All right, guys, that was helpful.

Sanjog Aul [00:57:34]:
Thank you so much again. Rajit, one last question. Subrat sahoo. Data challenges, impact analytics project outcomes so how does a small consulting firm measure CX. Given the data challenges of clients.

Abhi Sheth [00:57:50]:
I think getting really smart about what challenges to pick. I think if you go, you know, I think as a company, if you are in that space, you really need to be very good at understanding and scanning through. Okay, what is the landscape data landscape of a customer look like? And then based on that, what all the possible solutions you could be providing, what are the right ones that you. That are feasible. Right. And then, and then steer that way because you don’t control data maturity at your customer, but, you know, you just need to have a skill of understanding based on what’s available and the state in which they are in, what can they do to unlock value?

Sha Edathumparampi [00:58:31]:
Yeah, I think there is a tendency in general to go really deep into some very complex but very nice architecture, technology architecture that leads to, it’s a multi year roadmap of implementation, a lot of dollars to be invested and so on. I think that usually doesn’t go very far in the beginning, especially in a very constrained environment where you have a lot of problems and you have to prioritize. My approach would be to, first of all, keep things simple, overall articulated that we have a platform challenge, we have an access challenge or some such, and then break it down into smaller pieces. That’s what anything else these days, break it down into smaller manageable pieces and go after it. Perhaps your first approach is to say, well, you have eight different tools doing the same thing. It saves you this much money. There is a business case right away to say, start consolidating it, and then that, then I think that then allows you to articulate benefits upfront. So those are keeping it simple, breaking it down and picking the right ones.

Sha Edathumparampi [00:59:43]:
That has immediate value. That that would be one of the things I would do.

Sanjog Aul [00:59:49]:
So what a great conversation today. Now the special thanks to our panelists, Abhi Sheth, Shona Delhiro and Shah editun Parapel. Thank you so much for taking the time, for answering questions and sharing your insights. And thank you so much. All of you who attended asked a bunch of questions. Hopefully you got some good answers. And we would like to keep getting your feedback so we can keep doing these webinars and bring some good value to all people who attend. And thank you so much for Luminar, who have been our gracious sponsor who made this happen.

Sanjog Aul [01:00:23]:
Thank you so much. Again, I request everyone to please help and complete the feedback form so we learn and continue to improve. And this feedback form will pop up when we end this webinar. So thank you so much. And have a lovely rest of the day ahead.

Abhi Sheth [01:00:37]:
Thank you.

Shawnna DelHierro [01:00:37]:
Thank you, everyone.

Sanjog Aul [01:00:39]:
Thank you. Take care. Bye bye.

Sha Edathumparampi [01:00:41]:
Bye bye.

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