Meet the Data Experts Roundtable: NA/EMEA

October 13, 2020

Our Meet the Experts Roundtable is part of Unlocked: A Virtual Summit by Syniti. This session features Nate LaFerle, Alyssa Sliney, Pedro Cardoso, and Katie Scherrer: all practicing data experts and consultants who have extensive hands-on experience in businesses and public organizations.

 

 

Featuring some of our experts around the world, from the U.S., Australia, South Africa, New Zealand, and Singapore. Through their digital business transformation, where business and data converge, the theme for our virtual summit. Their expertise span across industries including, but not limited to, manufacturing and distribution; life sciences; regulated industries; retail and a wide spectrum of business outcomes; navigating business processes such as supply chain, procure to pay, order to cash, HCM, PLM, and others. Be sure to use the chat feature on the bottom of your screen to submit your questions and exchange ideas with insiders. Enjoy your interactive session and thank you once again for joining our virtual summit. 

 

 

Nate LaFerle (02:06):

Hello everybody. I'm Nate LaFerle, I'm based in Ann Arbor, Michigan. I've been with Syniti for about nine years now, most of them as a consultant leading some of our largest engagements. I have the privilege of supporting more than 600 consultants through our global consulting talent organization here at Syniti, and I'm excited to introduce you to three of these folks. 

 

Okay everybody, because you're all friends, I want to start us off with a little bit of a curve ball, and so, before we went live, I let the guys know that I would ask you to give me a quick introduction and tell me a little bit about your background. What I didn't tell you is that I'm also going to ask you to share your most embarrassing quarantine adaptation that you've had to make over the past few weeks. 

 

So, just to make this fair, I'm going to start. I'm both proud and very, very, very not proud, of the fact that I've been able to teach our four month old son to hold his own bottle so he can feed himself now. So, on that note, let's start with Alyssa Sliney. She's a delivery partner in our global MDM practice lead at Syniti, and she's entering her 15th year with the company. She's been really instrumental in growing our data governance offerings, and she is coming to us live from Massachusetts. So, Alyssa, could you tell us a little bit about yourself?

 

Alyssa Sliney (03:33):

Sure. Thanks, Nate. So, I started my Syniti in migration, but I found myself really drawn to the more solutioning side when it came to the migration, so I transitioned to the governance practice probably about six years ago. And so, since that time I've spent most of my time either actually implementing for clients or part of the sales cycle really doing some design work and advice to help our clients find the right solution. 

 

As far as my most embarrassing modification, I'd probably say my day to day hair-dos. So, I'm not on video too often. Today I've washed it, blow dried it, more often than not it's in a top knot on the top of my head. 

 

Nate LaFerle (04:17):

Nice. So, next up we've got Katie Scherrer, she's a managing consultant and she's an engagement leader for our company. And she's been with us for about 10 years now, and she's our resident glove trotter. So, she's lived and led projects in South Africa and Singapore, in Great Britain and Switzerland, and she is now coming to us live from San Diego. Katie, say hi.

 

Katie Scherrer (04:39):

Hi. I started my career in data actually in 2007, but joined Syniti about 10 years ago. I've mostly worked on migration. I've had the pleasure of working with both Pedro and Alyssa in the past, which has been great. I focus on those global systems consolidations and mostly in finance. Which is great, because almost every company has finance. 

 

So, my most embarrassing adaptation... I lived on a boat until just before the quarantine and now I live in a house. So, my whole life has changed. I think just having a whole big kitchen and I've been baking a lot. Which is dangerous. I'm much more domesticated than I used to me. 

 

Nate LaFerle (05:32):

I've actually started baking too, I'm kind of embarrassed to say. So, and then finally we've got the one and only Pedro Cardoso. He's a delivery partner who's been with us for 11 years. You guys might be noticing a little bit of a trend. And he's led some of our largest Canadian engagements. He's an expert in the automotive and retail industries and Pedro in Toronto, you're up. 

 

Pedro Cardoso (05:57):

... you Nate and team. So, many I've had a long period in IT, I've held many roles. I came out of university with an electrical engineering and software engineering background, which I think made me hardwired for data from early on. Learning how to spell SAP in 1999, and you can check the bio, I did start when I was 10. And from that perspective, held many roles, again, everything from BI or ERP implementations, to business process re-engineering, AS400 Operator, pretty much the whole gamut. I began to realize that data issues that were coming up and up were really more business process issues and more people issues, and that's really what drew me to Syniti when I joined, is Syniti had... and we have a tagline that a business owns the data. And that's where I've been for the last 11 years, as Nate says, and I'm excited to be here today, talking to you guys about our favorite topic, data. Oh-

 

Nate LaFerle (05:57):

Thanks Pedro.

 

Pedro Cardoso (06:55):

... and my most embarrassing COVID moment. 

 

Nate LaFerle (06:56):

Oh, yeah, yeah. 

 

Pedro Cardoso (06:57):

So, I have here my engineering hat. So, I do don this frequently when I'm having a early meeting and I haven't had a chance to do the hair this. So, that is for me, my COVID embarrassment. 

 

Alyssa Sliney (07:11):

Might have to take a tip, Pedro. the hat, that's what you're telling me.

 

Nate LaFerle (07:18):

Nice. So, before we get started, just a quick programming note for the audience, this session is 100% live, so we are here to meet you and answer your questions. So, please make generous use of the Q&A box below. I'll be asking your questions to our experts. So, go ahead and pick their brains and start submitting your questions now. And we'll get to them over the course of the session. 

 

So, I'll just kind of jumpstart a little bit. We, the four of us, have been friends and colleagues for a long time. I think we've combined got more than 40 years of combined experience just at Syniti alone, not counting other consulting background. And millions of miles traveled across the globe until March. You might notice [inaudible 00:08:10] experience, and we do firmly believe that experience matters here at Syniti and these are just three of over 100 consultants at Syniti that have actually been with the company for more than a decade. So, we're really proud of the experience that we bring every day. 

 

So, what I wanted to start with, and just pick your brains on, is really the notion of change over that decade that we've just lived through. I think about when I joined Syniti, then BackOffice in 2011. It was really not that hard to unearth unknown or surprising data issues that were having a massive impact. And we spent a lot of time surprising our customers with big issues and then helping guide them through the solution and optimizing their business's result. What I've personally noticed is, as the years have gone on, data literacy has increased so much. Our customers and our clients and our partners really understand their data in a way that they never have before. So, they really... they're tuned into the hot spots. They know what their issues are, they don't need any less help solving them, but I've noticed that it's much less of a fishing expedition than it used to be. And we're much more targeted and surgical because we're able to partner with the business in some of the pain points that they already know they have. So, I'm curious what you guys think has changed most working in data over the past decade. So, just open it up, maybe Pedro, do you want to start us off?

 

Pedro Cardoso (09:45):

Sure. For me, Nate, it's a real dichotomy. I think, thinking back I could say that the most profound thing for me is that everything's changed and nothing's changed. I mean, on the technology side you can look up and down the stack and we've got the most amazing tools, technology, and enablements, that wasn't existing 20 years ago, and even 10 years ago. But I think fundamentally from a data perspective, things haven't changed for many. I mean, I remember acknowledge when I was working in BI in the 2000s, and complaining about, "What do those ERP people do? And I'm trying to build good reports on my team, but the data's not right, we can't build good reports. What's wrong with the data?" Hearing users asking for better data, better information, and a promise for one source of truth. So, I think, a lot of those challenges still exist today and I think we're better prepared now though, to handle that than we ever were. 

 

I think on the other side, I think there's a huge difference now with respect to awareness about data. Thinking to this, the COVID-19 global challenge we've found all of us in, data is top of mind. And from a data perspective, everyone's looking at what the data tells us in terms of how we [inaudible 00:11:06] the new normal, how we look at the number of tests being performed, number of positives, number of recovered. I think the understanding of the importance of data today has changed, and I think that helps certainly us as practitioners, kind of start that conversation off. 

 

Alyssa Sliney (11:29):

I mean-

 

Alyssa Sliney (11:30):

Oh, go ahead Katie. 

 

Katie Scherrer (11:33):

Sorry. I think, looking back over my career, in 2007 when I started, almost no one had any idea what I did, and it was difficult to talk to people. And now everyone I meet or talk to, not even just for business interactions, but generally, has some story to tell me about their experience. And I think that's very telling. It just changes the starting point of the conversation. That's my experience. 

 

Alyssa Sliney (12:01):

Yeah, I think especially in governance, we spend a lot of time previously, doing a lot of education to get to a starting point, now what we're finding is, there's so many definitions of governance, we're actually having to just bring everyone into alignment. So, still an important starting conversation, but it's just shifted a little bit. 

 

And then, from an implementation perspective, I think we've seen a big move away from single instance. When we started, everyone was trying to get into a single place with their data, and now, I mean, not only do we have the bolt-ons of Sales Force, PLM, HCM, but we also are just seeing a move away from driving towards a single ERP. So, that's just introducing complexity in other management piece's business glossary, understanding your lineage, that we have to accommodate for and make sure that's part of our strategy. 

 

Nate LaFerle (12:51):

Definitely. And Pedro, I know you mentioned COVID, and I know that's something that's probably at the top of mind for our audience, I know it's top of mind for me. Have you seen some changes in the implementation strategies and projects since the crisis hit in the past couple of months? How have our clients been reacting?

 

Pedro Cardoso (13:15):

Yeah, Nate, that's a great question. I think from a project perspective, I think for those of us who are used to using some of the collaboration tools we're using right now, not a lot has changed, but it's been amazing to see, I think, the entire world sort of move at warp speed to really adopt a lot of this collaboration technology that we had already available, but were kind of moving a bit slower. I think the broader implication of that is I think we're shifting from what today is a short term response to COVID, but probably a long term pattern that's going to stay with us in terms of how we work and collaborate together. I think for projects specifically, I think it's actually a great opportunity. 

 

What I'm seeing on projects is... and I don't know if it's because of people having to adopt to the change that the COVID situation is putting us all in, everyone kind of working from home and adjusting to this new normal, but I find that from change management perspective on projects that I'm on, things that we used to spend a lot of time on around stakeholder management and getting people to make decisions and be willing to change, and we know data is a lot about change management as well, I think it's an opportunity for a lot of companies to really seize this new normal and the attitude that I think people are more open to change now. Which I think for data in particular is exciting, and maybe an opportunity to leapfrog the competition for those companies that can really seize this time and this phenomenon to some advantage. 

 

Alyssa Sliney (14:53):

So, one thing I'm seeing is even a larger emphasis on ROI for efforts. And so, starting with the end in mind is even more crucial now than it was before. You've got tons of budget pressure, we're seeing some companies go down to maybe a four day work week, and so your time is physically becoming compressed. And so, any initiative you're going to take on or continue needs to have maximum return on investment. 

 

Nate LaFerle (15:21):

Yeah, I think Alyssa, I'll actually stay with you on that one. I know the, as you mentioned, governance becomes so much more important and I think especially as we look at potentially disparate processes remaining in disparate systems, probably continuing as a trend in the short term as capital expenditures get deferred and things like that. Data governance isn't a new concept or a new initiative, and I think a lot of companies have made fits and starts in this direction, but maybe haven't gotten the momentum that they would have liked to. And I think those conversations are probably coming up all over again. And so, I'm just curious on what your thoughts on that and how to really start off on the right foot there?

 

Alyssa Sliney (16:06):

Sure. So, one thing actually, that's been pretty interesting working with healthcare industries, there's actually a pretty strong emphasis right now on the business glossary. So, they're taking many of the reports they already needed to satisfy HIPAA, and other requirements that they've got, but they're now putting emphasis on the business glossary to get the most value out of those reports. Which is actually something I was surprised at. So, that tends to be the thing that's a little bit harder to bet business buy-in on, and so they're actually doubling down on that because that gets the most value our of things and assets that they've already got. 

 

Nate LaFerle (16:43):

Interesting. 

 

Alyssa Sliney (16:45):

From a manufacturing perspective, I think there's a lot of emphasis on business process improvement, cost of goods sold, inventory management, they're just trying to optimize as much as they can. So, it's not necessarily new initiatives, I would say, but it's emphasizing and tightening up of the processes that they've already got. 

 

Nate LaFerle (17:05):

Interesting. And Katie, I know you've spent a lot of time in industries where it's maybe a little bit less manufacturing centric and I know that some of the challenges can be a little bit different when you're not [inaudible 00:17:19] things to make things to sell them. I'm curious what your experience has been there or what you think some of the challenges might be for the financial industries and others that might be more intangibly based?

 

Katie Scherrer (17:32):

Right, obviously right now, the financial industries and insurance industries are obviously in an unprecedented time for everyone. For my personal experience though with the current project I'm working on, it's a well established project. We already were working remotely most of the time across the globe, so we haven't seen too much of an impact. We're really in a very reasonable, repeatable process that's been established, and so we haven't had too many challenges there. I think the reporting and all of the need for reporting and just access to the data real-time, is always important and I think that will come out as one of the key takeaways, is that the ability to report real-time is critical, regardless of how much data you have. 

 

Nate LaFerle (18:23):

And when we think about working in finance and insurance and things like that, what are some of the specific data areas? Is it things like reconciliation or volumes that drive the conversation? What is really the big governance driver in those industries in your experience?

 

Katie Scherrer (18:45):

Right. So, from an insurance perspective, reconciliation is a huge process. Insurance companies tend to have a significant amount of customization due to their actuarial calculations. And every company has... from the beginning of the company they have their own deeply embedded customized calculations for their... the way the define risk. And that's how all the premiums are calculated. And so, having the ability to define what information they need in order to make those actuarial calculations, it's critical for it to be correct for them to assess the risk properly and consistently. So, seeing that type of information and really the reconciliation is a huge part of that. 

 

Pedro Cardoso (19:39):

And for me [crosstalk 00:19:39]-

 

Alyssa Sliney (19:39):

One thing I should have mentioned, Nate...

 

Pedro Cardoso (19:43):

Go ahead.

 

Alyssa Sliney (19:43):

Sorry, Pedro, go ahead. One thing I should have mentioned on the healthcare side, the other challenge I think they're seeing there, and I think it's similar to finance is the data volume. The transactional volume, the amount of history that they've got. When I did reinsurance project, I think they had close to 100 years of history in some cases. The ability to get your hands on that data, so whether that's change data capture, whether that's... you're using data, so you need to physically get your hands around that data, with that kind of volume, it can be very tricky. 

 

Katie Scherrer (20:15):

Right. 

 

Pedro Cardoso (20:16):

I think, just building on what you just said Alyssa, as well as Katie, amidst all those challenges, I think, there's also the ruthless pursuit in certainly automotive and in retail, where I've spent a lot of my time over the last few years, is standardization. We heard of Raul earlier, in the summit, talk about the importance of standardization. Everyone's looking at... think about customer experience. People are looking really to unify, regardless of whether they're on one system or many systems, as Alyssa mentioned, there's a myth of... the myth of you're going to move to one ERP's no longer the case. SAP's done a fantastic job of digital core, but they've also interoperable with many other systems. So, just getting that view and how to get that consistent view of whether it's a customer, whether it's a vehicle, whether it's a [inaudible 00:21:08] across the entire lifecycle of the relationship they have with the customers, is something that's really dominating at least a lot of the conversations I'm having.

 

Nate LaFerle (21:20):

Yeah, and so Pedro, I know you do actually spend a lot of time with the C-suites, in particular CIOs, talking about data quality and how those outcomes are uniquely tied back to data and what do you find is top of mind for those folks? What is the most impactful steps that they're taking or counseling us on?

 

Pedro Cardoso (21:48):

That's a great question, Nate. I think if I could pick just one thing is, we're talking a lot more about really how to manage the organizational knowledge around data. I think a lot of CIOs, a lot companies, they've spent enormous amounts of money on data related initiatives, but they often [inaudible 00:22:12] more in silos, maybe more... aligned with specific projects, and now they're looking to see what can they do more holistically to make sure that data's managed consistently regardless of application or process area or Sam, Bill, Tom, or Jerry, who've been with the company for 30 years and just know how to do things. So, getting that tribal knowledge out and really having a lot of discussions about how we... At Syniti we talk about that life cycle of data and harnessing information, so really about how to make sure that knowledge that's being collected, being created is available for all the other initiatives as well. Because again, you fix something around data in one area, it's going to be dividends everywhere else. So, for me, that's one of the biggest conversations we're having is how to actually take more of a knowledge and holistic approach to data. 

 

Nate LaFerle (23:13):

Yeah, and I think Alyssa, that's probably something that comes up quite a bit on the governance space, especially when we're kind of helping with that transition from a migration to governance. And really how to emphasize that tribal knowledge reuse and basically establishing those business rules as assets. 

 

Alyssa Sliney (23:33):

Yeah, so really any time you're working with data, you should be thinking about that as an asset producing effort. Now, migration is the best example of that. So, you've got mappings, you've got the tribal knowledge, you've got the code programs. All of of those really need to come out of those programs. What I still am continuing to see today is there's not really that transition plan. If you don't start that way, the project right, you need to have additional... let's call it a week to do readouts and movement of that knowledge into where ever you want to take that to the next level with governance, that really needs to be part of the plan from the start. But that's really true for any data initiative, not just a migration. 

 

Nate LaFerle (24:18):

Makes sense. Yeah, I think what I'm hearing from you guys, and certainly mirrors my experience as well, is the notion that data is not... even when we're talking about the world of SAP, it is not plug and play. This is not something where, "Oh, a vendor is a vendor is a vendor, and employee is an employee is an employee." There's real industry specific challenges and it really takes an understanding of that data to move the needle and make sure that we've made that transition from being technically ready or just meeting a requirement, to just actually being right and something we can execute a business process on. 

 

I think that's something that I think about a lot when we're at our customer's, it's about getting to know them, right? And I think that important step of understanding your client and their business processes and their business challenges are tricky. I'm curious, maybe Katie, if you want to start me off, what do you think is... and this is a question from the audience, what is the most important skill you identified when getting to know your customer? What is the secret sauce for establishing that relationship and really getting down to the root of what they do and how they do it?

 

Katie Scherrer (25:44):

Yeah, I think the best thing I've found is helping them to identify their true underlying problems. Sometimes you'll see the outcomes of several underlying issues that they're having and just because they see one problem doesn't mean... if you fix that you're just going to see something else. So, true problem solving and trouble shooting and getting down to the details, which help you understand their business better, and asking lots of questions, and allowing them to provide feedback and listening to their true pain points. Those have all been my approach to getting to know my customers and to better helping them. I love problem solving and I love coming up with creative solutions. Especially repeatable ones. I will talk about reusability and repeatability all day long. And so, I think just showing them the best way forward has been what I've done. 

 

Alyssa Sliney (26:49):

Yeah, so I think the listening, key word that you just mentioned at the end there, I think that's critical. I think too often when somebody thinks they know the solution, they'll start with that and then back the problem into it. When you hear one problem, often there's multiple root causes that's going to lead to a chain of other problems. I think listening is probably the most critical skill you've got there. 

 

Pedro Cardoso (27:13):

Yeah, I think when I go in, I normally look at two different key points and one of the things I often talk about is we got to get rid of the smoke before we see the fire. Understanding that, first of all, there is no such thing as bad data, right? Bad data isn't born. Data is through management of business process, through how it's curated, how it's created, and how it's updated, within the business process that's where the problem is. So, really understanding at a business process level, what is not working? What are those business outcomes, those business challenges, that are driving the conversation, because nobody wakes up in the morning and says, "I'm going to go clean me some data." That doesn't work. There's got to be a reason why. 

 

And then the flip side is, once you've got that clarity of what's actually going wrong in the business and in the day to day operations, what's the outcome they're not reaching, then it's finding those point of lights in your organization, the people who know the data, allow you to actually get access to that data, and then we have another saying at Syniti, let the data do the talking. Let's actually figure out what's actually wrong in the data, that's not enabling the process, and then let's focus on that, right? Let's not boil the ocean, let's actually deliver some value. And for me, it's those two perspectives, starting with the business process, drilling in, and then coming in from the data side and figuring out, okay, where is the actual issue. 

 

Nate LaFerle (28:48):

Yeah, I think that's exactly right, Pedro. I'm reminded of an example actually at a... one of our customers that was doing an HR migration, and it was something really simple. It was work schedules, so what days a week and what hours do you work. And the requirement basically is take the work schedules in the old system and move them to the new one. Not rocket science, it's pretty easy to follow that requirement, but when we did as you say Pedro, and we let the data speak for itself, we saw some really weird anomalies. And what it turns out was happening was, every different part time person had a slightly different schedule and had a different configuration element. 

 

So, that drop down box, when you went to hire someone, quickly became like 100 different options. And what happens when you get a drop down box of 100 different options, and you've got a stack of employees to enter? You certainly do not spend your time trying to find exactly the right one, you just create a new one. And so, once they hit that tipping point of 100 different options, it ballooned within the course of a month or two to 800. And so, they had a massive de-duplication on their hands they didn't even know about just because of the people side of it. And I think that's such an important point that you made there, Pedro, about data is a neutral party. Data is a symptom of people and process challenges. 

 

Pedro Cardoso (30:16):

Yeah. Yeah, I love that story, Nate. I have a story also from... there was one place we did in the food sector and grocery and it was interesting because couldn't figure out why from an historical perspective, it's not that the data was wrong in the system, in this case it was SAP, it's just that the data wasn't always right when they went and looked. So, I mean, kind of peeling back the onion on that one, ended up being a situation where there was a process that wasn't being fully enabled through data within, in this case, SAP, but what some very smart people had done was they had figured out how to pull all the data needed out of SAP and other systems, they had built this... I think it was actually Bill's Assortment Spreadsheet was the name of it, and they were actually building everything in Excel offline, and then on the Thursday every week they were uploading that into SAP in order to get the assortment right. 

 

So, unbeknownst to them, that was causing a lot of downstream challenges around just forecasting and planning and planogram. So, it was a really easy problem to fix, it was about making sure that we were able to bring the data they needed into their business process as part of what they were doing in the case of SAP, to make that spreadsheet go away. But until you drill down and understand that you going to have to spin your wheels really looking in the wrong place. 

 

Nate LaFerle (31:54):

Definitely. So, I'm curious, what makes this hard guys. Why is data so hard? Don't all talk at once. 

 

Alyssa Sliney (32:06):

So, I think Jeff spoke to it pretty well earlier, right? The idea that it's contextual. I think you used a good example earlier, a vendor is not the same across all companies, vendor's not even the same within a company. So, how the finance department talks about a vendor and how procurement talks about a vendor could be two totally different things. So, you're right, data's a symptom of other things. The people that are involved, the process that surrounds it, and without all three of those components, or not making sense of it all, the answer's not going to work. 

 

Pedro Cardoso (32:46):

I think the other thing on why data's sometimes hard is, I mean, speaking from experience, I think a lot of the data practitioners out there, you don't go to university and come out with a degree in data management. Or, maybe you do today, but certainly not in my day. And I think there's a lot of, I'd say, accidental data practitioners out there, who've kind of fallen into the role. I mean, every company I walk into, every project I'm on, there's always that one person that says, "I'm in charge of data, but I don't really know what I'm doing. I was given this role because I'm good with data, I've been here for 20 years, I collaborate well across process areas, and I'm great at Excel." And a lot of those folks end up being in IT. So, I think why data's so hard... I'm certainly not putting words into Katie and Alyssa's mouth, but I think as an organization, we don't believe data's hard, we believe data's actually easy. It's really the people and process side that we focus on because the data, well again, tends to take care of itself once we know what needs to be done. It's really not that hard. 

 

Of course, when you're out... you've got your day job, data is not all you do. At Syniti, data is really all we do. I like to say, "Data isn't what we do, it's actually who we are and what we are," because it's how we do it. So, I think that's part of the challenge, and I think as practitioners out there, we need to do a good job educating within organizations across... within organization, the importance of not just assuming that IT or individual can make those decisions and know what needs to be done. It's really about that partnership with, we'll say data experts, even though I don't like the expert word, but the folks who understand what it's going to take holistically to solve those data problems. I think that's part of what makes data hard. We try to put IT solutions and tools in place, when really it's not just about the tool. Because I've been in organizations, I can tell you, they have every tool out there but they still have a problem. 

 

Nate LaFerle (35:01):

Yeah, actually it's-

 

Nate LaFerle (35:02):

Go ahead, Katie, sorry.

 

Katie Scherrer (35:05):

I was going to say, I agree with Pedro. To us, where we live and breathe data every day, data isn't actually... we don't see it as being that hard. I see it as being an opportunity and a challenge. One of the things, when I go into a new client, I like to say, "I'm here to help. I'm here to make this easier." It's a skill that we've acquired, and it's working with IT, working with the business, being that translator for understanding what IT needs and understanding what the business needs. So, that's what, I think, is one of my favorite parts about my job is making someone else's life easier. Because it is overwhelming and it is challenging. But we are here to make it easier and that's why I enjoy the problem solving sessions with the business. 

 

Nate LaFerle (35:50):

So, what do you think are the biggest challenges or... I don't want to use the word mistake, but missteps maybe, that companies run into as they start a data initiative and as we help? What are the common pitfalls there? To Katie.

 

Katie Scherrer (36:08):

Something I see almost every time I start a migration project, someone comes to me and says, "Well, the data in the system's not good. We can't use it." And I typically ask, I say, "Do you run the business on that data today?" And I've never gotten a no on that question. And that's where we have to start with, is start with what they're using, what are they running the business on today? They need to leverage what they have, and not try to rebuild or restart, because they'll just be stepping over themselves. And it's to grow and nurture that data that they have, before... don't just throw it away, there's always value. And back to Pedro's statement, there is no bad data. 

 

Alyssa Sliney (36:58):

So, from a governance perspective I think siloing the IT and business sides, and I've seen that in migration as well, the idea that IT will get the data most of the way there and then the business just shows up at the end and validates it. When you take that approach, guaranteed the business is going to come in and they're going to validate it and say, "This is all bad." So, no bad data but how you got there from end to end, the processes that created it before hand, right now the business is seeing it in light of their new system where ever it's going. If you keep those two things separate, you're never going to get the results that you really need to operate as a business. And it carries over to governance. If you design tools to manage your data that don't involve how the business really uses that data, those tools are just not going to be successful. 

 

Nate LaFerle (37:46):

Yeah, I think our Chief Customer Officer, Leonard, has a... one of his many repeated phrases is this notion that, when you treat data as an IT problem, you can write a spec and code to the spec, and code it perfectly, it's still cod it perfectly wrong. And I think that's the pitfall that I see a lot, right? You can say that everyone's name should be Mickey Mouse in the spec, and we write that code, and it'll load perfectly. It'd be technically perfect. You cannot run your business on that, right? And to your point Alyssa, it's about what is the new system actually going to need to drive real business-ready data, and how do you get from that step of meeting requirements to being actually business-ready, that I think is challenging. 

 

I think you made a good point that... about the IT handing off data to the business. And it's interesting because I think when customers bring us in, a lot of times it's the business that brings us in as data experts, and I'm curious, and this is a jump all to any of you guys actually. If data is considered technical, why is it the business that calls us, do you think?

 

Pedro Cardoso (39:07):

Well, I can jump in on this one and take the first stab at it. I think Alyssa made a point earlier as well, that, I think, a big mistake a lot of companies make is they do treat their IT and data... or they treat their data projects as IT projects, and they also tend to time-box their data activities as just data's something I need to do now in order to go live. And the irony is that's not true. Data's not just something you need to do every day and it's not just to go live, it's to make sure you've got that right behavior within your organization so that after you go live, you're still going to be okay. It's like if you just went on a diet every time you hit a certain number on the scale, that doesn't work. You got to figure out what is that lifestyle change that's going to makes sure you're going to maintain that ideal weight that you want. 

 

So, I think, Nate, to your specific question, I think it's really about making sure that we look at the projects across a company's spectrum, that we're not just focusing on the project itself and what the outcome is, it's what are we going to do around data to make sure that it's sustainable.

 

Alyssa Sliney (40:35):

And careful with that weight metaphor there, Pedro, in COVID-19. 

 

Pedro Cardoso (40:40):

I know. I know. But Nate, I think there was another point you were trying to make on that, right? Which I probably didn't nail. [inaudible 00:40:50].

 

Nate LaFerle (40:54):

Oh, I think Pedro froze. 

 

Katie Scherrer (40:57):

Uh oh. I think one of the points along those lines, about why does the business bring us in when it's... a lot of times it's an IT problem, is that the business feels the pain on a day to day basis. [inaudible 00:41:08] run their practices properly because they're missing things and they're asking IT. But it doesn't hurt IT, they just... it's a ticket, and it's on a list of things to do. Whereas if someone can't do their job, and so I think that that's one of the reasons why, and it goes back to what I was saying about coming in to make the job easier, being able to bridge that gap between IT and business to understand processes. 

 

One client I worked with briefly, that had a great way of helping to bridge that gap was, they would send their IT out into the field to work with the people in the business processes. They had some of the best knowledge of how the business ran in the IT world. Their IT had great experience with the actual business processes and it was really helpful. That was one great experience I had. 

 

Pedro Cardoso (42:00):

Nice. I also think IT tends to build... come up with solutions that are really tool focused. So, I think the business also gets frustrated when... going back on my metaphor earlier, when if you just a put cleansing tool in front of the business saying you need to clean your data, the question is, "Well, why? And what's it going to do for me?" Right? So, I think recognizing that from a business process perspective, I think that business also reaches out because they don't really care about keeping the data clean, they care about reaching those outcomes that Katie just mentioned. So, I think pivoting the conversation to that outcome driven approach is really how you get the business engaged. The business wants to be engaged and traditional IT approaches just typically don't achieve that. 

 

Nate LaFerle (42:45):

I think that's a great point, Pedro. So, this has been a really great conversation. I want to kind of go to one last round robin before we wrap, and just get that nugget from you. What is a piece of advice that you would share with somebody that's about to embark on a major data initiative? Alyssa, maybe you want to start us off, just what's your takeaway?

 

Alyssa Sliney (43:13):

Sure. So, data governance at this point, it's a box everyone knows that we should be checking. I think there's a lot of thought pieces around it, there's a lot of research around it, but what I find a lot of companies struggle with is the ability to get started. So, when we're talking about data strategy, when we're talking about information governance, it's a mountain, and if you don't kind of take that into pieces and really focus on the outcome of what you're trying to achieve, think you're going to struggle to get started. So, to break it up into smaller parts, address procurement, address cost of goods sold, break those down even in smaller parts, and start to work towards those business problems. You'll get better business buy-in, you'll get more realistic budget approval, and that helps you work towards those larger goals. Yes, eventually you do need a data strategy to get the most value out of all of your data efforts, but it's not where you need to start to get a little bit of momentum. 

 

Nate LaFerle (43:13):

Katie?

 

Katie Scherrer (44:17):

Alyssa was great. I also think, from a migration perspective, embarking on a major or even minor data migration or any data effort is daunting. You have so much that you have to tackle. I think one of the best pieces of advice is to figure out what can be reusable and what can be repeatable. And if you're trying to tackle a global project, yes, all the regions, all the countries are special, but there is overlap. They're all going through the same process. And making sure to be able to leverage what you've done in previous ways or in different areas and use that again, and not lose that knowledge. So, having higher level overview of all the things that are going on I think is very valuable. If it's [inaudible 00:45:01] once the migration's complete, you can leverage all that for governance. I think Alyssa would like that. 

 

Alyssa Sliney (45:06):

That's right. Good plug. 

 

Pedro Cardoso (45:11):

I'd say that thinking about this virtual summit we're putting on, and sort of the theme of where business and data converge, I think we just need to... I think every CEO and senior VP, everybody out there wants to have... wants to be data driven. They want be data driven, they to have the right data, but I think we need to just stop talking about data. I think as data practitioners, we tend to lead with the D word and I think there's one thing I'd like to call out to all the data practitioners out there is, we need to stop leading with data. We need to stop talking about data, we need to talk about business outcomes. Marie [Villar 00:45:49], if you haven't watched Marie's YouTube series on... it's awesome content. I think we need to really understand that data's a means to and end and we can't have the tail wag the dog, right? So, I think less data, more business outcomes really needs to be where the conversation pivots. 

 

Nate LaFerle (46:15):

Thanks, Pedro. And thanks all of you. I think that's going to be a wrap for our experts. I wanted to thank you all for your insights and your willingness to share them with our audience. I am sure I'll be talking with you guys soon. To our audience, I hope you found the whole virtual summit to be worthwhile, and on behalf of our experts, we're so proud to have been a part of it. So, stay safe, be well, and take good care of your data everybody. 

 

Alyssa Sliney (46:41):

Thanks, Nate.

 

Pedro Cardoso (46:41):

Thank you. 

 

Alyssa Sliney (46:42):

Thanks guys. 

 

Katie Scherrer (46:42):

Thanks, Nate.

 

Nate LaFerle (46:43):

Thank you. 

 

Katie Scherrer (46:43):

Bye.

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