CDO Forum: In the New World is part of Unlocked: A Virtual Summit by Syniti. This session features Maria Villar from SAP, Lenno Maris from Royal Friesland Campina, and Chris Knerr from Syniti.
Our CDO Forum with Maria Villar from SAP, Lenno Maris from Royal FrieslandCampina and Chris Knerr, from Syniti. As the CDO share their perspective in the new world, a few quick words on our CDO forum speakers. Maria Villar is a CDO veteran. During her seven plus years tenure as SAP's CDO, she led the organization to a 75 million Euro saving to the business. As head of enterprise data strategy and transformation, Maria now serves as a trusted executive advisor to businesses in North America.
She is also the author and the host for the Outcome Driven Data Strategy Masterclass. Data strategy in Maria's book is a boardroom topic. Lenno Maris is global director enterprise data and authorizations competence center at Royal FrieslandCampina. He's a seasoned practitioner and leader in the industry, having led large scale enterprise transformations and data programs with his starts with the end in mind philosophy. Bringing value to the business through data and analytics at Med-IQ, PepsiCo, and Kraft-Heinz, along with a two term career at Royal FrieslandCampina. Get tips from Lenno on how to deliver and make value to the business tangible. Chris Knerr is our Chief Digital Officer at Syniti. Like Maria and Leno, Chris has been a practitioner and leader in the field. At Johnson and Johnson, Chris led multi-million dollar and multi-year digital business transformation initiatives.
Chris founded Mariana, a gardener cool vendor, a big data and advanced analytics company with due focus on supply chain and unstructured data management. Chris believes that without an end to end data strategy, digital strategy doesn't exist. Without a clear digital strategy, beginning with the business in mind, digital transformations will fail.
Maria Villar (02:16):
Hi everyone. My name is Maria Villar and I'm head of enterprise data strategy and transformation here at SAP North America. And in my role, I am a executive advisor to our most senior customers. I have a trusted advisor role where I work with customers to help them define a data program and how to build out the right kind of data strategy. And that advice and counsel comes from my own personal operational experience. So I've been a chief data officer three times for three different organizations, including from SAP, from 2010 to 2017. So I really learned what it takes to start a program from the ground up to get the executive sponsorship, to show value, to get the funding that you need and to make it sustainable. And ultimately to change the culture. And I think the one thing that you should know about me from a personal perspective, as you can tell by my name probably is that I was born in Cuba.
I came from Cuba when I was two years old, so that means I really love to cook Cuban food and represent the Cuban culture wherever I can. And then the one, I think from the standpoint of, what's my point of view around the chief data officer for the next decade, look, I've been a chief data officer now three times. Had to do it three different organizations with three different types of culture. And certainly 20 some odd years ago when I started the role was primarily defensive. We were trying to make sure that data quality was sustainable and operational for our business. And while that hasn't changed, we have become more strategic. We certainly in the age of digitization being a chief data officer, making sure that digitization is all about data and having the right data at the right time with the right content and data quality level. And making sure that we not only have a defensive role and a defensive strategy to guard against that, but also an offensive one where we can actually show value to the corporation.
And that's something new for many of us, and it's going to make the job a lot more interesting, but also we all have to up our game as well in terms of being able to play that role within the company. And that means having great communication skills, really understanding the business and the business strategy for your company, and then being able to be part of those executive conversations.
Lenno Maris (05:01):
Hello everyone. Good morning. Good afternoon. My name is Lenno Maris. And within FrieslandCampina, I'm heading up the Enterprise Data and Authorizations Department Global. FrieslandCampina is a worldwide dairy company, and it's actually the largest co-operative around the globe. In our company, we're managing the complete value chain from grass to glass. And by that we control the value chain from end to end. In my career, I've mostly been active in business transformations in various disciplines, finance, sales, and it. And also within various companies like Heinz, PepsiCo, Med-IQ and FrieslandCampina nowadays. I believe that we can. And honestly, I'm very passionate about this as well. Accelerate the business performance by the power of data and insights on a day to day basis.
Just like Maria just mentioned, we need to seek and articulate the business failure. So what I really like to do is basically to come into a company, understand the way that we are operating, understand the dynamics of the company, and then start to generate transformation on the basis of seeking where the pockets of failure are sitting. And every time that I come in into an endeavor like this, I get extremely energized. And that's basically, it brings me joy, not only from a working perspective, but moreover from a personal perspective as well.
Chris Knerr (06:50):
Hi, I'm Chris Knerr, Syniti's Chief Digital Officer, and it's really a pleasure to be here with Maria on one-on-one on this CDO panel. I'm an industry veteran. I've been working in business transformation, technology transformation, digital transformation for 20 years. Before I was Chief Digital Officer of Syniti, I was in industry for many years where I led large transformation programs and I've also been the CIO and an entrepreneur in the artificial intelligence machine learning and analytics space. It's an interesting role for me to have as chief digital officer. I think often you think of a chief digital officer as someone who's primarily focused on driving digitization within a company. That is my role to some extent, but to a greater extent, my role is focused around how helping our customers achieve their digital optimization and their digital transformation.
And one of the things that I think is particularly key in that is to make sure that the customers are outcome driven, that our strategies are outcome driven, which really picks up on the great points that Maria was making in terms of how she helps customers formulate their strategy. How I come at this as particularly through the angle of data. So I have kind of a syllogism, which says that your business outcomes are driven by metrics. Your metrics are made out of data. And if your data is no good, then your metrics are no good. And therefore your strategy is no good and it's highly likely to fail on execution. So when I'm helping customers with their digital strategy, I'd very much start in the same place as Maria articulated. And from a customer standpoint, as Lenno articulated.
And then make sure that we have both the right framework and the right empirical data to help customers understand specifically in terms of digital programs, new digital products, new digital services, how are we going to bring the right framework of data to bear on that? And in order for those strategies and programs to be successful.
Maria Villar (08:48):
Data strategy has three major components. And the first component is what I call the business. It's really knowing and understanding that most important data. So understanding the business outcomes for your company, how that drives different process changes, how those process changes and lead to data and data capabilities that have to be managed. And with that comes the organizational structure and the accountability model. And I call that the business strategy and that's the anchor from which everything else then builds from. So once you understand that business strategy, that data that's most important, then the next step is then to define the operational strategy. What are the key features of data that has to be managed from the functional capabilities to the data quality capabilities, to the process capabilities, the compliance capabilities and requirements.
And then the third part is overlaying the technical strategy and by the technical strategy, it's not just the tools for all the different capabilities, but the overarching end to end integrated data architecture. Because we're all understanding that the importance of all of these tools and solutions, really working together and not being just each as siloed approach to one part of the data capability. And those three capabilities and how to build out the right comprehensive data strategy is what I outlined in my masterclass that I have now. It's 14 videos that's available on YouTube.
Lenno Maris (10:29):
As a chief data officer, I think it's important to be able to articulate the value and have a complete clarity of an end state vision. And being able to do this, you actually need to start with the end in mind. And Mr. Kovi was actually onto something. It's literally also having the ability to maneuver, to articulate where you want to go, how you want to get there, and being able to also have that executive sponsorship. So what I've done is after I joined the company, I spent then approximately 90 days of my new role to get a complete understanding of the company. The company's strategy, what did we do? What are we after, top line? Where do we want to go from a business group level? An operating company country by country, but also departmental. Really understanding the needs of the different areas of my business.
Once I understood depths, I then laid out a complete end to end strategic plan around data to insights, which brings me actually back to standardizing on the way that we capture, validate and also publish data, which is fixing the basics. Secondly, simplify also the way that we are organized from a very fragmented and isolated type of organization. We are actually moving into an automated virtual organization where we are standardizing on the way that we capture, the way that we validate and the way that we publish this data. Therefore, the reusability of data and the trustworthiness of the data is increased significantly. And then last but not least with that stabilization of the data, we can actually start to embark also on our analytics journey. And with this analytics journey, we're then aiming to become a completely data driven company. I think at this moment on that strategic plan, we are more than halfway.
Luckily, we've already successfully implemented the foundational pieces. And we're now in the midst of also driving the change across the company. The minute that you are able to articulate the value and on that basis also show a positive track record of delivery, you will gain full buy-in across the board, functional leadership teams and executive sponsorship as well. Data resides everywhere. Everybody is using it, and everybody is in need of proper data and also analytics. And therefore my view today is that data strategy isn't particularly owned by a single individual or by a single role. I do think that there is a leading position and that leading position is actually very passionate driver of this agenda and is capable of bringing a lot of people together.
Chris Knerr (14:16):
So just to build on that point a bit. I think it's a very important premise. Now, how I think about this is that there is no data strategy without a digital strategy. Let me break this down into a couple of pieces with some specific examples. So one thing that's very important. I have a distinction in my mind between a digital optimization and a digital transformation. Digital optimization to me essentially is taking IT broad way. And that includes data that works within IT systems and making that more efficient. So in a sense, digital optimization to me is kind of the same thing that information technology has been working on in order to enable business for the last 30, 40 years. And there are a number of interesting examples of where in terms of efficiency and reducing friction, that data plays an absolutely key role in that.
So, for example you can think of a business outcome, like managing risk around suppliers and reducing cost of goods sold. And this is very simplistic and obviously there's more to it than this, but in order to drive those business outcomes, those optimization outcomes, it's very important to have rationalized product numbers. So I can't have the same product with multiple different numbers. The same thing is true of my vendor numbers. If I want to manage risk around my procurement and make sure for example, that I don't have too much spend concentrated in a single vendor. Or that I'm driving maximum leverage by having vendors compete against one another, in order to do that, I have to have an accurate digital representation of those vendors and those products. And again, that's something that's made out of data. So if the data is a mess, then your ability to drive that optimization outcome is a mess.
So that's kind of one major strand of how I think about digital and digital optimization. Now to come back to my first point, there are two main senses in which companies want to digitize. One is this optimization along the lines of efficiency. The other is transformation. In a digital transformation, generally, what companies are trying to do is to somehow monetize data or to combine data with a physical product or a physical service in order to enhance the characteristics about it. So characteristics [inaudible 00:00:16:43]. Excuse me. So very frequently when we have this whole drive to doing things as a service, as distinct from a physical product, in order for that as a service to exist, we have to have an overlay of data about how that service or product is being used. An excellent example of this is streaming data that comes from capital equipment, that's deployed in the field that gives a status of equipment uptime or a proactive signal when service and repair needs to be executed.
But again, that aspect of the digitization is made out of data and you can kind of climb the ladder from there and think of companies that are considered purely digital like an Airbnb, for example, or an Uber. That generally doesn't have very many physical assets. Their entire ecosystem is made out of managing the digital assets, which combine on that platform and that ecosystem. So the common theme in those which hopefully is coming through is that all of those require a thoughtful data strategy, which is both the physical data itself. It's the supply chain for the data, which means how the data is born, how it's managed over time and grows up. How it gets retired, how it transits from one space to another. It's what kind of data is involved, whether it's internal company data or third-party data or ecosystem data.
And it's also all of the systems and technology that supports all of that working together. So there's a lot that goes into it, a data strategy. The atomic level of it is a certain piece of data, whether it's a driver or a residence, an Uber, an Airbnb, or whether it's a raw material or a chemical on the pharmaceutical manufacturing supply chain. All of these combine upwards in this kind of interesting way and get combined. And all of that has to be thought out and managed in a very careful way in order to drive the business outcomes of the digital optimization or digital transformation that a company would like to undertake.
Maria Villar (18:52):
So my one advice is to really understand the business. And what that means is do your homework, read the annual report, read your company's 10K, read all of your investor interviews. And the reason for that is that it's in those external communication, that you really start to understand what the business is driving for. And you can hear those data rich initiatives, so that you can tie back the data strategy to the business outcomes that matter most. So that's the most important takeaway from my lessons learned. So I often get asked who owns the data strategy? And who owns the data? Is it the chief data officer, or is it the business?
And frankly, I steer away from the word ownership when we talk about this kind of program. And what I respond and what I say is everyone in the company has a role to play in effectively managing data to business outcomes. And also no one gets an out. So the word ownership implies well, someone gets to make all the decisions and someone is responsible for everything. And in the world of data management and life cycle of data management, that's not true. So the business will have a role to play. The chief data officer has a role to play. IT has a role to play, and the employee has a role to play in effectively managing data. And all of those roles should be defined in the accountability matrix. That's part of your business strategy.
Lenno Maris (20:39):
My advice to anyone around is make sure that you listen to your customer, understand the customer. And therefore read into the customer's need, listen to what the customer is actually articulating as being a problem or as being the biggest thing that he or she wants to go after. Then spin this around and make sure that you're completely clear on how you value the customer needs and bring this into a data to insights journey. Make sure that you understand your customer. That's to me is the best advice that I've been given. And that's also the advice that I would give anyone around me who steps into a data role. It's seriously exciting stuff. Its difficult area, but the more that we articulate the value that we're bringing, the better we can succeed. And you will be then successful everywhere and every time.
One of FrieslandCampina's prime domains is innovation and innovation basically touches every single angle of the company. And we need to do research and developments, we need to drive or create specifications of our physical products. We need to procure. We need to identify the customers to markets. Therefore, also we need to identify the price points. And if where we're bringing that back to data, you need to set up a lot of different data elements, which are all needed in support of just launching the product. So by definition, innovation cuts across every department in an organization. What we're doing actually now is that we're playing into innovation, literally showing the value that is there, if and where we are able to accelerate the speed to market of our products. Accelerates also by having the quality from start to finish of the data. Being able to assess the... What is it?
The business benefits of the innovation as well. Where do we cannibalize on the markets? Where do we create new markets, for instance, with our products. We can all drive this purely on the basis of data now.
Chris Knerr (23:33):
I would really encourage everyone to think about their data as an asset in exactly the same way as that. And so the outcome of your manufacturing plant as the product, the outcome of your data operations is quality data that can be used for metrics that drive analytics. That allow the business to be data-driven and allow it to achieve the business outcomes that it would like to. And I think that's a very important thought process that somehow in all the complexity of this technology and people erroneously in my view, thinking that data is like an IT thing, as opposed to a business thing, has kind of gotten lost. And I think as chief data officers and chief digital officers, it's absolutely incumbent on us to portray this and in business language like that example of the data factory. And why you run your data factory or your data supply chain with the same attention to detail on the same attention to quality that you run a physical manufacturing plant. And why that ends up producing quality outcomes at multiple levels of the organization.
I think there's never been a more exciting time to work in data and analytics than there is now. And serenity, my good friend, Leonard, our chief customer officer, always says, "We were interested in data before data was cool." Well, it's cool now, and it's going to get even cooler. And what I find so interesting, 20 ish years ago, when I started working in supply chain transformation enabled by technology, I spent a fantastic amount of time doing education around why is it important to use packaged software? Why is it important to have supply chain best practices? That sounds ludicrous now, like nobody argues about that now. I'm starting to feel 20 years later that we're finally entering into that space where we're crossing the chasms between doing a lot of education around why data is important and understanding in the marketplace, why it's really important.
And not only that from a technology stand point and in particular, from an analytics standpoint, the capabilities and the services that are available. The technical services are going to continue to explode over the next five, 10, 20 years. And my feeling is that some of the things we're going to be doing with data and analytics in 10 years are going to make what we're doing now seem very primitive. And not to be grim, but there's an interesting analogy with what happened with the pandemic, which is that humans are notoriously bad at understanding exponential growth. And I think particularly in some parts of the world, the explosion from the flat growth to the explosive growth of the virus took us by surprise. This is the same thing that we see happening everywhere in technology.
So it's Moore's law and processing power. And the same thing is going to happen with analytics capabilities that we're still, in my view in the relatively slow growth and in the next five to 10 years, the uptake of capability and what we're going to be able to do from a customer standpoint, from an innovation standpoint is just absolutely fantastic. So in my view, there's never been a more exciting time to be working in the data space. And there's also never been a more important time, if you feel like there's a problem in your organization with data debt. If you're saying we don't trust the data, we don't have the data. I would really encourage you as a business leader to think about, fix that now, because the benefits that we're going to get, that you're going to get by fixing it now, rather than waiting are also going to be astonishing and exponential.
Maria Villar (27:20):
But if you have a business outcome driven data strategy, you've communicated that strategy, that strategy has been prioritized, and you have a roadmap that everyone agrees to. Then like myself, you're able to then sustain the organizational culture and the support that you need.
Chris Knerr (27:40):
This has been a terrific discussion. Maria Leno, thank you so much for joining us in Syniti here today. It's been really a fantastic discussion. We really appreciate both of your insights. And as always was a fun conversation. Thank you again.
Thank you, Maria, Lenno and Chris for being a part of our CDO Forum and for sharing your insights and advice on the topic of Data Strategy, Digital Transformation, and the Role of Data.