Strategies for Embracing the Data Tsunami | SurveyMonkey CIO Eric Johnson + Okta CIO Alvina Antar

the data tsunami and what we are starting to see as CIOs coming into, I think, a new, the new normal post-pandemic. But through that process, quite a few things have changed in the world of data. So first, I'd like to talk to you a little bit about, you know, this phenomenon and as far as, you know, work from home, the migration into more of a digital space, and just broader conversations around how we're now looking to collect more and more data than ever. I really believe that there is a true data tsunami actually not only coming, but I think we're actually in the middle of it, and it's only going to intensify. So what we're, what we're going to be doing today is trying to do our best to give you some some very practical information around some things to consider, some things to think about as you start to tackle that same problem. And so we're gonna talk through kind of these 5 areas, some information around technology trends we're seeing, maybe some skills you should be thinking about considering either building out in your organization or recruiting for, some of the common questions we get as CIOs as far as frequently asked questions, some of the different things you should think about from a data strategy perspective, and then some leadership topics around this data tsunami area. And so with that, I'm going to go ahead and kick this off. We have about 20 minutes to have the conversation. By all means, it's an interactive conversation, so feel free to ask questions. We have the chat here in Zoom, and then we'll have a formal Q&A session the last 10, 15 minutes of the presentation. Okay, with that, the first question here is, which technologies have risen above the others to be the most crucial to the CIO's success with data? I'm going to kind of touch upon 3 areas that I have seen, and Alvina will be jumping in and sort of adding her perspective. I think one of the areas around AI and ML continues to evolve. This is an area that I think has been out in the market for a long time, but I think the promise of making a real true business impact is now starting to finally show up. Things like virtual assistants from an IT help desk perspective are now showing up on the scenes and actually starting to be impactful in our ability to manage data and actually manage how we interact with our employees. The analytics space has continued to evolve pretty dramatically, where the days of being these static analytics solutions and BI solutions are now starting to mature into things that are much more dynamic, with even machine learning and AI built into them. And so there's quite a bit of new technology coming on the scenes around AI and ML. I would say data infrastructure, I think we're all very much aware. There's a company called AWS out there. There's a company out there called Microsoft. And there's a company called Google. And they've been building this infrastructure infrastructure for a number of years. That infrastructure is becoming easier and easier to deploy and to drive value out of than ever before. And so I think that infrastructure and the services around that infrastructure related to data only continue to improve. And then finally, I would argue process automation and RPA. This is a kind of an area that is continuing to mature. Even over the last couple of years to now where I think organizations are able to step in and start taking advantage of this technology like they've never been able to before, especially around how we use data. You know, RPA and process automation many times are only as good as the data that you put into them. And so that data tsunami that we're experiencing is I think helping fuel things around process automation. The more data we have, and, and the higher the data quality, I think the more opportunity it presents itself for RPA and process automation. Alvina, some thoughts and, and, and maybe some, some expansion on any of those?

Yeah, um, Eric, I'm excited to get to hang out with you, um, and excited to, to, to have this conversation and an engaging conversation. So, um, you know, just, just all that you shared, I mean, I think about it more around just having organizations thinking about 5 to 6 core clouds, right? So we all know the CRM, your ERP, your HCM cloud, your collaboration. You mentioned infrastructure as a service with AWS and Google and the like. And then we have identity, right, to enable any user to use any technology. And then across all those core clouds, data infrastructure. I mean, if you think about the data that is required spanning all of those core clouds as truly critical to driving any business strategy, from data ingestion to storage to consumption, to really understanding the definition of data. So when I think about trends, I think about the importance of data dictionaries. I know governance for high-growth organizations may be a bad word, but the need for governance and the need for really investing in understanding and having a data catalog and understanding what the true source of data— because we have so many clouds and we have data everywhere, data is only as good as the investment that you put in it and the investment in truly defining quality and being able to measure quality. And so You mentioned ML and advanced analytics. I mean, tools like DataRobot are things that we've been looking at to really drive true intelligence in areas around understanding our customers. So if you think about, we're all recurring revenue business models, we're at SaaS turn, we're either fully SaaS organizations or we're looking to evolve and pivot our business from a perpetual business to a subscription business, the importance of really understanding your customer requires deep, deep data knowledge of your customer, their propensity to buy, their propensity to churn, or their upsell opportunity, right? Just the happiness of your customer and the ability to measure the success of your customer is integral to the success of your business. And so Those are areas that we are heavily investing in, in ensuring that we understand and have deep, deep knowledge in our customers and have, and allow for the entire organization to actually have a one-stop shop, one access point, a single pane of glass to be able to view and understand both customer data as well as enterprise data.

And I think it goes without saying, and, you know, doing this for 25 years and having a lot of experience in the data space, I think this is probably the most exciting time in my career for this topic. And the technology and the innovation going on around the data space now has accelerated like never before. So why don't we— let's move now to kind of the second area that we wanted to talk a little bit about, skills. Skills that we're now seeing a need for. You know, in some cases it's growing the existing team, sometimes it's going outside. But these are, these are some of the skills that I'd love to chat a little bit about with you, Alvina, and the broader group here that we feel are important in this time of this really this, this resurgence, and I think this growth around data and the tsunami we're seeing. So A couple of thoughts, and we'll expand beyond this, but the obvious one here is around automation. And process re-engineering used to be a really hot term a number of years ago. It sort of faded away, but it feels like there's a resurgence now around process engineering, process optimization, and just automation in general, and being able to manage data from an automation perspective. Work around employee experience is also an area that I continue to find as a critical component. Anything else that you would bring to bear there, Alvina, on some of those skills that you're starting to see a need to develop and grow within your organization around data?

So Eric, I couldn't agree more around automation. I mean, if you think about the investment that has been needed you know, not only even throughout this pandemic, you know, the importance of driving automation so that our employees have access to the information that they have and are not at the mercy of waiting for someone to respond. I mean, really driving automation, not from— not only from a compliance and from an optimization perspective, but from an experience for both employees and for our customers. Right. So just, you know, the whole focus around truly not throwing people at the problem, but really driving intelligence and really understanding what is required to truly automate is critical. And you need data to be able to make the right decisions around automation. What I would want to add that are more soft skills and not necessarily, you know, hard, hard skills that we know we need to invest in to drive a true data strategy are things around navigating and being influential across the organization. Because I mean, if you think about, you know, data and where it sits within your organization, a lot of times, I mean, it sits within, you know, the IT organization, or it could sit within the engineering, the R&D organization. But the reality is the data problem for the organization is a corporate-wide initiative. And in order to be successful and in order to truly drive change, you know, the importance of investing in individuals who can truly influence and influence and drive an organization that drives trust and transparency in data and builds data champions across the entire organization as stewards of data, you know, is critical to the success of any data strategy.

Right?

So, you know, a lot of times we've seen it, we've seen organizations try to invest in data, but have it be a pocket of the organization. And the reality is, in order to truly succeed, you know, everyone needs to feel like they are accountable for the quality of the data that we run our business with, that we make decisions off of our business. And so, you know, that to me is, is an area that, that is, that is critical when I look at hiring, you know, data experts within our organization.

Yeah, I think that comment, that last one around influence, is so important and key because many times data programs sort of stall out because there's not a real strategy around change management and awareness and and a priority across the organization. It ends up being in these small pockets, and it doesn't get very far. So I think very well said. So let's move to the third piece here around CIO FAQs. And I love this topic because I get asked all kinds of crazy questions all the time, and I know you do too. So we picked a few, especially around the world of data. This is one is around, how do you provide a competitive advantage to your company? And drive that, that, that continue that growth engine. And especially, uh, in your role at Okta, uh, just an absolutely fantastic company that's been on fire for a long, long time. Um, I, I think a lot of what I have heard, and what I— when I get this question, a lot of what I get back to people is I do think— I think data has become like this oil, uh, a highly valued thing. You have to mine out of the ground, you have to refine it. And then you can start to deliver some incredible value with that. But I do think it's, it's, it's about more and more, we as, as CIOs and as individuals that work in the data space, we need to start not just talking about the raw product, we got to talk about the impact. And I think that's many times what a lot of folks struggle with is, how do you actually move into the How do you, how do you make an impact with this data? So I would say that's, that's, that's one. Build a world-class employee experience. That, that's a constant kind of conversation we have around, you know, more and more, especially during this pandemic, but the amount of data that was generated, but also some of the new dynamics we have from the pandemic. And as we transition out of the pandemic, how do we, how do we focus on the employee? How do we give the employees all the tools, the data, all the assets they need to be highly successful. And when you have highly successful employees and happy employees, you also have higher retention. And so all these things start to come together, and data many times is at the core of that. So, Avinash, I'd ask you, what are your thoughts around that competitive advantage piece? Is that a question that you get? Do you get questions around employee experience? And that final question I'll give to you too is maybe about the hybrid. Any of those three you'd like to pick. Like what is going to change you, do you think, in this new hybrid world that I think we're all getting ready and prepared for as a CIO?

Yes, Eric, just around the competitive advantage, the reality is, look at IT and how IT has evolved through the years and how the importance of technology in truly being the backbone for the entire organization. And truly driving and empowering and enabling the business strategies for the organization, you've seen that evolve dramatically, right? And so we are no longer talking about, you know, IT as the back office. That is over, right? Now more than ever, the importance of technology driving decisions, enabling the business, and being in a position to drive true, true impact and actually be in a position to drive revenue. For technology organizations who actually sell to CIOs, to CISOs, to R&D CTOs, the reality is the importance of really knowing your business, knowing your technology, and being a showcase and being positioned to be able to showcase the best use of your product, not only impacting the product strategy, strategy and being able to be a voice of the customer and driving the product strategy, but also sharing insights with your customers. I mean, that truly is a competitive advantage for our organization. And so I get that question a ton, just through my years of experience. I spent 17 years, Eric, as you know, at Dell. And in the last several years, I was running M&A and did a lot of Dell on Dell, whether it was through our acquisitions or through Dell Corp as Dell was evolving from a hardware to a software and anything-as-a-service company. And then at Zora, same thing, right? Zora being a subscription billing organization, really investing in using the product and showcasing the power of transforming organizations from recurring to subscription business models. And then now at Okta, I'm I'm just having a blast being able to really share with my peers the power of enabling the most optimal employee and customer experience through our Identity Cloud. That to me excites me, right? And is a question that I get a ton from my peers around how to really drive and position the organization, position IT as truly a business. And what you mentioned about, you know, business outcomes, you know, that where we're not driving business impact by just, by just, you know, showcasing the laundry list of projects that we delivered for our business, but how we're measuring the success of the organization by the business outcomes that we are delivering. And then that's what truly is how we measure our business, right, is by enabling the business's outcomes as a backbone to our business. And so, you know, those are areas that I am extremely passionate about.

So I'm going to take question kind of the fourth and fifth subject and sort of munge them together a little bit just in the interest of time and making sure we have some chance for folks to weigh in here. And I've seen a few things on the chat, which I'd love to get to here right after this. I think this kind of goes hand in hand around the question around, you know, how has the data landscape changed? We've talked a little bit about tech. I think I'd like to touch on that. And in addition to that, how can CIOs move the needle for employees, for customers in the market? So maybe taking the first part of that question, which is one of the things that I have seen, and I'll pick just one, is is the tech is getting better and better. This landscape has changed around the data technology. It's actually starting to allow, I would call them, you know, data citizens and being able to— I'm sorry, citizen data analysts. It allows folks that traditionally had not been really close to the data, involved with the data, and making business decisions with the data The technology now, the landscape's changed now to where those individuals can now start being a much more active participant with the data. And so I think what it is is this democratization of data now inside your organization. So that's a really exciting thing. It helps to drive more value with the data. So that's one of those big things I've seen changing within the landscape. Um, uh, Alvina, was there, was there one thing that sort of came to mind for you that like what started to change in that data landscape?

I mean, it's what you have right there, Eric. It's, it's, it's, we're no longer talking about people, process, and technology, right? We now always say people, process, technology, and data as the, as the pillar, as the foundation across, across all decisions, across, you know, all. And, and, and it's really just showcasing how we've modernized our culture of, of business technology and IT to have a modern culture of data. And that it is, it's a business imperative to prioritize data, to be able to understand your customers, to be able to understand the retention, to be able to understand profitability, to be able to, you know, really drive decisions. And so that is the landscape change. And I'm more excited than ever, you know, to be able to not run blind You know, the importance of not running blind and really not making, not looking at reports and saying, well, I mean, it's kind of in the vicinity of what you're thinking. No, you know, you trust the data, you know the accuracy of the data, and you feel confident based on that data to be able to make informed decisions.

Yeah. Yeah. Well said. I'm going to, I know we're right here about 22 minutes past. I'm going to stop just here for a second and I wanted to open it up to— we have a number of folks here who have joined us. I wanted to open it up here to any questions, comments. Want to allow folks, if you want to come off mute, feel free to ask a question. It's either an incredibly shy group, Alvin, or we've answered every single question. Let's see in the chat. OK, let me see here. Let's see, Paulina, when data is democratized and more employees have access to it, how do you prevent situations where someone jumps into conclusions based on a few figures without understanding the whole picture? I think that's a great question. I think there's— when I say democratization of data, I think you have to put a bit of a caveat on that to make sure that people are properly trained. They understand the, they understand the structure that what you, what you, what you, what you need to ensure is that the folks you are giving this power to understand the data and the connections within that data. Traditionally, those folks many times still had to go to someone in IT to get the tooling to work correctly so that they could do that analysis. I would caution people to take some of this technology and give it to everybody. I do think that there is a fundamental prerequisite of understanding the data and the definition of that data to make sure that you're not creating a situation where people are running around— I think to the question here— running around with only part of the picture and making conclusions based on incomplete data sets. And so, Elvina, I don't know if you had any comments on that.

Yeah, I mean, no, just the importance of trust and transparency in the data. And that trust— I mean, investing in quality scorecards, for instance, so that you're not— you understand the quality, you understand what level of accuracy and completeness and validity of the data that you're looking at, so that you're not in a position where you're questioning the accuracy, where everyone is looking at the same pane of glass and understands, and you have quality scorecards at your disposal so that you're able to truly understand and measure the health of your data.

Yeah. So Chris had a question early on here. How are you able to coordinate data availability and portability across product and enterprise data in orgs without a CIO? Who typically owns this? Who typically owns this? Alvina, do you want to take a crack at it?

Well, I mean, I've seen it all over the place, right? The reality is— It needs to be in an area, and the reason why a lot of times organizations that have, like the CIO, is the logical space, is because we are an organization that truly spans the entire organization, right? And so you look for the right home where you really have deep insights as you're as you're integral to sales and marketing and services and finance, and you're able to actually have that breadth of exposure and be able to define cross-functional dependencies across the entire organization that requires that level of breadth of knowledge and depth of knowledge and influence. And so without a CIO, You know, an operations organization that spans the entire business is another logical space. A lot of times I've seen it within the engineering organization, but a lot of times that's too focused on, you know, your— the data that's required for your product. And there isn't a lot— a proper focus on enterprise data required to make business decisions. And so, yeah.

Alvina, spot on. Spot on. I mean, I couldn't agree more. I will say before, many times as a first-time CIO in an organization where they've never had a CIO before, a lot of times I will get there, and it will be inside the engineering organization. And it's not to say that the CTO can't manage that, but many times they are also saying, hey, this needs to be enterprise-wide. And I think Alvina's point is spot on, that it has to be someone that has that kind of visibility across the enterprise. Let's see here. A few more questions. Let's see. Sorry, I'm trying to read through this as fast as I can. I'm old and I'm a little slow sometimes. How and when do you integrate data scientists and formal studies into your strategy and process designs? So I'll take a crack at that. Very early. A lot of times— and I think this is something that I have made the mistake with in the past— is sometimes going out with the data science teams and looking for a problem, or looking for, looking for a solution. And I've learned over the years is more about we need to go and help. We need to go and start asking what are some of the business opportunities or challenges that are happening, and then work back into let's start with our data science team to see how we can help to build a model, start to drive signals and predictive, predictive process to help solve that problem or take that opportunity. Take churn, for example, which was a recent thing we did right out of the gate. It was like the business was coming to us with a challenge or an opportunity. And then we started very early in the design process with the data science team to build that versus sort of going out looking for a problem or looking for something to solve without really engaging with the business. So I think the takeaway there is engaging with your business partners, understanding what those opportunities are, and having the data science team start very early in that process. Alvina, I don't know if you wanted to add anything to that.

No, spot on.

OK. Nina had a quick question here. How are CIOs vetting tools to help implement the privacy programs within their org? What do you think, Alvina?

Well, I mean, the— you know, just around just privacy, compliance, governance, you know, the reality is, in order to really build an overall strategy around, you know, really driving the level of maturity required for a public company, the need to be able to truly invest and think about that strong, strong partnership with security and legal and compliance and understanding the overall strategy. That was actually, when I joined, that was one of my first hires was an investment in governance and risk and compliance and privacy, because it's an area that requires focus and requires investment. And requires us to really think about. And if you think about the tools that we use, a lot of the tools that we actually have that are running our business can be extended to support and drive deep, deep knowledge in this space. And so we've actually— we haven't really invested in new tools. We've just extended our existing tools to build much more maturity in this space.

And I don't know if I'm reading this question correctly, Let me see here. From Dave, and you're welcome to ask the question if I butcher it. Security of data is foundational and should be a key success factor of the data quality scorecard. And then the question was example. So I don't know if this was in reference to a prior comment or statement that was made. Dave, did I capture that correctly? Yes, as what I'm seeing is that the data is becoming increasingly valued in a crisis where the data has been accessed without authorization. And at the same time, we're trying to do all these really amazing things with the data to create these business outcomes. So how do we integrate the security of the data when we think about a data quality score. Yeah, you know, you know, it's funny, uh, Dave, that one thing that I have found is this is this really, really delicate balance that it's constantly being struck, which is we want to bring more and more data into the conversation, but at the same time, we have to be incredibly careful and incredibly diligent in ensuring that our privacy, compliance, and risk policies are being adhered to. So we actually partner really, really closely with our legal team and our security team to ensure that we vet as we bring data into our data warehouse and make it available for folks. Is it passing— is it passing through, uh, their— the policies that have been set around— in some cases we have to anonymize data, in some cases we're having to mask data. I mean, we're having to use all kinds of different strategies to make sure that that data is adhering to those policies. And I think in this day and age, especially with all of the regulations and compliance issues that we all have to manage, especially if you're doing any business outside of the United States, or hey, even if you're doing business in the state of California, right, with CCPA, it is something as a data professional, you have to have a tight alignment with your legal and security teams around very clear processes and policies on what is acceptable and not acceptable. And so it's a constant balancing act. Alvin, I don't know if you've seen anything different.

Yeah, I mean, just because we are taking data from all these cloud technologies and then we're consolidating, you know, within our— through ingestion and storing and then making it readily available, the need to be able to extend access and permissions and security across all all locations of where the data is stored is super important. And that creates a ton of complexity, right? And, and that is core to the architecture and design of your overall data strategy is to ensure that, you know, you know, for instance, the access and permissions of data that sits in Salesforce and that data is that, that, that, that is then extended into, you know, wherever you're housing the data or wherever you're exposing, exposing that same data, that those permissions are, and, and are extended at all, at all locations, right, in which the data is stored. And so, and so that is, that is, that is, that is an area that is integral to our overall strategy.

Yeah. So with that said, I'm getting, I'm getting like the hook. They're starting to give me that. I want to first thank an amazing CIO, Alvina, for joining me today from Okta, a longtime friend and a well-regarded and highly successful CIO. Alvina, thank you so much. Incredible insights. I really appreciate you attending today. And I'd like to thank everyone here that joined us today. Hopefully you were able to take something away, a nugget, a piece of information to go back and help you really manage, I think, this data tsunami that's right on top of us, and it's only going to continue into the foreseeable future. And with that, I'd like to thank everyone and enjoy the rest of the event and have a great rest of the week and a happy Memorial Day. Thank you, Alvinia. Thank you, Eric. It's been a pleasure having you both. We really appreciate it.

Thank you. Always a pleasure, Eric. Thank you, Caitlin.

Have a good one, guys. Thank you.

Bye.