 So, we're going to take a hard pivot now and go from football to Chernobyl. Chernobyl, what went wrong? 1986, as the reactors were melting down, they had the data to say this is going to be catastrophic. And yet the culture said no, we're perfect, hide it, don't dare tell anyone. Which meant they went ahead and had celebrations in Kiev, even though that increased the exposure, the additional thousands getting cancer, and 20,000 years before the ground around there can even be inhabited again. This is how powerful and detrimental a negative culture, a culture that is unable to confront the brutal facts that hides data. This is what we have to contend with. And this is why I want you to focus on having, fostering a data-driven culture. I don't want you to be a laggard. I want you to be a leader in using data to drive your digital transformation. So, I'll talk about culture and technology isn't really two sides of the same coin. Real-world impacts and then some best practices you can use to disrupt and innovate your culture. Now, oftentimes I would talk about culture and I talk about technology. And recently, a CDO said to me, you know, Cindy, I actually think this is two sides of the same coin. One reflects the other. What do you think? Let me walk you through this. So let's take a laggard. What does the technology look like? Is it based on 1990s, BI and reporting, largely parameterized reports, on-premises data warehouses, or not even that, operational reports? At best, one enterprise data warehouse, very slow moving, and collaboration is only email. What does that culture tell you? Maybe there's a lack of leadership to change, to do the hard work that Sudish referred to. Or is there also a culture of fear, afraid of failure, resistance to change, complacency? And sometimes that complacency, it's not because people are lazy. It's because they've been so beaten down every time a new idea is presented. It's like, no, we're measured on lease costs to serve. So politics and distrust, whether it's between business and IT, or individual stakeholders, is the norm. So data is hoarded. Let's contrast that with a leader, a data and analytics leader. What does their technology look like? Augmented analytics, search and AI driven insights, not on-premises, but in the cloud and maybe multiple clouds. And the data is not in one place, but it's in a data lake and in a data warehouse, a logical data warehouse. The collaboration is via newer methods, whether it's Slack or Teams, allowing for that real time decisioning or investigating a particular data point. So what is the culture in the leaders? It's transparent and trust. There is a trust that data will not be used to punish, that there is an ability to confront the bad news. It's innovation, valuing innovation in pursuit of the company goals, whether it's the best fan experience and player safety in the NFL, or best serving your customers. It's innovative and collaborative. There's none of this, oh, well, I didn't invent that. I'm not going to look at that. There's still pride of ownership, but it's collaborating to get to a better place faster. And people feel empowered to present new ideas to fail fast and they're energized knowing that they're using the best technology and innovating at the pace that business requires. So data is democratized and democratized not just for power users or analysts, but really at the point of impact, what we like to call the new decision makers or really the frontline workers. So Harvard Business Review partnered with us to develop this study to say just how important is this? We've been working at BI and analytics as an industry for more than 20 years. Why is it not at the front lines, whether it's a doctor, a nurse, a coach, a supply chain manager, a warehouse manager, a financial services advisor? 87% said they would be more successful if frontline workers were empowered with data-driven insights, but they recognize they need new technology to be able to do that. It's not about learning hard tools. The sad reality? Only 20% of organizations are actually doing this. These are the data-driven leaders. So this is the culture and technology. How did we get here? It's because state-of-the-art keeps changing. So the first generation BI and analytics platforms were deployed on premises, on small data sets, really just taking data out of ERP systems that were also on premises. And state-of-the-art was maybe getting a management report, an operational report. Over time, visual-based data discovery vendors disrupted these traditional BI vendors, empowering now analysts to create visualizations. With the flexibility on a desktop, sometimes larger data, sometimes coming from a data warehouse. The current state-of-the-art though, Gartner calls it augmented analytics. At ThoughtSpot, we call it search and AI-driven analytics. And this was pioneered for large-scale data sets, whether it's on-premises or leveraging the cloud data warehouses. And I think this is an important point. Oftentimes, you, the data and analytics leaders, will look at these two components separately. But you have to look at the BI and analytics tier in lockstep with your data architectures to really get to the granular insights and to leverage the capabilities of AI. Now, if you've never seen ThoughtSpot, I'll just show you what this looks like instead of somebody hard-coding a report, it's typing in search keywords and very robust keywords, contains, rank, top, bottom, getting to a visualization that then can be pinned to an existing pin board that might also contain insights generated by an AI engine. So it's easy enough for that new decision-maker, the business user, the non-analyst to create themselves. Modernizing the data and analytics portfolio is hard because the pace of change has accelerated. You used to be able to create an investment place a bet for maybe 10 years. A few years ago, that time horizon was five years. Now it's maybe three years and the time to maturity has also accelerated. So you have these different components, the search and AI tier, the data science tier, data preparation and virtualization. But I would also say equally important is the cloud data warehouse. And pay attention to how well these analytics tools can unlock the value in these cloud data warehouses. So ThoughtSpot was the first to market with search and AI-driven insights. Competitors have followed suit, but be careful. If you look at products like Power BI or SAP Analytics Cloud, they might demo well, but do they let you get to all the data without moving it in products like Snowflake, Amazon Redshift or Azure Synapse or Google BigQuery? They do not, they require you to move it into a smaller in-memory engine. So it's important how well these new products interoperate. The pace of change, its acceleration, Gartner recently predicted that by 2022, 65% of analytical queries will be generated using search or NLP or even AI. And that is roughly three times the prediction they had just a couple of years ago. So let's talk about the real world impact of culture. And if you've read any of my books or used any of the maturity models out there, whether the Gartner IT score that I worked on or the Data Warehousing Institute also has a maturity model, we talk about these five pillars to really become data-driven. As Michelle spoke about, it's focusing on the business outcomes, leveraging all the data, including new data sources. It's the talent, the people, the technology and also the processes. And often when I would talk about the people and the talent, I would lump the culture as part of that. But in the last year, as I've traveled the world and done these digital events for thought leaders, you have told me now culture is absolutely so important. And so we've pulled it out as a separate pillar. And in fact, in polls that we've done in these events, look at how much more important culture is as a barrier to becoming data-driven. It's three times as important as any of these other pillars. That's how critical it is. And let's take an example of where you can have great data, but if you don't have the right culture, there's devastating impacts. And I will say, I have been a loyal customer of Wells Fargo for more than 20 years. But look at what happened in the face of negative news with data. It said, hey, we're not doing good cross-selling. Customers do not have both a checking account and a credit card and a savings account and a mortgage. They opened fake accounts, facing billions in fines, change in leadership that even the CEO attributed to a toxic sales culture. And they're trying to fix this, but even recently there's been additional employee backlash saying the culture has not changed. Let's contrast that with some positive examples. Medtronic, a worldwide company in 150 countries around the world. They may not be a household name to you, but if you have a loved one or yourself, you have a pacemaker, spinal implant, diabetes, you know this brand. And at the start of COVID, when they knew their business would be slowing down because hospitals would only be able to take care of COVID patients, they took the bold move of making their IP for ventilators publicly available. That is the power of a positive culture. Or Verizon, a major telecom organization looking at late payments of their customers. And even though the US federal government said, well, you can't turn them off, they said we'll extend that even beyond the mandated guidelines and facing a slowdown in the business because of the tough economy. They said, you know what? We will spend the time upskilling our people, giving them the time to learn more about the future of work, the skills and data and analytics for 20,000 of their employees rather than furloughing them. That is the power of a positive culture. So how can you transform your culture to the best in class? I'll give you three suggestions. Bring in a change agent, identify the relevance or I like to call it with them and organize for collaboration. So the CDO, whatever your title is, chief analytics officer, chief digital officer, you are the most important change agent. And this is where you will hear that oftentimes a change agent has to come from outside the organization. So this is where, for example, in Europe, you have the CDO of Just Eat, a takeout food delivery organization coming from the airline industry or an Australia national Australian bank taking a CDO within the same sector from TD Bank going to NAB. So these change agents come in, disrupt. It's a hard job. As one of you said to me, it often feels like Sisyphus. I make one step forward and I get knocked down again. I get pushed back. It is not for the faint of heart but it's the most important part of your job. The other thing I'll talk about is with them. What is in it for me? And this is really about understanding the motivation, the relevance that data has for everyone on the front line as well as those analysts, as well as the executives. So if we're talking about players in the NFL, they wanna perform better and they wanna stay safe. That is why data matters to them. If we're talking about financial services, this may be a wealth management advisor. Okay, we could say commissions but it's really helping people have their dreams come true whether it's putting their children through college or being able to retire without having to work multiple jobs still into your 70s or 80s. For the teachers, teachers, you ask them about data. They'll say, we don't need that. I care about the student. So if you can use data to help a student perform better that is with them. And sometimes we spend so much time talking the technology. We forget what is the value we're trying to deliver with this. And we forget the impact on the people that it does require change. In fact, the Harvard Business Review study found that 44% said lack of change management is the biggest barrier to leveraging both new technology but also being empowered to act on those data-driven insights. The third point, organize for collaboration. This does require diversity of thought but also bringing the technology, the data and the business people together. Now there's not a single one size fits all model for data and analytics. At one point in time, even having a BICC, a BI Competency Center was considered state of the art. Now for the biggest impact, what I recommend is that you have a federated model centralized for economies of scale that could be the common data but then embed these evangelists, these analysts of the future within every business unit, every functional domain. And as you see this top bar, all models are possible but the hybrid model has the most impact, the most leaders. So as we look ahead to the months ahead, to the year ahead, an exciting time because data is helping organizations better navigate a tough economy, lock in the customer loyalty. And I look forward to seeing how you foster that culture that's collaborative with empathy and bring the best of technology, leveraging the cloud, all your data. So thank you for joining us at Thoughtly.