Self-Service Analytics and the Future of Work with Saket Srivastava, CIO at Asana

Thanks a lot, Thomas. Nice to meet you, VJ. That was some generous introduction. Looking forward to this conversation.

Sure. So I've been at Asana for about a year and a half now, and I've been a CIO at other places as well. A long-tenured IT career, started my journey with an undergrad and a postgrad in computer sciences. Worked for very large companies, started with more professional services, transitioned into IT leadership roles as well. And so I've been with companies like General Electric, IBM, Fujitsu, Symantec, and some very modern companies like Square, Nubank, Guidewire, and Asana. And just enjoy the work that we do here at Asana, motivated by its mission, and looking to move the company forward.

So we're going through a very interesting phase with this macroeconomic climate that we are in, and every CIO that I talk to, engage with, including obviously my priorities that I'm navigating at this point in time, it's really a lot about how can we drive efficient growth. How can we focus on growth but by removing the surplus, the excess that we have, and pivoting and redirecting all of that towards the growth initiatives. It's also all about the CIO function not acting as a backend function, an engine in the back, but more in the front as a business strategist, someone who has a seat at the table driving direction and strategy for the company. And for all of that, data is front and center. So that's how I sort of look at my role, and those are things that I'm prioritizing.

So Asana is a consumerized enterprise software company. For very long, we at least in as IT leaders, the enterprise software that we've been experienced with are softwares that do the job but no one really loves it, no one really likes it. Asana is different, and there are some companies like this, right? Which means that these are companies that individuals and teams and functions try out and they love, and then their usage expands broader within the enterprise. So that's sort of the product-led motion wherein the product itself sort of acts as a sales vehicle for the company. So obviously when a product is peeling for itself in many ways and acting as a sales vehicle, on our end we're collecting a ton of data as well. We're collecting a ton of data around how what we do is adding value to the customer, what can we do more that will add value to the customer. So from a product and a customer standpoint, that's clearly a focus. From a data standpoint, understanding how our customers are using our product and thinking about how our customers will get more value from our product. From an internal standpoint, also collecting data from the different parts of the business and seeing how can that be leveraged, the insights that we gain from that, how can that be leveraged to again serve our customers best through serving our business and functions, giving them the insights and the capabilities so that they can serve our customers best. So I do feel that Asana is a data-heavy, data-rich, data-mature company wherein all our key decisions rests on foundations of data and insights and analytics that we built over the years.

Well, it's something that inspired me because a lot of this has been done before my time at Asana, and so that's certainly inspired me to consider joining Asana. But really, I think the way the company's mission is, that's really where it starts, right? So Asana's mission is all about helping humanity thrive by enabling the world's teams to work more effortlessly together, right? And it's a lofty mission, right? And as missions should be. So really, when you start from a customer standpoint on how can you enable, empower, benefit the customer, and if everything that you do is from that lens, I think that's how it really starts, wherein you're truly trying to understand the customer pain point and how you're going to serve and improve the customer's day in a life. If you start from that mindset, I think you're starting on the right foot. Clearly, there's a ton more for you to do. And it's sort of obvious, as VJ, you're saying that every SaaS company aspires to do that or needs to do that. As a CIO who looks at a lot of such vendors and companies, I am still very surprised that a lot of companies are not able to get that. And there are some that are, and those are clearly standing out. And to me, really, it's about workers today, millennials, Gen Z, all of these workers today, they experience in their day-to-day personal lives an experience through the companies or products that they experience a very different experience. And when they come to their work, they don't get that experience. So the companies that are able to sort of give them that kind of experience are going to be successful. And really, as I mentioned earlier, it starts from that customer lens, trying to build that empathy, trying to understand truly what the customer is trying to do, and then applying that design mindset to help solve for it.

Totally. I mean, I think it starts from there, and then everything that you do from there on, that customer empathy, that customer appreciation, it really starts from there, right?

Totally. Again, this was one big reason why I decided to join Asana in its journey. Because again, as an IT leader, as a CIO, I've had the experience, and a lot of my peers will share this experience as well, where from a function that we have, we're tasked to run large cross-functional programs. And we're at a vantage point wherein we understand what every function within the company is trying to do. Anytime you have to run or execute large cross-functional programs, it is hard. It is really hard. When things are managed and done just within function, I think it's still manageable. But when things start going across function, it becomes really hard. And increasingly, we've done some research around this area, we find that increasingly more and more work is done cross-functionally. That's where platforms like Asana stand tall, right? In the past, when we've had to do these large transformations, it's been very hard and the chances of success is rather low. Also, not being able to connect the strategic goal with the initiatives, or even for the workers, the work that they do with what's moving the needle for the company, these are the reasons why I think someone should consider an Asana-like platform. It's a work management platform wherein you're able to connect your strategic goals for the company with the actual initiatives and the work that needs to make that strategic goal come true. And also for the people who are actually doing the work, how does their work ladder up to the strategic goals of the company. And then obviously there's the automation around workflows and stuff, program management, portfolio management. These are hard problems to solve. There are many players trying to do that. I'm just inspired and motivated by how Asana is going about doing that.

I love that term, right-sized collaboration. Yeah, again to that point, Thomas, there's a fair bit of research that Asana does, and there's a Work Innovation Lab that we have, and they talk about collaboration. Over-collaboration is bad, under-collaboration is bad, and there's a right amount of collaboration that's needed for teams to be highly productive, high-performing. And if you've not seen that, I'd encourage you to see that.

I think it's a combination. But certainly, our product managers, our growth managers rely heavily on data to see data on how our customers are using our platform, how frequently are they using, what capabilities are they using, right? Which capabilities are resonating more with them and which are resonating less with them, and that sort of informs in large part how we sort of decide to go about our product roadmap as well. And yes, there's enough self-service that happens, but there are times wherein they rely on data scientists to build models and experimentation and all of that stuff to see what's working or what's not working.

So it's a combination of build and buy on our end as well. In terms of the tools that we use, we certainly use Tableau across the board. We've got Snowflake that we use for enterprise data. There are a bunch of other tools, Airflow and stuff for orchestration and stuff. And then we've got data engineers, we've got analytics teams, we've got the traditional sort of BI kind of talent as well. You've got data scientists who are understanding product usage. There are data scientists who are trying to understand and guide how we run our business as well. So there's sort of a well-thought-out way of how we leverage data to drive the company forward.

There's a reason why shadow IT happens, right? I'm not the one to say that shadow IT is just bad, right? If there's a gap that's not being met, someone needs to go solve for that problem, right? If the CIO function or the IT function or the data function is not solving for the need, absolutely someone needs to go and solve for that problem. But again, as a CIO function, it's important that we provide the necessary guardrails where things just don't go haywire, right? From a security standpoint, from a compliance standpoint, from a privacy standpoint, we are the ones who need to start thinking about that and provide that guidance to our teams also. Especially around data, data governance is huge, data quality is huge. If you allow things to just mushroom on their own without any sort of central governance, then that data could just become so messy for you that one team's talking about something else and other team looking at the same definitions getting some other numbers, right? So creating the right level of data governance and as I mentioned, those checks and balances around the security, compliance, I think it's the important step. And I'm not the one to say that everything should be centralized. There are certainly needs where things should be decentralized and enough self-service made available so that people who can build on their own, and that certainly gives you greater velocity as a company. So we're not the ones to say that let's just drain everything in, but just put in enough controls and checks.

Yeah, I do believe, I concur with you, VJ, there that best of breed, there is a place for best of breed. There was a need for best of breed. The platforms of yesteryears could not serve the niche needs of some use cases and functions, and that's why best of breed came about. But we all might have sort of over-indexed and gone towards the other extreme in this journey of best of breed. So I believe that a central function like the CIO, the data officer, the digital officer needs to have control in limiting that sprawl. It's important to standardize on a few platforms and yet look for areas where you need to go towards best of breed because that provides you a strategic differentiation and an advantage that the platforms that you've centralized on is not providing. But it can just be that anyone and everyone is deciding to use a tool of their own because that's what appeals to them. So again, a function like ours should provide enough control and guidance and education to tell people, hey, you're going out looking for something, here there is something already available in our suite and in our offerings that you should consider as opposed to just going somewhere else. Because the challenges, as you highlighted, VJ, is manyfold, right? Your data is now siloed. You need to start thinking of integrating these so that if you're not integrating these, there's so much swivel-chairing that someone needs to do just to get a complete answer on anything, right? If you're trying to, just for an example, if you're trying to get an understanding of a customer or an account or a user, if that complete end-to-end, let's just say customer 360, sits across multiple tools, then you're having to swivel-chair as a user across multiple. That's a time suck, that's a productivity kill, right? And so that's where thinking through from a platform mindset is important. And yet if there's a real need for best of breed, you might want to consider that. That's how I think about it.

I actually think about data warehouse more from a single version of truth, if you will. I look at those operational systems where data has been captured. Some of that needs to, like a customer master or a product master, I would expect one of my operational systems to perhaps act as that. And then you bring all of those different elements of that asset in the data warehouse so that you have a fuller view. And that's how we use it as well, right? So we've got pipelines that feed data from several of these systems, tools into data warehouse, Snowflake in our case, and then we create models on top of that, and then we visualize for the use cases. But yes, the full view of say a customer or a user is certainly maintained and managed within our data warehouse as well.

There's certainly a lot of promise to it. I mean, we're early in our experimentation in the space as well. But we recently rolled out a capability around prospecting for our sales team wherein we built an application directly off Snowflake. And what stood out was the rapid prototype iteration that we were able to do and the time to value. So this required less of piping data into different systems and less of building those integrations and stuff. The data is already there, you're building an application on top of that. And the feedback that we got from the field was overwhelmingly positive. So that's a good quick prototype that we put out there. I think that shows us that there's promise in this and we want to kind of lean in more heavily into this. But I'd love to hear from you if you're seeing more of this because this is how you're sort of building your platform on as well.

Yeah, in our case, we were able to shift delivery from months to weeks, and that clearly sat well with the users who got to gain value from this way.

Absolutely. I can certainly see that. Bottom line is if there's value, if there's security, appropriate controls, role-based access controls, privacy, all of that stuff is taken care of, and faster time to value that we're talking about, then why not? I'm familiar with this connected apps kind of concept. I've seen other CIOs show me some of the work that they've done. I can absolutely see other CIOs and IT leaders warming up to that.

I think there are two perspectives to this. One, there's just a whole lot of talk around generative AI, right? It's overwhelming to some extent, but it's a game changer as well, right? So we at Asana, I don't know if we should call ourselves fortunate, but the foundation on which Asana is based on, our architecture, what we call the work graph data model, lends itself beautifully to building, creating AI capabilities on top of that. And not every company can say that. So maybe I shouldn't say fortunate, it was well thought through by our co-founder Dustin Moskovitz and the people who were here earlier. So it sets us up well to make our investments and move forward in this AI journey. So how it helps is we'll be able to again bring AI capabilities faster to our customers because of how our data model is structured. And we've recently launched, as I mentioned, Asana Intelligence, and there's just a ton more work that's happening in the space. And this could be anything around how can we add more productivity and velocity to our customers. Our approach to AI has been more human-centered, wherein we're not saying that AI is going to replace humans, but at the end of the day, the accountability sits with humans, right? And AI is here to sort of be that co-pilot, that assistant to the human. So that's from a product standpoint. From an internal technology leader perspective, I'm staying curious, I'm staying hungry, I'm listening to everything that I'm seeing around that my partners and vendors are doing because I don't want to be going ahead and solving for all of those use cases myself. Where need be, I will, but I also want to lean into my partners who are also investing in generative AI to be brought into their products as well.

And really, VJ, the amount of waste that happens in an employee's work time is surprisingly very high. Again, the research that we've done, we find that an average worker spends 50-55% of their time doing work about work, right? And if you have an AI assistant that's able to meaningfully sort of reduce that waste for you, which is how we're thinking about our AI assist, Asana Intelligence, then it's a game changer, right? There's just so much more that an individual and teams and companies are able to then do because now they have this Asana Intelligence which has all the work data that's being captured on the platform and it's able to provide you with insights and guidance. It's able to now make your tactical, even more intelligent things easier for you, and then you're able to spend your time doing more strategic stuff.

Yeah, that makes absolute sense. The future of work is certainly much more collaborative, and with AI and automation to eliminate the unnecessary work is really going to be a game changer. And I can certainly attest to my own personal need to be able to focus on more of the strategic versus all the day-to-day execution tasks.

So data analytics is something that's been on a tear for the last several years, right? I mean, there's just so much demand, so much need that you've seen so much innovation happen in this space as well, right? There's clearly a lot of attention that the VC community, that the startups, you all as well, have provided to this space. And we're clearly in a much better place. There's more democratization of data, there's easier access and tools for end users to go build on top of and not just have to rely on teams like ours to come to us and ask for reports and data and all of that stuff, right? So from that perspective, I see the data journey to continue, right? With the generative AI, massive amounts of data, and how can that all sort of be computed and provide guidance to users continues to happen. I am just excited to be sort of on this journey and see how as data leaders we are able to solve more real problems faster and drive company's direction in a more meaningful way.

Thank you. Thank you for having me, both of you. It's been fun talking to both of you.