Asana CIO Saket Srivastava: "Best of breed" SaaS has gone too far

Cloud computing sparked an explosion of entrepreneurship in enterprise software, but 15 years later, the situation has gotten out of hand, according to Asana CIO Saket Srivastava.

Asana CIO Saket Srivastava
Asana CIO Saket Srivastava

Cloud computing sparked an explosion of entrepreneurship in enterprise software, freeing IT customers from the burden of having to implement big expensive packages of enterprise software and allowing them to pick and choose the best products for a given task built by focused vendors. But 15 years later, the situation has gotten out of hand, according to Asana CIO Saket Srivastava.

"Standardizing on key platforms absolutely makes sense," Srivastava said in a recent interview. "We are taking a harder look at which (tools) make better sense for us, which ones are the ones that are giving us more value, and doubling down on those."

If this approach catches on more widely — Srivastava believes a lot of CIOs currently feel the same way — it could shift power back to the larger established enterprise software companies and make life a lot harder for startups and other enterprise tech companies built around a single killer product. But don't expect to see a return to the "CIO Knows Best" days of top-down technology purchasing decisions, he said.

"Our employees, workers, engineers; they are really smarter than us," he said. "You can't necessarily be just telling them 'this is the answer' and not listening."

In a recent interview, Srivastava also touched on Asana's approach to the internal use of generative AI tools and the "new age" CIO.

This interview has been edited and condensed for clarity.

How does Asana think about its infrastructure strategy?

I don't necessarily know if we're doing something very different from what (other) companies might be doing, because it's pretty much a playbook in many ways. (But) what might have happened, what has certainly happened in our case through COVID, there have been investments that have been made in the name of technology to improve employee experience in this concept of the future of work and we might have created a fractured digital experience.

So now is really a good time for the CIO function to double down and simplify our stack in many ways, wherein we take a harder look at the technology that we have in our environment and double down on technologies that are driving value for us. Also start thinking in more of an enterprise architecture mindset, where there's a cohesiveness around the experience for the employee, and look at the tools and technologies that might be out there that we're not getting value from and then eliminate those.

Can you give me some specifics on exactly what you're doing to double down and simplify your stack?

Essentially what we're looking to do is consolidate. So if there's a use case, let's say around go to market, around pipeline generation, or it's around enrichment of information or data infrastructure that we implement and support for the organization, I want to make sure that we have a consolidated stack. We are taking a harder look at which ones make better sense for us, which ones are the ones that are giving us more value, and doubling down on those.

There's all kinds of different approaches and opinions about enterprise software and cloud computing, like, do we want to be all in on one cloud? Do we want to be spread across multiple clouds? What does Asana think?

In the journey for Asana, and more broadly for the CIO community that I engage with, there was a shift — even in the large companies — when we've probably gone overboard with best of breed. And over time, there is a realization that in some cases, best of breed makes sense. But that's not a good answer without going deep into the "why."

Standardizing on key platforms absolutely makes sense. From an experience standpoint, from a cost standpoint, there might be better value in standardizing on a few platforms, and then looking at best of breed use cases where platforms are falling short and then plugging those holes.

Going overboard on the best-of-breed thing is something I've definitely heard from a lot of people over the last year or so. I know a lot of people are struggling with this question, and how to think about making these decisions. What helped you understand that you might have been over indexed on best of breen and needed to think about "good-enough" solutions that allow you to really move forward?

It's a balance of moving fast at all costs, or being thoughtful in the investments that you make. And I do believe that there are several companies and industries, especially through COVID, who had tail winds and in the name of wanting to move fast, a lot of visions were made which were not as well thought out.

Really it's about, what is a strategic differentiator for you? If there's a use case that really is going to drive your business forward, then you absolutely want to go all in trying to meet each and every must-have requirements that are out there. That might compel you to go towards more of a best-of-breed use case.

Other than that, there is a lot more merit in standardizing on platforms, which in some cases, meets you exactly where you need to be met and in other cases, it's good enough. Because something that we as CIOs see quite a bit these days, there is so much productivity loss that happens when employees are having to navigate across tools and systems. And sure, we've invested in data and iPaaS platforms and all of that stuff to try and improve that experience but that is a significant source of drain.

A lot of that's come up because over the last, let's call it a decade, a lot of the purchasing power for these tools shifted from sort of the top-down CIO approach to the department level, where folks basically had the budget and the authority to choose to choose the tools that were best for their teams. Do you think that that has really come back to the point — especially when an awful lot of technology companies are watching their technology spending very closely — where the CIO has a little bit more central control?

I like to think about it as less of a know-it-all IT, because that will not persist.

Sure, this is a time with a challenging macroeconomic environment and there's a ton of sprawl, and you can over index and sort of centralize everything. (But) if you're not able to meet and partner with your employees and create an environment where there's trust, and then you sort of seem to be overriding them, and not taking them along in that journey and the rationale of the why, then this is not going to be sustained.

I liken this to maybe spring cleaning. We've got a ton of sprawl, this is a great opportunity for us to sort of control costs by consolidating and standardizing, but do it in a thoughtful way; not because you have the mandate and you can drive this change. This is the time to establish that trust, and take people along on that journey.

This is again a shift for the CIO function, wherein we need to sort of be sort of in lockstep with our employees a lot more. Even for technology companies, our employees, workers, engineers; they are really smarter than us. You can't necessarily be just telling them "this is the answer" and not listening.

That's sort of another important aspect of a new age CIO function, wherein you're listening more, you're communicating more, you're taking your workforce along on that journey, as opposed to operating on the back end and rolling out things and visions that no one seems to understand.

How does Asana advise its employees on how to work with generative AI tools?

It's a balance of being excited and curious and yet be cautious. What we're doing specifically at Asana is we are encouraging our workforce to learn more and experiment. We've given them the guardrails, we've told them the ways that we support people using and the ways that they should not be using generative AI.

Can you give me a better sense of what those guardrails are?

We've done some training wherein we told our people, this is a more secure way to use it. We've also purchased enterprise licenses of some of these (tools). And we allow people to use that, which helps us (ensure) our data does not go outside and train the models. So really, it's that approach of training people continuously on an ongoing basis and providing them secure ways to engage (with the tools).

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