Friday, October 26, 2018

CEO SPECIAL .....From start-up to scale: A conversation with Box CEO Aaron Levie PART II


From start-up to scale: A conversation with Box CEO Aaron Levie PART II
Simon London:But that’s really interesting, isn’t it? It shows that there is patient capital out there, but you have to align the investors.
Aaron Levie:And it can be very scary at times. Because if you go off course for one or two quarters, then all of a sudden the whole model changes in some fundamental ways. When you’re burning cash, the model is very, very sensitive to what your assumptions are, and the moment those are wrong and either your growth is faster than you expected, so now you need more cash, or the growth is not there, but you spent the money. In both of those scenarios, it’s very dangerous. We have been blessed by a very strong finance and strategy-planning function. Without that, I think we’d be in a very different position.
Simon London:Right. Can we talk a little bit about technology trends?
Aaron Levie:I love those.
Simon London:You were born on the right side of history with respect to cloud, right?
Aaron Levie:Yeah.
Simon London:Then you got on the right side of history with mobile, as I understand it.
Aaron Levie:Yeah.
Simon London:That was, you saw that coming, and you moved on it. So what’s coming next, and how do you make sure you’re on the right side of history? What’s the big thing?
Aaron Levie:I think today’s version of those is, how are you or how is any company thinking about AI and machine learning? One of the really important things is, it’s not enough to just say, “OK, we’re doing AI” or “We’re doing machine learning.” The dependency of doing AI or machine learning really well is, do you have your data set in a form that you can make use of and make sense of?
And a lot of companies are not thinking through their long-term technology strategy to say, “Is my information being managed, stored, organized in a way that I’ll eventually get the kind of accretive benefits of AI on top of this data?”
Simon London:I think it’s what people call data strategy, isn’t it? You’ve got to get your data strategy right before you even really start rolling out.
Aaron Levie:That’s exactly right. And you have too many organizations that have fragmented data where you don’t have the connection between different objects and between different data sets. For us, we are benefiting from the architecture decisions we made 13 years ago about being in the cloud. It means we have all the data in one place. I think a lot of customers have to think through, in three, or five, or ten years from now, are you going to be able to leverage best-in-class AI or machine-learning technology? Is your data in a format? Is it stored and managed in a manner that lets you take advantage of that? So that’s a big one.
When we think about our overall strategy, some of it is becoming one part technology as it relates to the deep technology architecture and one part more the science of management and how that is changing. The coupling of technology and business culture—and are we setting our product up and are we setting our business up to be at the center of where we see the future of work?
That obviously is super important to us because our whole product is 100 percent driven by, can we enable companies to work in a modern way? Which means we have to make sure we understand and we see what that modern way of working is all about. That’s where we spend the majority of our time.
Simon London:Let’s talk about the future of work, because it’s an interesting topic that has a number of different meanings. A lot of the stuff you see written about the future of work is just how much work there is going to be ten years down. But I’m guessing that’s not really what you’re talking about. You’re talking about how work will get done within enterprises.
Aaron Levie:To that point, there’s a future of jobs. So the jobs themselves: What are the job categories? Who is going to do what? Then to us, when we say future of work, we think about, OK, what does work look like? How does work get done inside of an organization? Whether that’s knowledge work or industrial, mechanical work, whatever that work tends to be.
We think we’re at this fundamental juncture where the 100-plus years of industrial-age management systems and practices are showing signs of not being able to scale for the digital age and not being able to translate well into the digital age. When you look at the hierarchies of organizations, when you look at the workflow patterns and processes of organizations, the waterfall methodology of product development and decision making, the asynchronous flow of data throughout an organization—all of these things we think are going to be rendered completely useless in the digital age. And not just useless, but in most cases slowing down companies and how they operate.
We think that, interestingly, a lot of the lessons to be learned are from software start-ups and the practices that smaller start-ups have had to learn in the software-development practice of being agile, being able to iterate quickly, having a tremendous amount of data to make decisions from, making sure that you have small teams that can move rapidly, being very, very close to the customer . Those practices that were built out for software and for the internet translate now into every part of a business, whether that’s HR, finance, product development, and marketing. That’s the profound change in business, which is taking these agile, team-based practices of building things and now translating and having that manifest into every part of an organization.
Simon London:It’s moving from what I like to think of as agile with a capital “A,” or actual hardcore agile software-development methodology, to agile with a small “a,” or agility.
Aaron Levie:Yes.
Simon London:And how do you take some of these practices and that whole ethos and spread it out across a company?
Aaron Levie:Now, the question is, are large enterprises prepared both culturally and technically to be able to get there? We spend a lot of time with large-enterprise customers that are going through that journey, and they’re kind of saying, “OK, it’s not enough to just have modern technology. I can buy every cool new Silicon Valley software start-up product, but if my culture doesn’t change, I actually can’t get that much use from this technology.”
Conversely, you can have the world’s best HR leader and the world’s best CEO driving transformation, but if your technology stacks mean that people can’t share data, they can’t work in real time, they can’t collaborate across the traditional divisions in their organization, then no amount of “cultural change” is going to manifest in real productivity.
The thing that we’re seeing, which is a pretty interesting trend, is the complementary transformation that’s being driven from the IT technology organization as well as HR and operations. These things are feeding off of each other in a profound way and that we think are going to collude to then ultimately transform how companies will operate, which is that you have to get to smaller teams that move much more rapidly and that have permission to fail but iterate constantly. They have to have data to get their jobs done. They have to be able to connect up to the rest of the business, so people know what’s going on. That creates an environment of a lot more transparency, a lot more openness, and a lot more inherent accountability, because you can see what’s going on.
There are a lot of cultures that are not prepared for that. That’s going to be one of the biggest tests of which companies in the Fortune 500 make it to the digital age, or make it through the digital age, and those that don’t.
Simon London:How do you think about that in terms of Box’s own operations? Because, increasingly, you are delivering at scale, it has to be an incredibly reliable, secure service. So in many ways, you’ve got that foundation that you need to operate. It means we are totally reliable and secure. But on the other hand, as you say, you’re trying to move fast. You’re trying to iterate. You’re trying to learn quickly in agile-type practices. How do you marry those two things together? Which is the challenge that a lot of big companies face.
Aaron Levie:This is absolutely the paradox of the digital age, which is that you have to move insanely quickly to stay competitive. At the same time, there are a lot of business processes that were not built for that kind of speed of iteration: if you’re building a car, if you’re building a jet engine, if you’re delivering a new medical treatment.
Simon London:Yeah. Is it even desirable?
Aaron Levie:Right.
Simon London:I’d rather have my plane made slowly. I don’t want it to fail fast.
Aaron Levie:This is definitely the challenge that a lot of organizations face. I think the key is to be very, very clear on which business processes you can afford to have this kind of level of iteration, agility, and fail-fast mentality. We don’t have a take-risks approach in our accounting process. However, we still use a lot of agile practices when we are closing the books.
We effectively have scrum team meetings where everybody’s getting together, standing up, talking about what are the latest activities that we have to do. The failing fast is, if something’s off track, we’re going to iterate, and we’re going to know within a day or two of that happening, as opposed to the very typical process, which is, I only find out three weeks later that somebody upstream from this process ended up doing something in a way that had the numbers wrong or created some problem.
The idea of agility, and the idea of agile with the capital “A,” is, you get people much closer to the work and much closer to the ultimate customer. They are sharing information on a more frequent basis. They are much more accountable and fully own the problem. That transcends whether you’re building the most trivial software or doing jet-engine design or missile design.
CONTINUES IN PART III

No comments: