When Paul Chapman assumed the role of CIO at Box, he moved from an established enterprise at HP to a company “born in the cloud.” I recently synched with Paul to hear his current perspective on digital disruption and learn how other, more established companies might pivot their innovation strategies to drive better business value.
Paul, how do we talk with you about digital disruption? As CIO of a company that was "born in the cloud," you ARE digital disruption. You work in an IT environment unencumbered by the technical debt legacy companies have. You have a workforce born and bred in an Amazon, Google, smartphone world. There is no “lag” at Box. How do you think about disruption coming from that environment?
There are two sides to this, right? There are established companies. And then there are the companies that were born this side of the century. These companies have been able to start with a clean sheet because they don't have the anchors of legacy that represent how they got to this point. So, they get to re-imagine the way things work.
I certainly have the perspective of coming from the large, 75- to 80-year-old enterprise to a company “born in the cloud,” one that is growing up digital with a Millennial workforce that knows no different. But it's not just about the technology—it really is about the culture and how a company like Box thinks.
We often get companies visiting on their Silicon Valley tour who want to understand how a company that is a “digital disruptor” thinks. They want to know how we operate, how we're set up, how we're organized. And it really does boil down to the fact that we have a new style of employee, a new style of workplace that is very open, social, and collaborative, and a new style of IT that's very much built for today's modern disruptive company.
What does this mean for incumbents in the marketplace? They have technical debt, legacy systems, and proprietary processes and platforms, all great from an intellectual property standpoint but maybe not great when they're competing with a company like yours.
Big successful companies have been focused on staying optimized to win in the industrial economy. And it's not like they're doing things wrong—in fact, they're continuing to do things in an incremental, step-driven, linear way to continually improve and make things better. But the rules have changed. You can’t continue to do what you’ve always done to stay ahead and be successful.
You can’t continue to do what you’ve always done to stay ahead and be successful.
At the same time, I think big companies know what they need to do and why. We live in a network economy, and we can connect with partners, suppliers, employees all over the world. Cloud computing has given us access to almost infinite compute. And mobile is everywhere. But incumbent companies struggle with the “how,” because they still have to take orders, ship product, and recognize revenue and so on. The how is very tricky. And there's no single way of doing it, as different companies use different approaches.
Incumbents have brand, capital, customers, and data. They have all of these very powerful pieces they can leverage to pivot, change, and transition. But the pivot to a different company is not driven by technology—technology is the enabler to the outcome. I think people have this sort of techno-panic because they think it's a technology disruption when it’s really an enabler. The disruption really comes from changing your business model and establishing a different operating model.
It's a different way of thinking, and that's something I appreciate being at a company like Box. If I think about the business and operating models of previous companies and how we could have taken the old model and made it look like this model, it wouldn’t have worked.
Companies with brand, capital, customers, and data might laugh at the idea that this is new. They feel they've been continually innovating or transforming themselves since inception. Certainly, some are not laughing, companies like Borders for example that have been entirely run over by digital disruption. But it does seem as though there are opportunities for established companies to fight back.
It's true with one exception. Some companies do change over time (look at Wrigley). But they change their business model over time, or they reinvent themselves as a different company. What is different now is the ability for companies to be disrupted so quickly. Over 50% of Fortune 500 companies since the year 2000 are no longer on the Fortune 500 list. The speed at which they are getting displaced is very, very fast and in some cases, you don't even see it coming because it's almost orthogonal.
You mention Borders, and I’m thinking about Blockbuster. In the early days, Netflix lagged way behind Blockbuster in market cap and revenue generation. But then this confluence of technology happened. Cloud computing enabled a new company to run on somebody else's infrastructure and thus, scale very reliably and very quickly. In the past, that couldn't have happened. You couldn't put a start-up together and go and disrupt Blockbuster if you didn't have access to massive amounts of compute. The time it would take you to procure it, invest in it, and manage it made the process very slow.
I do think that companies have a time window with which they can reinvent and come out the other side. But where they're also struggling now is on the cultural front. The millennial worker you mentioned, who has grown up digital and thinks and behaves with a different set of expectations, doesn’t necessarily want to go work for the stodgy old company that's 70 years old that makes infrastructure. And therefore, an established company’s ability to attract and retain top talent is actually becoming as big a problem as anything else.
Our status as a digital disruptor speaks to the culture of the company as much as anything else.
Changing tacks, how are you incorporating machine learning and AI at Box?
The latest research I’ve seen is that we will generate more data in 2018 than has been generated in the previous 5,000 years.
At Box, we see 40,000 files a second hit our platform. You know, billions, and billions, and billions of API calls every month. It's this massive tsunami of content and information that's being captured, and the machine learning algorithms are now sophisticated enough to provide real, meaningful business value back to your organization.
In the last year or so, we've started to see the emergence of real value coming back to enable better business outcomes, better intelligence insight, and so on, and what I really like the most about it is that it gets pushed to us. It's not like we have to go find it. Instead, there's this high level of intelligence around me as an individual, as a company and so on.
What are some examples of the value you’re seeing?
We see some of this in our personal lives, in the form of intelligence around our patterns and what we do on a daily basis. Think about what's going on when you travel today. Machine learning around your travel patterns is helping to create frictionless travel experiences, telling you whether your flight is on time, the gate has changed, and that type of thing.
We also see it with pictures. A meter reader today can take a picture of a gas meter and AI can immediately return the name, the make, the model, even the working condition of that meter.
But where we see real practical value in the enterprise is in being able to leverage machine learning services, whether they're built by Google or IBM or whomever, to add significant value and levels of intelligence to content that we previously couldn't access.
For example, somebody may have a video or an audio recording of a sales call or an audio recording of a customer service interaction. You can now take that voicemail, and based upon machine learning characteristics, break down that conversation into every word that was said and complete a full sentiment analysis on that dialogue.
Many things like that are just emerging. With something as simple as a contract, we now have the ability to quickly extract intelligence about terms, conditions, and so on. Not only do we have intelligence gathering speed, but the data is being collected at a higher sophistication level.
Contrast the act of filing a picture. Our human selves take a picture and store it, but it's really hard to find later. You have to categorize it, name it, add notes ("This was my vacation"), etc. for each image. Whereas, if you could just put an image on Box, AI will tell you, "Oh, this is a picture of you in Hawaii, on the beach, at a particular restaurant, at a particular time." And you don't have to put in all that information because it’s automated. And that's very real today with things like Google Vision and more.
That sounds exciting and frightening at the same time.
Yeah. The intelligence is getting better and better. If you sent a picture a year ago to Google, it might have returned a finding of “This is somebody with an animal." Now it will say, "This is a picture of a man with a poodle in front of a pet store." And it’s continually evolving. You can send the same content over in six months and it will come back with even more intelligence.
If you think about the applicability of that in the enterprise or the business world, the possibilities are endless. We're on the tip of the iceberg, but some of the things that we're seeing today are really amazing. You could upload 1,000 pictures, and then you could say, "Show me every single picture in which somebody is wearing a Nike Dynamic Fit in black." You could take a picture of a crowd, and it could tell you that.
What kind of data is most helpful to you in your role as CIO? How are you using data today and how do you envision new data changing your IT environment?
Well, the data we use at Box is not as sexy as the drone captured image of damaged railway tracks. Nonetheless, we capture data that is very relevant to us. We get usage statistics, interactions, engagement data, etc. around our platform—we call it the Sophistication Index. The analysis we get from that is critical to the evolution of our service delivery, and so on.
On the flip side, we're tied in with a lot of what other companies do, where the data analysis is about our pipeline and intelligence. For example, we’re able to automate digital assistance, which replaces the need for mundane, manual type of work like chat. So, we use data to think about business metrics and how we can move those metrics in the right direction.
What are the top ways that machine learning or AI will fundamentally change your business?
In an almost boundless way, AI fundamentally changes how we help our 80,000 customers. For example, there are companies that are dealing with hundreds, if not thousands, of contracts every year. Historically, people would have to scan and upload the contract and then they'd have to decipher it and enter a whole bunch of information about that contract. Well, now you can literally onboard thousands of contracts and completely eliminate the need for human data entry. There's a subscription-based machine learning service that will effectively pull the same intelligence that a human being would have entered into the system—the error rate is far lower and the quality of the intelligence is higher.
Those are things that will change the business because you're eliminating mundane tasks, and that focuses your employees on higher value work.
When you are thinking about the business case for adopting AI, do you model the potential savings in terms of a reduction in human labor and does that labor shift to something else? How do you model the additional value you’re getting?
These types of investments do not necessarily have a hard ROI or savings that goes to the bottom line. Instead, they improve employee productivity which is less quantifiable.
However, a lot of the investments we’ve made do have metrics behind them which can be quantified into productivity gains. Once the core infrastructure is in place, investments in the area of workplace productivity are primarily software driven. Through proof of concept and a pilot process, we are able to evaluate the benefit of implementing before deploying more broadly.
What is the overall effect of the convergence of these tech trends?The slowest rate of change we'll ever experience is the one we're experiencing now. Every time we think things are accelerating, we realize they're actually slow compared to where we're headed.
The slowest rate of change we'll ever experience is the one we're experiencing now.
And if you think about where we were within just the last decade, in terms of the technology we had available to us, it’s amazing. How many devices do we have in our homes now that are connected? Printers, refrigerators, toasters, thermostats, doorbells, high definition TVs, and so much more. A ring connects my whole home security system, and it's simple to set up and manage on an app.
It’s all about this ability to connect, and the technology that supports that. Today, we rely on stable, scalable capacity, mobile ubiquity, and a networked world we didn’t know could exist ten years ago. As this confluence of tech trends comes together, we're going to see a whole new set of things emerge that we can't even imagine right now.
How do you get your head around this rate of change and how do you use it to your advantage as a CIO?
You could go crazy running around and chasing the next thing that's out there. But you have to distill it down into what is important for your business. How can this emerging capability be applied to the business to add value? What business problems are you trying to solve?
At Box, we're in the business of solving challenges and adding value for customers who have more complexity than we do. I don't have a lot of need today for massive amounts of machine learning to run the business at Box. But I do think there's an opportunity to leverage machine learning to increase employee productivity. How do I make my workers or employees more productive? How do I take the work out of work? How do I create more of a touch/text tool interface? How do I create more digital systems to handle mundane, standard, repeatable work? That’s where I want to focus.
What's important for CIOs and other IT leaders to recognize across the spectrum of technology is how things fit into their environment. When I was at HP, my perspective on technology was different than it was at VMware. Some things are probably applicable at HP around machine learning that aren't applicable at Box. So, you have to ground yourself on what applies to your current environment and company.
In this environment of accelerating change, is it a good time to be a CIO?
I think it's probably the best time ever to be a CIO. No matter how you define the role, the value that a CIO brings to an organization is only going up. The years of underinvesting in IT, keeping the lights on and running the back office, are over.
Most companies are now saying, "Hey, we're a technology company." For that to be true, you have to think like a technology company and, you know, CIOs are pretty good at that.