The Big Deal About a Big Data Culture (and Innovation)

Bruno Aziza, Vice President of Worldwide Marketing & Data Geek, SiSense

Bruno Aziza is a self-professed big data nerd.

His title at data analytics company SiSense: Vice President of Worldwide Marketing & Data Geek. His LinkedIn profile photo is of a guy displaying a t-shirt hidden under his dress shirt, Superman style, emblazoned with the words (you guessed it) Big Data Nerd.

Aziza?s credentials, both as a nerd and a thought leader, are robust. Prior to SiSense, he ran data analytics programs at Microsoft, Apple and Business Objects (now a SAP company). He is the co-author of two books in the business analytics space, one of them the best-selling tome, Drive Business Performance: Enabling a Culture of Intelligent Execution (Wiley, 2008). He is a fellow at the Advanced Performance Institute, an independent advisory group specializing in organizational performance, and he has over 12,800 Twitter followers at @brunoaziza.

In a conversation with Renee Boucher Ferguson, Data & Analytics contributing editor at MIT Sloan Management Review, Aziza talks about the burgeoning role of data analytics in today?s organizations, what it takes to be successful in utilizing data and analytics effectively (in a word: culture) and the role of innovation in a data-driven organizations.

What do you think has changed in the last two or three years since you wrote Drive Business Performance, in terms of how companies are developing an analytic culture?

Joey Fitts and I worked with Tom Davenport, Robert Kaplan and David Norton on the book. We gathered insights through interviews of organizations to determine what it takes to develop an analytical culture. We developed a methodology called the Six Stages of Performance that you go through as an organization to develop an analytical culture. That hasn?t changed.

But there are quite a few things that have changed. The first thing, the motivation for why we wrote this book, is that we saw that there is a divide in the industry. The first divide was, there are lots of books out there that talk about the technical capabilities required in order to be more analytical. And while they were good, they focused so much on the dashboards and the bells and whistles that people kind of forgot why they were doing it. They were just doing it because they could, and that?s detrimental.

The second type of books was talking about culture theory, but really weren?t giving much specific, pragmatic guidance. What are the stages that you go through in order to develop an analytical culture. How do you start from scratch? It?s great to have a theory about the benefits of why anybody should be more analytical, but if you don?t help them get there, they?ll never get there.

So that gap, there?s more awareness about that. It?s not about the business in IT, and I think that?s becoming more of a well-known problem.

Secondly, I think the term analytics has raised the awareness of the problem. Before we used to call this business intelligence, and it?s funny how just the change of a term to business analytics made other people want to be interested in it. Also the financial crisis has helped people realize that you can be doing business in the old fashioned way, or you can be trying to be smarter than the other guys. And a lot of times, logistics efficiency and all that can only give you optimization. But if you?re looking for a game changer, analytics is probably where you?re going to be. And we?re seeing that now, by the way, where companies are realizing analytics are actually at the center of their company, whereas before it was just at the edge.

There?s also the interest of students and more talent that want to develop in this world of the data scientist, so there?s an appetite both from the companies, and from the people that will create the space 10 years from now. That is interesting.

How does a company that doesn?t have an analytics culture in place move forward in developing one?

What we found is that there are six cultural stages, kind of like the five stages of grief, except that this one is a positive one because the higher you go the better shape you?re in.

The first stage we call Increased Visibility. This is when people are looking at data and they?re not able to realize what the data is telling them. They see a picture and they say, ?Well, is this a picture of somebody robbing the bank or somebody that?s protecting the safe?? They see the context but they don?t understand the details.

The second stage we call Move Beyond Gut Feel. It?s the ability to understand the data and its details and apply judgment to it in a way that tactically, you?re able to react to information faster than anybody else. In these first two stages, the types of problems you?re trying to solve are backwards looking analysis. With respect to technology, you?re basically building infrastructure so you understand where your data comes from and what happened yesterday.

The third stage is Plan for Success and it is essentially saying, ?Here is what success means.? Here is what we can say, based on what we know, what we think we should be able to achieve. And that informs our strategy, It?s really only when you have that kind of handle on the world, if you will, that you?re now able to do the next set of stages.

Stage four is Execute on Strategy. So basically we can now align our strategy to our knowledge, our understanding of the world from a complete standpoint, and our ability to adjust based on success or failure on certain actions. Very few companies are at this stage.

Now there are a few more organizations that continue climbing. What happens next is what we call the Power to Compete, or stage five. It?s only when you have visibility, when you?re able to understand your full context and define a strategy that you can execute on, and you understand the levers, that you can truly then stretch your organization to a point where you are able to compete. But when we mean compete, this is not just making deals. We mean compete like taking strategic market share from the market you?re in, or adjacent markets.

Stage Six is achieving a Culture of Performance, which is more of the North Star rather than a place where you end up.

Are there characteristics that you can point to that leading organizations ? those very few that are at stage five or six ? have in common?

We talked to a VP at Wells Fargo. His name is Walter McFarland. He talked about the culture of ?run it like you own it.? I thought it was a really good tagline. Run it like you own it means this is your business, you?re in charge of it. Credit or issues, you?re fully responsible. And this sense of empowerment, of course, came with a bunch of other tools that the company would give the teams, and help them with increasing performance.

We also found a mandate coming from the top is highly differentiating, compared to people looking for validation or sponsorship from the top. So in the case of run it like you own it, most of the companies, they all have a leader that believes in it and drives performance across the company.

Does cultural change have to come from the CEO level down, or can other executives in the organization drive cultural change?

Absolutely, and we saw this again and again. One of the best examples was with Energizer?s CIO Randy Benz ? he wasn?t a typical CIO. He was a business guy and he saw IT as the driving force behind the change for an analytically driven culture. We saw this with Henrik Amsinck, the CIO of Lego, who was a particularly savvy guy. The accountability he took on was business accountabilities. So I guess if the CIO is on board, that?s also important.

What is the role of analytics in innovation?

You can innovate in many different ways. I related to this first hand when people say Microsoft doesn?t innovate, or Apple is the only innovator. I think people are missing the point, because innovation can take multiple suits. It can dress in different ways. Sometimes you innovate because you create something new; sometimes you innovate because you improve something that already exists at a scale that?s never been matched before.

I was joking with a friend of mine recently. He was saying, ?Yeah, big data, it?s like looking at the world with just one eye, and if I uncover the other eye, then I?ll be able to see everything.? And I said, ?The bigger problem here is that you don?t have the right glasses.? So if you?re looking at the world of data without the right glasses, you?re screwed. I think that?s where analytics comes in, because there?s so much noise that analytics allows you to filter and focus on what?s important.

There?s this big debate in the space of ? does decision making allow you to be smarter? In other words, the more you make decisions, the more you learn about making decisions, the smarter your decisions are supposed to be. There isn?t a clear answer on that because decisions are not born the same.

I?ll give you an anecdote. Michael Lewis wrote a piece on [President Barack] Obama and they?re explaining how Obama is getting rid of decisions that take his energy away from the big decisions. So for example, he wakes up in the morning and his clothes are laid out, because he doesn?t need to spend CPU power to think about what he?s going to wear. He needs to conserve his energy to put it towards something that really matters.

So when you think about innovation, I think you?ve got to think about it this way, which is innovation is the ability to absorb a lot of information and direct your energy and your thinking power towards the things that are going to have a tipping point, and going to make a drastic improvement. That?s when you can innovate. And analytics for me are here at the center of it, because it allows you to filter the noise and focus on the stuff that really matters the most.

Do you see any impediments to getting to innovation?

I don?t think there?s going to be much. If you forward 10 years from now, the people that were able to run their business with analytics, they?re going to be either retired or their company is going to die. I have a 10-year-old daughter. She?s part of the analytics generation. She wants to know something, she pulls out my phone, she talks to it and then she gets the answer. There?s no other way that she can think about life. She doesn?t think that it?s possible that we could be in a situation where we don?t know and have to make a judgment call. But you look at people that are 10 years older than we are, and that?s how they grew up. They grew up thinking most of the time you?re not going to have the information and you?re going to make a judgment call on just about everything.

Most of the time it?s okay to run a business and not know exactly when is the peak hour of your traffic in your store. Well, our kids are not going to go to work like that. They?re going to go to work thinking I don?t need to work 10 hours. I need to work the most two productive hours so I can do a bunch of other things in between. I think they?re looking at the world in a totally different lens than we are, and I think it?s going to be the norm.

Think about the finance function. The finance function in an organization, nobody questions if you need a CFO. Of course, if you have a business and you have to pay bills and count revenue, you need a CFO. Analytics is going to be the same. If you have a company that?s collecting any type of data, you?re going to need to have somebody running your data analytics.

Do you think it will get to a point with analytics where there?s no longer a competitive advantage to be had because everybody is doing it?

Oh, no, no. I think this is a big fallacy, where you get all these vendors talking about let us come in and we?ll provide you an end-to-end cookie cutter solution, and you?ll catch up with the rest of the industry. Analytics is not a consultation like a doctor consultation, or it?s not like a pill that you take and then everybody is back on the same even field. It?s something you have to develop inside your organization, and some organizations are just going to have a better culture than anybody else. That?s what?s going to differentiate them. It?s not building business analytics; it?s the way the organization reacts and pro-acts on the analytics. You can?t duplicate that.