Lee: I’m here at the Tableau Conference 2015 with my friend and colleague Francois Ajenstat, Vice President of Product Management at Tableau Software. We’re going to have a conversation about product management at Tableau and the keynote where we heard a lot of exciting announcements. Francois, thanks very much for spending some time with me.
Francois: It’s great to be here and good to see you again Lee.
Lee: Let’s kick this off with a customer story that made you really feel great about the software.
Francois: Well, so I will actually talk about the story I shared this morning where I got to meet with one of the world’s largest retailers. It was a typical meeting in one sense where there were people from all over the organization in the same room. You had people from business, people from IT, all sharing and collaborating. But this meeting was different. There was energy in the room. People were engaged.
IT was sharing how they were getting so much more traction, unlike anything they’ve seen before. The business users were telling us all about their use cases and what they’re doing with Tableau and how it’s helping their organization and their jobs.
But for me, the thing that resonated the most was one user Brett, who manages HVAC systems. He’s the heating and cooling guy. Brett uses Tableau to find ways to improve the results for the organization and reduce costs. But the thing that struck me the most, and that’s why I shared it this morning, is he said Tableau makes him creative when he’s not a creative person.
I get the pleasure to hear those kinds of stories every single day in my job. That is just the best part of what I get to do day in and day out at Tableau.
Lee: I thought that was a really great story because probably everybody in the audience is not an HVAC person and would never think that someone in that role would be using Tableau. Everybody here is a data analyst or some type of business manager, and I think really talked to the idea about how Tableau is making information accessible — and usable.
Francois: Ultimately, every person across the company could use data to improve their jobs, to improve their results for the company. It’s not just about that one big decision that you made, that one big insight that you made. It’s about the thousands of decisions that happen every day and if you can make each and every one of those just a little better, well, think of the results that will have on the entire company.
Lee: So Christian, the CEO, he always makes sure to talk about how much money the company is investing. I think usually it’s about 30 percent of revenue goes back in to R&D.
Francois: We’re going to be investing more in R&D in the next two years than we have in the last 10 years combined. Think about that. More in R&D than in all of our history that brought Tableau 8.0, 8.1, 8.2, 8.3, 9.0, 9.1 to market. We’re doubling that. It’s going to be amazing in the next two years.
Lee: So we should have some great expectations. I think everybody would be interested to get a little bit of an inside view of your role, because I think people don’t even really know what product management means. How does Tableau do that work differently that makes it so successful and you’re able to have the great features, but also at the pace that you’re able to produce that? Because I think that makes a huge difference.
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Francois: The key thing of product management is that we get to think and prioritize what we build, why we build it, how we build it and when can we deliver it. It’s really a collaborative process that we have across the team and the hardest part across all of that is not figuring out what you should do, but rather you have to know what things you will say no to or that you will have to delay. Making those right bets is really the art in the job.
We really think about the use case. By use case, I mean the scenario that you’re trying to achieve, the job you have. We have amazing UX designers and amazing developers that think not just about delivering it, but delivering it in the smartest way possible, in the simplest way possible.
Simple is hard as we all know, but that’s really what they try to do. So for instance, we’ve been wanting to add clustering to Tableau for a long time. It’s an advanced analytic. It’s something that stats folks really know how to do. But how do we take that concept and make it mathematically accurate but applicable to thousands upon thousands of people that don’t really know what a cluster actually is?
We came up with a really simple drag-and-drop cluster. It takes care of everything. It’s magical how it works. But it’s that kind of thinking of not just the algorithm that you’re trying to deliver the feature, but thinking of that scenario end-to-end and how somebody would use it.