 Okay, everybody we're back. This is Dave Vellante with Jeff Kelly and we're here live at theCUBE at the Tableau Customer Event and the hashtag is pound TCC13. So check that out, I'm at Dave Vellante. He's at Jeff Kelly at Furrier. My normal co-host, John Furrier, is in California crunching data of all things Jeff so you are the beneficiary of John being in California. And we've been talking about visualization, big data. We've even been talking about chess and Socrates today, a cube first. Sarah Nell is here. She is the global corporate account analyst at Manpower Group. Sarah, welcome to theCUBE. Thank you, thank you for having me. I mean I would think, I mean the downturn affected everybody almost in a negative way and I'm sure you guys weren't immune from it but I would think coming out of the downturn it could have actually helped your business in the sense that people are looking, you know we talk about the cloud all the time, you buy compute capacity and increments and you can dial it up or dial it down. People sort of want to do that with human resource management, don't they? They do and I admittedly human resource management actually isn't my forte too much, so. But it did, you're talking about the downturn and how it could have benefited our business and it didn't at first. I mean we were impacted just like every other industry that was out there but just like we're looking at how business was done before that point in time when that happened we had to start thinking about that too. The data is every person that we place in a job, every single person there's a point of data, multiple points of data going into that. So you talk about over 400,000 people who are on assignment at a given time right now. Those are so many unique points of data that you could track. So that's the data, the people are the data that's feeding it. Okay so you were brought in to basically develop a set of metrics around those people. Yes. Essentially things that you would expect from any employee performance metrics for example or? Well the big one when you're talking about people honestly is how long are they on assignment and when they aren't on assignment anymore? Why aren't they on assignment? People really focus on end reasons why they're leaving their job and especially in today's climate that's a huge thing. You want to know what's going on, why are they going somewhere else? You want to retain those people as much as possible and not lose them. So that's really one of the big focuses of our metrics is how are we keeping these people, how are we retaining them and when they are leaving why they're leaving. So how did you get involved? Well I've been with Manpower Group for eight years now so I've kind of started in a very unsavory role honestly. I wasn't a data person, I wasn't. I was actually your collector. I was the one calling people for money. You were working thumbs. I was in a nice way with a smile. But that was me and so I just got to know the business. I got to know how the data flowed and I talked to the people. I talked to our people working out in the field and the branches and I just learned the business in and out and so I started doing reporting for them and it led to analytics when it was formed back in 2010 pretty much so here I am. So if data is locked inside an oracle or a cognos system was that your corpus of data? How did you get it out? How did you, were there other sources of data that you were utilizing? Pretty much, it was all out of that one platform and it was a learning curve. We weren't an IT team, we weren't. We were people who were trying to meet business needs more than anything and drive business decisions. So we kind of had to educate IT on what those business decisions were so that they could build solutions to fit what we needed for our immediate demands data-wise. Okay and I'm sorry to ask so many Colombo questions but it just helps our audience understand. So, okay so what, you said this is the data we want? Just dump it? Here's what we need, how can you do this for us? And then what, they gave it to you in the CSD file? Oh heck no, they fought us tooth and nail. So why do you need that? Right? Yes, yes, no, they fought us tooth and nail. Who the heck are you? Yeah, I never heard of you before. Weren't you calling me for money? No. No, no. Yeah. Okay so it was carrot and stick I'm sure. Yes, yes. And you had top senior management support which I'm sure was critical. Yes, it was critical. Because without that you wouldn't be here right now. No, not at all. No, it's been a learning curve for all of us. You know, we've had to play nice together and get to know each other and what we're trying to accomplish, so. So a big part of that was communications? Yes. Okay, so you were able to get the data and what kind of form did it come in? Was it just a dump to a CSD file? Honestly it was a big huge freaking data dump. Here you go, have fun and luck. Figure this out, yeah, it was enormous. And is that when you brought, was that the driver to bring in Tableau? Now we're going to figure this out and hey, I hear this platform or tool called Tableau, is that the way it went down? Yeah, and Tableau was the way for us to really take all that mess of data that we were looking at and start translating it. How did you hear about Tableau? Actually from a guy who no longer works at Manpower. So some guy had heard of him and said, check these guys out. Yeah, yeah. Okay so you did? Yep. And now were you part of that, a big part of that decision process? Was it your decision? I have really been the driver as far as Tableau being used within our organization from our end. Now were you, prior to that, were you like an Excel jock? I mean, okay. So you're really comfortable with data? Yes. You know, a new Excel inside and out, new all the functions? Yeah, they call me the Excel nerd at work. Okay, so for most of us we don't even use 10, it's like our brains, we don't use 10% of our brains, we don't use 10% of Excel, but you were the minority that was using 90% of the function or at least knew how to use it. Yeah, there's some happiness when you figure out a formula and then it works. So, I mean, if you really- Writing macros and doing that whole thing. Yeah, actually. Yeah, thanks, look at how excited I am. I know, who does that? Who gets excited over something? David Floyer, or David Floyer who's out there, he loves that stuff. Yeah, I see you. Okay, so you, I mean, this is the thing. So to use Tableau, I mean, we saw the demo in there and of course, like any demo, it made it look so simple. All you do is right click, it did it did it. Wow, okay, but it's a very powerful platform. Yes it is. Okay, so you had to go through some kind of training or a learning curve. Oh, I would like to tell you that I picked it up just like that. You know, just to make myself sound good, but I didn't at all. It took me a bit and honestly, were it not for the community that exists for Tableau, I probably wouldn't know half the stuff I do today. So really leaned on the community, exactly. I do, I do. And I have to say, Wisconsin alone is trying to really establish a very strong Tableau community as well. Really? Yep. We are actually in the middle of two user groups that are newly created. So I think one of the curve falls that people are thrown a lot with data and that the pitfalls they tend to fall into is over-complicating it. And I think the big key is actually my mantra, kiss, keep it simple, stupid. You know, you want to make it elegant and clean and simple. I mean, there's beauty in it. And I think that's why Tableau does that so well. I mean, especially coming out of the keynote. It's so obvious. It's clean, it's simple. It's attractive. You want to look at it. You want to play with it, you know? You know, that's easy to say though, Sarah, but so it's an old saying in the writer's world, right? If I had more time, it would have been shorter. You know what I'm talking about? Jeff's a long time writer. You write something that's 10 pages and your boss wants it to be two pages. So how do you simplify? How do you keep it simple? Well, you're really, you're translating the data. So if you don't know the data, you can't keep it simple. And then you do over-complicate it. So I think that's the biggest part. Know your industry. Know your data, where it's coming from. Have a relationship with it. Understand the ins and outs, you know? Take it out for dinner once in a while. Take a bath with your data. Yeah, buy a bottle of wine on Valentine's. Come on. Well, absolutely, I mean, that we've heard that how many times now today, Dave, for practitioners, keep it simple. You know, don't clutter it up with things you don't need. You know, make it very simple, elegant, I think it was a good word to describe it. And I think about that compared to something like Excel and something like the other traditional business intelligence applications, which are the furthest thing from simple and elegant that you could imagine. I wouldn't say that yet, because there are many people who still use it. Well, but when you think about some of the alternatives, you know, it's very hard to make something simple and elegant in a lot of the more traditional tools. So does Tableau really, you know, allow you to do that? Obviously that's their- It does. That's what they're trying to get across. I mean, as a practitioner, I'm sure there are some things that you would like to see improved or maybe streamlined. But, you know, overall, what is your impression of the tool? I honestly love it, and I've been using it for so long now that it's actually really hard for me to go back to using Excel other than a data source or a connector for Tableau, because I'm so used to writing my formulas and calculations in Tableau. It makes it so easy. They make it, pretty much it's a pivot table on steroids, you know, and they make it so it's intuitive. I know where stuff is. Here's how I'm going to find it. And the greatest thing that I've actually found for it, when I find something that works, I try to create my data around it then so it's always going to be the same no matter what. So I can keep coming back, reconnecting it and pretty much creating templates then pretty much. That's been my success in the whole Tableau product is templates overall. So if you know if it works, keep going with it. Back on that. Very good. All right, Sarah, really appreciate you coming on theCUBE, great enthusiasm, and you know, you're a data scientist in my book, so start calling yourself that and you'll get a big raise. Hey, come on theCUBE, change your name to the title and good things will happen. So really appreciate your insights, excellent case study. So congratulations on all the progress and enjoy the rest of the event. All right.