Podcast Series: Getting Started with Tableau, Intel

Tableau: This is Elissa Fink of Tableau Software and I’m here today with Jennifer Monnig, the Manager of Global Staffing, Reporting and Analytics at Intel and Jason Alvey, a senior research analyst at Intel.

Jennifer, tell me what do you do as a manager of Global Staffing, Reporting and Analytics?

Jennifer: Thanks, Elissa. Well, as the name implies we manage the reporting and analytics within the global staffing world here, focusing primarily on headcount and hiring data. Over the past several years, we’ve worked on developing statistical modeling and analytic solutions, really meant to support our global head count management and our staffing and hiring data. We work with several partners across the Intel business groups including finance and HR to provide a strategic and a holistic look at our talent acquisition policies, plan, data, efforts, etcetera, to try to impact strategic business decisions.

Tableau: That’s cool. Jason, how about you? What do you do as a senior research analyst?

Jason: So, I’m a senior research analyst in a group called Staffing Market Intelligence and so the focus of our group is to really try to create a competitive advantage for Intel by providing information on the availability of labor and critical skills across the world. And that information is used to help influence both business decisions and also decrease the time to market that it takes to get that talent onboard at Intel.

Tableau: Wow! Intel really recognizes the connection between people and business results. So, Jennifer, how long have you and your team been using Tableau?

Jennifer: We started using Tableau around the end of 2008. So, we’re close to three years now. We’ve seen a lot of momentum pick up over the course of those three years, and we’ve introduced Tableau to many other groups within HR and within Intel. And we’ve seen a proliferation. So, we’ve really seen things move and have seen other groups pick it up and start to use it. I think Intel had about 41 licenses at the end of 2008 and today I think we’re over 130 as a total company.

Tableau: Great. How about for you, Jason? How long have you been using Tableau?

Jason: About the same time as Jennifer started using it. So, back in October 2008 our manager first picked it up and then rolled it out to Jennifer and me shortly thereafter. And as Jennifer mentioned, it’s kind of grown ever since then.

Tableau: Cool. So, Jennifer, in getting started three years ago with Tableau, what do you remember that were things that helped you get started? What things would you recommend to someone who’s starting up with rapid-fire analytics and business intelligence of the Tableau style?

Jennifer: So we have this conversation frequently actually within the company.

Tableau: Uh-huh.

Jennifer: One of the first things I always do recommend actually is attending the training. I think Tableau offers great options on training both the call-in sessions where you literally are talking to a person and have that ability to ask them specific questions as well as get that really initial feeling of “this is how you move things, this is how you look at things. These are rows, these are dimensions,” etcetera. So both the call-in training and the Web-based training and I think the fact that it’s broken up into topics or chunks really gives people the ability to pick and choose what they want to look at, what they want to learn about and how much time they want to put into it. So, I think their training is great.

The second one that comes to mind is the work Tableau creates. I think you’ve got one out there called The Wow Workbook, but any of those Wow Workbooks or anything that Tableau creates internally I think it’s a fabulous reference and a fabulous resource. I tell my folks and people who work for me, and including myself, to look at the things that Tableau has done because I figure you guys are the experts. If anybody can create cool stuff, you ought to be able to do it. [laughs]

And we get a lot of ideas, and a lot of reference points from those who say, “Oh, look how they set this up. Oh, I see how they set that up.” You know, “how can I copy the way they put that together or bring that into something that we’re doing,” or “How would the way you guys have set something up in one of your workbooks apply to the kind of data analysis that we’re either trying to analyze or present in our world?” So, those are two that come to mind for me.

Tableau: That’s great. Learning by example is a great way to help people get started. Jason, what about for you? What, what worked for you?

Jason: You know, I agree with Jennifer. I think that there are a lot of great resources online to the training that’s available. One of the things that really helped me is just to get in and start playing with it initially. I mean, literally, my manager and I sat down. I think we had, maybe, a quick 10-minute overview and I was off and running. A lot of it is so intuitive that just getting in there and having – whether it’s the sample datasets that Tableau provides or if you can come up with a similar dataset that you have and just kind of get in there and start practicing and familiarizing yourself with the different shelves that are there, and pulling data and looking at the different types of displays that are available, I think you can really pick it up pretty quickly.

And then the other thing is just there are certain things I find that I tend to use almost all the time. I kind of call them the basics so things like creating groups or aliases, things you can do that don’t necessarily impact the original dataset but make it so much easier for you to go out and do analysis not easily available in some of the other analytical software packages that are out there for me has really helped saved me time. And, most of the things I can do, 80% of them are pretty basic. And so, just getting in there and learning those things, I think, is valuable. And then, as Jennifer said, take the time for that online training to really enhance your skills because the power of Tableau, can go from, as I mentioned, very basic to all the way to a very detailed and sophisticated output which I’m still learning myself.

Tableau: [laughs] Well, I have to be honest. I think all of us, even at Tableau, we’re always learning too. That’s the great thing about data and rapid analytics. So, you both are going to be doing a talk at our upcoming Tableau Customer Conference in Las Vegas. We’re really excited about that. I think it’s called Tableau..Inside Intel. Can you guys give me a little preview about what you’ll be talking about there? Maybe, Jennifer, if you could start?

Jennifer: Absolutely. So, yes, Jason and I will be speaking jointly. We will be up on the stage together. We’re really going to focus our talk around talent acquisition. That’s really the space that we play in, and on how Tableau has enabled greater data analysis and better visual presentation in the work that we’ve done, both on the side of the analysis and the work that we do and looking at information and putting things together. And then, when we’re presenting them or making that available to other people, be it to our customers, to our partners in presentations, the way that we’ve used Tableau for that visual, analytics piece of that.
And that element of self service. So, there are presentations and then there’s “we’re going to give you this data with the ability to play with it, to use it, to tailor it, to whatever specific question you’re looking at and you’re asking.” So, we’ll focus a lot around that area. Jason, why don’t you add some more to that?

Jason: I think, along with what Jennifer said, we really want to try to couch it within some examples that we’re currently focusing on here at Intel right now. Tableau is helping us and Intel, I think, to change and improve our strategic planning, reporting, forecasting, execution of talent-related actions across the company. By the end of the year we’ll probably be around 100,000 employees spread across the world. And so, as you can imagine, there’s a lot of data that flows across the company. Yet I would still say that Intel heavily relies on Excel spreadsheets and PowePoint and things like that. And so one of our goals in our two teams is to really help facilitate better or faster decisions with data. And we think that Tableau is one of the catalysts to help us with that. And we’ll talk about some examples and some things we’re doing currently to help with that effort.

Tableau: Cool. Well, I’m definitely looking forward to your talk at the conference in Las Vegas in October. So, thank you both for being here today with us, and we’ll see you in Las Vegas.

Jennifer: Thank you.

Jason: Great. Thank you.