In this interview recorded live at Financials and GRC 2014 in Orlando, James Fisher, VP of Product Marketing for Analytics and Mobility at SAP, describes how predictive analytics can elevate finance professionals to strategic advisors within the organization.
Lucy: Hi, this is Lucy Swedberg with SAPinsider, we’re here live in Orlando for our Financials and GRC 2014 event. I’m pleased to be joined by James Fisher, he’s our VP of Marketing for Analytics at SAP, welcome James, thanks for joining us!
James: Thank you Lucy, how are you doing?
Lucy: Very well, thanks!
Lucy: So this morning in Christian Rodatus’ keynote, we heard a little bit about, he talked about sort of three key areas for finance teams in particular, around execute, which had a lot to do with sort of the day-to-day operations and gaining as much efficiency as you could, and control, more of a GRC slant, and then finally predict, and I wanted you to sort of maybe elaborate on that last point, predict, what should that mean to SAP customers today?
James: Yeah, it’s interesting, I mean, the story that we’ve been telling at SAP, and I feel very close to it, having kind of helped define it two or three years ago , has evolved, and it’s changed as technology’s evolved, it’s changed as the role of finance has evolved, and you know, Christian this morning talked a lot about, to paraphrase, the idea of the CFO, finance professionals, being more than just stewards and really becoming that strategic advisor to the business. The reality is we’ve been talking about that I think for quite some time, but actually now what we’re seeing is the technology skillsets of people within finance are evolving to where there is an opportunity for people to really become a strategic advisor to the business.
Now, the three pillars that you talked about really reflect three different elements as you said within the role of, the role of finance. Now, predict kind of implies predictive technology, right, predictive analytics technology, and I think actually that, you know, while we often look at that last pillar of being that, that performance management piece in many respects, that planning, that reporting piece that goes with finance, the narrative and the methodologies around predictive analytics certainly apply there, but they actually apply across the other two pillars as well, if you think about fraud management in the control piece, right, fraud management really is about a predictive technology. I think, in the panel this morning, Rob Kugel talked about the role in accounts receivable, which is really the execute piece, you know, if you can predict with more accuracy what’s happening with someone in terms of their payment schedules and their payment terms, perhaps you can service your organization and them more effectively through predictive analytics, so the role of predictive is very broad, and I think that applies right across the finance spectrum.
Lucy: Great. From your experience, do you sense that customers understand the business value of predictive analytics, is this something that you’re having to explain to people or do you think that they get it, they understand that it’s more than just a buzzword, or something like that?
James: Yeah, I mean, it’s a very good question because I mean, at SAP we published some research about a month ago which really looked at the role of predictive analytics within the organization, and we took a kind of US versus UK approach, which is great sport for us to be sat here and having a debate, we’ll save the audience that, but the key message and the reality is that you know, predictive analytics are perceived to offer a huge amount of value, both by those that have already deployed them, and those that would like to deploy them.
The difficulty is that predictive analytics has for so long been the domain of data scientists, very specialized, very skilled individuals, that are able to look at the data that’s there, look at the business, create the types of models, optimize those models, extrapolate meaning for the rest of the business. Finance organizations, you know, while I think, you know, the traditional role of the accountant, the type of skillset, that you would see there needs to become more predictive-orientated, they need to understand how to use real, pure play analytics capabilities. They’re never going to become data scientists, you’re never going to get rid of your IFRS specialists, replace them with data scientists.
So the trick becomes how would you marry the skillset that we have today within finance, and quite frankly, across any line of business, with the technology that can help people automate and embed those predictive models, because if you do that, you can bring those two things together, then you get finance people using predictive capabilities; marketing people, salespeople, without really even knowing, without knowing it, and I think that’s the opportunity that people need to get to.
Lucy: I actually was reading an article that you wrote recently, and sort of this thought that people feel like there’s some sort of a skills shortage when it comes to these data scientists, so what you’re just explaining sort of should help customers understand that that’s really not the case, they need to sort of think of who they have in their organization and leverage their skills to the best use?
James: Well, I think the data does speak for itself, you know, I think there frankly are not enough data scientists to go around, so, you know, kids out there, if you’re looking for a…you know, becoming a data scientist is not a bad career choice. But I think we have to see the tools converge and become easier to use, to automate more of these types of analytical capabilities. But at the same time I, a kind of slight personal kind of project of mine has always been around the role of education in terms of analytics, and I do think that we need to see a shift, generally, not just in finance people, but in business people in general, to really learn how to use analytics, and that’s not about becoming data scientists, it’s actually about learning when to query what’s happening.
There’s a very good partner of SAP’s, a guy that’s worked in the BI community, a guy called Donald MacCormick, wrote a blog about a year ago about the role of a weather website, and the role that—I love this story, I thank Donald for it—but the role of a weather website is, you know, you ask someone, “Did you look at the weather?” Well, you’ve just looked at an analytic, it’s a big data problem, it’s predictive, it’s multidimensional, and Donald creates a very compelling argument about it, but the reality is when you and I were to look at the weather, we’re here in sunny Florida, but let’s just say we’re back home where I’m from, in London, and we’re here in March, and the weather, I look to the weather website and it told me it was going to be 42 degrees outside, sorry, that’s in European speak, but, say it’s over 100 degrees, you know, and it’s going to be clear blue sky, and I’m in the middle of March. I’m going to look at that and question that.
Lucy: Think twice!
James: I’m going to look out the window and see what’s really happening. So that’s really the type of education I’m talking about, how do you learn to use those type of analytics in your day-to-day job, because companies like SAP, we can prescribe, we can come to these great sessions at SAPinsider and learn about all the different ways you can deploy the technology, but ultimately it does come down to people in their organization who know their business being able to identify a unique opportunity, and that’s where these type of solutions can then differentiate their finance processes, make them more efficient, and allow those finance processes—and again, we’re talking in the context of finance, for them to then become more of a strategic advisor to the business and add more value.
Lucy: Interesting. Do you have any use cases, maybe a case where you’ve seen predictive in action that really sort of wows you, that, as we look forward to the capabilities here, you know, anything that sort of jumps out at you as something that you’re surprised by?
James: Well, you know, the one that we talked about this morning that came out was the planning example, we saw that in the visualization piece as well, as I said, Rob talked about the accounts payable, but really the applications in predictive are huge. It was interesting, I was a little bit late running up here because I got sidetracked in a meeting, but just before I went into that meeting, I got a phone call from my telecom provider back in the UK. And the guy on the end of the phone says this call is being recorded, he doesn’t actually know that that particular organization uses our predictive analytics capabilities. He’s just a guy on the phone, and the offers that he was trying to give me, get me to upgrade my broadband connection or these different HD sports package or whatever it was, are all coming out of a predictive engine that’s running behind the scenes, telling him what the next best offer is.
And it really comes down to, whether it’s eBay, the example Christian gave, I do think it comes down to people being able to identify those opportunities—SAP can help, education sessions like Insider can help, but whether it’s customer next best offer, campaign management, planning, you know, predictive maintenance, there’s a whole raft of these types of use cases out there, and you know, we can certainly help share that with people, just got to go look at SAP.com/predictive and it’s all there!
Lucy: If he only knew who he was speaking to, right, as he offered you these deals!
James: Exactly. The good news is it allowed me to make sure I knew how to swerve all of the offers he gave me and not get my wife the movie channel that she probably does want.
Lucy: Fantastic. So, a great case of predictive analytics in action there. Again, I’m joined by James Fisher, we’re here live in Orlando for SAPinsider Financials and GRC 2014, thank you James so much for joining me today!
James: Thank you!