Ep. 14: Brian Kalish - FP&A Embracing Big Data and Technology

Sep 3, 2019

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FULL EPISODE TRANSCRIPT

Music: (00:04)

Adam Larson: (00:05) Welcome to “Count Me In”. Thanks for coming back and listening to another engaging and insightful accounting conversation with us here at IMA. I am Adam Larson and I think you're really going to enjoy today's episode, as, in a minute we will listen to my co-host Mitch Roshong talk with Principal and Founder of Kalish Consulting, Brian Kalish. At the end, please take a moment and write a review and let us know what you think. Tell us how we're doing and what you think about the series either on this episode or by sending us a message with some feedback. So as I understand it, the theme of your conversation, Mitch, was why and how FP&A should embrace big data and technology. Tell us a little bit about Brian and some of his interesting points.

Mitch Roshong: (00:46) Sure thing. Brian is an avid baseball fan, a history buff, and an extremely successful FP&A, a professional. For our conversation. He was able to explain how the emergence of big data is an asset to financial planning and analysis and that technology is not necessarily disruptive. One of my favorite quotes from the conversation was, the science of today is merely the technology of tomorrow. And Brian does an excellent job shaping the conversation around the opportunities created in FP&A. This was a really well rounded and interesting discussion. So let's listen now.

Music: (01:26)

Mitch Roshong: (01:28) Brian, what kind of impact have you seen big data have on FP&A?.

Brian Kalish: (01:33) Well, I'd say Mitchell off the bed. You know, my, my gut answer is a huge impact. You know, in FP&A, we're really in the process of developing an analytics based culture of data driven decision making. And certainly utilizing big data is one of the components of that evolution. It's just incredible the amount of data that just exists today. I always like learning new things. And one of the things that I've learned recently is that we are now operating in a world of Bronto. So B-R-O-N-T-O-B-Y-T-E-S bytes of data, which is 10 to the 27th power. So, you know, we're now just, you know, given all the conductivity that that just exists in the world today. We just have so much data available to us. And what's, you know, kind of what's really changed is that we now have tools and infrastructure that permit us to actually analyze all this data in a useful, timely and, and cost efficient way. And so if you think about what the whole purpose of FP&A is, which is to help the organization make better, faster, smarter decisions, big data really flows into that. So as organizations begin to utilize big data, what's important from my perspective is really kind of the persona that FP&A has within the organization. So for most FP&A groups, you know, the aspiration is the move from being a reporter to a commentator, to an advisor. And I'd say kind of at a truly visionary standpoint becoming a strategist and why this matters and how big data plays into it is it really can help us answer the questions that the organization has for us. So whether you're at the corporate level, you're embedded in a business unit you're helping marketing or HR by utilizing big data, we can move from just answering the question of what happened to where did it happen. And then where it really becomes important is why did it happen, what might happen? And again, kind of at that top level is, you know, having the impact to actually make something happen. So you're looking at another way of dictated will move us up the maturity curve from just providing hindsight to what I hear most business partners asked for today, which is insight and I, you know, I'm a little bit further out the curve. I really think FP&A can actually begin providing foresight to the organization. So if you think about the level of analytics that we can use, you know, we can move from just providing descriptive to diagnostic to predictive and then ultimately to prescriptive. And certainly big data is one of the pieces that can help us get there.

Mitch Roshong: (04:36) Sure. So as this big data flows into FP&A, and I love how you talked about the, the value maturity curve. As we kind of move along that curve, what are the challenges that are presented because of big data and the amount of it that you previously mentioned?

Brian Kalish: (04:54) Sure. So, for me, I kind of have four pillars of what FP&A is built out of and they're certainly, you can always find challenges within any of the pillars. So, you know, what are we talking about as people, technology, process and culture. You know, you have to have a culture that wants to consume business new level of analytics. I was recently with an organization engaged with them and basically their management doesn't want it, like they're not interested in it. It's hard to implement it if you don't have a consumer. So you have to be in a proper culture that is willing to embrace it and utilize it and, you know, spend the resources to make it happen. But you also have your, you have to have the right processes in place because obviously as we're introducing new data sources, it's important to have from both a data governance perspective, but also from a decision making perspective. Do you have the proper governance in place? Do the people have the right skills? And then I think where we spend a lot of our time with big data is, is the technology. So it's great that we have access to this incredibly large database of structured and unstructured data, internal, external. But do we have the proper technology to do the analysis? And do we have systems that are actually powerful enough in place? I mean, these things all exist today. I mean, there are organizations that are certainly leveraging big data and utilizing even in artificial intelligence. But for individual organizations, do they have the proper technology in place? And one of the things that's I think has been fascinating is that we've really, and I'm not trying to get too wonky too soon but just the infrastructure, you know, we've been dealing with for the last 30 years, what's kind of known as an ETL, which is extract, transform load environment, which is, you know, data warehouses and we've very familiar with that. But what's really incredible, and I think what really poses a lot of tremendous op...