Ep. 75: Shifra Kolsky - The Effective Roll Out of RPA Implementation
Count Me In®29 Juni 2020

Ep. 75: Shifra Kolsky - The Effective Roll Out of RPA Implementation

Contact Shifra: https://www.linkedin.com/in/shifrakolsky/

FULL EPISODE TRANSCRIPT
Adam: (00:05)
Hi, everyone. Welcome back for episode 75 of Count Me In, IMA's podcast about all things affecting the accounting and finance world. I'm your host, Adam Larson, and I'm pleased to introduce you to our featured expert speaker, Shifra Kolsky. Shifra is the Vice President and Assistant Controller and Finance at Discover she is responsible for external reporting, the SOX compliance program, accounting policy, corporate accounting and financial systems. In this episode, Shifra talks about the value of an effective rollout and what all aspects of an RPA implementation look like. Shifra launched the finance RPA team in 2018. The first RPA team at discover. So to hear firsthand experiences and actual applications, keep listening as we head over to the conversation now.

Mitch: (00:56)
So Shifra, you know, we've had a lot of episodes here talking about artificial intelligence, RPA, and from your experience and you just, how you answer questions regarding these topics. Can you first start off with telling us how is RPA different from AI?

Shifra: (01:13)
So RPA is robotic process automation, AI artificial intelligence, and the main difference is that the way I think about it as the bots are a little bit stupid. So AI tools can and learn from, the different data that they're exposed to and they can develop more sophisticated responses over time. Bots can strictly do whatever it is you tell them to do so they just follow instructions, nothing more.

Mitch: (01:45)
So as far as following instructions, you know, I know you are in finance and accounting, right? VVce President Assistant Controller here at Discover, and again, your perspective, what are the best type of tasks for these bots to perform?

Shifra: (02:00)
Bots are great at doing simple, repetitive tasks where you can give exact step by step instructions. Some of the examples in controllership might include things like pulling reports or setting up journal entries based on specific data fields in that report, preparing reconciliations where the bot would compare data from one source to another source and create a list of exceptions. So again, all simple, basic repetitive tasks, but we have a lot of those in finance and accounting, and so they're very helpful to us.

Mitch: (02:38)
And being in finance and accounting, you know, a lot of people probably outside the function would look at this as maybe a cost cutting measure, right? It's, it's a way to kind of eliminate some of the human tasks that are out there, but from within the function and the organization as a whole, really, how do you get in to get people to understand the benefits of these bots and RPA?

Shifra: (03:04)
Yeah. So when we first launched our RPA program, we were not looking at cost cutting, and we were looking at, ways to become more efficient and free up people's time to be able to do more high value work, to kind of critical thinking things that you need a human to do and so when we took on this program, we started by, we asked people to tell us about the things they hated doing, the things that they found, kind of mind numbingly boring. And thought let's take that list and see if we can get a bot to do those things instead. We also made it very clear to people that it was about shifting people to doing the higher value work, the critical thinking, the analytics, so that people weren't focused on the, Oh my goodness, the bot is going to take my job. Building a foundation of trust that it really was centered around helping people, was really important to get buy in and to get people engaged. We also enlisted one specific team at the start, to be guinea pigs for everyone. So they test it out. They were the first ones to have a process automated, and they were specifically selected because they had two clear qualifications. One, they had a whole bunch of tasks that were repetitive and easy for us to automate the box. But the other thing they had was a sort of general sense of excitement about the program and the possibilities, and so they were able to really carry the message and they were able to help the bot developers understand things quickly. And then they were also able to convey their enthusiasm to other people as they started seeing the results. And so having those natural cheerleaders or business champions was a really effective way for us to build some momentum around the program.

Shifra: (05:11)
And what were some of the recognizable benefits of implementing this program? How did it ultimately impact your team?

Shifra: (05:18)
So there are a number of different ways that this has helped our team. You know, on the simplest level, it changed the energy. I mean, it got people excited and really thinking in different ways. Our team has long been focused on continuous improvement, but this is really taking things to a different level and helped folks think more creatively about the things that we can do instead of feeling hampered by the things that we can't do. You know, so that's one element of it on the people's side, but frankly, it's also allowed us over the course of the last two years to redeploy about 10% of our headcount in the controllership team to take on new opportunities within the group. So this furious focus on automation has really enabled us to keep up with the growing needs, that are coming at us from all of our business partners and, and keep up with those demands without increasing head count.

Mitch: (06:25)
One question that I hear a lot when we start talking about RPA is the length of time it takes actually to implement the program. So are you able to share how long this whole process took from the analysis through identifying what people hate until you were able to recognize the benefits and get these cheerleaders for the program?

Shifra: (06:45)
Sure. I would say for us, the research we did before we jumped into it probably took longer than getting it moving once we started. So we spent a good couple months really talking to a lot of other companies and understanding, you know, some of the things that worked for them, some of the things they wish they'd done differently. We spent a chunk of time looking at the different tools that were available and deciding what the best tool was for us. And then we invested in, recruiting and training some folks, and we did all internal recruiting. We thought that it was smarter to take people who understood the business and understood the business processes, and teach them how to use the tool rather than taking somebody who knew how to use the tool and try to teach them the business. So we spent a couple of months with all of that kind of upfront research and, and training. And once we got into the training it was fairly quick. So depending on the nature of the process that you're trying to automate, things, can we fairly quick, if you know how to use the software and you understand how some of the different connections work, okay. You can get something going in as little as a week when you're first starting out. You're more likely looking at things taking between eight and 12 weeks for a process. And again, probably depending on the complexity and the number of different, systems the process might touch. But we had our first process in place within about 10 weeks and built on things from there. And one of the things that we...

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