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ASC 606 is wreaking rev rec in biotech. Here's how one tech-savvy accountant aims to fix i…

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Paul Giese: One of the challenges that the accounting industry faces is a lack of talent. I think one of the ways that companies, and accounting firms can address this is by utilizing systems very well. I think a creates real opportunity for niche industry tools to really excel, and really add a lot of value to companies. Blake Oliver: Welcome to the Cloud Accounting Podcast. I'm Blake Oliver. We're joined today by Paul Giese. Paul is an accounting manager in [00:00:30] the biotechnology industry, and the founder of intheBlk software, a collection of web-based tools for biotech accountants. Thanks for joining us today, Paul.  Paul Giese: Thanks, Blake, for having me. Blake Oliver: Paul, you and I connected, I think it was on LinkedIn- No, Twitter. You found me on Twitter, right?  Paul Giese: Yeah, Twitter.  Blake Oliver: Particularly, about ASC 606 revenue recognition, which is all the rage these days. For those of you who are not familiar with ASC 606, this is the new [00:01:00] revenue recognition standard that has been adopted by FASB, and has gone into effect already for public companies, and is going to be effective for 2018, for most private companies, for financial statements. Everybody is trying to get their ship in order for revenue recognition. We're talking a lot about that at FloQast. We are talking a lot about that online. Everyone is trying to figure out what to do, scrambling to get ready. Paul, [00:01:30] I'm really excited to talk to you, because you work in the biotech industry, and I had no idea that there were some really unique challenges for biotech, when it comes to revenue recognition. Paul Giese: The ASC 606 has been one of the biggest monumental changes in accounting standards over the last decade. It's been a very big change for the industry, and across all industries. Accounting firms have been putting out a lot of guidance, and companies [00:02:00] have really been struggling with how you recognize revenue, because it's a very drastic change. I think it might help to talk about the economics of a biotech collaboration, where a small biotech company would partner with a large pharma company. Blake Oliver: Yeah, that sounds great. For everybody who is not familiar with the ASC 606, check out, if you're looking for more information. Go ahead and pause and head over on there. It'll give you a great understanding [00:02:30] of what exactly this massive change is that we're talking about. Paul, please do continue. Paul Giese: Yep. Typically, what happens in the biotech space is that a small biotech company will partner out several of its program pipeline to a large pharma company, where the exchange is the small biotech company gives away commercial rights to future drugs, and in return, the large pharma company will provide cash. [00:03:00]Typically, what happens is that, with a large upfront payment, that would go to revenue, and then you'd recognize the revenue over the performance obligation, which is typically getting a drug through to commercialization, and approval with the FDA. Paul Giese: Under the old guidance, which is ASC 605, companies would identify what the unit of accounting was in the agreement, and [00:03:30] then, they would straightline whatever the valuation of that obligation, over the performance obligation. Typically, that could be 5-10 years out from the signing of a contract. Under ASC 606, now, instead of straight-lining the value, you're gonna be recognizing the revenue on a proportional performance method, where, essentially, it's a percentage of completion. On day one, you have to identify [00:04:00] what the total cost is for you to take that drug from preclinical, all the way out to commercialization, which could be, as I said, 5-10 years. That's a very difficult task for a small biotech company, where they might have an accounting department of three, four, five people. Blake Oliver: Let me make sure ... Let me pause you there, and make sure I understand. Under the old guidance, 605, if I was getting $50 million, over five years, to develop a drug, I [00:04:30] could just straightline that, so I'd add $10 million a year of revenue.  Paul Giese: Exactly. Blake Oliver: Easy.  Paul Giese: Yep, very easy. Blake Oliver: I cannot do that anymore. Paul Giese: No. Now, the FASB has said, "We want to recognize revenue as the transfer of ownership occurs," so, you need to identify a way to track your performance, over the performance period, which is typically costs, for biotech companies, [00:05:00] because there's no ... That's the easiest way to kind of track how well the company is doing. Then, as you're recognizing those costs, you would recognize the revenue. If, in year one, you incurred 10 percent of the cost, then you would recognize 5 million of the 50 million upfront payment. Blake Oliver: 10 percent of the cost ... How do I know what my total cost is going to be? What's all this based on? Paul Giese: It's really based on estimates. A [00:05:30] budget would ... For most companies, you go out 18 months, or maybe 24 months, but, beyond that, you're typically relying on a long-range planning tool, or some high-level estimates, where you might say, "Okay, a patient enrolled in a Phase I trial costs $150,000, and I'll assume that I have 100 patients." That cost goes into your model. You have [00:06:00] all these high-level estimates that are gonna obviously change, as time progresses, so that could potentially create wild swings in your revenue. I think people - analysts, audit committees, boards, management - are all concerned, because under 605, you just straight-lined your revenue. It was very predictable, and everybody was happy. Now, you can have some really wild swings, period over period, depending on how well you can [00:06:30] budget, and how well you're long-range planning. Blake Oliver: I'm just thinking through this. Let's say nothing really changes, and, in a particular period, I don't have that much more, in terms of cost, but, for some reason, I don't know, maybe a trial goes well, and we realize we're not gonna have to do so many trials. Suddenly, my total cost estimate is less, right? Paul Giese: Yep.  Blake Oliver: That would then mean that I'd recognize more revenue? Paul Giese: Exactly. Blake Oliver: Interesting. Paul Giese: The opposite can happen, too. Perhaps, you [00:07:00] get bad data, and you say, "Hey, we're gonna terminate this program," and then, suddenly, your costs are reduced, and you recognize more revenue, which is kind of the inverse effect. You would think, "Oh, we got bad data. That's bad news," but, in fact, now the pie has shrunk, so, you're recognizing more revenue. It's a little wonky on how the revenue's recognized. Blake Oliver: What kind of data do you now need to collect, in order [00:07:30] to make these estimates? Paul Giese: That's a great question. You would historically have your external costs, which are costs with a clinical research organization, your manufacturing vendors, any lab supplies. Those costs all are now ... Typically, you were always recognizing all those costs. Now, the classification between the various programs matters a lot more, because if you have a program that's in [00:08:00] a collaboration agreement, and you have a program that's not in a collaboration agreement, because the expense is driving the revenue, auditors are a lot more concerned about the classification of the expense between program A and program B. As an organization, you have to have better controls around ensuring that the costs are accurately coded to the correct program. Another piece of data that needs to be collected is as time reporting, because, typically, for a biotech [00:08:30] organization, your headcount is a substantial part of your costs, because these are PhDs, who are doing work, and they're expensive. You have to collect the data from your employees, and then you will recognize the cost. Typically, in these agreements, they have a negotiated FTE reimbursement rate. The large pharma company might would [00:09:00] reimburse the small biotech at a fully loaded rate of, say, $250,000. You would use that rate, times the number of hours incurred in the quarter. Then, that goes into your cost, as well. Predicting the number of hours incurred in a quarter, and over a 10-year period is extremely challenging. I think that can also really swing the total cost of your agreement. [00:09:30Blake Oliver: Right. I'm accumulating expenses by program, and I'm also tracking hours, because that's an element of the cost, in detail. In terms of the FTE hours. I've got to project those out 5-10 years. I imagine there could be some really drastic swings on those estimates, from quarter to quarter, or year to year.  Paul Giese: Yep, exactly. Whether it's a timing [00:10:00] difference, or a cost savings also matters, because if it's a timing difference, then you push a cost from Q2 to Q4, and your full-year revenue recognized doesn't change. If it's a cost reduction, it reduces the pie, so to speak, so you would get a true-up of revenue. Blake Oliver: Right. Paul Giese: Then, you also have to think about the long-term, and the short-term classification, as well, because the auditors are gonna care about that classification for the balance [00:10:30] sheet. Having your controls around the long-term, and short-term component is also another factor that you need to consider. Blake Oliver: Wow, what a humongous difference from simply straightlining that revenue. Paul Giese: Yeah, it's been very challenging to implement. Blake Oliver: Let's get to the technology part, because I like that. How are biotech accountants, and really, I suppose this would apply to anyone, under ASC 606, that's doing [00:11:00] percentage of completion, right? How are accountants, who are doing this percentage of completion based on cost, or revenue based on cost estimates, how are they doing it now? How would you do it? Paul Giese: Currently, everybody in my network, here in Boston, is tracking their collaboration revenue in Excel, because there's no solution. You have massive Excel spreadsheets, where you're keeping track of all this data. Every [00:11:30] period that you're recognizing revenue, you have to save ... What we're doing is we're saving down a new version of the same file, every quarter, where we update the inputs, and any changes to the estimate, and it's basically saved on our network drive. It's, frankly, disorganized, and ... Well, not disorganized, but it's just very [00:12:00] challenging to keep track of any meaningful data, because maintaining a very complicated spreadsheet is challenging. It's hard to derive real data from an Excel spreadsheet. Forget about any sort of IT controls. Blake Oliver: Right.  Paul Giese: You can lock cells in Excel spreadsheets, but that gets really challenging to do, and there's no documentation of changes, and user rights, anything [00:12:30] like that. Blake Oliver: I imagine that, in terms of the estimates, you have to involve outside parties. Paul Giese: Yes, you're certainly ... It involves the entire organization. You're gonna have to talk with your project management team. You're talking with your clinical team. There's some helpful resources that are available that give clinical data assumptions of how much ... If you're in oncology, how much should you [00:13:00] budget for a Phase I study, and how much should you budget for a Phase II study? There are external resources that can help with that, and lots of consultant groups. CFGI is an example of an organization that's been probably really helping a lot of clients figure out how do we implement this, and how do we get these costs, and model out the revenue recognition. Blake Oliver: Are controllers, CFOs [00:13:30] just trying to brute-force this? Are they hiring more people to handle this?  Paul Giese: I think, right now, people are kind of in a wait-and-see mode, we’ve gone through the 1:1 true-up, for public companies, which is the 2017 audit. Now, the Q1, and the Q2 reviews are completed. It'll be interesting to see how things fall out, as you're doing your first-year audit under the revenue [00:14:00] recognition model. In my company, we have a really strong team, and we've been able to manage the process. When I was talking to another controller, he said, "With one collaboration agreement, it's pretty manageable. You can manage it in Excel," but, some of these companies have two or three collaboration agreements.  Depending on how things fall out, within the technical accounting analysis, in steps one through four of the revenue [00:14:30] recognition model, you could have multiple models for recognizing revenue within one agreement. You could potentially have multiple proportional performance models under one collaboration. If you have three agreements, you could potentially have 9 or 10 models that you're trying to track. I don't know how a company that size would manage that, without a tool. I think you would ... To your point, you would need to hire another person. Blake Oliver: Let's talk about that. What are you working on that would potentially help accounting [00:15:00] teams not have to add headcount, in order to manage this? Paul Giese: intheBlk software is an idea that I had of the pain point of managing all of these Excel spreadsheets. My tool is really built to be the home for every closed period of your model. Because each model builds off of each other, you can have a more controlled environment, where you're only ... The [00:15:30] actuals are locked, once that period is closed. The actuals have been locked, and nobody can accidentally change those numbers. All the calculations are done for you, so you don't have to worry about hardcoded formulas, or miskeyed data. This basically gives more control around your model, because, again, revenue [00:16:00] recognition is always a material risk for an audit. The more controls you can have around the revenue recognition, the better. You're trying to identify areas, where you can put in system controls, whether it's user access rights ... If you're my controller, and I'm a staff accountant, Blake, I can enter all my data, and I can click review. Then you get a notification saying, "Hey, Paul submitted the revenue recognition model. It's [00:16:30] ready for you to review."  You can go in, and type up a few review comments, and send it back to me. Then, I can go in, and say, "Okay, yep, I should have put this number in." Then, you have documentation of all that. That's what auditors are really looking for is documentation of review. I think the other thing is being able to predict how cost changes could potentially impact the current-period, and future-period [00:17:00] revenue. This could be helpful, if you have to give guidance to Wall Street, and you wanna say, "Okay, if our expenses swung a million dollars, over the next three years, what's the impact to the current-period revenue, and the future-period revenue?" Those are kind of the problems that I'm trying to solve, and then, also being able to consolidate multiple collaborations in one place, so a CFO [00:17:30] could potentially be able look at a dashboard, and see, "Okay, here's where all three of my collaborations are, and the revenue that I'm anticipating to recognize." Blake Oliver: It's fascinating. It's so great to see such a niche tool being explored that you're building. It wouldn't have been possible 10 years ago. It's only because we have easily accessible SaaS, and cloud, that we can do it. Paul Giese: Yeah, exactly. I think the cloud really [00:18:00] opens up so many possibilities for these niche accounting tools. I was reading ... Ernst & Young put out a study that said that 80 percent of finance-department tasks hold potential for automation. There's just so much possibility for well-executed tools that are user-friendly that can really save accountants a lot of time. I think that that's kind of the vision that I want to set out with my tool.  Right now, my tool is in beta mode, and [00:18:30] were trying to get user feedback, and improve the tool, but the overall vision is really having a tool that syncs right with QuickBooks, or Xero, or NetSuite. You just bring in all your GL data, and then it spits out the journal entry, and you don't have to touch the revenue at all. You think about the time savings from a tool like that. I think that it makes not only management more comfortable, but I think your auditor is more comfortable. That's really the value [00:19:00] proposition that I believe that intheBlk software offers. Blake Oliver: Yeah and being able to handle this increased complexity in the regulations, without having to add headcount, hopefully. Paul Giese: Yeah, exactly. I think you've mentioned on previous podcasts that one of the challenges that the accounting industry faces is a lack of talent. I think one of the ways that companies, and accounting firms can address this is by [00:19:30] utilizing systems very well. I think it creates a real opportunity for niche industry tools to really excel, and really add a lot of value to companies. Blake Oliver: Well, Paul, thanks so much for sharing your insights into biotech rev rec, and what you're up to with intheBlk. If our listeners would like to get in touch with you about what you're up to, where's the best place for them to reach you online?  Paul Giese: They can reach me at www.intheBlksoftware ... With black spelled B-L-K. they [00:20:00] can also find me on Twitter, @TheBiotechAccountant. Blake Oliver:  Paul, thanks so much for your time, and it was great chatting with you. Have a great week. Paul Giese: Thanks. You, too. 

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