From Fantasy to Forecast: What Clinical Trial Budgets Get Wrong

Maria Abouseif (Condor): Hi everyone, and thank you so much for joining. We're thrilled to have you with us today. I know many of you are navigating the ever-growing complexity of clinical trials and everything that surrounds forecasting and budgeting, so we have a packed discussion ahead on how to work through those challenges.

A quick intro: my name is Maria Abouseif, and I lead our commercial function and partnerships here at Condor. I'm joined by Chris Chan. I know his title on screen says Bruce Lee, and we'll get to that.

Chris has spent the last three decades in biopharma companies of all shapes and sizes. He's a thought leader in the industry, has written extensively, and has worked primarily in FP&A and clinical R&D. He's given numerous presentations at conferences and developed sound methodologies around budgeting, financial accruals, and outsourcing. Some of the companies he's worked at include FibroGen, Genentech, and Exelixis, and most recently he was VP of FP&A at IGM Biosciences.

A fun fact about Chris: when he retires, he hopes to become Bruce Lee or a Jedi Knight - hence the name on screen. Chris, welcome. Do you want to say a quick hello?

Chris Chan: Yes, thank you. I want to explain to everyone that the Bruce Lee title is not because of any delusions of grandeur. Maria and Audrey made me sign in to get into this webinar, and I just put in any old name to see if it would work. It did, and now I can't change it. So you can call me Chris or you can call me Bruce.

I'm very happy to be here. Anytime anyone pays attention to me, I'm a happy person. I know Maria has questions for us to go through, and I'm looking forward to the questions from everyone joining, which I really appreciate.

I do want to make sure you all know you're here for clinical trial budgeting. This is not Comic-Con. Mark Hamill is not showing up. You're just going to listen to me talk about budgeting, so let me be very clear about that.

Maria Abouseif: Thank you, Chris. Before we dive in, a little about us for anyone who hasn't heard of Condor. We are the financial cloud for R&D, purpose-built by pharma teams for biopharma. What we do every day is help biopharma finance, accounting, and clinical teams drive efficiency, compliance, and accuracy by automating the end-to-end process for clinical trial accruals, forecasting, budgeting, and benchmarking. If you're interested in learning more after this session, feel free to reach out. But today the focus is on strategies and lessons from Chris.

We have a lot to cover, and we want engagement from all of you, so please use the chat for any questions as we go. We'll get to them at the end.

We've structured this around three big themes. First, common budgeting and forecasting pitfalls - Chris has seen a number of those over his career, and we want his perspective on what he's experienced and the best practices that came out of it. Second, bridging the gap between accruals and clinical budgets, because we see a lot of teams working in silos between accounting, forecasting, and budgeting. And third, how to plan for uncertainty in a dynamic market and balance that uncertainty against optimism bias.

Chris, let me start with budgeting and forecasting pitfalls. We've been hearing a lot from sponsors lately about the challenges around investigator grants. It seems to be a very challenging area, and one that often doesn't give sponsors much visibility or transparency. From your experience, how do you go about budgeting or forecasting for it?

Chris Chan: Happy to talk about that. The reason people are interested in the investigator grant component is that it typically makes up a very large part of any clinical trial budget. I always say it's about 50 percent, give or take. It could be more, it could be less.

Before I dive in, a word on clinical trial budgeting in general. How many people listening who have some responsibility for budgeting and forecasting for clinical trials have been asked by a boss, a CEO, or a CFO, "We're going to run a trial - how much does this cost?" Whenever I get asked that, my smart-alecky response is, "Well, how much does a car cost? How much does a shirt cost?" It's a huge spread. Is the car a Ferrari or a Yugo? Is the shirt from TJ Maxx, or is it what Leonardo DiCaprio wears? The point is the range is enormous, and the trick is knowing what the assumptions are.

Coming back to investigator grants, what makes them hard is that it's genuinely difficult to know all the parameters up front. The clinical team has a rough idea. There's a protocol, and it changes over time, of course. To get the budget right up front you have to make a lot of assumptions - and you're going to hear that theme again and again.

The easy question is how many patients there will be. But to get to cost, you need to know where you're enrolling them. Is it all in the US? What types of institutions? What regions? Are you going into multiple continents? All of that has a very material effect on the final budget. There's also a rough idea of how long a patient will be on study, and of course patients drop off, there can be open-label extensions, and many things can change the parameters. These have major budget implications, and you cannot fathom all of them up front. You can suspect they're coming, but guessing at them is like guessing whether the 49ers or the Chargers win the next game.

The last thing I'll say here is that the patient visits within investigator grants are actually very straightforward. You look at the CTAs, the clinical trial agreements for all the sites. The budgets are there, the cost of each visit is there, the procedures associated with each visit are there. If you have that plus a source that tells you what the verified patient visits are, it's simple math. Multiply patient visits by the budget, and you have a forecast - and accruals, when you're doing the accounting. That part is relatively simple as a calculation.

The part that's really hard for companies to estimate, and I've seen this time and again and experienced it myself many times, is the invoiceables component. There are site invoiceables - you sign the site and there's an upfront fee, a setup fee, storage, dry ice, all sorts of cool things. And there are patient invoiceables: procedures where the doctor says this was unscheduled, but we want to give a couple of additional MRIs or biopsies to patients. Those are by definition unscheduled, so they're hard to guess.

Normally they're not that material, but for some studies they can be, and once they add up to something material it becomes a problem, because a lot of companies say, "They're not material, so we're not going to explicitly account for them in our models." That works until it's a little too late, until you start seeing a bunch of them and you're scrambling.

So in conclusion, there are a lot of variables that can affect the budget and the accounting, which we'll talk about later. That makes it dynamic and fun, quote unquote.

Maria Abouseif: You brought up a great point about invoiceables. We hear that all the time. What's one best practice you'd recommend for forecasting around procedures or invoiceables that aren't scheduled with visits? And I'd be interested to hear from the audience in the chat as well if that's an area you're challenged with.

Chris Chan: I can tell you my practice, which by definition is not a best practice - that would be presumptuous. Different people do it in different ways.

One way I've done it, which is fairly rational, is to build an assumption into the forecast. To make up an example: for every ten patients who go through visits, maybe one or two might have an additional procedure of a certain type, and you build that in. Then as the trial runs and you start seeing unscheduled invoiceables come through, you tweak it. In the original budget you might assume two procedures every three visits, and later you change that to four, or to one.

It's more art than science, but I can verify that this is how many companies do it. If anyone is doing some version of that and feeling sheepish about it, don't. That's the best we can do, and I can verify it - I've done it many times and I still had a job. It's as effective as any other methodology.

Maria Abouseif: For those of you on the webinar, please use the chat - I'd be interested to see whether you're doing this today, and how many of you are leveraging trending information and look-back analysis and adjusting on a periodic basis.

One other thing, Chris. We see a lot of different models. Some sponsors use CROs, some run trials in-house, some use a mix or an FSP model. When it comes to investigator payments, should there be different considerations around budgeting and forecasting depending on the approach? If the CRO is the one paying the sites, we often hear sponsors are challenged with delayed invoices. What are your thoughts, and what would you recommend?

Chris Chan: I apologize if there are any CROs here at this webinar. Maria, I told you specifically not to let any CRO personnel in.

If anybody does a budget forecast based on an estimate a CRO provides, I would whack you upside the head with a ruler the way my teachers used to do to me. They're notoriously inaccurate - I've seen them wrong more often than right. Keep in mind that for CROs, the investigator grant component is a pass-through. When you look at their contracts, you'll see the grants component below the line, below all of their direct fees, as a pass-through sitting right next to travel expenses. They make some assumptions, and if the assumptions are off there are really no ramifications, other than the sponsor sneering at them and paying anyway.

So I highly recommend that if you're forecasting the investigator grant component off a CRO estimate, do your own instead. Get the parameters. Get together with the clinical team and get the number of patients and visits. They most likely have, or they had better have, study budgets, or at least the initial model they used for the request for proposals or for the templates sent out to sites. That's a good starting point. Take those budgets, put them into this software I've heard of called Excel, plug in your latest thinking, and build the budget that way. I can almost guarantee it will be much better than anything the CRO provides.

The other nice thing is that even if it weren't significantly better - which it will be - you can at least track your assumptions, because you can see the model. You can see the visits, the cost per visit, the timings, the numbers. In many CRO estimates for investigator grants, it's one lump sum. The best you can do with that is straight-line it across the trial, which isn't good at all.

If there's one strong suggestion I'd give, that's it. And I know there are a lot of vendors here - I see some in the participant list - and they can help with these things, which is great. But what I can verify is that even something more primitive, an Excel file or a yellow sticky note, will project this out better than any CRO estimate. That's my opinion.

Maria Abouseif: Great advice, thank you. Let me shift gears a little, because we have a lot to cover. Teams often don't have much time to find where the errors are. If you yourself were reviewing a clinical trial budget today and you only had five minutes - we'll really put you to the test - what are the key focus areas you'd look at? Where do you recommend people start if they can't dig into every nuance?

Chris Chan: There are many moving parts in a clinical trial budget, which is what makes it interesting and challenging. But I'd immediately look at two very big buckets that I'm sure many people here look at too. What are the assumptions for the direct fees, say if you're using a big CRO? And then investigator grants, which we already talked about. After that, the other components that are significant - if the trial uses comparator drug, for example, that becomes really big.

There's one thing I really want to emphasize. People recognize that CROs and investigator grants are roughly 50/50 or 60/40 based on past experience, but there are important factors you have to build in.

First, there are companies - as scary as it sounds - that may not use a full-service CRO. Some, in an effort to save money, go with regional CROs or service providers. Say they use five different ones across five continents because they can find the cheapest in each. That changes the budget.

An even bigger one is the company's assumptions about outsourcing versus insourcing. That changes the equation a lot. Investigator grants are what they are, but I always remind people that everything a CRO does for you, everything that makes up that enormous, impressive budget, you could do in-house. A company can hire its own people and do more or less everything the CRO does. You choose not to because it isn't efficient, so you use external CROs for resourcing, to meet the ebbs and flows of clinical trials.

I've worked for companies whose whole philosophy was, our competitive advantage is that we hire the brightest and best people - that's why I worked there - and we only contract out what we call the commodity. You don't need to be a Wile E. Coyote super genius to monitor a visit, so we'll contract that out. But for CTM or CPM-type work, we're not using CROs, we're hiring our own people.

That decision changes the cost structure. All of a sudden your outsourcing budget goes way down. If you don't also look at what changed in the insource component - did we hire a bunch of people, did we change the model? - and you only look at the clinical budget, which a lot of people equate to the external clinical budget, it's misleading. You end up asking why this is so big or so small.

The flip side: I also worked at a small company, under 50 people in total, running two global Phase 3 trials at the same time. Everything was outsourced. The external budget looked very impressive, and the internal budget was tiny. People sometimes don't pay attention to that.

Those are the areas I'd jump to first: what are the big-ticket assumptions? Then, given time, I'd get into the other smaller but still significant assumptions, like patient duration and the number of monitoring visits. I always mention monitoring visits because they're such a big part of any CRO contract. It makes a huge difference whether the company decides on a monitoring visit every four weeks, every six weeks, or every eight weeks. That usually equates to millions of dollars. So that's my long-winded answer to your very concise question.

Maria Abouseif: So lots to look for, but mainly around direct fees and the various CRO models.

Let me shift gears again, to alignment. We sometimes see big discrepancies when accounting is using one methodology to calculate specific line items and the FP&A team is using a completely different one, and you end up with huge variances between budget and forecast. In your experience, how do you encourage teams to keep the accrual side in sync with forecasting so those variances don't show up unexpectedly?

Chris Chan: Let me answer it this way. I encourage them by very gently reminding them that if you don't match the accrual methodology with your forecast methodology - or rather, if you budget without taking the accrual methodology into account - you have now built in a variance.

One of FP&A's big jobs is explaining the variance on a monthly, quarterly, and annual basis: this is what I budgeted, this is what came in, and here are the differences. If you don't take the accrual methodology into account when you budget, there's already a built-in variance. Even if the trial went exactly as planned, which almost never happens, you'd still be explaining why the budget differs from actual expenses. That job is hard enough without a self-inflicted gap.

Let me interject here. I'm a strong believer in finance - FP&A, accounting - being very kumbaya close to the clinical team. I've seen both sides, adversarial and genuinely team-oriented, and the latter always works much better. So in that spirit I'd remind my clinical counterparts: if we don't do this properly when we budget, and if you don't understand what we're doing on the accrual side, both of our teams will be called in front of the principal to explain why these numbers are so different.

I really emphasize that every FP&A person who isn't responsible for the accounting and accrual side, and every clinical person, needs to understand how the company does accruals. Methodologies vary enormously. I've said this many times: there are no standard methodologies. If you join a new company assuming clinical trials are accounted for the way they were at your last company, you're probably wrong.

Because of that lack of a standard, it's always fair game for finance, together with the clinical folks, to propose alternative accrual methodologies. People think they're stuck - this is how we do things, the auditors are comfortable, the CEO and CFO are comfortable. That may be true, but sometimes it's important to do something that makes sense.

Maria Abouseif: What do you mean by that?

Chris Chan: I mean something that's efficient. I use the analogy that if your goal is to count the grains of sand on Waikiki, you can hire an army of people to count every grain. It'll be very accurate, but not very efficient. Or you can find a way to estimate it - bring in some engineers, work from square footage and acreage, and calculate.

My point is that companies go through stages. A Phase 1 company, or a company running Phase 1 trials, is very different in its nuances from a company running Phase 3 trials, or five Phase 3 trials. The accrual methodology you use in the earlier stages may not be efficient for the later ones. It works the other way too: if you come from a company that's done nothing but 40 Phase 3 and pivotal trials and you join a company with two Phase 1s, you shouldn't use the same methodology. So always explore whether there's a better, more efficient way.

Here's a quick story. I joined a company that will remain nameless - I don't think they exist anymore. They used a methodology some of you may be familiar with: they accrued trial expenses based on a regular report they got from the CRO. They paid the CRO a couple of dollars and said, before our close, please send us this report, and we'll record that amount. In theory, who knows better what the direct fees are than the CRO? It's their work.

In this case, some of my very smart FP&A people said, this doesn't make any sense. I asked what they meant. They were looking at the trends, and the direct fees being recorded month over month went straight up and down the chart. They called it an EVA, an earned value analysis report. We called it an EKG, because that's what it looked like. It made no sense.

We told the accountants, and they said, don't change it, we're very comfortable with this. It's third party, the auditors ask and we hand them the email from the CRO. But it made no sense. So we proposed a new methodology that combined that report with internal models built on the data we already had from the EDC and elsewhere. We changed it, and we made the process both more efficient and arguably more accurate. That's just to underscore that it isn't set in stone - you always have the opportunity to change an accrual methodology.

Maria Abouseif: That's really helpful. In that situation you leveraged homegrown models. But when you think about the growth in complexity - protocols getting more complicated, global studies, multiple CROs on one study, multiple vendors, labs, imaging - this is a space where technology historically wasn't up to par. Now there are tools on the market and we're seeing the space evolve. What are your thoughts on where tools and technology are today in terms of driving alignment across accounting, finance, and clinical?

Chris Chan: The tools I've seen have been getting better over the years. Some of the ones I saw years ago, where the founders were very optimistic, were fairly primitive. The ones I see these days, with more experience and industry feedback behind them, are better. So I think they'll help.

That said, I've yet to see a tool that will easily predict all the assumptions for a clinical trial. What tools do very usefully is track the myriad changes over time. Take protocols: if you have an initial protocol and four amendments over the next two years that drastically change the study assumptions, that's very hard to keep track of. And those protocol changes don't neatly align with the timing of finance budgets, forecasts, and long-range plans. They're all moving parts. I find it very useful when a tool helps me keep version control, and when information is available at the proverbial push of a button.

Down the road, when Neo and the Matrix take over the world, maybe there'll be something that helps even more. But for now I think we're still waiting.

As a note on that, for fun: people told me there's this neat thing called ChatGPT. Have you heard of it? So earlier this week I went in and typed, how much does a Phase 2 trial in multiple sclerosis cost, and left it at that. I think the machine cursed at me, because it went through several screens and rounds of calculations and data pulls. I encourage all of you to try it. The punchline is that it asked for more parameters and then spit out a range: it could be as low as $70 million, it could be as high as $150 million. And I thought, that's very helpful - if I gave that to the CFO, I'm sure he'd love me to death.

The point is that this is really about keeping track of all the detailed assumptions that are constantly moving and changing. A tool that helps with that will be very useful for 95 percent of the people listening here.

Maria Abouseif: I'm conscious of time, so let's get to the third and fun part: planning for uncertainty and optimism bias. We see shifts all the time - protocol amendments, enrollment targets. We've all seen budgets that assume 100 patients enrolled in six months, and 12 months later we're barely halfway there. How do you balance between being too optimistic and too pessimistic? What's the right balance, given the complexity and global scale of these trials?

Chris Chan: A related and funny story. Someone asked me a few weeks ago, "Chris, when you budget, how do you budget for all the change orders that are going to come?" I stopped for a few seconds and thought, okay, Chris, be nice, don't say anything too sarcastic. And then I said, well, by definition, a change order is something you don't know about. But you get my point - it's an uncertain environment.

There are two dynamics to keep in mind, and I think everyone here has experienced them. Clinical trial budgets are, at the same time, too optimistic and too pessimistic.

What do I mean by that? Let me differentiate between the overall study budget - call it a Phase 3 budget over three years, external costs - and the corporate budget, which covers this year. We have to care about both, because finance has to explain this year's variances. When the CFO asks where we are against budget, they aren't necessarily asking about the whole trial. They're asking how we're doing against this year's budget for this trial and that trial.

There's a strong and frequent tendency for clinical trial budgets to be overly optimistic on the annual view, and it's easy to understand why. You sit down with your clinical colleagues and they say, we're going to enroll this many patients in this many months. You can say, are you sure? It was a lot slower in the last trial and the one before. And they say no, no, this time it's different. It's hard, because that's their goal. You don't want to hand them a budget that says we're assuming you'll fail, so we're knocking the budget down.

So the annual budget tends to be optimistic, and you adjust as you go. But when enrollment takes longer, your annual corporate budget will show an underspend, because things are slower than you budgeted. And that same delay will most likely add to your overall clinical trial budget, all else equal, because it prolongs the timeline. It also pushes the clinical team to bring in more sites, do more site visits, and hand-hold sites to speed enrollment up. Both of those things are happening at once, so it's important to differentiate between the short term and the longer term.

There are two ways to deal with it. For the annual budget, what I and a lot of people do is apply what some call an adjustment and others call a float. Rather than telling the clinical team, you're going to fail, you're not going to enroll all these patients, so go have some coffee - you put their plan into the budget as they gave it to you, and then you make an adjustment on the back end.

A simple example: clinical thinks they'll enroll 100 patients this year. On the back end, my finance team and I ask, what would it look like if they enrolled 80, or 75? What does that do to the model? Say that reduces the annual budget by $10 million. I'll adjust the overall budget down by $10 million in a different area of my corporate forecast. The important part is that the clinical people running the trials are not responsible for that adjustment. It's purely a finance exercise to make the overall budget more sensible. The clinical team still manages to their own budget and still explains against it, because implementing what I just described at their level would only confuse them.

For the overall budget, where this really applies is the long-range plan, when you have to put in budgets for the next five or ten years. There you use something called PTS, probability of technical success. You apply percentages based on a predetermined formula. If you have five Phase 2 trials running right now, you know not all five will necessarily go into Phase 3 - maybe the results won't be good enough. But you don't want to put nothing in the budget. So if you decide that 80 percent, or 50 percent, or whatever the case may be, will progress to Phase 3, you apply that probability in the long-range plan.

Those are a couple of very common tools people use. And to your point, if you have systems that make that process easier, people will love it.

Maria Abouseif: Great advice. So essentially you're keeping two budgets, or one budget with an override, where you weigh in the different scenarios - change orders, dropouts, the optimism the clinical team might have - and apply an adjustment on the back end to account for it.

I'm conscious of time, but these are fantastic strategies. We do have a couple of questions, and before I open it up, please put your questions in the chat or the question box. And to answer one that came in: yes, we will absolutely share this recording with everyone after the webinar.

One unrelated question first, since you're the Bruce Lee and the Jedi Knight. What type of Jedi Knight do you want to be when you retire?

Chris Chan: I've always been partial to Obi-Wan. But now that I think about it, I'd rather be Neo from The Matrix, because AI is becoming the big thing, and Neo could fly. So let me rethink that. If I were a Jedi, Obi-Wan. All else equal, I want to be Neo.

Maria Abouseif: One question from the chat: would you recommend writing a memo on the accrual methodology? And if the accounting team is outsourced or fractional, how would you recommend keeping them in the loop?

Chris Chan: The accounting team is a very big part of the accrual process. In most places they'd be the owners, so they definitely have to be involved. I'd almost say they should be the ones writing the memo to tell everyone else what the accrual methodology is.

Personally, I would document it. I don't know that it has to be a memo, but I'd write it up. I wouldn't make it so formal that it becomes auditable - where someone can say you didn't do one of these 100 things you said you'd do, so you're out of compliance. But I do want at least an outline of how we do things on accruals, and I'd use that as the guidance.

In fact, I'm a big believer in developing an easy-to-read deck, with cartoons and Neo from The Matrix, and sharing it with the different stakeholders across the company - accounting, clinical, and even the CEO and CFO. They need to understand how the company does accruals, because they're the ones signing the financial statements saying they understand everything, or they go to jail. That's a better version of a memo. But yes, something that documents and shares the methodology and is available to everyone. And not just available - push it out, and hold regular meetings as a reminder: this is how we accrue, so when you look at your next variance analysis and at those actuals, this is what you're seeing.

A simple example of why that matters, and this actually happened. I see my colleague John Gouze here - at one of our previous companies we used straight-lining. When a CRO contract was signed, we'd take the amount and divide it by the number of months. So after the first month, there's an expense. Clinical people who don't know the methodology get very confused: why are there expenses? We haven't done anything yet, we haven't even started. And then you have to explain that this is our methodology. That's a very simple example of why understanding the methodology is so important. So yes, I agree that having a memo or something shareable is very important.

Maria Abouseif: And it can be revisited every so often, when you look back and do that flex analysis and see where the variances are.

Another question for you, Chris: can you talk a little about forecasting and closing tools - software?

Chris Chan: Let me answer this way. I personally have not encountered an all-encompassing budgeting and forecasting tool. There are a lot of tools out there, and I know some people in the participant list are saying, hey, pick me.

I'll cite only the ones that have been around a very long time, which doesn't necessarily mean they're the best. A lot of companies use ClearTrial to estimate CRO expenses. GrantPlan is used to estimate investigator grants when you have no detail beyond the regions and the disease area. Those help. They're benchmarks, and benchmarks always help.

I will caution you on benchmarks, though. What the world publishes as a benchmark is often an average, and it carries its own assumptions. Your company's specific trial nuances may be very different, so make sure you use benchmarks properly. But they help. If someone asks you for a clinical trial estimate for long-range planning - we're starting a Phase 3 next year, we have no quotes, no protocol, nothing, but give me a number - industry benchmarking is very useful there.

In terms of tools where you punch something in and get something very specific, I'm not familiar with ones that are all-encompassing. I see a lot of companies developing them, and I fully anticipate they'll be fantastic in the not too distant future. For me personally, when I forecast a clinical trial, it's less about the tool and much more about the assumptions. So a tool that helps me efficiently track all the assumptions and the 50 changes I'll make over the next six months would be very useful.

Maria Abouseif: There's more we can share there, so we're happy to answer questions about Condor's capabilities when it comes to tracking both accruals and forecasting, and our role in helping sponsors close the books and track accurately, to Chris's point.

One final question, from Naomi. For investigator grants, invoiceables are probably one of the most challenging areas to accrue and forecast for. You mentioned estimating a certain number of procedures per patient as one methodology. Is there any type of EDC report you've seen that might have this detail, similar to visit data reported in the EDC?

Chris Chan: That's an excellent question. In my experience it's not so much about the tool as about the procedure.

I've asked a lot of clinical teams a very simple question: does your EDC have details on unscheduled procedures? The answer is typically, some of them do, but it depends. If we ask the sites to enter it, it might be there, but it's inconsistent. If we don't ask, then no. And in that case you won't know about it until the invoices come in, and those invoices could arrive quickly or a year later, and you won't know for a year or more.

So the answer is that if all the data were entered completely and in a timely manner, then yes, there are many tools that tie directly to the EDC. But whether the data exists in the EDC, the IRT, or whatever source is supposed to capture it - that's the problem.

One thing you can do is encourage the clinical team, when they write the protocol and the operational SOPs, to say to the CRO and the clinical leads: make sure we incentivize investigators not just to input all the patient visit data, but to input unscheduled procedures too, and make sure the EDC can handle that easily. So unfortunately it isn't as simple as use this tool and you'll be fine. It comes down to how the input is captured.

Maria Abouseif: Absolutely. We're on time, and this flew by. As a recap, I want to personally thank Chris for sharing such wonderful strategies. I hope you all found it helpful, and thank you for your engagement and for attending.

If you have further questions, or if we didn't get to yours, feel free to reach out to Chris Chan directly on LinkedIn. And if you're interested in learning more about Condor and our platform's capabilities in automating accruals, forecasting, and budgeting, reach out to us at condorsoftware.com or at info@condorsoftware.com.

Chris, thank you so much for sharing - I appreciate all the strategies and best practices today. Thanks everyone for joining us, and we'll be sharing the recording following the webinar.

Chris Chan: Thank you. Bye.