Em Daigle - From Bean Counter to Business Partner: The Rev Rec Edition

Em Daigle - From Bean Counter to Business Partner: The Rev Rec Edition | Ep 029


Episode - 029: Where we learn from Em Daigle about the transformative power of automation in finance, how she moved away from just running the numbers to building strategic partnerships, the telltale signs that your business might need to consider automation more seriously, and the potential pitfalls of relying too heavily on traditional tools like Excel.


Em and Adam delve into the complexities of revenue recognition, the importance of data visibility, and the exciting possibilities of AI in the finance sector. They also explore the challenges and opportunities that come with evolving business models and the increasing volume of data. Importantly, they discuss the shift in finance's role from "just running the numbers" to becoming strategic business partners, leveraging data and technology to drive key business decisions.


This episode is a must-listen for anyone interested in the future of finance, the role of technology in driving efficiency, and the strategic decisions that can propel a business forward. Tune in to uncover how you can leverage these insights in your own journey and elevate the role of finance in your organization.



Show Notes


Where to find Em:

- Find her on LinkedIn - https://www.linkedin.com/in/emdaigle/


Tools Mentioned

- Zuora Revenue: Audit proof revenue recognition for any business model - https://www.zuora.com/products/revenue/

- NetSuite: Modular ERP system: https://www.netsuite.com/

- NetSuite ARM (Advanced Revenue Management): A module of NetSuite that automates revenue forecasting - https://www.netsuite.co.uk/portal/uk/products/erp/financial-management/revenue-management.shtml

- Alexa: Amazon's virtual assistant AI technology - https://www.amazon.com/alexa/

- Xembly: An AU tool that integrates with Slack and helps with task management - https://xembly.com/

- Slack: A channel-based messaging platform - https://slack.com/

- Causal: A tool that helps you build models effortlessly - https://www.causal.app/


People mentioned:

- Taimur Abdaal: CEO at Causal - https://www.linkedin.com/in/taimurabdaal/

- Glenn Hopper: CFO, Author & AI expert - https://www.linkedin.com/in/gbhopperiii/


📧: Sign up for The Tech for Finance Newsletter + More Goodies @ https://linktr.ee/adamshiltontech


Transcript


[00:00:00] Em:


I think one of the things that bothered me most in my, I'll say previous life was I just felt like I was running numbers and I didn't really have an impact on the business.


But being able to give some of that real strategic, insight and approach and working with the other teams as a true partnership in the organization really, you know, can help with even retaining really great talent. And giving them the ability to really find their way and grow into a, a role where they can ultimately really be impactful to the growth of the business.


[00:00:33] Adam:


Hello and welcome to Tech for Finance, where we help finance professionals leverage technology to level up their lives. I'm your host, Adam Shilton, and in this episode we are chatting with Em Daigle, passionate Revenue Accountant and Rev rec automation expert.


Em has always been fascinated by the intersection of accounting and technology, and today is the VP and General Manager of Zuora revenue.


She's on the mission toEmpower every corporate accounting team with the latest technology. Make sure to follow Em on LinkedIn for insights that help accounting leaders evolve their career, modernize their teams, and ultimately become more influential partners to their businesses. But before we start, if you like what you hear today, please make sure to subscribe to Tech for Finance on your favorite podcast platform and on YouTube.

It's really good to have you today.Em.


[00:01:23] Em:


Thanks for having me, Adam. I'm looking forward to it. Yeah,


[00:01:25] Adam:


no worries. So it'd be good to understand it a little bit more. Cause obviously you've, you've not always been fully in the tech side, have you? So if you could just give us a, a quick run through of how you've ended up at Zuora.


What, what, what's, what's that process look like and, and why you ended up where you are.


[00:01:42] Em:

Yeah, absolutely. So, you know, it's funny, I'll, I'll take myself back, and age myself immediately by talking about how I started at Arthur Anderson as an auditor a number of years ago. I think everybody knows what happened with Anderson, as a result of Enron.


So, everybody can do the math as to how old I am. That being said, I, you know, I took that role coming out of college because, frankly, I was an accounting major. and when I had a job offer before, you know, the holiday season, my senior year in college, it was sort of like all my professors just said, well, you have to take it.


It's like, no question. So jumped right in. I think a lot of folks end up in auditing or, or some fashion of that coming out of, out of college with an accounting degree. I immediately realized that that was an experience. I could check off my list and move on, uh, quickly. So, Quickly get into industry in various sort of accounting roles, you know, up through accounting manager and then realized that the, the rev rec space was really far more interesting to me than just the straight debits and credits.


And so, you know, being in that aspect of it started to go through and, and dive into the rev rec world. However, I quickly realized that there was so much of it that was. Uh, repetitive. There's a lot of data that's needed, and so it was really time intensive when we would spend all this time working on.


The, the, the data collection and the pivoting and everything and spreadsheets and I was like, this, there's gotta be a better way. And so got quickly into some of the, automation projects and ultimately had my own consulting business doing that for a number of years. So I would help companies go through and do, An evaluation, a selection, and then an implementation of the tool.


and so then it was the teams that I was working with that would ultimately own and, and use these tools. And so I actually got in with Zuora because I had done two RevPro. Now we call it Zora Revenue. implementations, from a customer's perspective. And so, in working with the teams, ended up getting really close to the Zuora folks and ultimately got hired where I started at Zuora with a team, that we dubbed our revenue advisory team.


And so what those are is a group of individuals like myself who had been in rev rec teams and ultimately came into Zuora to help. Other teams realize the value of what that looks like, try and make their current situations better. and then sort of, you know, through all of that work really was very passionate about growing our Zora revenue business and now general manager to try and help figure out the best go-to market way, uh, strategies and be able to drive the business in that way.


So it's been a really. Interesting, but, but gratifying, sort of evolution in a path that I never thought I'd be in this position, but really glad and grateful that


[00:04:47] Adam:


I am. Very good. Thank thanks for that. Yeah. And, and is, it is interesting, and I think it's really good that you've come from a customer end user perspective and then switched to, to sitting behind the tech.


So what, what advantage do you think that that gives you? Is there. What, what do you think is, is the key from the experience you learned from an end user perspective that's helped the most in moving to facilitating the tech?


[00:05:17] Em:


That's a great question. I think part of it was just under having the ability to understand all of the layers that are needed and required throughout one of those sort of implementation, let's say projects or initiatives.


I think, you know, data is such a key aspect of it, but it's not just the data cleanliness, it's the data sources and all of the different ways in which you might be integrating or you know, whatever that looks like. And then being able to really map all of that data in a way where then the automation is clean.


And so coming from a background where, I understood the use cases, I understood even the heartache that goes into, you know, knowing where all of those different data aspects are and being able to help our customers now really kind of understand better. How, how to even start that journey because, you know, it's really one of those things that it really is a lot easier knowing going into a project like that, what you're up against there, rather than trying to like work your way back and then, you know, kind of almost rework it once you're into that project.


So I think just having been in the seat gave me sort of that, that understanding and, and also a little bit of empathy for what they're dealing with. So that, knowing that when we ran into an issue or. They, they find some sort of gap that it's, we know there's an, a, a, a good fix for that and being able to help them along.


[00:06:43] Adam:


Mm-hmm. And so you, you've got an interesting perspective, so I think your terminology is X hell, as opposed to, right? Yes. Which totally understand. So, I mean, from your experience, I'm guessing there's probably a lot of companies that that's, that's the go-to, right? Uh, I mean, the assumption is that there's a huge amount of people that are still doing the rhetoric piece in Excel,


[00:07:10] Em:


right?


Absolutely. And I think one of the things that I've found most interesting is in asking customers and prospects, anybody that I'm working with in asking them what they have and what sort of level of automation. It's very interesting. A lot of times they actually say, oh, well no, we we're actually automated.


But when I ask some additional questions, it's actually not that automated. They may have a system of record for their, their, their revenue recognition. Oftentimes it's an e r p. Mm-hmm. And even those ERPs have rev rec modules that I don't wanna say claim to because for certain, uh, use cases, those are valid modules.


But the second, the rev rec gets a little complicated, there's changes in the contract, there's, you know, maybe there's variable consideration. There's things that need to be thought about all the way through. The level of automation really comes down to how many times you have to touch that contract after it's entered into the system.


So that's how I think of automation and a lot of times. X, hell we'll call it. and that came as a joke because it literally was, a password that I, I had to password protect one of my Excel spreadsheets, and I literally named it X Hell h e l l because I couldn't stand it any longer. and so it's kind of been like a longstanding joke, but really what it came down to was, yes, I had a system of record.


But what I actually had to do to manipulate all of the data after that to get the true accounting correct, required a lot of extra effort. Mm-hmm. And so trying to help companies really understand, yes, you may have a system of record that is in the E R P. But how much of the work that that is, or how much of that is actually being handled in spreadsheets outside of the system that then need to be added back in.


And that's where, you know, we see a lot of companies, I, you know, I'm not sure I've talked to one prospect or customer who didn't have some sort of spreadsheet workaround. So we're just trying to lessen the amount of times that that actually occurs


[00:09:22] Adam:


and. When, when do you think is the, the right time? So what, what I find with sort of any, and, and sometimes, you know, revette could be a major project, it might not be so major, right.


And mm-hmm. Obviously it depends on the complexity of the business, right? But Sure. Let's say somebody is using, I don't know, an r p or, or a finance system and, and a lot of work in Excel. What, what are some of the telltale signs that they might want to start thinking maybe a little bit more seriously about that, that automation piece?


[00:09:52] Em:


I think for me, when I think of, volumes of data, because as we know, Excel is capped at a certain number of rows and, and, columns. and so just understanding the increase in volume, a lot of companies obviously have. Growth initiatives. And so being able to like figure out when that, when you're nearing a, a situation where there's so much data, I think also there's something to.


The number of times that a particular contract needs to be touched or reviewed. Mm-hmm. And so thinking about, okay, we have a number of contract amendments that occur over the lifetime of a customer, especially now is we have more ways in which we want to enable customers, their own customers to buy from them.


And that flexibility is key. But what that does is that ultimately requires some sort of, Contract revisiting. And so as that happens, there's often a number of times where it results in a different accounting answer. And so trying to figure out how to manipulate, you know, a cell, which is really an ultimately a hard, a, a, a formula and a cell is a hard, is hard coded, right?


And, and so trying to figure out all the different permutations and how you do that, it's ultimately gonna break something. And so being able to make sure that all of your. Transactions are being, handled consistently across, across the board. Cause that's ultimately what your revenue policies are, right?


Like mm-hmm. You wanna make sure that your revenue policies are being adhered to across all transactions. That's really hard when you're trying to like, manipulate a cell or add something in here or, you know, remove something there. And it's really hard to sort of follow that and keep that history over time.


And then finally, I think the thing that I see most is, Companies trying to figure out new ways to go to market. You know, now we're bundling different offerings. We might be thinking about consumption in different ways. I don't think I've been in a conversation over the past six months that didn't include consumption in some way.


Like, how are, how is, uh, uh, end user ultimately using or, or, consuming your offering? And so being able to make sure that you've got the ability. Again, if it's in a spreadsheet, it's really hard to be able to figure out how you're gonna take on an account for those new offerings in a different way.


It's gonna mean more hard coding of formulas in a cell, and that ultimately is gonna start breaking down because you will it, it will end up in errors. So I think as they, as a company, sees the evolution of growth, whether it's. Increased transactions or new ways of go going to market, that's really like a key aspect of understanding when the right time is to, to think about automating it.

Mm-hmm.


[00:12:46] Adam:


And it's, and it's interesting, isn't it? Because a lot of the time we get swept up in, in the world of I've got no time. This, this is a, this is a time saving exercise, but I think sometimes people need to, to step back a little bit and say, right, well actually what's, what's the wider picture that you've, you've alluded to there?


So you, me, you mentioned data right at the beginning. Right. You know, it's not just about, you know, a list of transactions and how we post, you know, deferrals or accrual or what whatever happens to be. Right. Exactly. We we're trying to get to the point where we can. We can make better, better decisions essentially.


Right? So when you look at this in terms of not just the rev rec piece, but the other data that supports that, where, where are we? You know, is there a, is there a business case to say, look, you know, If we have analysis of marketing spends, for example, or if we have, you know, data from, from other places as as well.


Can that sort of thing be done alongside sort of a, a rev rec automation project, or is that kind of maybe a separate exercise from, from a business intelligence point of view? How, how, how do they set alongside each other or do they go hand in hand?


[00:14:00] Em:


I think that anytime you have. A project going on, it's going to require data.

That's just the world we live in. Mm-hmm. And I think there is incredible opportunity that is oftentimes missed if other projects aren't taken into consideration at the same time. Mm-hmm. I, you know, there may be sometimes where the evaluation is done and it's determined that that is not data that is specific to rev rec or, you know, the rev rec data is not specific to say, a marketing activity, whatever that might be.


There's certainly situations, but I think every company is doing itself a disservice if they don't look at their data as the the starting point to everything and what that ultimately impacts. And that just helps streamline everything. One, it could help to avoid getting to the end of a project and realizing, oh shoot, we wish we had taken that, you know, all these other cross-functional teams into consideration cuz we missed X, Y, and Z along the way or.


What that could ultimately do is set up for a future project that even if it's not in the works, but you've included that cross-functional team in the efforts around data and, and what that looks like. Ultimately, that's just going to benefit all of the teams and make all of the, the go-to-market activities that much easier going forward.


You know, I think it's just a matter of aligning and making sure that everybody's. Uh, requirements have kind of been thought through and figuring out what that data, journey is. And I say that because sometimes data as a field in an e r P can look like it doesn't impact very much, but unless you sort of have that full understanding of where that data goes and what it impacts really ultimately will help to make the entire process that much easier, whether it's your current project or future projects as well.


[00:15:54] Adam:


Okay. Thank you. And, and for the people listening that, you know, maybe aren't as up to speed with the concept of, you know, go to market strategy and you know, that they, they want to be better business partners, but at the moment they're, you know, they, they're a little bit, I won't say siloed, but you know, they know what they know, they do what they do, and they focus on their, their little piece of, of the operation, right?


Mm-hmm. When we start getting into this territory, What are some of the, I wouldn't necessarily say quick wins, but how could something like a, a rev rec automation platform support that next step of then identifying what the go-to market strategy could be, especially for people that haven't really crossed over into that space before?

Am I making sense?


[00:16:41] Em:


Yeah, absolutely. Well, I think there's something to understanding first, what your current system and your current. Financials look like. Mm-hmm. And one that they're obviously, you know, reliable and accurate, but also being able to look at the forecast of that. See where the revenue is coming from and where, when it can be recognized, and what does that mean for future quarters, especially as we have recurring revenue type of models and trying to figure out what that looks like and being able to see that over time.


Then what those RevRack teams can do is, as opposed to running the reports, doing the pivots, being stuck in the spreadsheet, then what they're able to do is take a step back. Look from a strategic standpoint and say, okay, this is what the business looks like. If we were to go and work with, even say the product management team, maybe we can package something a little bit differently.


Knowing that a certain business model works really well for having that recurring revenue model over time, and it's that predictable revenue which all investors like to see. Mm-hmm. How can we take that and, and do that and replicate it in other ways? What are there opportunities? To take what we currently have and maybe repackage it in a way where now we're maximizing our, our revenue over time, so we have that predictable revenue stream.


I think where I've seen that happen most in, in a most, Productive way is having regular meetings between the finance teams and marketing and product management, acro, even engineering, and just kind of trying to figure out what does the roadmap look like for the product? What are the ways in which they're going to price and package that?


What could that impact be on the revenue recognition of it? So it's more proactive as opposed to reactive. And that's where I've seen a lot of, Positivity on the growth side of the business, but also I think there's something to be said for the job satisfaction of those accountants. I think one of the things that bothered me most in my, I'll say previous life was I just felt like I was running numbers and I didn't really have an impact on the business.


But being able to give some of that real strategic, in insight and approach and working with the other teams as a true partnership in the organization really, you know, can help with even retaining really great talent. And giving them the ability to really find their way and grow into a, a role where they can ultimately really be impactful to the growth of the business.


[00:19:24] Adam:


Mm-hmm. And I, and I think that's a really valid point because, Data is just data until you find a way to make it actionable. Mm-hmm. and, and I think that's, that's a fundamental shift that is still going on in, in a lot of organizations because sometimes the data isn't even at the point where it's accurate, let alone actionable.


Right? Mm-hmm. And there's, there's a big difference between being able to say, I do have my rev rec schedule mapped. So I can see based on our present state, what it's gonna look like over, over this time. But let's say that in line with inflation or, you know, the cost of everything going up, as we, we know it is at the moment, the, there's logic behind a 5% price increase, right?


The, the, the admin overhead of that without a tool. A can be difficult to manage because you may be going into multiple contracts, manually updating them and you know, you, you know that cause you come from from that sort of background. But it's also then, as you say, it's that being able to, and it might not always be mega accurate because you know, there's only so much that we can do with future predictions.


But if you are then able to go to the business and say, look, based on my analysis, we think if we were to increase this particular. Contract type by 5%, you know, or from a project perspective, if we were to increase our hourly rate by X, you know, we could be in this position in, in 12 months time. And then that's directly crossing over into exactly what you, what you're saying there.


You know, how can we become better and more useful in, in the business. Right? Yeah. Yeah.


[00:21:10] Em:


And I think it's really interesting too, to see the evolution of teams. Kind of realizing that over time. Mm-hmm. You know, when I, when I first started getting into the, automation space in, from a technology perspective, I was up against a situation where I had the product team coming to me and saying, we need to be able to do this.


At the time it was a managed service and immediately, As the back office, you know, team that was trying to be, was, was, was trying to be the ones that could take that and then actually, uh, account for it. We had to literally push it back like, Two quarters because it was just a matter of figuring out how we were gonna account for it.


Mm-hmm. Can you imagine the amount of lost opportunity that we had, because it was coming from a point of trying to figure out how to account for it instead of just being able to jump in, try it, iterate on it, see how it was impacting the business, you know, making it most impactful. Instead, we had to wait two quarters just to even like think about how we could start offering it to customers.


So I think there's a a huge piece of seeing how we can use technology to help. Accelerate that and the, the teams that have figured out how to do that have been extremely successful with it and being able to help grow the business rather than, hold on, we gotta wait a couple quarters. Let's figure out how we're gonna do this.


It's gotta fit into this Excel model and doesn't right now. So we can't offer it to anybody. So I think those that have kind of been able to figure that out andEmbrace it. With the technology that we have today has been a, a really interesting evolution and being able to see like the teams that really canEmbrace that and take that on have been, have been really successful with it.


[00:23:03] Adam:


Mm-hmm. And going back to, to the point that you made earlier in terms of team makeup and team structure. So you know this, with this podcast we've got quite a wide range of listeners from really small businesses to obviously LA larger enterprises. Right. Do you need a dedicated revenue team or is it just a case of maybe working smarter with existing resource?


What? What are your recommendations? Do we need to make this into more of a fundamental part of our business and start breaking up responsibilities? Or is there an argument to say that no, if we've got the tech, we can do more with, with less people? I dunno whether you've got any thoughts around that.


[00:23:43] Em:


I do.

I think, you know, to your point, it depends on the size of the business anyway. But I think auto, what automation does is it either will allow it, it always allows you to do more with less. Mm-hmm. But it depends on what that MO doing more is, mm-hmm. Is doing more, being more strategic or is doing more being, uh, now I can handle more tasks.


So I see like smaller companies are probably looking to maybe replace headcount because they wanna spend more time in, in other areas. With less people. Mm-hmm. Where I see some of the larger, maybe public companies or more mature companies that have reached probably, I would say over a hundred million in annual revenue, where they're starting to really get their footing under them is where it's not necessarily a replacement of headcount, but it's.


Allowing the headcount that exists to be able to be more strategic and be able to read that data. So rather than as the volume increases, you don't have to increase the headcount. It's okay. We have an increase in volume, but we just know that now the system's gonna handle more the same number of people.


But we know how to be smart about what we're doing with that, right? Like being able to take the output of the system and have the, the heads that are working on it be more strategic. Maybe it also allows them to move into different areas of the business as well, that they can be helpful. They, they have the basis of understanding on the accounting and RevX side.


Mm-hmm. Maybe it's getting them into a product. Management position, maybe it's getting them into a marketing, you know, product marketing position. Like it depends on what that looks like. Mm-hmm. But it's allowing that same headcount to be far more effective in the organization than just running the, you know, uh, running the reports, pulling together spreadsheets.


and I also think ultimately what that does too is helps to even look at how contracts can be. Negotiated how contracts can be put together, so that it's maximizing the amount of revenue instead of just running around trying like, okay, we're gonna do this and now we have to figure out what that means on the backend.


Instead, it's proactively going and working with the business. Maybe it's working with the sales teams to make sure that you're putting together the, the right contracts that allow you to take the most amount of revenue at the right


[00:26:07] Adam:


time. Mm, no, that's, that's a really valid point. Thank, thanks for that.

So, Let's, let's imagine that we've got business, you know, that they don't have technology for, for this purpose in, in place, but they're thinking more seriously about, you know, revenue operations, revenue recognition, that sort of thing. So for those that aren't familiar with these sorts of tools, Are there levels?


So for example, if a company is literally just using spreadsheets, is there, like a, an SME or like a mid-market solution that's like a, an easy win? Or when we start getting into this territory, is it, is it, is it more of a, a jump up to a more elaborate solution? I dunno whether you can just talk through some of the, the levels of, of applications that were available.


[00:26:53] Em:


Yeah, there definitely are. And I think, it comes down to the, the maturity of the business and how long it's, you know, uh, been in business, how large their, their contract base is, like, how many contracts there are. If you have 10 contracts that are each a million dollars, it's probably a lot easier to handle than, you know, a hundred thousand contracts at $10 each, or whatever that looks like.


and so being able to figure out that piece of it, there's also the complexity of the go-to-market strategy too. Mm-hmm. so I see, you know, some of those ERPs that I mentioned, they have the ability to handle some of those less complex scenarios quite well, and so it may not require maybe the, the additional spreadsheet work is.


Not so vast at that point in time where that's a, that's an okay solution for the meantime. I think when there's the, the transaction volume and complexity, when that comes together and starts to be too great where the manipulation and a spreadsheet is getting. A bit too over the top. Anytime you've got that manual human intervention, there's the risk of error.


And so I think there's, there's something to the, the volume plus complexity where it starts to break down. And I think, you know, NetSuite arm, for example, is great for the lower transaction volume customers. Maybe something where there aren't, different. Data points that need to be combined into the same contract, or maybe there aren't many contract modifications, maybe a NetSuite arm is, is perfectly fine for that.


Mm-hmm. When you start to get to that threshold where there's an increased volume of transactions, now you've got the complexity of maybe it's multiple contracts or, or, uh, sales orders being pulled together into the same contract, or you need to look at contract modifications or those contract amendments over time.


That's where it gets a little trickier and we have. Maybe those, those, what we call revenue subledgers, that really can help to, help the, the ERPs in a way where it's the revenue is handled in that sub-ledger and then fed back into the E R P. So I think of it as less of a, a competition, but more like a better together, you know, you have your E R p ERPs are great for.


Certain areas of accounting and they're needed and, and they're very strong. When you have a subledger that can easily bolt onto that and be an integrated system, then that it's even that much stronger cuz it gives you that flexibility and allows you to do all of those different things that we kind of talked about here with go to market strategies or, more complex contracts.


So there's certainly something in between. And then Zuora, for example, has even levels of, Licenses that we offer too. So for less complex, situations, we do have a, a product that allows you to purchase or that you can purchase that, that allows you to be able to handle less complex situations, but still be able to handle the volume and then some added functionality should the, uh, company require with more, advanced requirements.


[00:30:09] Adam:


Hmm. And, and what, what should people be. Be looking for then. Cause of course, you know, there's, there's probably probably a ton of options on the market. And, and I think we, you know, we, we both agree that, you know, there's no point in automating what you don't need to. If the complexity's not there, then they just not, might be a business, might not be a business case.


Right. And, and I'm an advocate, you know, even though I talk about finance, tech and AI all the time, I'm still an advocate of keeping things simple and not doing something if it's not. Essential, right? Yeah. Yep. Gonna take time, resource, you know, so, so you need to be serious about the project. So yeah, as you say, first step could be speaking to your existing provider because I, and I think I, I've seen this as a bit of a gap as well.


There's. Sometimes communication between customer and the technology provider just isn't there. And it could be cuz the technology provider doesn't have the right point of contact in the organization or the changing account manager or whatever. Some customers might not know that that facility already exists and they're just not using it.


Right. You know? So I think true, you and I agree that that's maybe a question that that could be asked, but then we need to look into this and say, right. Well, We do have that complexity. We do have those, those volumes we need to go to market, to, to, to try and solve this problem, essentially. So from your expertise, if, if I'm trying to compare and contrast, are there any must-haves when you're looking at these sorts of solutions, what, in your mind is a, is a deal breaker?


Is a, is a, a fundamental tick in the box during an assessment? You know, is it, is there a couple of points that you can talk through there just to help people if they are undergoing a selection process?


[00:31:42] Em:


Yeah, absolutely. So I do think there's a few key, I'll say requirements. Mm-hmm. one being, first and foremost just integrations, what's available, out of the box versus needs to be built for integrations.


secondarily to that, and it's a bit more accounting specific, is the type of functionality that's required to meet. Uh, I'm gonna say a majority of the revenue policy requirements, and I say a majority because there's no solution out there that can claim a hundred percent out of the box for everything.


Mm-hmm. And if anybody says that, then I would question the validity mm-hmm. Of what they can actually do. Yeah. And I say that because every company. Has such different requirements, and I think at the end of the day, revenue policies are very gray in area across companies. What I mean by that is there are a set of standards and rules that everybody must adhere to, but at the end of the day, it's the policy elections and how consistently those policy elections are being applied to the transactions.


That really comes down to how accurate they are. One company may consider grouping contracts a certain way versus another company, but as long as those companies are doing it consistently is what matters most. And so I think being able to figure out what the majority of the requirements are for the use cases for a company and what can be covered there.


Because at the end of the day, what can be covered mostly out of the box without requiring custom code is really what what's critical the, the more. You get into what's out of the box versus, customized, you're basically getting, if it's customized, you're getting yourself back into a, a spreadsheet situation, right?


You're, you're not allowing your team to. Uh, take full advantage of what the flexi, uh, the flexibility that you need. And so I think figuring out what those key areas are, I always group them into sort of, I think of like ASC 6 0 6 or IFS 15 as like the five steps. Mm-hmm. So I think about like, okay, you have to figure out what determines a contract.


So like, are you doing any contract grouping? Are you trying to take multiple transactions or, Sales orders or orders, whatever that looks like, and pulling them together, what does that look like? And so thinking about. What kind of companies or solutions can, can solve for that. And then there's the allocation piece of that.


So you've, you're determining your transaction price, you're allocating. So what kind of, functionality comes out of that? thinking about actually then scheduling the revenue mm-hmm. And reporting out on it, but then, Overarching to that is any time that that contract is being touched. So those amendments, and so I kind of think of that sort of world of rev rec and what is needed across.


The majority to, or to cover the majority of those for your company, if those are handled out of the box. That is a, that is a key aspect of it. Mm-hmm. and then finally, I think that just the visibility in reporting, the ease of reporting. What do you have available to be able to ultimately get out of the tool?


Not just a journal entry back into your E R P, but what kind of visibility do you have into your, your data and what that looks like. So those are kind of like the three major areas. If I can just recap it as like the integration piece for the, like the data coming in, just the, the rev rec policies and being able to cover, a majority of your use cases and then the visibility that you're actually provided as output from that system.

Yeah.


[00:35:22] Adam:


Tha thanks for the summary. You, you, yeah. Sa saved me, saved me a, a job there. No, that's, that's great. Cemented in, in my mind. So, so that's, so on the, on the second point, cause I, I see this. Quite a lot. Is there, is there things that people can do to, to help themselves? So I, I'll give you an example, right?


So I was speaking to, a company not too long ago, and we were talking through what's your, uh, what does it, what, what do your revenue policies look like? You know what, you know, what, what do your contracts look like? Mm-hmm. And they said, they could look like anything. I said, what do you mean? Well, and.


They said, well, we, we, we just built them around our customers, you know? I said, okay. Right. Well, are there any, you know, themes, you know, is it monthly billing? Is it annual billing? You know, is there any sort of, because they did a bit in telecoms and, and that sort of stuff as well. So they, they had the concept of usage based billing as well and, and all that sort of stuff.


and I was looking at it and thinking there's a limit to how much I can help or a technology provider can help. Without at least an element of consistency. So I dunno whether you'd agree with this, if I was in that position as much as sometimes it may be tricky. Mm-hmm. And you might have some awkward conversations with customers if you're changing their billing.


But in the long run, in my mind, it's better to take a step back and design those policies with a view of consistency. Rather than making the job harder for yourself cause that that's, that it's not gonna scale. So is that a recommendation that you'd make as beforeEmbarking do a bit of a review map, what you want that consistent approach to look like before you then go into a project like this?


Cuz as I say, you might end up making life a lot harder for yourself, right?


[00:37:14] Em:


Yeah, absolutely. I couldn't agree more on that and I think there's something to. Having the expertise available to be able to make the, to, to challenge prospects, to challenge customers. You know, sometimes I think maybe there are folks who are, I don't wanna say scared to say something, but you don't wanna rot the boat.


You're like, oh, this is, this relationship's going really well to me. I actually think we're doing ourselves and, and our clients a disservice if we're not do we're, if we're not challenging. Right. Folks like you and I, we get to deal with a lot of different, scenarios, a lot of different clients. And so we see a lot across the board.


And so we kind of, we know what best practices are, so we'd be doing a disservice to our client if we're not challenging them. Taking the step back, resetting and saying like, how can we make you most successful long term? And that starts with clear policies that. At times, especially as companies are growing, may feel a bit boxed in, but really what it's ultimately doing is defining a best practice way in which they can sell as well.


Mm-hmm. So it's only gonna be advantageous to themselves as well if they, if they pause and figure out what is the best way to go to market. And maybe they quite haven't quite figured it out yet. Mm-hmm. But if they do start to try and. Formulate some bit of standard policy around those, those things, they're gonna actually, ultimately see that in the long term, that's gonna help them grow.


Sometimes standardizing some of those things, it doesn't mean being super strict and not being able to have flexibility to offer things in different ways. It's just understanding. Their business in a way where they know what is most successful and then you can help them repeat that over and over again.


So I think there's a lot of benefit in doing that. If, if that's not something that's clear to them, I think them engaging with some sort of, consulting team or consultant to, to be able to help pull that together and define what that is, will only set them on the right path, for growth in the future.


[00:39:26] Adam:


Mm. Anybody who's listening, don't, don't take this as a, you know, you need to reinvent the wheel and straight away tell all your customers that you're gonna change that buildings, you know, it's, oh, no, no, no, no, no. It's not the way that it has worked. So, so, you know, Rome wasn't built in the day, as they say.


So, I'm sure as in, in, in your world as it is in my world, you know, there is nothing wrong with doing this sort of stuff in, in phases. So if you absolutely, if you have a vi high value customer that there is some nuance in. Their contract and the agreement that you've got with them, leave that to a, to a later date.


Give yourself more notice because doing it that way, you can say, right, well, we've moved on to a, a new process, so, Just to make you aware when it comes to contract renewal, whether it's 12, 24 months, whatever, we will be migrating you to this, this, this new way of, of billing. that then gives you an amount of time to manage that, that conversation.


Right. You know? Absolutely. You know, so, so quick wins first, you know, as many of the standard contracts as possible. Right. And then the trickier stuff can, can come later. So as I say, don't, don't think that it has to be this, this massive big bang whereby everything changes at once. It, it can be sort of baby steps before giant


[00:40:43] Em:


leaps.


Right? Absolutely. And I find a lot of times that's kind of with all initiatives, everything sort of, especially the world we live in, it's so cyclical with. Month ends, quarter ends, annual reviews, like audits, all of those things. Everything is so cyclical that it's important to understand that it's okay if, if certain things in your world, maybe it's the data cleanup piece, that might be a phase, maybe it is the policy setting, that's a phase.


Mm-hmm. But as long as teams are thinking about those things and working on them, Perpetually. I don't think there's ever a time where someone's gonna say, well, I've set my revenue policy and now I'm done. Like, I wish that were the case, but unfortunately we all hope that's not, and it, it keeps, it keeps other, uh, accountants in business too, I guess.


But yeah, it's just, you know, it's something that's always changing and so holding ourselves to a standard where we should feel like we need to have it done at a certain point in time and all one big bang is, is virtually impossible. So I think you're, you're spot on, Adam with. Yeah, doing things in cycles is, is perfectly acceptable.I guess so, but


And actually probably most ex setting yourselves up for the greatest amount of success.


[00:41:55] Adam:


Yeah, ab absolutely, that's it. And you've gotta set yourself up to make life easy where you can because you've still got a day job to do, right? Yeah. And, and unfortunately, it's just human nature. As I often mentioned, we've all got this instant gratification monkey on our shoulder, you know, and as soon as we, we identify a problem, we want to solve it as soon as possible.


Right. But the thing that must be appreciated is that even if you did a phase project whereby you only get 50% of your contracts or, or whatever the project is onto the new system, you've just gotta think about the amount of time that that saved you in the Instagram. Yeah. Yeah, so, so even if there's six months between that second phase, you've just gotta focus on the short term gains and that and that sort of stuff.


So, yeah, it's, it's difficult sometimes cuz as I say, human nature is to just wanna get something in and get it done. but as I say, it doesn't make for an easy life. So, you know, just as you say, try and set yourself up for success and, and focus on the, on the quick wins first. we don't have to overcomplicate things, do we?


[00:42:56] Em:


Absolutely.


[00:42:59] Adam:


So, The one thing that I wanted, wanted to touch on, of course, it's, you know, it is a buzz at the moment, obviously, the, the whole, the whole concept of, of ai. mm-hmm. It's, it's not going away. we haven't been talking about it as much in recent podcasts cause I think everybody is suffering from a bit of ai, anxiety, AI continued with everything that's going on.

Right. But nevertheless, it is still something that, that we've gotta be very, very aware of.


Right. And, and I know, from some of the points we were discussing before the session that you were involved, was it with pwc there was a, there was an AI in finance forum. So, and, and again, you know, you, you don't have to go into, into war and peace over what topics were discussed, but from your perspective, and it could be, you know, revenue, accounting, it could be another area of of tech and finance.


What do you think are someEmerging trends in line with AI and new technologies that we need to be aware of? are there any predictions that you've got, even though, you know, I, I don't like sort of holding people to predictions, but it'd be good to get your perspective on the way you see these things evolve, evolving in the next, well, it, it could be next week.


We don't know how, how quickly this stuff's gonna come in, do we? But I don't whether you can talk a little bit about, you know, your, your perspective on all of this.


[00:44:15] Em:


Yeah. I think there's something with accounting where. There are certain tasks, and this probably goes for a number of different areas with the the concept of AI and how it's gonna impact our lives.


But my hope, I'm gonna say hope rather than prediction, but my hope is that we can leverage AI to replace some of those more mundane tasks that take away from job satisfaction. Make us feel like we're not as impactful to the business. and, and maybe just help out from a, from a headcount perspective.


But ultimately I don't see, at least in the near future, and based on a lot of conversations I've had around this topic recently, is there is still so much, Judgment that is required, especially in rev rec where I, I struggle to understand how AI could even replace that. you know, I think. Especially as we have, security concerns around AI as well.


It's not that we're opening up our systems to all of the, the various, you know, uh, data inputs that feed AI and make it better and better and better. And so, You know, maybe six months ago when the conversations really started to heat up around this, I immediately thought, oh God, this could like negate everything and then, you know, it didn't pass the CPA exam.


I'm sure at some point they're gonna figure out a way to make it pass the CPA exam. It has, it has, it has


[00:45:48] Adam:


done now. Yeah, it did.


[00:45:49] Em:


Yeah. Oh yeah. All right. See, I guess you can make AI do anything, but that being said, You know, I don't see how it can bring the judgment piece in, in the ways in which we would be securing our own data aspects to what is required around ai.


So I think it's a, it's, to me where we'll be most successful is when we can figure out how to leverage AI for good. Mm-hmm. And be able, like I said, take away the mundane me, me more. Repeatable tasks that an AI system can take care of and leave the judgment still to humans being able to also think strategically around what we want to do with those things.


So some of the things we talked about earlier is how, how can you take the output of what you're seeing in your rev rec today and then help that drive your strategies going forward? I don't know how AI can really. Make those strategic type of assumptions to be able to drive it. I think AI is more taking the output and just understanding how to report out on things.


But I, I don't yet understand how it would be able to help drive strategy per se, which still requires some bit of that human judgment and, and I'll say, uh, Input, I guess, for lack of a better term.


[00:47:15] Adam:


Yeah, yeah, absolutely. And, and, and we touched on this a few podcasts ago with, Tamer. Tamer Abdi, who's CEO at Causal.


Mm-hmm. Uh, we really interesting conversation. and we're talking about that decision support piece. And, I use AI as a sounding board, um mm-hmm. And, and, and I, I use it, you know, cuz everybody's got decision fatigue mentally fatigued and. Every now and then when things get a bit overwhelming and I've got a decision to make, I'll put the variables in and I'll say, from, from your perspective as an ai, what are three scenarios that could be outcomes from what I've, I've given you, right?


Mm-hmm. so from a support perspective, it can be useful, but what I often find, and it's bizarre, it's, it is very weird. How it works, is often the first answer it gives is the one that you already had in your own mind. And, and, and it might interesting. Yes. Might, might be, might be coincidence, right. Or it might just be way mm-hmm.


That, that you frame the question. But, but it is interesting, to have that level of knowledge. Cause obviously it's built with a vast amount of data, right. Just to Right. Get a quick, a quick response on that. But I think for, for people listening and now I've had some conversations recently with some, some people with really big, big brains talking about, finance and AI is, accuracy is still a concern.


Because AI doesn't see numbers in the way that we do, right? So, we can input values and based on the formula, the output of those values is always gonna be the same. Because it's class, right? But with an ai, and the best term is Glenn Hopper. That that described it in this way was predictive text. The nature of AI being generative.


It might not always provide the same answer every time. And it's those variations, uh, the, the bits to, to watch out for. You can connect either to war from alpha now, which is very accurate. database in terms of metrics, uh, statistics and all that sort of thing, which, which really helps. But there's, there's still still a big gap, you know, and, and, everybody says that the more you use ai, the more quickly you start to appreciate its limitations.


Yes, but that's not to say that it can't be useful in some instances. I think the quick wins with AI at the moment are, and, and using a finance specific example here, you know, providing the data protection policies are in place for whatever tool that you're using is giving it data and doing a q and a.


Because as a finance pro, you probably get a lot of questions every day. Oh, can I have the report for this? Or What's going on with that number? Or what's going on with that number? If you can hand that off to an ai, you know, sort of internal support bot, that's just gonna get mm-hmm. Those very simple questions.


I think that's, that's a real quick win. And obviously from a personal perspective with, you know, some of the softer stuff, document creation, you know, all of that foundational stuff, I think that's, that's gonna be really useful. But I think you're right. There's, there's still a bit of a way to go. From my perspective, it's just that, it's just that timeline because it's not, it's not incremental and steady in the same way that tech evolution's been today.


It's, it is a hockey stick. It's so the, it is durations are becoming closer and closer and closer, which is why I. I just don't try and make predictions because we end up being wrong. Anyway, I could talk about this, maybe


[00:50:43] Em:


we can use, maybe we can use AI to make a prediction or something like that and see where it lands.

Yeah, yeah,


[00:50:49] Adam:


absolutely. Yeah. We'll, we'll, we'll get chat GT to generate some Python code, link it to a machine learning algorithm and we can ask it load of questions, which I'm sure loads of people have already done. Glen Hopper did actually send me a link to research that. I might put it in the, in the show notes.


But, anyway, we, we digress. So I appreciate we we're coming up to, to time and the, the question that I tend to ask all of my guests, and this wasn't on the list of topics, is, I'm a bit of a nerd when it comes to like, productivity apps, you know, uh, Google Chrome extensions, you know, all of that sort of, you know, stuff that, that you can download as an app on your phone or, or whatever.


Some of the answers we get quite often is stuff like notion from a, you know, database, task management point of view. we've had, smartphones listed as a, as a gadget. So, so the question to you is, is there an app on your phone, you know, any sort of software that you use, either in your professional or your personal, you use every day that you literally could not live without?


[00:51:47] Em:


Um. I wish I could use Alexa because she's like in my kitchen with me and I can order like paper towels at, you know, at every drop of a hat, but it doesn't actually help me in my work. So what I would actually say is SMB is, it, it was, it's through Slack and basically I'm gonna say she, yeah, for lack of a, a better way to, talk about it, but.


She literally tells me when I need to block time for myself. She gives me readouts on notes from my meetings. She gives me, I, I mean, she has been such a lifesaver and I was so nervous to use it when it first popped up, as in, do you wanna use Zuli to do these tasks for you? And I thought, what is this thing?


And I took the dive in. I love it. She has saved me so much time and more importantly, like I said, reminds me to block time for work andEmails and that sort of thing. So she has been a saving grace for me.


[00:52:43] Adam:


How so, so you've, you've done, well, you've actually introduced the tool I've, I've never heard of before.


How, how are you spelling it?


[00:52:51] Em:


Okay. It's X E M B L Y.


[00:52:57] Adam:


Wow. Okay. I'm gonna check it out. Does it only work with Slack?


[00:53:01] Em:


Yep. It's, it came to, it was like suggested to me in Slack. I don't even know how it came through to be honest, but it has been a saving grace. She's now in all of my, like my calendar everywhere things pop up.


Do you want me to send you this summary of a meeting? Do you want me to block time? She's a godsend.


[00:53:20] Adam:


Wow. Just raised 15 million. Apparently. Well, end of last year, raised 15 million. Wow. I'm gonna check it out. Thank you for that. Yeah, of course.


[00:53:30] Em:


And secondarily to that, it's always Alexa. She's my, she's my go-to too as well.

Yeah,


[00:53:34] Adam:


yeah. I've been a bit annoyed with Alexa recently cuz she sometimes just makes up answers. May, maybe it's just cause she doesn't understand me. But yeah, there's, as an ai, she's definitely not as advanced as some of the other other stuff out there. Well,


[00:53:50] Em:


if anybody's listening and they have children school age, I did realize you can go and look at, past history of what it's been asked and I realized my daughter was using it for her homework.

So something to be aware of. She was asking all the math questions.


[00:54:04] Adam:


No, at the, at the moment for me, it's uh, baby Shark. the new, Kylie Gue song. Ah. Mm-hmm. Which is always in my head at the moment. Mm-hmm. I mean, it, it's great to have the kids dancing around, but it messes up my Spotify playlist cause I've not yet got the family account.


Cause I'm, I'm, I'm too tight.


[00:54:28] Em:


That's a must. You're gonna need


[00:54:29] Adam:


that. Okay. And where, where can people find out more about you?


[00:54:34] Em:


So on LinkedIn, it's m dle, very simple to find. and then we are also kicking off a podcast as well, which you'll be able to find through my LinkedIn as well. So would love to connect and have any additional conversations that people would like


[00:54:48] Adam:


to have.

Perfect. We'll put those in the show notes. and that's Daigle spelt d a i g l e, correct. E m e M. Perfect. Cool. Alright, well absolute pleasure having you on the show. Really appreciate you, you coming on and sharing your insights. I think that's been really useful. So, yeah, hopefully catch up soon.


[00:55:09] Em:


Absolutely. Thanks for having me, Adam. Thank you.


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