Joel Blachman on Getting Off the Ad Hoc Analysis Treadmill
In this episode of The Role Forward, Joel Blachman, an operations and finance lead at Amper Technologies, gets into the importance of automation tools while doing ad hoc analysis and getting more proactive with analysis so you aren't constantly behind requests for numbers.
Subscribe to the podcast
Episode Summary
Ad hoc analysis is often used when there is a need to investigate a particular issue or answer a specific question, and it can be a powerful tool for gaining insights into data quickly and efficiently.
But ad hoc analysis can be time-consuming and challenging without automation, especially if you are dealing with large datasets.
In this episode of The Role Forward, Joel Blachman, an operations and finance lead at Amper Technologies, gets into the importance of automation tools while doing ad hoc analysis and answering ad hoc requests. Joel and our host Joe Michalowski discuss the ad hoc analysis treadmill, the challenges of responding to last-minute requests, and how Amper Technologies raised their Series A.
Watch the Full Video
Featured Guest
Joel Blachman has been working as an operations and finance lead at Amper Technologies for four years. While studying industrial engineering at Northwestern University, Joel was part of their startup incubator, The Garage, and worked at different manufacturing technology startups. During a research project, Joel came across Amper Technologies, founded out of The Garage in 2016. He started interning there one summer, stuck around throughout school, and upon graduation, joined full-time in a finance and operations role.
- The challenges of investor due diligence isn't the specific metrics they're looking for. SaaS metrics like ARR, retention, burn multiple, LTV:CAC, etc. are always key. You get bogged down in constant ad hoc analysis because investors want different granular views of those metrics.
- Startups have to make rapid decisions all the time and need instant access to data, but being able to answer those ad hoc requests quickly is tough if you don't have any automation in place or analysis tools beyond Excel.
- Financial and accounting departments are intertwined, so it's essential they have a close relationship. But these departments also need to know how to collaborate with other departments, especially sales. When departments align on the same goals and find a common language, workflows run smoother and problems are solved quickly.
Episode Highlights from Joel Blachman
23:51— Challenges Responding to Last-Minute Requests
“One aspect is certainly just being able to manage that at a very rapid pace. Obviously, around month-end close, my time is spent on accounting, so being able to switch out of that and still make sure I have the numbers updated on time when they’re needed. That’s certainly one challenge, but an even bigger challenge is being able to do that analysis. So, for example, our CEO might just ask something simple, like, ‘What is our average deal size over the last six months?’ Maybe we are trying out a new pilot program that we launched; we want to see how that was working. I can generally provide that answer pretty quickly, but that’s not enough. I have to understand why I am being asked this question. So, in the case of what is our average deal size, if we’re looking at marketing budgets and what we should plan for over there, I want to go one level further.”
30:53 — Automate Data Collection
“In preparing all those materials during the Series A, process was a huge lift to get the initial data room put together in the beginning, but every month — the process continued to drag on rolling forward, countless spreadsheets, all of the financial models and the SaaS metrics, and all of that data — it was taking so much time every month, and even every week. If we had a big deal close, we were trying to get that data as close to real-time as possible, and there’s just no way to do that while ensuring you have accurate data. So, that was definitely the breaking point for us, and I knew that we had to turn to technology to be able to automate some of the data collection.”
32:47 — Lessons Learned from Raising a Series A
“There are two major changes I would make going through that process again. The first would be all of the data needs to be structured in such a way that you can get as granular as possible. Some investors wanted to look at data monthly or quarterly, but if you construct a report quarterly and you don’t actually have, for example, a point-in-time metric — like ARR at the end of a quarter — as soon as that investor says, ‘Oh, okay, that’s cool, now can you show it to me monthly?’ If you don’t already have it ready to go, you have to either go reconstruct that from another spreadsheet or sometimes go through all the source systems, contracts, et cetera. So getting as granular as possible with the data allows you to answer all of those requests much faster. The second change, definitely tech comes into this, but making that data self-serve is so important. “
Full Transcript
[00:00:00] Joel Blachman: Instead of getting a re, question in real-time and saying, “Oh, not really sure how to answer that right now, let me get back to you in a few hours.” Or, “I’ll send that to you tomorrow.”
[00:00:09] That stalls the conversation. We’re stopped in our tracks, we’re kind of just using our intuition at that point. And answering those questions in real time really allows us to dive deep in those conversations and, as I said, just make better quality decisions much faster.
[00:00:24] Joe Michalowski: Hello and welcome to another episode of The Role Forward podcast. My name is Joe Michalowski, and this episode is brought to you by Mosaic, a strategic finance platform that transforms the way business gets done. And today, my guest is Joel Blachman, Operations and Finance Lead at Amper Technologies.
[00:01:01] Joel, thank you so much for joining me today.
[00:01:04] Joel Blachman: Thanks for having me, Joe. Excited to be here.
[00:01:06] Joe Michalowski: Yeah. Excited to have you here, hear amazing things. People, internally at Mosaic, have, uh, chatted with you before I have and everybody here loves you. So, I’m excited to chat. Before we get going, I would love to just hear the quick background about yourself, who you are, what your career’s been like, what you’re doing at Amper, things like that.
Joel Blachman Introduction
[00:01:22] Joel Blachman: Yeah, absolutely. So, I’m originally from Cincinnati, Ohio, born and raised. Moved up to Chicago a few years ago to study industrial engineering at Northwestern. Actually got involved in startups pretty early over there. They have a startup incubator called The Garage. And I was working at a different manufacturing technology startup, doing some consulting on basically lean manufacturing.
[00:01:49] And during the research project over there, I came across Amper Technologies, where I work today. Believe it or not, Amper was actually founded out of The Garage a few years ago, in 2016. So, through that network, I was able to meet The Founder and CEO, Akshat Thirani, started interning there, one summer in college, when we were just 10 people on the team.
[00:02:13] Fell in love with the whole startup world, obviously, you know, building an amazing product, working with great people, and of course serving customers in an industry that, that I was really passionate about and interested in. So, stuck around throughout school, really fortunate to be able to join full-time in a Finance and Operations role.
[00:02:31] Once I graduated and, you know, we were discussing earlier, I’m still a finance team of one. And I’ve been able to build up our finance function from essentially nothing, when I started, to, now we’re supporting over 150 customers, 40 employees and several million dollars of revenue. So, it’s been a really exciting journey. I’m excited for what’s to come.
[00:02:54] Joe Michalowski: Alright, man. Totally, start from the ground floor. That’s such a cool story. Brian, on our, our team, who you’ve spoken to, was telling me about that. He was like, “Oh, Joel’s got such a cool story.” And I didn’t, one, didn’t realize that, uh, you were there for industrial engineering as someone who went to school originally for chemistry and then ended up in English and now is doing marketing.
[00:03:12] Totally understand how that can kind of lead wherever it goes, but really cool that you just kind of landed there at the absolute ground floor. And so, yeah, I’m, I’m excited to chat about that journey ’cause very unusual in startup world to have that kind of like end-to-end experience. It’s a lot of job hopping in this world.
[00:03:32] So, yeah. This is pretty cool, man. Yeah, all the story. The main topic that I wanted to talk to you about, that we discussed before, was what I sort of saw as this ad hoc analysis treadmill. And I’ve heard it from other people too. It’s just this constant cycle of, like, running the numbers, redoing the numbers, having to go back and, and kind of look at it again.
[00:03:50] And the backdrop that you told me about was kind of your, the Series A round that you guys raised. I believe it was early last year, in 2022. And I think it’s just a great set of context for this topic. So, I, I would love to hear more about the Series A fundraise, the process you went through, the timeline, and kind of what the, the team was looking like at the time.
Raising a Series A for Amper
[00:04:15] Joel Blachman: Yeah, absolutely. So, just to set the backdrop, we raised our Series A, closed that round in March of 2022. Raised about $11 million from several investors across the US. But we actually started fundraising in mid-2021. So, basically during/right before the, the real peak of the market. And we had just crossed like one and a half million ARR, and we were, you know, looking to take advantage of a great market opportunity to fundraise and really accelerate our growth in a Series A.
[00:04:51] So, at that time, you know, still now, I’m a finance team of one. So, I was working directly with our CEO, Akshat, to raise from VCs. He was the main external face of the company, and I was doing all of the supporting work, building out all of our metrics, financials, helping with the pitch decks, due diligence, et cetera, kind of in the background to really support him through that process.
[00:05:18] Joe Michalowski: A daunting task for sure, obviously. I mean, lucky you guys and anyone who got to raise at that time, because obviously, things look so much different now. And so, that was when I wrote this question down, I was like, I was really curious if you got in ahead of sort of the big downturn. It sounds like you really, you really did.
[00:05:36] If you raised in March, it was, if you went in a few more months, it was probably gonna look a lot different than it did at the time.
[00:05:42] Joel Blachman: Oh, yeah. We, we definitely timed it perfectly.
[00:05:45] Joe Michalowski: Yeah.
[00:05:46] Joel Blachman: Somewhat by luck. Also, we had raised a few million dollars of seed funding.
[00:05:51] A few years previously, so it was about time to go out and, and raise a Series, Series A, as well.
[00:05:58] Joe Michalowski: Yeah.
[00:05:58] Gotta love when, when timing works out like that. Obviously, there’s a lot of scale, a lot of strategic thinking involved, but there is always some luck involved to dwell. So, yeah, cool to hear that you guys landed right there. I want to dig into, into the due diligence process, into that process you talked about, about
[00:06:14] building those metrics in the background. And so, just first off, as you were raising the Series A, just high level, what were the metrics reports and financials that you were required, either by VCs or by the CEO, to put together for this process?
[00:06:30] Joel Blachman: Yeah. So, everyone really wanted to start with the SaaS metrics. At an early-stage company like that, obviously, the financials are important, but at the end of the day, you’re really, as a VC, you’re making a bet on the growth potential, the market opportunity, the founding team and really the product.
[00:06:49] So, they cared the most about the SaaS metrics. You know, ARR, retention was a big focus, as well. Very lucky to have a really solid customer base, very low churn. And they also cared a lot about the efficiency metrics, like burn multiple LTV to CAC, magic number, et cetera. So, I would say the main focus during that really building our initial data room.
[00:07:14] And then, even later in the diligence process, once we got a little bit more serious with a few VCs, the main focus was on building up all those SaaS metrics in a very easily digestible way. Most of the VCs were asking for similar metrics, you know, similar numbers, but they all wanted it presented a little bit differently.
[00:07:34] So that was where every single request that came in was essentially a one-off request that had to be customized for that specific person.
[00:07:45] Joe Michalowski: That’s a great point. I, I’ve always wondered about this, and I, I think that leads me to the next question that I had, which is really like, I’ve always heard that the challenge of, and that’s kind of why we’re talking about this ad hoc analysis treadmill sort of topic is that, the challenge is that, that idea that you just said where you have to present things in a different way for everyone.
[00:08:03] And so, off the bat, I’m like, “All right, like, I can think of the, the 10 SaaS metrics that everybody under the sun is gonna wanna see.” So, personally, I’m like, “Well, you already pulled all these metrics, like it should be pretty simple.” So, can you give me like an example, I don’t know if there’s a, a good metric to use as an example, but that you presented one way for one investor, that another investor was like, “Hey, I need to see it a different way.” And just sent you down, like, the rabbit hole.
[00:08:27] Joel Blachman: Yeah, absolutely. So, I would say one we were definitely looking at was our compound monthly growth rate, CMgr, and then compound annual growth rate, CAGR. And what was really interesting about looking at this metric was depending on the timeframe that we looked at the trend looked very different.
[00:08:47] So, some investors, again, wanted to look at it monthly. Some people wanted to look at it quarterly, based on calendar quarters, other investors wanted to look at the last three months, which depending on when they made that request, might not be the same thing as a calendar quarter. So, being able to adjust the timeframe we were looking at to really answer those questions was definitely one aspect I was not expecting to be so different across every request.
[00:09:17] Joe Michalowski: Yeah, that’s a good one and one that I, I haven’t heard before. So, I love that. Is there, were there any other analyses or reports that you were pulling together that were particularly challenging or time-consuming, I guess, on the backend?
[00:09:30] Joel Blachman: Yeah. So, another one is, as I mentioned, retention, you know, net dollar retention, gross dollar retention, very big focus for any SaaS company. And one aspect that maybe somewhat unique to our business is, you know, we obviously sell to manufacturers, and the beauty of Ampers Technology is that we are able to capture the long tail of the market.
[00:09:51] So, a lot of Mountain Pop Shops, you know, smaller companies, maybe 10 to 20 assets that were, were monitoring. But we also work with more mid-market in enterprise accounts. And what’s unique about those businesses is that many of them are owned by private equity firms. They have, you know, 30 or 40 subsidiaries.
[00:10:12] They have factories all over the world. So, we had to be able to split up our customers and essentially run that, you know, like a cohort analysis, looking at what I would consider a parent company. So, think at the enterprise scale, looking at, maybe they have five factories, looking at that as a single account versus looking at each factory individually
[00:10:36] and understanding the metrics under each of those different frameworks. That was definitely interesting. And, as you can imagine, required pretty complex data hierarchy, data structure to do that analysis.
[00:10:50] Joe Michalowski: Yeah. And especially, uh, so early on. I mean, you, you’re fortunate that you were there at the ground floor. You didn’t have to come in and, like, start cleaning up a mess of data. I, I’d imagine you were in a little bit better shape than somebody who is starting with total chaos, but even, still, at Series A, like, you don’t have that data infrastructure in place.
[00:11:08] That must have been so hard, man.
[00:11:10] Joel Blachman: Yeah. Well, I mean, yes and no. So, we did have accurate data for, I would say, you know, the two most recent years, ever since I’d been in the role. That was obviously, basically, my number one priority so we could understand the business, as we were growing. But before I joined, there were one or two years where we did have some customers and the data,
[00:11:32] you know, we had some data over there. But I spent a lot of time early on, in the fundraising process, going back, checking over every single contract that we had, all of the different email exchanges, different adjustments that, you know, you have to make and be flexible with some of your earliest customers.
[00:11:50] So, really building up that historical picture, as well. Because most VCs wanted to see at least three years of data. So, building up that historical picture definitely was one aspect that took a lot of time in the beginning.
[00:12:05] Joe Michalowski: Man, don’t envy the position. I, honestly, could get a headache just thinking about trying to manipulate all that data. It is not my world. So, better you than me. I think I know the answer to this one, mostly ’cause I have some context, but I will ask for posterity. What did the tech stack look like, at the time, as you were dealing with this?
[00:12:21] I assume, on the FP&A side, it was pretty much just spreadsheets and your brain. But curious about the source systems, as well, as you tried to build all this out.
[00:12:30] Joel Blachman: Yeah. So, on the analysis side, we just had Excel, really, Google Sheets for easier access, to do all that analysis. The data was coming from the store systems, so QuickBooks Online, for all of our financials, we’re using Gusto for payroll, which we still use today. And then, HubSpot is our CRM, as well.
[00:12:50] So, we had all that data there. But, obviously, getting it into a single, you know, Excel sheet to get the full picture of the business, all in one place for that analysis, that obviously takes time too.
[00:13:02] Joe Michalowski: Yeah. I might have some, some follow-up questions about the HubSpot CRM after the, not, not for this conversation, but, uh, we’ve been getting some questions about it. And I recently, we did a project on CRM hygiene, so I might steal some, some extra of your time.
[00:13:13] I’ve actually talked to, I think, Ryan, at Mosaic, about the CRM hygiene, so definitely happy to, to take that conversation, nice. Love it. Yeah, I remember that, when we did that project, we had Ryan kind of going out and talking to people ’cause Ryan is our in-house CRM setup guru.
[00:13:29] Joel Blachman: So, uh, I hope it was helpful.
[00:13:31] Joe Michalowski: So, I mean, in, in a perfect world, all these things you’re talking about, I know that there are different views, but as far as the metrics go, like you, you should be able to, you know,
[00:13:40] you wanna be able to build your reports and your dashboards, and they are, they’re in, I assume, a very large, maybe unwieldy, Excel sheet and, or Google sheets tab some way. But it, it never really works out that way. You always have to keep rebuilding things, rebuilding metrics, rebuilding dashboards.
[00:13:55] So, that is really the, the ad hoc analysis cycle that we’re gonna talk about. I’m wondering, what that looks like? What, like what kind of requests are you getting from the CEO last minute? What are your timelines like? Like, how much time do you have to put these things together? Wanna know how that all happens in the background?
Handling Last-Minute Ad Hoc Analysis Requests
[00:14:13] Joel Blachman: Yeah. So, you know, obviously, in any startup it’s really important to carry forward any momentum that you have. You have to make really rapid decisions all the time. You need that data accessible pretty much instantly. So, most of the requests, especially during the fundraising process, came with, in most, a next-day turnaround.
[00:14:34] But, I would say, I would often wake up in the morning, pretty early, with a request from our CEO, like, “Hey, I’m meeting with this investor, or this VC firm at 9:00 AM.” I’m noticing this at maybe 8:30, even later. It’s like, “We need this data.” So, literally under an hour, probably as close as like five minutes, is definitely the shortest timeline.
[00:14:56] So, being able to answer those questions that quickly is really tough If you don’t have, really, any other automation tools in place besides Excel. You, you know, it’s tough to get certain visualizations set up properly. And I would say, the hardest part is every month all that data rolls over. You need to export it from the source systems that we just discussed, manipulate it to make sure that it’s formatted properly to go into all the different Excel files and especially,
[00:15:29] you know, the fundraising process, while going with the best of intentions expecting maybe three to six months, it ended up taking about nine months. So, as you go through that process, every single month, you need to update the data. And as we get more and more of these ad hoc requests from investors, now, all of a sudden, instead of starting with one master spreadsheet that just needs to be updated,
[00:15:52] now you have 5, 6, 7 and so on. And everyone is presented a little bit differently. They all ingest the data a little bit differently. So, maintaining that across everything definitely prevents you from being able to answer those last-minute questions.
[00:16:08] Joe Michalowski: Yeah, I want to, I want to keep on that same topic because I’ve heard this before where like, you know, and our founders, as well, like, they were in finance positions before. And this was always, honestly, when I first started working with them on content I was trying to, like, gather pain points in the inboard deck presentations, investor pitches, like that was always, Joe, our COO, Co-Founder has called it like, board meetings, like, the Super Bowl for finance teams.
[00:16:31] It’s like where you finally get to show off all that data that you spend so much time working on. But he always said like, you know, you get five minutes to do this. You’re just constantly, like you’re in a, a war room, like, trying to figure all this out. And I want to know what that conversation looks like when the CEO comes to you, and you got, let’s say, five minutes, even like a few hours to put something together, but you know that the actual timeline to get that answer should be, I don’t know, a day or something.
[00:17:00] Like, obviously, like, you’re, what do you say? You say, “No, I can’t do that. I’ll get you something else.” Like, how does this happen when the timeline just doesn’t make sense?
[00:17:07] Joel Blachman: So, usually, I would start by trying to read between the lines, “What is the CEO or the investor? What are they really asking about? Can I answer that question with an existing report that I built, that I know the data is trustworthy? Can I make a quick change?” Or sometimes I would even just, you know, use a quick calculation, just in the Apple search bar, whatever I could do to try to get an answer that was at least indicative of the trend they were asking about.
[00:17:34] But that definitely always made me nervous, and I would always recommend like, “Hey, let’s actually follow up with that investor after your call, with the real data.” Because making those rapid calculations, obviously, you start introducing rounding at different points, and was always, wanted to make sure that I was giving the complete, accurate picture to an investor. So, try to answer it as best you can, and then, ultimately, you’d have to send follow-up materials after the call.
[00:18:03] Joe Michalowski: Makes sense. And probably, honestly, like, not an unusual situation. Like, I don’t, it’s probably, it sounds like, you know, make yourself, make your CEO look as good as possible in the moment and then make sure you answer as thoroughly as possible later on. I can’t imagine investors are not used to that situation, given how often they’re asking for last-minute information.
[00:18:24] Joel Blachman: Right, right. But, you know, my perspective is every little detail matters. It’s a competitive market, and especially when we were raising, when the market was so hot, every company was trying to get money. So, VCs had to be very selective with their investments. And one unique thing about Amper, even though we’re a SaaS business, we do have a hardware component, which I’m sure we’ll, we’ll touch on a little later, but that was one unique aspect.
[00:18:50] So, choosing our VC partner very carefully was pretty important. And, from my perspective, if we can put our best foot forward on literally everything, it only helps, right?
[00:19:01] Joe Michalowski: Yeah, for sure. So, I, I wanna tie a bow on the, on the Series A part. ‘Cause, like I said, it’s, it’s a good backdrop. It gives a lot of, uh, opportunities to give examples about this ad hoc analysis. And we’re gonna, we’re gonna move on to more of the operational side, but I’m curious if you’re looking back now, it’s been almost, like, exactly a year since you raised that round.
[00:19:20] Is there anything you would’ve done in the moment, given the context yet? Obviously, like, we’re gonna talk about some tech later, like, maybe you wish you had tech at the time, but, given the context that you had with your spreadsheets and, and the tech stack that you were dealing with, anything that you would’ve handled differently or maybe approached in a different way?
Lessons Learned from the Series A Fundraise
[00:19:40] Joel Blachman: Yeah, there are definitely two major changes I would make, going through that process again. The first would be, all of the data needs to be structured in such a way that you can get as granular as possible. I mentioned earlier, some investors wanted to look at data, like, monthly or quarterly, but if you construct a report quarterly and you don’t actually have, for example, like a, like a point in time metric, like ARR at the end of a quarter, as soon as that investor says, “Oh, okay, that’s cool.
[00:20:12] Now, can you show it to me monthly?” If you don’t already have it ready to go, you have to either go reconstruct that from another spreadsheet or sometimes go through all the source systems, contracts, et cetera. So, getting as granular as possible with the data allows you to answer all of those requests much faster.
[00:20:33] So, that would definitely be one change I would make. And the second change, which, definitely tech comes into this, but making that data self-serve is so important. Because, in the example, I gave where, you know, Akshat, our CEO, he’d ask me literally five minutes before his call, “Hey, can you answer this for me?” If I was on another call and didn’t see the message at that time or, you know, whatever other reason, maybe it’s at night, and he’s trying to prepare for the next day,
[00:21:01] I base, I mean, fortunately, I was able to be very responsive, but being able to make that self-serve would be the best-case situation. So, hopefully, I don’t even have to be best.
[00:21:11] Joe Michalowski: Yeah. Those are great points and I, I like the granularity one a lot because you can always simplify the report. You can always simplify the view, but, yeah, like you said, you can’t, you can’t on the fly suddenly make that view significantly more granular than it was before. So, I think that’s a really good point, especially for anyone that is still kind of struggling
[00:21:30] with the manual approach. But, like I said, we’re gonna move on to the operational side. But, especially for the VC side, you know which metrics, like, you’re looking at, like, you know it, yes, there are different views, but those core SaaS metrics are the core SaaS metrics. And so, if you can at least get granularity there, probably a little bit easier, maybe a little harder on the operational side, but I think it’s a good point.
[00:21:50] Yeah, like I said, would love to extend this ad hoc analysis conversation to kind of the day-to-day of working at Amper, obviously, nine months to raise a Series A. It’s significant pro, I’m sure it took up a lot of your head space and your time, but you still need to run the business. And so,
[00:22:07] what was your experience, like, working day-to-day with your CEO? What are some of those ad hoc requests that you’re getting? What’s that timeline like as opposed to, you know, the due diligence request that you were getting?
Finance Business Partnership
[00:22:20] Joel Blachman: Yeah. So, working with the CEO day-to-day, either throughout the fundraise or even, you know, after the fact, just as we’ve been running the business, I definitely get a lot of requests around revenue metrics and our sales data coming out of HubSpot. Up until a few months ago, we didn’t really have a SalesOps or, like, RevOps position, so operations and finance, right,
[00:22:45] that was kind of my wheelhouse, as well. So, I would often have to contact switch out of the, wearing the finance hat over into more of a, a RevOps role to be able to pull that data from HubSpot and provide analysis. And one aspect that I’ve heard a lot is in the finance position, it’s one thing to pull the data and just send that over to someone in a spreadsheet, but that’s not really what someone is asking for, especially as a CEO.
[00:23:13] They have so many things going on. They don’t need to just get a, a data dump and a spreadsheet. They’re really asking about answers, and they want you to conduct an analysis, provide a very clear recommendation. So, taking that time and having all that revenue data available, I would say, is the bulk of the requests that I would get.
[00:23:33] Joe Michalowski: Yeah. What are some of the challenges there? I mean, like, if you’re getting those requests last minute, is it at month end close where you’re like trying to, to finish out reports? Is it making strategic decisions? Like, what, what sort of efforts are you trying to support as you’re making these sort of rapid updates to the numbers?
[00:23:51] Joel Blachman: Yeah. So, one aspect is certainly just being able to manage that in a very rapid pace. Obviously, around month-end close, my time is spent on accounting. So, being able to switch out of that and still make sure I, I have the numbers updated on time when they’re needed that’s certainly one challenge.
[00:24:09] But, I would say, an even bigger challenge is being able to do that analysis that I just mentioned. So, for example, our CEO might just ask something simple like, “What is our average deal size over the last, you know, six months?” Right? Maybe we were trying out a new pilot program that we launched.
[00:24:28] We wanted to see how that was working. Well, I can generally provide that answer pretty quickly. But that’s not really enough in my opinion. I have to understand why am I being asked this question. So, in the case of, “What is our average deal size?” If we’re looking at marketing budgets and what we should plan for over there, I wanted to go one level further.
[00:24:51] So, in this example, I look at, okay, we actually really have two kind of cohorts of customers. I was mentioning this earlier, we have one smaller group, maybe 15 K and below per year, where it’s Mountain Pop, locations or even just like single factory manufacturers. That’s kind of one group. And then we have another group that has, that’s multi-site, multiple factories around the country, even the world.
[00:25:17] And those deals could be 30 K plus, 50 K plus, et cetera. So, looking at both of those, while 25 K would be a great number as an average, right, makes sense, easy to do math that kind of obscures the full picture. From a marketing lens, maybe most of our inbound investments are on capturing some of those smaller customers where we can’t afford to spend as much on customer acquisition compared to taking more of an account-based marketing approach
[00:25:47] on some of those larger accounts. Because they’re larger they tend to sign multi-year contract. We can invest a lot more in a, in an account-based, like, outbound strategy. So, but, again, that all stemmed from the question, “What’s our average deal size?” So, you have to be able to double-click and go one layer deeper when you’re asked those questions.
[00:26:09] Joe Michalowski: That’s such a good example. And I, I appreciate you kind of digging in on that a little bit because I think that’s really the crux of this, is, you know, like you said earlier, reading between the lines and understanding what the actual question is, and why it matters, and how to build out that analysis.
[00:26:22] It’s why this topic is so challenging. I want to ask, one more follow up which, honestly, that sounds hard enough as it is, the example you gave, but I’m sure there are more challenging examples than, I’m curious if there are certain departments you work with where you get ad hoc? Like, there are ad hoc analysis requests or partnerships in the business that are particularly challenging to figure out how to do that process of reading between the lines and getting the real answer out the door.
[00:26:52] Joel Blachman: Yeah. So, I’ll give two examples over there. The first is working with our customer success team. So, I mentioned that when we’re looking at retention, we want to look at that, at the parent account level, an example of our enterprise multi-site customers. But from a, an operational
[00:27:13] level, we also need to look at it as individual factories, right? In the example of an enterprise customer with maybe five locations, a single customer success manager, that’s essentially the same as managing five smaller accounts, right? So, when we’re doing a capacity planning, you know, a model for our customer success team, we really need to be able to look at it both ways, right?
[00:27:38] That would be one example. The other one that’s definitely a challenge for us, with the reporting, is on the inventory side. I said that Amper, somewhat unique in the SaaS world in which we have a hardware aspect of the business as well, so being able to communicate our revenue plans, which could change, you know, weekly at, at least monthly, if not weekly.
[00:28:03] Right? Being able to communicate any updates to our, our pipeline, our revenue forecast for the upcoming quarters is really important. Especially over the last year or two, supply chains have been relatively constrained, and so we do need to order some parts as much as a quarter in advance. Being able to communicate that
[00:28:23] efficiently when there are changes is lead times develop, having that data accessible for our hardware team was definitely another challenge.
[00:28:32] Joe Michalowski: Wow. We spend so much time, and I, I mean, all the content that we write here at Mosaic that I work on is so SaaS-focused that we haven’t, I mean, I, I haven’t had the opportunity to talk a lot about the hardware. So, I, I’d love to just click into that a little bit more and understand a little bit more about those challenges.
[00:28:48] I think, one thing I heard sort of as the market shifted was that a lot of people were really good at forecasting revenue and sort of like the cash flow forecast, the, the, forecasting the balance sheet was more of a challenge and there are some people that just haven’t had to be as strict about that as they do now because of what the situation is in the market.
[00:29:13] So, I’m curious if you have tips or anything for getting stronger in the balance sheet forecast, obviously, like, with that hardware component need to be on top of it. So, I’m curious if you have any tips for anybody?
[00:29:26] Joel Blachman: Yeah, absolutely. So, should give a bit of background over there. At any startup and especially early-stage, burn and runway are two critical numbers. You can’t, you can never take your eyes off of those. And before the Series A fundraising process, we spent most of our time modeling out the P&L.
[00:29:45] So, as you said, focusing on the revenue, building out the revenue model, scaling up the sales and marketing functions, et cetera. But, obviously, we’re missing a huge aspect of the business, which directly impacts our cash burn and runway, which is inventory in purchasing that hardware in advance. So, being able to model out that balance sheet was essential.
[00:30:08] And, frankly, we weren’t able to do that until we started using Mosaic and have the ability to forecast a true three-statement model.
[00:30:20] Joe Michalowski: Yeah. I mean that, that’s where I wanted to go next, was like, you know, we spent a lot of this conversation, most of the conversation, talking about challenges and kind of figuring out what that treadmill looks like, and I know, you know, full disclosure, like you said, Mosaic customers, so I’m not gonna turn this into, like, a Mosaic case study or anything, but I do wanna know, like, what was your breaking point?
[00:30:39] Maybe it was that balance sheet aspect, but what was the breaking point when it was like, “All right, these ad hoc requests, like, I can’t just keep doing this in spreadsheets.” Like, “We raised a Series A and it’s time to upgrade.” I’m curious what the thought process was there?
[00:30:53] Joel Blachman: Yeah. So, definitely hit the breaking point, so to speak, preparing all those materials during the Series A process. Obviously, it was a, a huge lift to get the initial data room put together in the beginning, but every month as the process kind of continue to drag on, rolling forward countless spreadsheets, all of the financial models and the SaaS metrics and all of that data.
[00:31:17] It, it was just taking so much time every month and, honestly, even every week. If we had a big deal close, we were trying to get that data as close to real-time as possible. And there’s just no way to do that while ensuring you have accurate data. So, that was definitely the breaking point for us
[00:31:35] and I knew that we had to turn to technology to be able to automate some of the, the data collection.
[00:31:40] Joe Michalowski: Makes sense, obviously, like, anyone listening, if you’ve paid attention to Mosaic, we, you know, direct data integrations, making life easier on the rolling forward of the data, all that. Like I said, not gonna make it a Mosaic sales pitch, but I, I do want to know if there are any other, any other tools, any other, software that you implemented to help sort of automate your way to success here.
[00:31:59] Anything else that’s helped?
[00:32:00] Joel Blachman: Yeah. So, we actually started by looking into subscription management tools. So, I spent a lot of time evaluating tools like Chargebee and SaaSOptics, which is now Maxio. And I thought that’s what we needed. They had a lot of great capabilities on the revenue side, handling the complex account structure that I mentioned, and recording all of our revenue also with, on the accounting side, revenue recognition, et cetera.
[00:32:26] But I realized that was only part of the picture. You know, we obviously spent so much of our time on revenue, but we’re entirely missing any of our expenses, right? Any payroll. So, I knew that those tools were not going to be sufficient. And, especially coming out of the Series A, I was really looking for three things to level up that finance tech stack.
[00:32:47] So, the first one is just having access to all of the data across the business. So, certainly, revenue, but also all of our expenses and headcount planning. We needed all of that in one place, and being able to easily manipulate that data, have really good visualizations, that was kinda our one major requirement.
[00:33:08] Another one was being able to do better financial modeling, as I said, on the inventory side. And with that came more stringent requirements around budgeting and controls, right? As we grew from about 20 people to over 40 now and we really have true departments being run within the business, we needed better visibility, not only for myself and our CEO, but also for each department head to really run their own function, have a budget and, and have true accountability to our plan.
[00:33:44] And then, finally, having a really robust financial modeling software, which would allow us to have those three-statement financial models, obviously historicals. But then forecasting and being able to do scenario modeling with different hiring plans, different marketing budgets, et cetera. Being able to have all of that flexibility, all within a single tool, was really important for us.
[00:34:08] Joe Michalowski: Yeah, love to hear that. I mean, obviously, like, that’s the core that we believe, like, everyone in finance should have. So, makes sense to me. I know, uh, I’m running out time with you, so I wanna make sure I get to these last couple of questions. But the sort of tech path to solving some of these challenges it’s, automation is kind of the only way to get out of that ad hoc analysis cycle.
[00:34:26] So, there’s really no manual way to simplify it, although you gave some good tips. So, I appreciate that. I want to get to, like, lessons learned. And I, I’m curious, like, so you spent the last year having accomplished those three pillars that you wanted, you have a new sort of tech stack in place, new analysis and planning capabilities.
[00:34:44] What has this done for you? How does it make your role more strategic? What are you able to do because you’ve made these upgrades?
[00:34:51] Joel Blachman: The biggest impact by far is on our ability to make better decisions and make them faster. So, Amper actually, we used to have a saying, “Your factory at your fingertips.” Where we really wanted to give manufacturers total visibility and control over their operations. And I wanted that for running Amper, right?
[00:35:13] We’re not a factory, but we still need to have that level of visibility into every aspect of the business. And I would say, again, not to make the sales pitch, but having some sort of tool like Mosaic, or really just having automation and technology in place, allows us to make those better decisions. So, the example I love to give now, anytime I’m in my one-on-one meeting with our, our CEO, instead of, you know, getting a re, question in real-time and saying, “Oh, not really sure how to answer that right now, let me get back to you in a few hours.” Or, “I’ll send that to you tomorrow.”
[00:35:46] That stalls the conversation. We’re stopped in our tracks, and we, we’re kind of just using our intuition at that point. Whereas now, I am able to run through those meetings with our data right next to us, literally at our fingertips, so we can answer our questions in real-time on things like sales efficiency, you know, our marketing budget, et cetera.
[00:36:08] And answering those questions in real time really allows us to dive deep in those conversations and, as I said, just make better quality decisions much faster.
[00:36:18] Joe Michalowski: Love to hear that, especially with, like, busy life of a CEO, you know, if you’re not answering in that moment, they might move on to 15 other different things by the time you get back to them later. So, being able to sort of have that conversation when the question comes up.
[00:36:31] Joel Blachman: I, I remember, the first time I, I really felt that was our CEO said, “Hey, I’m not sure if this is gonna be possible. You know, it’s, I know it’s only five minutes of notice, but we really want to see the ARR changes.” So, like, new expansion, you know, churn, et cetera, over the last year, like month by month.
[00:36:51] And they wanted that, you know, as a visual in a graph. And in the past there’s no way I would’ve been able to provide that right away. I may have had it on a different timeframe, but giving that to him in five minutes would take way too long. But I was able to give him that in literally one minute. I just went, adjusted my timeframe to monthly, and was able to send him, like, a screenshot.
[00:37:14] So, I was so happy at that point because I viewed supporting our CEO, making better decisions, uh, the main aspect to my role. So, being able to do that so quickly just felt amazing.
[00:37:28] Joe Michalowski: Love to hear that. Obviously, it’s a, goal for our company is to, to kind of make those moments happen. So, yeah, really, I think everyone here is just thrilled that you have stories like that, it’s great. So, yeah, love, love all that. I think it’s awesome. I wanna get to our last question, ’cause like I said, I know we’re, we’re coming up on time, and this is, uh, outside the realm of everything that we’ve talked about so far.
[00:37:48] Tie level. You, I know you’ve listened to the podcast before, so you know I ask everybody that comes on just very simple, what’s something you know now that you wish you knew when you had first started?
Finance Career Lessons from Joel
[00:37:58] Joel Blachman: Yeah. I love this question, and I definitely love hearing all the different responses from the other podcast guests. And I have to say, for me, one of the most profound, like, ideas I came across recently is that communication is not what is said, but what is heard. And this really stuck with me when I heard it for the first time, and it’s really changed how I communicate
[00:38:22] across the business. I’ve noticed for communicating with investors, communicating with executives, you know, like our CEO, they’re making a lot of decisions all the time and they really just need, like, high-level information and any, like, clear asks that you have for them. You have to keep any, like email communication,
[00:38:42] even verbal communication, very concise and straight to the point. Whereas, when you’re working with someone with an engineering background like me, you know, tend to like to get lost in the weeds, well, not lost, but get into the weeds and really understand the full thought process behind anything. So, being able to understand what your audience is looking for and what’s going to resonate with them, I’ve found to be tremendously valuable in improving how I communicate with really anyone.
[00:39:12] Joe Michalowski: Love that. I think, uh, you’ve probably heard me say it a bunch of times, but what I like about this question is that it always applies much further than just finance. So, nice lesson for me, as well. So, a little bit selfish on my part, but that’s okay. Joel, that was the last question I had for you.
[00:39:26] I wanted to just say thank you for coming on. I, thank you for listening to the podcast, too, ’cause I know you have been. And so, just very much appreciated. Want to turn the floor over to you. Where can people connect with you? Where can people learn more about Amper and all the work that you guys are doing over there?
[00:39:39] Whatever you need to plug.
[00:39:41] Joel Blachman: Yeah, thank you. Connect with me on LinkedIn. It’s just Joel Blachman. You can find Amper at www.amper.xyz. You should check us out.
[00:39:50] Joe Michalowski: Cool. Well, Joel, thanks so much for being here. Really appreciate you taking the time, I know life of finance person never quiet really. So, yeah, very much appreciate it, and I hope we can do it again sometime.
[00:40:00] Joel Blachman: Yeah. Thanks, Joe. This was fun.
Never miss new content
Subscribe to keep up with the latest strategic finance content.