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and now onto the show. From Data Reels, this is FPNA today.
All righty, everyone, welcome. We're really excited to have you join us for the FPNA and
RevOps working together to drive value discussion. I have three great guests with me today,
and so I'm going to go ahead and start by introducing the guests I have here with me. As I
mentioned, my name is Paul Barnhurst. So why don't we start with Jeff Ignacio. Jeff, can you go
ahead and introduce yourself to our audience? Thanks, Paul. My name is Jeff Ignacio. I'm the head
of GoToMarket Growth and Operations at ReGrow Ag. We're a mission-focused climate company in the
agricultural supply chain space. Been in the revenue operations space for a good 10 years, and
prior to that, was an FPNA at companies like Intel and at Google. Arvind, Arvind and Shell, why don't
you go ahead and introduce yourself? Yes, sure. And first, let me see how honored I am to be on the
panel, and I'm just excited as our listeners to learn from the three view as I am to participate.
Currently, I'm VP Finance and Optsat, audittrator.ca. It's a marketplace where Canadians can come
to buy and sell vehicles. My current role, I lead a team of six awesome people where we partner
across the business to ensure alignment between strategic operational and financial goals.
Prior to joining audittrator, I was in the Robop space for about six years. I spent about
four and a half years at Shopify, leading a couple of different Robop's teams. Before all that,
I spent the first 10, 12 years of my career in capital markets, quantitative finance. I've
been very blessed to have had a few different chapters and adventures in my career. So happy to
be here today. Happy to have you, work. Thank you for joining us, Arvind. Drew, why don't you go ahead and
introduce yourself? Absolutely, Paul. First off, thrilled to be on.
Honestly, a huge fan of yourself and also Jeff and great to meet Arvind,
stoked to be here overall. VP revenue at SCS Cloud, we're a revenue operations and financial
operations consultancy, doing implementations, upgrades, alignment across primarily revenue and
finance teams. And that's our mission and just seeing a lot in terms of my background,
mostly on the consolidated go-to-market operations side. I originally come from marketing PR and
also as an AE, then bringing into marketing operations, sales operations, and then most recently
at Matt Kudu, Manhashikart, before that, a certain amount of CSOPS as well, and interacted heavily
with Jeff as well, you know, in his capacity, I would consider Jeff a mentor, who degree, and
stoked to be on the panel with him in his capacity. It's, uh, uh, Revops Co-op.
Thank you, Drew, for that introduction. I thought this was an interesting comment we got coming in.
We'll throw this up here. Kelvin's letting us know he's transitioning from Revops to FPNA as we speak.
So I think many in our panel have done that so they can relate either one way or the other from
FPNA to Revops or Revops to FPNA. But thank you for sharing. Just to mention, we have guests coming
from all over the globe. We got Canada, Ukraine, Romania, Madrid, London, Singapore, Mexico.
So keep sharing where you're coming from. Feel free to ask questions throughout our conversation
and where I want to start. And I'm going to guess anyone who especially has worked in a small company
or spent a long time in FPNA has probably seen one company define Revops this way with these tasks
and cells ops with these tasks. And another company differently, maybe you've seen Revops in FPNA,
maybe you've seen it as sitting cells ops, maybe you're not sure what they are and how they all work
together sometimes because it can be very different from company to company. I see some smiling
from the panelists. I think they can relate to that. So why don't we start by giving each of you an
opportunity to just state how you define revenue operations? What do you think of when you hear the
term Revops? And for this question, why don't we start with you, Arvind, on this one? Sure,
yeah. Happy to get started. When I think of Revops, I really think of that function that helps
keep all the different go-to-market pieces aligned. So let's go to market typically, you know,
some combination of sales, customer success and marketing. And so Revops sits at the center
there, really make sure that those teams have the right systems, the right tooling, the right
technology, the right reporting, the right operating rhythms to keep all those functions aligned and
make sure that that go-to-market strategy, how executioning and so strategy is occurring and also
identify where there's opportunities to identify new strategic opportunities.
Thanks, Arvind. How about yourself, Drew? What would you maybe add to that or change from your
perspective? I agree with Arvind on the majority there. I think the operating cadence is central,
and I think you'll hear that probably from Jeff as well. The main point is that I would divide
strategic revenue operations versus deep or entrenched revenue operations being a split between
directional or advisory level information, strategic level information, forecast, capacity,
planning, which are often owned by FPNA organizations. We consider that strategic revops,
whereas you have the aspect of entrenched or systems level revops being that data supply chain
function that feeds those decisions, right? So they are truly interlocked. There's no way for
them to exist without one or the other, but how you organize them really depends on the organization
that you are in and how that organization goes to market. Thanks for that, Drew. I agree, Jeff,
your thoughts on this. Yes, I'm working on getting this in the Webster's Dictionary. I have an
inquiry, so hopefully they'll follow up with me. But I have to find it as the revenue operations as
the discipline of aligning go-to-market strategy and execution through four key pillars,
and those four pillars are process enablement, advisory, and systems excellence. So strategy
and execution, peas and a pod, PEAS, process enablement, advisory and systems. I like it, process
environment, not government enablement, process enablement, advisory and systems. Got it, process
enablement, advisory and systems. I like it. I took me a minute, but I got there. So let's go to the
next question. We're going to start with one here. Now that we've talked a little bit about
definition, how have you typically in your career? And I used the term typically loosely,
but how have you seen revenue operations, finance operations, kind of working together during
your career? How have you seen that, you know, kind of the functions coordinate and work together?
And Drew, why don't we start with you? Sure. Well, I can speak to the first operations role that I
took on was transitioning from a director of corporate marketing and a media firm to really,
like, head of marketing operations. And I reported directly in that capacity to the CFO,
which is a really an interesting point. And I think, you know, whether that makes sense for
operations to report directly to CFO or not is really, again, headed on the organization and kind
of the, I would say go to market savvy or maturity of the organization, right? Because in terms of
consolidated CRO role, that may make more sense. But I really enjoyed reporting directly to CFO
because of the accountability within campaign reporting, within metrics, alignment to finance,
alignment to budget, right? And being able to really have that quick back and forth,
facilitated with the financial wing of the organization and then report back on findings and
results to the finance org. I think I wouldn't say that that's typical necessarily, but I will say
that that's how I started my career. And I found that that was also a really fascinating aspect
that was echoed in a later point in my career when I was in Haji Corp. You know, if you look at
the go-to-market functionality that was in place there and the firm ended up going public and,
you know, just really had a great scale period. The organization also was headed by somebody who
had an accounting background. So the CEO there, right, had an accounting background. And I think
that rigor in terms of the go-to-market and also the finance organization was really deeply
entrenched there. And we worked very closely with finance, you know, in terms of quota structure,
commissioning, you know, the alignment with, you know, we also rolled out CPQ during my tenure there
and really making sure that the go-to-market organization was aligned with the capability to not
only meet targets, but also meet them effectively in terms of a degree of variance within
the financial expectations. Thank you. Appreciate that Drew Jeff. How about yourself?
So I've been at different stage firms. Series A to be old way up to public-traded companies.
And they're quite different depending on the stage. So your Series A, your Series B,
there's a lot of, hey, you've got this. If you don't, don't worry. I can cover you. So, you know,
you have a left-fielder and a center-fielder to use a baseball analogy. The ball is flying in between
those two outfielders. You're both probably going to converge. So there's a lot of coordination that
needs to be done between two outfielders there. But so several deliverables where we overlap.
Resource allocation, primarily around headcount planning, operation expenditures and tooling,
looking at unit economics, trying to drive customer acquisition and payback periods downwards,
looking at cost of retaining or cost of renewal as well for the ongoing customers. So a lot of
those areas we're going to work together. So board decks, QBRs, MBRs, a lot of that executive level
reporting. Then there's some tactical things that we might be working on. So closing the books,
when a deal closes, you have some close-one processes. So you're talking about a deal desk,
all the way to pricing coding, making sure we're hitting the deal matrix, moving the closed one,
and then once we close one, you're handing it off the finance for all the invoicing and moving
into the building platforms. Other areas might be tooling. I think we've gone through a period of
cutting and at least in the south space. So 20% discretionary cuts across the board, across software,
maybe even people. And some of that, at 20% mandate doesn't really look at the specificities
of how that impacts the go-to market capabilities. And so we're trying to figure out as good stewards.
Now can we work with our finance partners to drive those costs downwards? At the publicly
traded companies, there's a little bit less overlap. But we start to bleed over quite a bit more.
Once we're doing large enterprise deals, we're in the deal room together. I'm reviewing it from a
go-to-market perspective, looking at the gifts and the gets in terms of negotiations. Binance is
looking at it from the perspective of making sure it's kosher with all of our ability and our
deal matrices. And then there's also the annual planning side of the house. Annual planning side
of the house is from August through January. We are hooked at the hip. We are working together. V1
plan all the way to V22. And V22 finally. Only 22? Only 22. So don't get it twisted. If you get to
23, you're taking too long. Yeah, if you get 22, you're taking too long. But I didn't say that.
No. Arvind, anything you want to add? Yeah, great responses from Drew and Jeff there.
You know, when you ask the question, the word that immediately popped to mind as partners,
like I said, most of my time has been on the Rev-Ops side and now I'm on the other side of that
PNA. But I think of the two teams as working together, partnering together to ensure alignment
between go-to-market and financial goals. When I was on the Rev-Ops side, most of what we did,
the finance team was involved in some form or another similar to what Jeff said, whether it was
more tactical things, like weekly metrics reviews, certainly finance was there, whether it got to
more planning projects, like comp setting, annual planning, budgeting, again, Rev-Ops and finance,
usually partnering together. Give you a quick anecdote of what something that's going on right
now for us at Auto Trader, you know, our product team, they're thinking about making some changes
to the product roadmap in the back half of the year. And that puts some of our revenue,
budgeted revenue at risk. So my team and the Rev-Ops team will work into identify, well,
based on the changes in that product roadmap, you know, what's the revenue at risk,
what the commercials, the commercials of the product changing, and then what's the plan to
sort of plug the whole, how are we going to migrate customers from that one product to the new
product, you know, how much do we think will successfully migrate, which ones might there be churn,
which ones can we give some offers to to try and save, et cetera, et cetera, right? So
there's a problem that the finance team has identified and we're partnering with the
with the Rev-Ops team to figure out, okay, how are we going to manage this this risk and
is there even up new opportunity because of this change? Thank you for sharing that. And so,
you know, a couple things that we have heard in our conversation so far. One, it's critical
for Rev-Ops operations, FPNA to be coordinating, to work together. The second thing you're hearing
is it's going to be different depending on size, company, and leadership. The tasks have to get
done, but exactly how it's distributed will vary a little bit. But the key message, and I think
we'll come back to this again and again throughout this conversation, is the importance that we're
all working together and that we're all coordinating and that there are some clear differences between
the tasks, even though at times they can be blurred or a little overlap. So we've got a lot of great
conversation here going on in the chat, more people coming in with some from Montreal. We have a
Kelvin sharing why he made the switch to FPNA, some great conversation there. I want to ask a
question here. So I had, I don't know how many people may know him, but I had Scott Stofer. I think
you know who he is, Jeff, right? So he's been a CEO, I think about five companies now from beginning
to public. And we had quite a conversation around Rev-Ops. And he shared that he thinks Rev-Ops
should be under FPNA if analytics and deep analysis really the focuses what you need from that
go to market team. He did say though, if you have a really strong CRO, someone who's more than just
a sales leader, that a lot of times in small companies you see a CRO who really just madges
sales. They don't know marketing in the other areas. He said, if that's the case or if your folks
is really around the tech stack, it makes sense to have it under the CRO. So I'm just curious,
we'll start with you, Jeff. What's your perspective on that? How do you, how do you think about that?
Yeah, I always think the word question is a little bit of a mislave up, misnomer, right? So
what you want go to market to do is have the ability to push back and inform the decisions
grounded in data that tell a story in a narrative, but it's informed by the data within your
organization or at the very least bringing in third-party benchmarks that are relevant to your
peer set. And that's from the data side of the house. From the process out of the house,
you're playing the role more of an operating officer to the Go-and-Market organization. So
revenue rhythms, operating cadences, making sure that you're running forecast calls, pipeline calls,
win loss reviews on a regular cadence that then bring in the right data pack, the revenue rhythm,
and the right feedback loops that then allows you to adjust the organization in real time. That
can happen under both banners. It doesn't need to be under the CFO or the CRO. I just think it has
to be able to one, de-conflict the areas of interest and play a lot of offense on the areas where
Go-to-Market can be, Go-to-Market ops can be completely helpful. So on the sales, process improvement,
marketing, process improvements out of the house, bringing in the right data. The right data in real
time has to be for some organizations like Front and Center on a daily or weekly cadence. Now,
if you're in the finance org, interfacing with the Go-to-Market org, that daily or weekly frequency
can be hard to come by because you're not necessarily embedded deep within the Go-to-Market team. So
I've seen, I ran a poll on LinkedIn recently, 300 responses, so N300, and over 50% of responses
that they reported to the CRO, and then another 13% reported to CL. So you're talking about,
you know, five-eighths of individuals reporting to the revenue organization, and I think that
works for many companies. Makes sense. And I think you make a good point a little bit of a
misnomer. It's really more about, do you have alignment than who should own what?
Right? I see your right-shaking head. That's really the most important thing. Like I've also heard
the conversation, who should own data analysis? It can be an IT, it can be in finance. I can make an
argument for both. I think there's a real argument for finance, but I get totally sitting elsewhere,
it depends on the leadership and what makes sense for your company. And so, you know, you bring up
the key point to that whole question, and it's really about, are you guys aligned? And is the work
getting done? And are you de-risking the conflict and working together versus, this is my territory,
so to speak? Arvin, any thoughts you want to add to that? No, I think, I think, I think, Jeff,
you know, raised a really great point that it's less about where it sits in the organ,
making sure that the function is operating, whether to hit on its mandate. If I had my default
way, it would be in a CRO's house to Jeff's point, because I think it makes it a little bit easier
for a RevOps team to get, you know, that time with their go-to-market counter-parts, and then they
can still be partnering with other teams across the org, like the finance team, for example. You know,
every RevOps team starts somewhere. They're not just emerging as some fully functioning, mature
group of people. I've definitely seen or heard of RevOps teams, yeah, starting in the finance
function, or even starting in like a marketing function or something like that, right? So, they're
probably going to start somewhere, and where they start is probably going to dictate where a lot of
the initial strengths and focuses of the team is, but I think the point is as the org grows and
matures and evolves, the RevOps function needs to grow and mature and evolve as well, and then
you've got to think about, well, where is the place that, where is the right place in the org for
this function to sit, or these, you know, collection of functions to sit so that it can hit on its mandate.
I appreciate that. You know, we have a lot of great conversation going on in the chat. I'm not
going to read through all of it, but I thought, you know, I'm odd, interesting here. It also depends
on what the CR owns. You know, this gets back to what I said, if the CRO only own cells, for example,
and not all RevOps may be pressured to be less neutral and more biased, they get all their
simplicity to that. I like this one. If CRO only own cells, they are an inflated VP of cells.
We've never seen that at a company, right? Because everybody nods their heads and laughs.
If you call a CRO glorified sales leader and you call, then you can call RevOps a glorified
revenue IT shop. It's a little facetious with the labeling.
Yeah, it is, but I mean, you know, you do see times when CRO is really just focused on cells versus
the owning the whole thing. And so you just got to think through all of it. I think is the main thing.
I like that. They're Kelvin Spicey. I like it. All right. So we're going to move on past that
question to the next one here. This one's for you, Drew. So, you know, obviously as a consultant,
you work with a lot of different companies. What do you see as the key challenges to ensure that
RevOps, FPNA, that they're on the same page and they're working together? Have you seen any kind of
key issues or trends there when dealing with companies?
So I think it's exacerbated too because I work largely in the mid-market and those companies,
a lot of private equity owned shops that are really trying to get their financial rigor in place,
their accountability in terms of targeted attainment in place, things of that nature.
I think, yeah, I mean, as Jeff spoke to the unit economics really become a focal point.
And I think a couple of stories and I'm trying to anonymize them as best I can. But I had one
interaction where I was speaking to a CFO and ahead of FPNA only and brought up the point of
RevOps, brought up the point of alignment to their CRM and also their sales and go to market
organization overall. And it was the strangest response I'd ever heard was, well, we don't really care
about the data quality on the actual CRM. We don't care about how that's all working for the
sales organization directly because we've built it into the close, literally the close of the books
and the model would just account for all of these errors. And the person who had basically built
the model on the FPNA side was just accounting for all of these random variables. And I was like,
well, that sounds really nice in terms of your direct mandate, but I wouldn't want to work at
that sales organization either. And having myself, I mean, as a seller myself now and also as a
go to market person overall, right? Because I do care about marketing. I do marketing every day. I,
you know, am also very involved in our customer success process. I just kind of went, that sounds
like a real rough scenario for the actual experience of that data supply chain, the systems and the
visibility within the go to market organization overall. That was a very interesting experience there.
I'll also say that I think if one of the points that I think FPNA, especially in consumer product
and health and beauty, that's a strong category for us, they often own the allocation, right? And
unless that's well coordinated with the marketing organization and some of that actually sits
within marketing those allocations, they can be misallocated effectively, right? Because the model
might not be correct and making sure that there is really strong, I mean, this goes back to my very
early career was in consumer products and direct marketing was, you know, the aspect of being able
to take the campaign performance and directly turn that around on a fast basis and get
the new allocation established in order to optimize that budget and potential marketing
performance as well, just in terms of your, your Romy and your ROS. So those, those points are really
interesting at the top of the phone. Yeah. And one thing you said there really struck with me as you
shared, hey, we don't care what they do. We just fix it all on the back end. If you're doing that,
stop and have the conversations. You may have to continue to do it for a time. I've done it.
I've fixed a lot of things on the back end, but you always need a long term, hopefully short term
strategy to fix it on the front end because it makes no sense to be like, you can have all your
data wrong. We don't care. We'll get it right over here. So they're doing analysis on data that's
wrong and you're doing it on analysis that's right. And then what happened, you get into a meeting and
Joe says I have 1.2 million for CAC and Pete says I have 1 million. You spend the whole time fighting
about right why it's right or wrong versus accomplishing anything. And I can see Drew laughing.
I'm sure Jeff can relate to that one as well. So that, that would be my comment there is always
try to fix the the data at the source. I have been in roles. I worked in an FPNA role where my whole
role was coordinating between cells, loss and revops and trying to help fix everything in cells force.
And I was constantly talking to them versus I'll just figure out how to fix this on the back end.
So we're going to shift here a little bit. Jeff, you mentioned this earlier, but I want to go back
to it. You mentioned the four pillars, the four pillars for revops, right? Process enablement,
advisory and systems. Why are those the four pillars in your mind? Why are those the four key things?
I think the original triangle that folks will say often with any sort of center of excellence is
going to be people, process and technology. And I think we've gone away from using the word center
of excellence, but a lot of what go to market does truly harkens back to those days of center of
excellence. And you know, really borrowing from people, process and technology. However, I do think
there's something that's missing, which is the concept of decision making. And that's where I think
advisory comes into play. And it goes beyond, you know, cleaning up the data. That's table stakes.
Getting to a place where you can perform analysis, deriving insights, not only deriving insights,
but also marrying that with the business acumen to then be a revenue leader onto yourself and
partnering with your sales product and marketing leaders so that you can, you know, achieve those
outcomes that you're looking for. So it's really racing up a data maturity and decision maturity
curve. And then there's also the enablement piece. So I think a lot of times folks can make some
changes on the process out of the house or the system side of the house and not necessarily
communicate that effectively to the team. So change management, driving new behaviors,
removing bad habits from the organization. That has to be part of I think what a qualified
good market organization can do for kind of the modern, you know, kind of hyper growth phase
of the company. And so that's why I believe that enablement and advisory are two key pillars.
And then process and systems are always been there. I didn't include people. I just figured
that's obvious. But now I was also trying to fit in the monocle piece in a pod. So that's also
what I went with those four pillars. Yeah, I think those pillars can apply to finance as well.
You know, finance has processes that just help people understand how the business is performing.
The fight finance team can partner with other groups, the product team, marketing team,
like whoever, enable them with a little bit more financial fluency, help them understand how
their business is, they're part of the business is performing and affecting the overall company.
There's obviously they had an advisory piece of it where your the finance team is working
with leaders to help them make strategic decisions. And of course, you've got systems all over
the place to collect and consolidate data to help you with your analysis. So I love that,
framing that Jeff has developed for REVOPS and I think really astute finance leaders will
actually see their function in a very, very similar way and figure out how their function,
how their finance function can add value in those four pillars as well.
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All right, so I'm going to go here to a few questions. I think that triggered some questions
from people. Bill asks, and this is shifting a little bit, and then we'll go to the next one.
He asks, what are the typical bad behaviors you've seen in a go-to-market org? I see Drew
chuckling a little bit. I'm curious, Arvin, maybe you're take. What are some of those things you see
that you've seen done that you're just like, why are we doing it this way? Outside of a messy
Salesforce, right? Does anyone have a clean Salesforce? I was going to say the first one that came to
mind is just bad reps. Adlets of entry and stuff. But hey, that's on the RevOps team then to
figure out, hey, how do we reduce the overhead of data and take? I think one bad habit of any go-to
market org is start doing finger pointing. The sales team is pointing at marketing saying,
oh, you're not giving us enough leads or doing enough demand, or blah, blah, or marketing,
saying, hey, we're throwing you stuff, but you're not doing anything with it. At the end of the
day, we're all responsible for revenue. We've got our part of it, the marketing got their part of it,
sales got their part of it, customer success got their part of it. But if the leads that are coming
through and sales is feeling like they're not quality, marketing and sales has to figure that
out together. That's not a marketing problem, that's not a sales problem. That's not go-to-market
org problem. I think that's a bad habit that I've seen a few times where people just try to point
fingers and forget that you're all one go-to-market team. I see two really good points in there. One,
the data. That's not often, you see bad habits around data and who's responsible for it in putting
it. I think the second, which is a major cultural problem and I'd say is more important is when
you start getting into finger pointing. If people aren't aligned and they're not working together,
it doesn't matter if your data is good or not. You're going to have a lot of problems. You got to
have that cultural understanding that I am responsible for helping the team be successful. Jeff
and Drew, anything either of you would like to add to that? I'll name a few. All right, go for it,
Jeff. Yeah, I'm sure this has never been done by any of the folks who are on the channel,
selling outside of the menu. Typically, your business doesn't operate like in and out. I'm assuming
there's no secret menu, the gummy bear milkshake, bypassing, discounting, duck policies,
just willy-nelly handing out discounts without any checks, focusing on the wrong channels,
not following up with leads, not tracking renewals, focusing on the wrong segments. Those are
just certain things. Flying first class. That's a good list. I'll share one I ran into out of,
we had one where our Salesforce had been set up in such a way. I had to approve as the director of
FPNA. Any deals over a certain percentage. I just got promoted. I got my first deal. One of
the first ones I got and I denied it because we were going to lose, it made no sense. I'm like,
why did you sell it at this price? I immediately get a call from the sales guy. The customer has
already signed the contract. Wait a second. I haven't even approved it. He's like, yeah, we can print
them before you approve it. Why am I rubber stamping this? What's the point here? I immediately went to
our ops team and said, okay, we need to fix Salesforce. I told the salespeople, yeah, we're not doing
that game anymore, but I did it in a way where it said, come to me if you need to do a discount.
Let's discuss what makes sense. Help me understand what you're doing with this customer. Not just,
okay, it's 15% no. Not just trying to be the no person, but really working with them.
It ended up being a really good thing in the long term because I developed some great relationships
with our sales team. They started to realize I was a resource to help them, not a hindrance.
But initially they weren't pretty mad at me. They were not happy because they were being allowed
to pretty much do whatever they wanted. I'm like, yeah, it's not a good idea. But I tried to
not do it in a finger pointing way. What are you guys doing? How do we solve this together?
So that was a good learning for me just when you said that, Jeff, it reminded me of that experience.
All right. So if we move on here, I want to ask a little bit of a different question for you, Jeff.
Because I think you're the one here that went from FPNA to RevOps. What brought you to make the
change? Why did you switch? So prior to finance, I was in sales. So I wore the bag, a wore a bag,
and I thought for sure I was never going to go back into supporting the sales organization or
be anywhere close to go to market. So I ended up going to business school pivoted to FPNA.
And to sure enough, at Google, I was the sales FPNA partner, and I remember asking myself,
how did I get here? Oh, yeah. Okay. Well, you know, it's fine. I started enjoying the role.
And I partnered so much with the sales operations team that quite frankly, we were doing a lot of,
we had a lot of overlap. We talked about this earlier today within the hour. And quite frankly,
I found a lot of joy in what I was doing. So made the switch to sales operations a year later
at a hyper-growth company. There, I brought a lot of what I did in finance. So a lot of data analytics
taught myself some hard skills like SQL, BI, really getting the data out of a raw database.
And then surfacing those insights and working face to face with the sales organizations
who get closer to the customer. I actually wanted to get more towards the strategic side of the
org and the acquisition side of customers. And I thought sales operations was a natural extension.
But there's not a data that goes by even now 10 years later where I don't leverage a lot of the
skills that I've developed during my FPNA days. Great. Thank you for sharing that. And I'll add two
thoughts here. You know, one, I've said this a number of times on LinkedIn. I encourage anyone
working in FPNA to try to get at least at one time during your career a role outside of FPNA.
I think operations is a great place. It just gives you appreciation for the rest of the business
that if you spend your whole time in finance, you often don't get. And I imagine Jeff could tell
some stories having seen both sides of that. And the second thing, he's mentioned a couple times
in others have the importance of insights. And there's a quote I love from Jim Cook, former CFO of Netflix.
He said, remember, your product is not a spreadsheet. Your products are the analysis and insights
you provide. And I think sometimes we get so focused on the spreadsheet and what we're building
that we forget the purpose. And so I think you brought up some really good points there.
So next question I have here is for you, Arvind. You know, something we often see, I think a real
challenge we see is making sure we're all defining and reporting metrics the same way.
Cells may have one thought, marketing may have another customer service, finance, etc. Anything
you can share with us, any advice on how you go about making sure they're aligned?
When we're talking about a metric, I think there's sort of three who's to it.
There's who defines it, who reports it, and who's accountable to it. And ideally it's not the same
team or same person that's doing all three. You know, you hopefully there's a little bit of a
separation there. But I think that defining it and reporting it, that team's the same, that's fine.
But I think the first step is to define on those sort of three areas, who's the owner,
who's the person who's going to be defining it, who's going to be reporting it, and ultimately
who's accountable to that metric. So, you know, super quick, simple, simple example, something like
I don't know, weighted pipeline. You know, maybe it's the RevOps team defining how the weighted
pipeline gets calculated. And then it's the maybe the RevOps team or the data, data team,
they're actually building up the reporting infrastructure around it. And ultimately it's the sales team
that is sort of accountable to the size of the pipeline versus revenue targets. So, I think
having that common understanding of while for a metric, who's the person who's actually owns the
definition of it, who are we trusting with giving us accurate reporting on it, and they're keeping
on top of the data systems and who's responsible for how that metrics performing. Having clarity on
those, I think helps keep everyone aligned on ensuring you're looking at and defining reporting
metrics the same way. Appreciate that, Arvind. I really like how you broke that down into the three
buckets, the defining, the reporting, the accountability, and the importance of not having it all
sit with the same person, right? Having what we want to call separation of duties in finance often,
right? Drew, I see you nodding your head a lot. What, any thoughts or anything you want to add to that?
Yeah, I mean, I think it's actually a cross between systems or process systems and the
enablement aspect of things is really having a structured data dictionary within your organization.
I mean, really in an actionable level, that is something that I find missing all the time,
or something that's grossly out of date. So much so that recently from an advisory perspective,
I engage with a client and it was the first thing I brought up. Like their pre-revenue,
they're actually pre-processed to a large degree, but they do have a PLG function.
And I immediately said, look, what's your data dictionary in terms of the product tracking
and the tags and making sure that your naming convention is tight, your actual definition of
what all of those things are so that you can do aggregations and roll-ups and
actually start to track product-led growth metrics accordingly, right? And then that builds into,
of course, your modeling later on, right? Because you're looking at the bridge between product-led
growth overall to self-serve conversion or self-serve pay to eventually a product-led sales model,
right? Where you're bridging to the enterprise motion after that. And I think all of those things,
I mean, really one of the most critical steps is just data dictionary, making sure that you have
those data points tagged, aligned, mapped out, and everybody knows what they mean.
All right. Since you've been our fun ones to discuss,
data dictionary, we're going to throw this question your way, Drew. Should the data dictionary be like
Wikipedia or Websters? If the latter who owns it? Any thoughts on that?
I think it should be a combination of the two. So I would say that if you have a relatively
decentralized organization, it should be like Wikipedia with a review function. Where do you have
somebody who's the ultimate arbiter of acceptance or qualification, right? And I would say that
that needs to be probably at the sea level, right? Because I mean, you know, it finally rolls up
there, but of course, like tracking all of those specific points. And I think it could also, you know,
a strong VP Revops could definitely take that role and say like, no, this is what everything
means. And this is the tiebreaker. And this is how we're going to adjudicate the final definition.
So there needs to be an official final document, but it could be crowdsourced in terms of the
base level documentation. I agree. You could do the base level, but at the end of the day,
you need somebody who owns it and says, Hey, this is the final definition. So I think ultimately,
it's more like Webster in that someone has to own what that true definition is. But I think without
having a little bit of that Wikipedia where people can comment and provide their input, it's hard
to get buy in. I can still remember one company joined and we're trying to switch to be more of
a SaaS business and having the conversation of just trying to align with the CFO and the CRO and
a bunch of people. What a booking was. Yeah, you think something as simple as that would be easy.
Now there were all kinds of definitions for a booking. And so it's really important to have those
conversations and make sure people are heard because it can be a real challenge. But, you know,
one thing it leads to is the data dictionary and good data is even more important today as we see
more and more AI coming because AI relies on lots of data. And so I'm curious to get all of your
guys' thoughts on the panel here. How do you see AI impacting the operations function? Maybe
today, what have you seen? You know, kind of in the last year. And then how do you think about it
in the future? And then if you're using it, maybe just a little bit of how. So I guess on this one,
we'll start with you Drew. I actually think that, you know, somebody who's who's dug in on this
more than any of us is actually Jeff. I saw a sub interesting post from him recently on this
exact point, but I will speak to one point, which is enablement. And I think enablement is probably
going to shift in a direction of using, you know, taking that brain trust of the organization.
If it's codified at a reasonably structured level, you would probably see more and more
enablement level of GPTs across an organization, right? So that killer of revenue operations,
I think will largely move in that direction. And I think that'll be great in terms of
just data distribution and democratization access to that information overall. But that's
probably the primary point that I see becoming largely automated in the near term with
the generative AI at least. And we'll go to Arvin here next and we'll finish with Jeff. Arvin,
what are your thoughts on this? AI is going to help just open up time and capacity for people where
you can get a lot of the lower value activities out of the way through through AI and you can start
leveraging AI to answer some insightful questions. So I gave the example of earlier where our
product team is changing the roadmap in the back half the year and that introduces some revenue
risks. So I can see, you know, leveraging AI to be a bit of that advisory function that Jeff's
talked about before that. Hey, we've got this revenue at risk. These are some of the parameters
of the situation. What are some potential options that the team team team team should explore?
One one area where where I've been pushing my team on leveraging AI is just skill development.
I've got them to develop some scripts in VBA and Python. Folks who haven't done that type of work
before and I've challenged them and I've said, hey, you know, here's a couple of, you know,
relatively against low low value tasks that I think you folks do that could be automated a little bit
more. Just go to chat, ebt, describe what you needed to do, ask it to to produce some code in
Python or VBA and start automating some of your work. So that's how my team has been leveraging it
is in just short, short circuiting the learning curve of developing some new skills where when they
identify some opportunities for automation or some need for some code development, they get 80%
of the way there in like half an hour by leveraging chat, ebt, or something like that.
And it's a great way to use it is definitely to shorten the learning curve. It can definitely
help with that. Jeff, what are you seeing? What's your thoughts? Yeah, so I've had the pleasure
of actually interviewing quite a few founders in the AI space, particularly for my newsletter,
but ultimately I think what this leads to is increased worker productivity. For example,
the amount of ARR that a CSM can support, the number of accounts that a sales rep can
prospect into the amount of lines of code that an engineer can produce and push into production.
So you just think about those ratios. What we classically viewed as, you know,
hope, heuristics for whatever work use case that is, those ratios are probably going to start
moving up. Now the question is, is it going to be incremental or is it going to be exponential?
And those are the curves that just don't not quite sure. But you can make the argument that
certain engineers today with the aid of AI and their GitHub repo or in their code editor,
you could probably be for X-More productive. You could probably push more codes in every before.
And maybe we see that up and down, different roles in finance and in revops. And I know right now
we're talking about LLM as a model, but at some point these models are going to turn the street.
And you're going to be able to do real math in a meaningful way at scale in a lot of these models.
So a couple of use cases that I've toyed around with, content creation, both internal external,
internal documentation, training, knowledge bases, even something as small as description,
help text fields inside of your Salesforce. External, a lot of folks are now trying to prospect
with AI. In fact, when you go into a chatbot for customer service, you're probably not going
through a decision tree anymore, probably interfacing it some sort of AI that's now taking the context
of what you said and blending it with the right data points, cookie tracking, for example,
and then sending it down to the right knowledge base for channel. Next research and context,
the hardest working intern is a term that I've thrown around quite a bit. They may not get it right,
but hey, it does the amount of research and a fraction of the time and 78% good enough. I've used it
for an account scoring project. I can't use data providing tools to get the data insights that I
need to score my accounts. And so I've just fed it EDFs and URLs and it's done to work for me.
I've mentioned co-pilots and debugging. If you ever wrote a complicated if statement and
side of Excel or if you're writing a complex query on a data editor, it could debug it and
probably shrink it by a factor of two or three. And then at the application layer, there are tools
being built that are not just sprinkling AI on top of their tooling, but you're talking about
unlocking true natural language processing, the ability to speak out loud and then have the AI
listen, speech recognition, and then turn it into the results you're needing and feed fetch the
reports you want. And then not only that, I think these no code, low code, seamless workflow
builders are only going to get built better with AI in it. Thank you, Jeff. I think there's a lot of
great points there and the reality is that's here. It's here to stay. It's making us more productive.
It will continue to do so, whether it's revops, FPNA, marketing, sales, engineering, product.
And if you're not learning how to use it, you're missing out. I think that's just the reality of it
today. So we're coming up near the end of our time. If anyone else has any questions, please
throw those in the chat now. We'll try to get to a few of them. So I have two more questions
for each of you. And the first one here we're going to ask is, what is your favorite function
or feature in Excel? This is something we ask all our guests. So you're all going to get it.
Should I pick on first? We'll start with you, Jeff, on this one. I don't even use Excel. I
use Google Sheets. Come on. You've used Excel in your career though. You did work for Google.
Fine. What's your favorite feature of functioning Google Sheets? I'm a big fan of the query function,
big fan of filter and then combining it with filter unique accounts.
Yes. I like, I use unique and count a lot. Not so much filter, but yeah, I use filter
a fair amount. Just not that combination. That's a great one. Appreciate that. And yes, we have
Ezra saying pivot tables and concatenate. Feel free to add yours in the chat. What your favorite
one is. We always like to see him. Arvin, how about you? Yeah. I know a lot of your guests,
they like to mention like a lookup function. So I won't repeat that. But if you remember,
I said I started my career in quantitative finance and a lot of quantitative finances built on
a form of modeling called stochastic modeling. So trying to model random processes. I actually
built a lot of stochastic models in Excel. I wouldn't recommend them for any production purposes,
but if we're little hack jobs, I'm just kind of getting some directional analysis of things or
we're just getting even a production process off the ground. Excel is still pretty reasonable
for building stochastic models. Just by using the RAND function and a camera member if it's
norm as inverse or norm as disk, but combination those two and you can basically create a stochastic
model on your own on Excel. So I'll go with the stochastic modeling functions in Excel.
Drew, how about you? I think it's not necessarily a favorite, but I will say something that I
kind of used again very recently. And I think it's underappreciated. It's just trim.
I was like so annoying. I was like, oh good trim. I kind of want to just call out the humble trim
function. Also, I think a feature of Excel that I think if you're trying to do pilot level dash
forwards or design like a preliminary dashboard or something like that is spark lines are a great
function. So I'm a big fan and it gives you a little bit more visual candy than just having
a bunch of numbers in a row. And so I'd call that out.
Mark lines is a great one. Trim, I love the other day I was dealing with one and used a trim,
didn't clean it up. You're thinking it's a space and it's a special character. So wrapping trim
with clean, you're around the whole thing to get it to work. So it'll take out those special
characters. So that's one of my favorites. Wrapping things with trim and clean and converting it.
So it's actually a number all in one one formula. Everybody's nodding there. I think they can relate
to that one. All right. So we're going to give Drew one question here that we got asked by Christopher.
And then we're going to go to our last question. We just have three minutes left. This one was
specifically for you. And I got to read it. So because we will, you know, not everybody will hear
this. So he asked, what's the harder metric to improve? GRR are Watts per kilogram. And I'm sure
there's something behind this. Well, I mean, my second job as a competitive cyclist on
one of weekends is what it's referencing. And Watts per kilogram, of course, being the
the amount of energy output of a 40 kilogram body weight. And, you know, I will say on a micro,
I'll give you a kind of it depends answer. So it depends isn't allowed on a podcast. You got
to pick a side. So then I'm going to pick if I have to pick the the harder one to improve in a
short term in the short term is GRR. But the harder one to probably maintain in the longer run
is Watts per kilogram because we as an athlete, you lose fitness three times as fast as you gain it.
So I actually was just at our company onsite this week. It was great, you know, totally awesome
in terms of the relationships and, you know, our overall strategy for the year effectively wrapping
up an operational kickoff with a sales kickoff. But yeah, I lost some fitness this week. So
I'm going to call that out. All right. Well, we had some fun with that. So we have just one minute
left. So I'm going to quickly go around with this last question here. We'll start with you, Jeff.
If you could give one piece of advice on how FPNA and operations can work better together,
what would it be? Just one piece communication communication, Arvind empathy for operators.
I like it. Drew. I think building on top of those two is consideration. But I mean by that is
really just really trying to stack on top of empathy and communication that reality of how it is
within that area. So, you know, taking it maybe one step further and that cross-training
cross-functional aspect is super critical. Thank you, Drew. Appreciate that. I love that communication,
the empathy, the building on top of it there, the things that were mentioned. There's a lot of
human element to all this and keep that in mind. You're dealing with people, not just systems.
And again, thank you for joining us, Jeff, through Arvind. If our guests want to get a hold of any of
them, you can find them on LinkedIn. I know they're all out there, so feel free to reach out up
to them and thanks again for joining us today. Great time all. Thanks everyone. Take care.
