Britni Borrelli on this episode
Britni Borrelli, VP of Global Sales Strategy and Chief of Staff to the President at Mitratech, was tasked with implementing AI across a $600 million company built from roughly 24 acquisitions. With over a decade at Tableau and deep experience in data-driven operations, Borrelli brought a forensic approach to a company drowning in complexity: seven Salesforce instances, $5 million in overlapping software that nobody had quantified, legacy systems leaders had emotional attachment to, and customer insights scattered across so many tools that the chief product officer was told to just listen to Gong calls.
The core insight: you cannot implement AI on dirty data, and you cannot consolidate 24 acquisitions without first understanding what you actually own, who built it, and why they will fight to keep it. Rather than starting with tools or AI platforms, Borrelli started with people and data, building relationships across the organization while conducting a brutal audit of the tech stack. She discovered that most of what leadership called AI was either three-year-old thinking or software purchased for the wrong reasons, and that the real work was consolidating data sources and eliminating process bloat before any AI could meaningfully scale.
The episode covers how she assessed decades of tech debt without breaking the business, navigated the politics of replacing systems leaders had personally built and owned, uncovered millions in software waste via a single Excel spreadsheet nobody had examined, and why consolidating on one platform beats trying to keep everyone happy. It also explores the relationship between process consistency and data quality, why close rates of 85% and 15% tell different stories than they appear to, and how boards often fail to ask the questions that would actually matter when reviewing go-to-market performance.
What we cover in this episode
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1:12
What AI Implementation Actually Means Leaders wanted to buy software with AI in the name; the real work was explaining what AI actually does for efficiency.
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3:12
Data First, Tools Second Garbage in, garbage out. Borrelli started with assessing data quality, sources, and redundancy before touching the tech stack.
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5:29
Observation and Relationship Building Before changing anything, she spent weeks listening to every team to understand motivations, pain points, and political dynamics.
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7:12
Seven Salesforce Instances and Consolidation The company had multiple CRM instances across acquired companies, paralyzing operational efficiency and preventing a single source of truth.
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9:44
Software That Replaces 12 Tools at Once Exploring alternatives like Sellular that consolidate Gong, Outreach, and Salesforce functions into one platform for AI-native workflows.
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13:21
Managing Political Pushback on Change Leaders resisted overhauls of systems they had built. The solution: transparency, connecting pain points to solutions, and reminding the team repeatedly of the long-term vision.
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21:32
A Decade at Tableau and Data Transparency Data transparency prevents hiding; everyone can be held accountable. This philosophy shaped her entire approach to consolidation and trust-building.
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30:30
Trusting AI When It Produces Data With AI generating answers, you need fail-safes, triage teams for accuracy, and agents that triple-check answers to prevent hallucination or contradictions.
The lines worth sharing
If you're going to put AI on top of dirty data, you're just going to get more garbage.
Britni Borrelli · 3:12
Seven Salesforce instances. Let's just period. It's impossible to work quickly when you're going in and out of different instances.
Britni Borrelli · 7:12
The best thing is got to just rip that Band-Aid. Don't wait. And it's painful, but don't wait.
Britni Borrelli · 18:17
We're spending $5 million in overlapped or repetitive software. That's not a small chunk.
Britni Borrelli · 13:21
Common questions from this episode
How do you implement AI when you have multiple acquisitions and messy data?
Start with data assessment, not tools. Identify redundant systems, build relationships with stakeholders, and consolidate on one platform rather than trying to keep everyone happy. Band-Aid ripping beats consensus-building when the stakes are efficiency and scale.
What is the difference between buying software with AI in the name and actually implementing AI?
Real AI implementation requires a smart plan for how data flows, where it lives, and how silos get eliminated. Buying point tools creates inefficiency through token waste, multiple prompts, and lack of data consistency. Integration and automation across one platform matter more than individual features.
How much software waste did Mitratech uncover?
Borrelli discovered $5 million in overlapping or repetitive software through a single Excel spreadsheet that tracks all software purchases and ownership. She uncovered seven Salesforce instances and similar tools duplicated across acquired companies that could be consolidated into platforms like Sellular.
What is a close rate of 85% vs. 15% really telling you?
Both numbers can be accurate but mean different things. The 85% person likely builds pipeline only when close to certain; the 15% person takes bigger shots but closes more revenue overall. Single metrics mislead; you need process consistency and multi-level data analysis to understand real performance.
How do you ensure data accuracy when AI is generating answers?
Assign a dedicated team to data accuracy and triage. Use fail-safes and agents that triple-check prompts to prevent contradictions or hallucination. Remain transparent and open to stakeholders poking holes in the data, and explain where answers come from if they're questioned.
Why did the Chief Product Officer have to listen to Gong calls to understand customers?
The company had no unified customer insights system. Data was scattered across multiple tools with no central way to surface sentiment, objections, or feedback to product teams. This is a symptom of silos and the need for consolidated platforms that automatically surface insights.
SEO meta description
Britni Borrelli on untangling 24 acquisitions, consolidating $5M in software waste, and implementing AI without garbage data at Mitratech.
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Read the full transcript · 70 KB · Britni Borrelli
EDDIE0:04Welcome to Go to Market. In this podcast, we share tangible, actionable playbooks from the trenches working as go to market strategy and rev ops consultants for our clients here at Union Square. Consulting and candid conversations with revenue leaders in the market that have been there. Now let's get into it.
RACHAEL0:23Today I'm talking with Brittany Borelli, VP of Global Sales Strategy and Chief of Staff to the President at Mitra Tech.
RACHAEL0:29Metro tech is a $600 million company that builds legal, risk, compliance and HR software built up from roughly 24 acquisitions. Brittany was brought in to implement AI across all of it. Today, we're talking about what she found stepping into the role, how she did it, and the hard truths about large scale AI that a lot of people avoid.
RACHAEL0:48Unfortunately. Hi, Brittany. Welcome on. So good to have you.
BRITNI0:53Thank you so much, I appreciate it. I'm excited to be chatting with you.
RACHAEL0:56Yeah. So you were brought into each tech to implement all of their AI systems, right? So first, without getting into how you did it. What did they have in mind when they said to you implement AI and what kind of environment did you step into?
BRITNI1:12Yeah, such a good question. Yeah. It's an older company which is an older company with legacy, pretty much everything. And also leaders who were fascinated and are fascinated by AI. But a lot of what they were looking at was like custom tracking or a few other things that like three years ago, were absolutely insane. But that is not three years ago.
BRITNI1:38And in the world they I that is that ancient. And so what my biggest hurdle was, was really explaining what is AI and how can it really help us from an efficiency standpoint and what else is out there, because there's a lot of education that had to, had to be done to get us to where we are now.
BRITNI1:58I mean, it's still a big process.
RACHAEL2:00Yeah. And so what is the difference between a company that's quote unquote implementing AI and a company that's just buying software with AI in the name?
BRITNI2:10Yeah, I it's I think a lot of companies and a lot of sales teams or even just departments in general, are looking to implement AI because it is a focus of boards. It's a focus that everybody sees that there is efficiency, but they don't really have a smart plan. And what I mean by that is, you know, at AI to one particular piece of software, you've got AI for another.
BRITNI2:35And then all of a sudden you have siloed deployments of of data everywhere. And then how is it actually talking to each other? And are you actually getting accurate use of AI, or are you using tokens inefficiently, which is then charging you a whole lot more because you should. Based pricing is also new to a lot of companies.
BRITNI2:59And so there's there's definitely a lot that goes into that.
RACHAEL3:03And so how did you approach AI implementation at Metro Tech, especially considering, you know, you have all these different acquisitions under the company?
BRITNI3:12Yeah, it started with data. Because if you're going to put AI on top of dirty data, you're just going to get more garbage. And so and that's just a tale is all this time. And my time at Tableau definitely has created this like a data love in me that I wanted to be accurate, I wanted to be efficient.
BRITNI3:31And I want to make sure that no matter whoever is asking questions of the data, it's accurate and people could trust it. Because again, if you can't trust it, they're just going to do what they've always done, which is we're living in spreadsheets, we're living in, you know, everything takes seven years to complete. So a big part of it was figuring out, okay, what's off, where do we have and how many instances of it do we have?
BRITNI3:54And we had several instances of essentially everything. But also we also had similar software but in different parts of the business. So there was a lot of overlapping. There was a lot of inefficiencies when it came to the software that we had. So it really started with partnering with the chief operating officer and the CTO, really trying to understand, okay.
BRITNI4:20Where are we trying to go as a business internally and partnering with them there? Because, you know, a lot of it were babies that they had deployed, whether it was in the last three years or ten years ago. And a big part about, you know, implementing new things or doing something that's completely new, you have to also obviously play the political role that someone probably is still there, that implemented something that just isn't good enough anymore.
BRITNI4:48And that was a essentially where we had to start and really showing them the difference and how we're going to go into the future that it it really started there. And and it's I'm glad that we started there because at the end of the day, we'd still be having of of data and hitting walls because you just have to partner with all the different groups of people to really implement something on, even on the sales side.
RACHAEL5:17So what does that look like when when you first came in and you had to assess everything, what exactly did you assess and who was in the room and how did those first conversations start happening?
BRITNI5:29Yeah, I mean, I just I do a lot of observing. And also I'm just one of those people that loves to connect to every single person and understand what is it that they do and what is their motivation, and how likely are they to be in my corner, and how likely are we maybe not going to be on the same page?
BRITNI5:49And so a lot of my first few weeks, few months were just building those relationships with everyone that I possibly could. And it wasn't just sales, it was operations. It was product. It was our obviously other strategy, the board. I mean, it's it's everyone. And I think a lot of times sales leaders or sales in general just think about themselves and just hitting a number.
BRITNI6:15But as sales strategy, everyone in the company is and should be your teammate. And so I spent a lot of time building rapport, making sure that if there were things or hurdles I could support them with or, you know, really just be an advocate for them, that I was doing that because I knew that it was going to be a pretty big overhaul, and I was going to need a lot of people to, to help us do
RACHAEL6:42And what kind of data did you have to pull to decide? You know, what instances stay, which ones go, what's redundant?
BRITNI6:51a big part of it was what do we what do we want as the platform are all speaking about and all speaking to. And honestly, where was most of our data at the end of the day? And so was it easier to rip and replace something that was just a lot easier to move from one to another?
BRITNI7:12Did we were we all working out of one particular one that made it easier for us to, you know, really hone in on and focus on? But other things too, were trialing other software, especially early on, that could maybe eliminate a few other things. And that has been a very interesting road to go down, especially in the world of AI, where I, I do not believe that what we we, in the general sense of sales, like what we were brought up with over the last 20 years, is what's going to take us into the future, because a lot of what we've done as sales leaders is we're just so used to platforms like Salesforce, and
BRITNI7:58we're so used to working out of things that it's just how it is and it's just how it's supposed to be. And gosh, if I can, if I never say, hey, please update your opportunities, it would be amazing. So we're on calls all the time. We're all recording those calls all the time. There's software that is understanding people's sentiments and what's being said and who's saying them.
BRITNI8:24So why do we not have software or utilizing software that's not updating opportunities automatically? Why don't we have sentiment analysis or lead analysis? That's all sort of like working together or, you know, we've got a lot of that data that's happening between internal calls and external. Like, again, all of that is just the pain in the, you know what admin that I, as a sales leader or sales strategist or operations leader, has to harp on the sales team to get updated or we can't forecast or we don't understand what's going on within the customer base, but it is still all opinion based because it's what are the actual notes that are getting added?
BRITNI9:13Who's actually doing it? Some people are better at details than others. Obviously every salesperson wants to make themselves look good, so all of their ops are always going to swing more of their positive way. So how do we get that? Like real, rich, honest, transparent data all being recorded all the time? So some of the software that I was looking at or sell a URL sell is one of those where essentially can eliminate 12 different pieces of software.
BRITNI9:44So that includes things like Gong and outreach and Salesforce. And obviously I don't dislike any of that software. I've partnered with a lot of them. I have a lot of friends that are working there, too, and they'll also work with that software, because ripping all of that out is terrifying, because what if it doesn't work? But really trying to get to that ability of we all are actually working in the place that we are in every single day, rather than the 50,000 tabs or the different soft pieces of software that we're working with every single day we had just found, especially in AI.
BRITNI10:25While it's making us efficient, in some ways, it's making us paralyzed in others because we have things everywhere. So, long story short, how did we figure this out? It was a lot of trial and error. It was a lot of where's our data? How can we move the least amount of data? And obviously we still have to hit our numbers.
BRITNI10:46So how is it also just not disrupting people as much? But also where do we want to go in the future? And if we disrupt it now in an early part of this year, where could we be next year? And, you know, five, ten years from now? So there was a lot of that analysis that was going on.
BRITNI11:06And did we do it right? Who knows. At the end of the day, I think a lot of people are ripping up in that Band-Aid and seeing if it's working or not. The nice thing is that the company is very fast to switch something, so we don't have to be bleeding for a long time if something doesn't work.
BRITNI11:25But yeah, so that was
BRITNI11:28a, I guess, a longer version of how we got to where we are now.
RACHAEL11:31did you find that there was a lot of pushback or, you know, a lot of retraining that you had to do, moving all these other acquired companies onto this totally new system? And how did you navigate that?
RACHAEL11:43Yeah.
BRITNI11:43I mean, there's a lot of retraining from the executive side and from the leadership side. And but there's also a lot of making sure we're talking about long term that needed to happen. And part of what that was as far as like what my analysis was, is what are some of the things that the sales team is griping about all the time?
BRITNI12:07How do I take those pieces and build a story to the executive team that, hey, yes, this might disrupt them. They might not totally love it right now, but they are all in want of something that's different than what they're doing right now. And so making sure that there's you're connecting the story of motivation. You're connecting the story of where we're trying to go all the way along the way, not only to the front line, but also to the executive team, and keeping that in line and making sure you're reminding the team over and over again was a big part of what I was doing.
BRITNI12:47And it really is just that transparency, that honesty that really went a long way to a lot of time and effort. But it is so important in this world of change because everybody says they want change, but nobody actually wants to act on it. And so trying to understand those motivations and, you know, the problems that people are feeling right now and connecting all of those to, you know, where we're trying to go.
RACHAEL13:11So what does your AI tech stack look like right now then? Is it all kind of under or sell, or do you have still a bunch of other tools that you use?
BRITNI13:21We still have quite a few tools. Big part is, is they don't all renew on the same day. Man, if that would be okay, that would be so nice. And a some of those were multi-year contracts. Some of them are easier to get out of than others. But you know, that's just the world in which we're dealing with right now that five, seven years ago, multi-year contracts were a big thing.
BRITNI13:47So, you know, trying to navigate that is definitely necessary. Obviously, user based consumption is another piece of that. And how do we either ramp it up specifically or ramp it down specifically? Because at the end of the day, my initial observation was we're we're spending $5 million in overlapped or repetitive software. That's not a small chunk. And we're not, we're not we're not a big, huge company, but we're also not tiny.
BRITNI14:21And so all of those pieces are relevant. And hey, at the end of the day, I think there's still this nervousness when it comes to AI and really trying to hone in on one thing because, hey, what if Oracle goes down and something doesn't work and everything is in it? People are terrified because they haven't seen what it looks like when potentially it goes down and every like it might.
BRITNI14:50We always obviously have to have a contingency plan. So at this rate, we still have several pieces of software, not only because of, you know, their contracts that we've signed in the past, but also just making sure that we feel really confident in moving forward with one or the other or whatever it might be. And as a business, we're three different pals now, which was different than when I originally started.
BRITNI15:17So we also have several different governing bodies to to manage as well. So there's lots of opinions that are floating around and how the distance is being worked, which comes with its own complications.
RACHAEL15:33But yeah. And like I'm so curious about that and I a part of it doesn't even know, like where do we start to dig in there. Because I mean, 24 and I'm guessing counting acquisitions inside this company. Right. So 24 companies that were completely self-contained before they became meter tech and had all of their own tech stacks, all of their own AI workflows and ways of doing things.
RACHAEL15:59Just what is what's the process now for consolidating all of those AI tech stacks and workflows with new acquisitions? Yeah.
BRITNI16:07The the team did a great job and integrating them. And then there was this like quick wave of a lot of acquisitions without like a better word, decent plan. And so that's something that I'm also working with with the team, the executive team on how when we start raping back up to acquire again, we have to have a better process and and implementing those different teams.
BRITNI16:33And that's another part of the software analysis is, you know, Salesforce love them. Obviously you used to work for them. A big reason why they're so sticky is it's practically impossible to take one and move it into another, because it's so unique and it's so specific to the actual team. And it makes it really hard to rip out.
BRITNI16:58The thing that I am also looking at is, okay, if we're going to go back into this like crazy acquisition, is there other software out there that makes it easier to ingest all of that and make it easier to rip that Band-Aid? I was a part of the Tableau transition. Wild. How difficult it was when Tableau was acquired by Salesforce to be implemented into the Salesforce ecosystem.
BRITNI17:22It was it was an enormous feat and it was Salesforce. So yeah, knowing that and have been part of all of that, you know, that's another part of, you know, as we continue to ramp that back up because we slowed down quite a bit, that is a part of our AI strategy. And what the, you know, the execution is going forward.
RACHAEL17:48And what kind of advice would you give to other companies, either they're the same size as Metro Tech or smaller or bigger. Maybe it's their first merger and acquisition that they've done. How what what what kind of advice would you give to them on how they should consolidate this data and consolidate their AI workflows during a new merger and acquisition?
BRITNI18:11The best thing is got to just rip that Band-Aid. Don't wait. And it's painful, but don't wait.
BRITNI18:17if you know where you want to go and you know what the platform is in your all in on that, you just have to recommend it and move on to whatever that might be. Now, obviously, being open to other teams ideals or whatever efficient processes they had, obviously you have to make sure that you're staying aware of some of those things because, for instance, Tableau was a lot better at e-commerce than Salesforce, and so there was a lot of learning that was happening, you know, both ways.
BRITNI18:49And so similarly with other acquisitions that we've done, some other some of the companies that we acquired were doing a lot better job in certain things. And we took note of that and, you know, made some switches. But as far as like best advice when it comes to software, it's really figuring out what is the software that we are going to do, like we're going to implement as an entire team.
BRITNI19:18And we just can't have multiple instances and different teams having different ways of communicating that data, because at the end of the day, we need one message and one story that goes to the board. And if we're all talking different languages, that makes it really hard to create that connected story. So it's really important for us to just rip that Band-Aid as quickly as possible, because a lot of the problems that we've seen in the past were because we just want to make everybody happy.
BRITNI19:52And by making everyone happy, you actually make that one happy.
RACHAEL19:55Absolutely.
BRITNI19:56A lot longer.
RACHAEL19:59Absolutely. Yeah, I, I could go on so many tangents about just that one like concept, but yeah. So and for like if you're giving advice to these other companies with their immersion acquisition, who would you say should be responsible for overseeing that consolidation of tech and AI and data?
BRITNI20:20There should be a head of acquisition and mergers, like there should be somebody who's at the head of that that has the control or has the, you know, backing of the executive leadership in the board, someone who is partnering with operations and product and sales and marketing, someone who is essentially at their same level, but is the one that is just focused on that acquisition and just focused on how to deploy that quickly.
BRITNI20:52When you don't have anyone that is really owning that, it won't get done. And so I, I have seen that as long as there is someone at the helm that is given the rights or the authority or the responsibility to go and implement that, it makes it a lot easier. Otherwise, if everyone owns it again, no one owns it.
RACHAEL21:17Yeah. All right. So switching gears a little bit here, I know you mentioned Tableau a couple of times. You spent a decade at Tableau before meet your Tech. How did that change the way that you saw data efficiency. And what did you bring from that into Metro tech? Yeah. So I.
BRITNI21:32Was at Tableau for quite some time. So I was there when Christian Chabot was still barefoot, walking around in the office to Adam, who led the team into the acquisition of Salesforce. So was there through all the big changes, which was a lot of fun to see. You know, how a company really changes through all of those moments in time.
BRITNI21:56But it it not only changed the way I think about data internally, because I also was at Yelp during its IPO era. And the difference between the two is Yelp was really transparent and then became a really not transparent after the IPO. And then Tableau even post IPO as they're active. The IPO was still very transparent. And to me, if you had data transparency, nobody can hide anywhere.
BRITNI22:23Like everyone essentially has everything out there. We we can't manipulate how we're thinking about data in any way, shape or form. And I just think that that is a, obviously you've got to make sure that, you know, data is not getting out to especially if you're public or whatnot, like, it's not getting to the market before it's supposed to, but that that trust and that.
BRITNI22:56I as a person inside the understanding of really how the cheese is made, also helped me as not only a sales person, but a sales leader. And I also knew that we're all in this together and there's really no where to hide. So it just it has changed how I think about how I go to market myself or my strategy perspective is, hey, all of your data, all of your, you know, bury bodies, all your dirty laundry is all going to be out there for everyone to see.
BRITNI23:29And in this world also of, you know, this like hybrid or remote or whatever, but, you know, global teams again, there's nowhere to hide, which I love the flexibility of being able to live wherever you want to. But we also have to be accountable to our roles and to our teams and to our peers and to our partners.
BRITNI23:52And that data transparency is, to me, a big place before that started. So I, I have seen it. I know what it feels like between one or the other. That is has completely changed how I want to build a strategy team. And then on the outside of just seeing how companies changed, by being able to ask them into their own questions, because at the end of the day, marketing knows the questions that they want to ask.
BRITNI24:21Operations knows the questions they want to ask, but they don't have access to it. Then how do we really move forward? So Tableau was very beneficial, I think to me. And man, good days.
RACHAEL24:36Yeah. And when it comes to like nowadays at me. How do you bring in those philosophies and ensure that on an operational level that you can have that data visibility to have that data efficiency and, you know, people in marketing or people in sales or whoever, whatever executive, they have a question that they can ask and be able to pull that information up quickly and easily without, you know, having to listen to a bunch of gong calls or something.
BRITNI25:05Like that. Yeah. I mean, that was actually the reason I giggle is because our chief product officer didn't have access to what the customers were saying, and someone told him to just go listen to gong calls. And when he told me that, like, you've got to be kidding, I'm not going to go listen to calls.
RACHAEL25:24There's less time for that. For that. No one has time for that. Yeah.
BRITNI25:29And so there's just there.
RACHAEL25:30Are.
BRITNI25:30Ways to pull at that data to be and we should be surfacing that information not only for products, but also so that sales knows that product is listening so that sales can it just is this like ever infinite loop. If everyone knows that everybody has access to all of this data, and if we're if our product team isn't getting what customers are saying, how how are we building a product that people want to renew or continue or newer, you know, prospects, how do we know that they'll actually want to stay on top of those things or purchase because of that?
BRITNI26:06So, so.
RACHAEL26:08Valuable.
BRITNI26:08So, so, so important. So anyway, and now that I tangent off of that, I forgot your question because I was just.
RACHAEL26:17Yeah. Sorry. So how like on an operational level, how do you ensure that you're building a system in like a tech, an AI ecosystem where somebody can just like ask a question or, you know, have a question, go into a dashboard and be able to pull those numbers up quickly without like needing to actually go and route through gone calls.
BRITNI26:39It goes back to the motivations and it goes back to like, what are we trying to do long term? And a big part of the conversations I was having already on was understanding, like, what are everyone's pitfalls? What are the biggest struggles that they're trying to come in? Every single time I came back to data. And so and to me, that is the easiest thing to be able to solve, because once we can get it to a place where we can all, you know, pop into it and start asking questions, man, we can absolutely springs, you know, whether it's leveraging something like glean or, you know, having one place to ask the super intelligent questions
BRITNI27:17across Gong and Salesforce and everything else have again in one place is is really important. But it then also goes back to who do we have at the helm for our technology stack, and who is managing that, and what is their long term strategy there? And that was a big part. Two of the conversations I was having is, you know, what is their likelihood that they're going to want to do something completely different because the executive team might have a particular thought on where they want to go, but those that control where the data is and how it's deployed, you know, maybe they have a completely different opinion on that.
BRITNI27:59And it's it really it goes back to building relationships with people that are meaningful, but also, you know, making sure that you also, if you are going to be responsible for making the changes, you know, there's a lot of revenue leaders that are looking to take on responsibility or new roles or things like that. My biggest advice to them is you make very clear, make sure that you have it bulleted, that you are responsible for x, y, z, because you're going to need to be able to, you know, back into that if someone pushes back on you, especially if they put blood, sweat and tears into implementing something and you're about to completely change, you
BRITNI28:45know, whatever that might be, you know, it would be similar if we worked out Salesforce, for instance, we've got Salesforce Architects. I'm sure they would be terrified if we did that. What does that mean to their job? And so that's something that is really important, especially in this like uncertain world where everyone's a little worried all the time is, you know what, only making sure you're communicating the things that are accurate and transparent and whatnot.
BRITNI29:14But if you're going to go and make some changes and flick some tables, you make sure that you have the ability and the authority to go do that. And I found in the past that I wasn't as clear about that early on. That did not work so well. So I'm very adamant about that
RACHAEL29:33Quick pause. Everything we talk about on this show. Diagnosing go to market ops. Prioritizing projects for revenue. Impact processes. Metrics. Insights. Building a predictable go to market engine. We've built frameworks for all of it. They're free and undated on our website. Union square consulting frameworks. The link will also be in the show notes, so make sure you check that out.
RACHAEL29:56All right. Back to the episode.
RACHAEL29:58So now, now that everything were, I guess, probably always an ongoing thing implementing AI and tools and processes and stuff. But now that it's been about a year I've been to take for you. Let's say somebody from marketing has a question about the marketing numbers, reporting whatever, and they need to look something up. How how are they sure that those the answers that they're getting are accurate and consistent and something that they can actually stand behind.
RACHAEL30:30What kind of data collection
RACHAEL30:34infrastructure needs to be in place for that?
BRITNI30:37Yeah. I mean, at the end of the day, there's data going in and data going out constantly. And so a big part of that is being open as a strategy team, as a data team, to allowing people to poke holes on it and to ask the questions, hey, can you make sure that this is absolutely accurate? And if if someone sees something that's off you, you know, you've got a triage team that can go and figure it out and and back into, okay, why did it get this answer and be able to take screenshots of it or being able to explain?
BRITNI31:15I mean, now you can just dictate into a whisper app or whatever it might be and just, you know, word vomit, whatever you're thinking or seeing how they I clean that up and send it over to the triage team or however you want to do it. But making sure that there is a team that is dedicated to data accuracy that that helps make sure that, hey, we feel confident about this because there is someone who is owning and responsible for data accuracy.
BRITNI31:46But also, if we ever do have a question or if the board ever has a question, we've got someone who understands it well enough to be able to back into why that is the answer. And if something is off, then you have to be transparent and say, hey, based on my calculations, you're based on what I'm seeing here is here is maybe a different answer, but at the end of the day, it's making sure that there is someone who owns that, because that is why we to have and you know, all those things that probably feels excessive because there's it is not an easy job.
BRITNI32:24But also, you know, it's just one of those roles that might feel excessive, but it is so, so. Important to a company. Because if your people don't trust the data and they can't like, then everything that we're implementing doesn't matter.
RACHAEL32:44Absolutely. And like Union Square Consulting, we work with clients like this all of the time. And for us it like always comes back to, you know the processes that the company has across the board, especially if they went through mergers and acquisitions. And they have different like companies being absorbed. You know, what are your processes for collecting this information.
RACHAEL33:05What are your IPS and biopics? Are they actually accurate? Like can you trust that data when it comes in? Can you trust your close rates? Can you trust like this this and this. Like if you if, if if you can ask three different people across your company, you know, what's our ICP and they give three different answers, then you can't trust almost any of your data down the entire line because it's like a complete domino effect.
RACHAEL33:29So and I think that.
BRITNI33:31At that, when was the last time that leadership asked, what is their ICP. And what is it that we do? And I had given someone, I don't remember who it was advice they were going into their first year with their company, and I was like, what you should do and don't do it, you know, at any other way, except just as a a data gathering opportunity, have every single person that's doing a QBR explain to you what is our ICP, what is it that we're doing and what is our five year plan without giving them any other directions and just see how people articulate it and who, not necessarily who's running, who's wrong.
BRITNI34:16So you don't want to absolutely no reason to, you know, go and ask people who are completely off because it is the executive team's responsibility and their lack of, I guess, education from the top down. But if people can't regurgitated that or explain it like similarly, that's that's not on them.
RACHAEL34:40That's absolutely.
BRITNI34:41And it was a really interesting exercise for him because it was totally different across departments, even across leaders within similar departments. And that just gave him some fuel for fire of like this. That actually is the first thing we have to go attack is who is it that we're really trying to go after and what is it that we're doing?
BRITNI35:07Which sounds so simple, but if you don't have everybody on that same hamster wheel like it's it's not going to move anywhere. So, Yeah. Really?
RACHAEL35:18Absolutely. And it's for like most processes to like you think of closed rates. You know, we have this example that we talk a lot about in our content. One sales person has an 85% closed rate. One person has a 15% close rate. Like both of those closed rates are pretty ridiculous. Like pretty much no one has 85%. Pretty much no one has 15%.
RACHAEL35:38So what's going on there? It's because not everyone is following the same consistent process for who is actually an opportunity. Who qualifies for an opportunity? When do you put that opportunity into Salesforce? What are the stage exit and entry criterias? Is that all built into the CRM as like guardrails? So we find that all the time, like companies wondering why they can't trust their forecast numbers is because no one's following the same processes or their bad process.
RACHAEL36:06Maybe people are following it, but they're bad processes and they need to be reworked.
RACHAEL36:11And it just, it multiplies when you add in acquisitions, like it multiplies significantly more than you think it would.
BRITNI36:19Oh, yeah. I mean, and that's part of what I was sharing earlier too, is, you know, if you're asking humans to go and implement or, you know, add data, not only are they going to make sure that it's positive and swings positive for them, but, you know, it also depends on what is their background and how did they learn like that 85% person might have gotten in trouble for having a lower close rate.
BRITNI36:45And so they're really sensitive to building pipeline. They probably only build pipeline when they know it's going to close anyway. That 15% person, what's their background and what was their experience? Maybe they're actually closing more than anyone else in a substantially, but they also are opening a lot more opportunity. But maybe you're taking more shots and being more creative when it comes to, you know, whatever shots they're taking.
BRITNI37:11So it's it that's the thing I think you and I were talking about too, is like, what data should the board really be looking at? And it shouldn't really be like, what's what's the forecast and what are those specific numbers? Because at the end of the day, all of that can be explained. But that's why statistics is so fun.
BRITNI37:31It can all be manipulated to whatever someone wants to believe. Yeah, it's really the the, you know, what are we doing from a cap perspective? What are we doing from like full revenue that that really gets back to that dollar and everything else goes back into that. That from an economics perspective matters more than what's our forecast, what's our likelihood we're going to hit this number.
BRITNI37:59Like that's just so broad. What is our close rates. It could be 15. It could be 85. And those actually could be accurate depending on who it is. But what does that mean. Those are the things that actually really matter. And how do you actually go and make changes against that. And I think a big part of that is data and is using software that brings all of that into one place, gets everybody working out of the same, you know, out of the same mentality that we all have, you know, similar, guardrails, you know, regardless of if it's an acquired company or not.
BRITNI38:41But that's, that is that is a huge undertaking. It definitely is not completed by any means. But that is where I'm trying to get us to for sure.
RACHAEL38:53Yeah, yeah. And like you said, you mentioned for for optimization like that data is so important not just for forecasting but for seeing like okay, this 15% close right person, they have like a quote unquote low close rate, but they're actually closing so much more revenue than everyone else. They're just following the wrong processes. Yeah. If you if you didn't know that specifically, you would look at that sales person and be like, oh, they're just doing really badly.
RACHAEL39:17Let's put them on pipe or something, I don't know. Right. But you would never think to ask them, like, how are you closing so much revenue? How are you closing on these accounts? Is there something that we can learn from you to implement or coach across our other reps? How can we get this person to a point where they're following a process consistently enough that their close rate actually reflects the performance that you know, they're achieving?
RACHAEL39:41Yeah. It's I feel like I could go on and on about this because you talk about this so much here at USC.
BRITNI39:47Yeah. It can never be one data point. It should never be one data point, ever. It really shouldn't, because every piece of data, like every piece is going to help design that story. And if you're just looking at one, it's it's going to manipulate how you actually think about it. Because you're right. Like, I actually very much valued my that had lower close rates because that meant they were taking bigger shots.
BRITNI40:15So those that were at like an 85% were usually the ones that were actually having more conversations with me because I knew they weren't taking as many shots and they weren't adding their opportunities early on, which meant they weren't getting coaching early on, which meant we had no idea what was going on from a forecasting perspective. And if it just pops and it just happens, that is so much harder.
BRITNI40:37Yeah. From a again, an analysis perspective. So and that is how I've kind of been brought up. But that's also how I've seen, you know, success versus others. But you know, I'm sure you've talked to someone else who thinks the complete opposite. And so it's just also figuring out what is that person's train of thought and why is it that they're thinking it and but it goes back to data.
RACHAEL41:02Yeah. Yeah, it always does. And just to tie this. Yeah. And just to tie this back to AI, like the reason this is such an important thing is because like you said earlier, garbage in, garbage out. If your processes are bad and it makes your data inconsistent and not reliable, then how can you implement AI onto that? Because AI can't tell the difference between Baghdad and good data, it's just going to work off of that data you give it and automate the things that you things that you give it, and then suddenly you're scaling.
RACHAEL41:32Just I depending on what AI you're using, you're either scaling stuff that doesn't work or you're making decisions based on something that's incomplete or. Yeah, yeah.
BRITNI41:45And I will admit, I am not a data engineer. I do not come from that like super tech side of the house. Which man had I done that when I was in college? Wildly different career I'd be doing right now. But but it is. It's you've been saying that there are like cloud, for instance. Like I have automatic agents that are doing a lot of the things that I'm like, I used to do manually, like I've got failsafe that any time a particular prompt is going out, it's triple checking, it's work, and it also is making sure that it's not deploying an answer that contradicts something else, that it's shared with me previously.
BRITNI42:27There's ways to get around that, but you have to do a bit of that work ahead of time to make sure that you've got those agents in place. You have those fail safes in place so that when AI is giving you answers, it's going it. It likely is going to hallucinate. At the end of the day, we have to remember that like humans will make human errors, AI will make AI errors.
BRITNI42:48And but how do you get ahead of that? And and what are the things that you're seeing every single day that are those similar errors. So that you can, you know, stay on top of it. And that's, that's something that's a lot of fun from a trying to stay ahead of AI like it is. I, I'm a part of Pavilion, which is an executive I guess social network for lack of a better word.
BRITNI43:16And there is a group of us in Seattle that gets gather every single month to just talk about what is the newest AI that we're using and why is it so helpful, and walking through how we're using it and, you know, sharing how we are building different agents and whatnot? And I'm learning a ton in an hour or two every single month.
BRITNI43:39And had I not done things like that, then I would be years behind. Yeah. Because AI is is really moving so, so fast.
RACHAEL43:49Absolutely.
BRITNI43:50That's another thing that as you're buying software, everybody can build everything. It's all likely built on the same LLM. And so how are we making sure that the stuff that we're buying and the software that we're buying is really going to take us into the future? It that's still a question yet to be answered, because, you know, I've worked with several different companies where they just kept building based on whatever customers were saying.
BRITNI44:20And then there ICP was a complete question mark. Their real direction was all over the board because it had software that supported sales, but then it also had an RFP system that didn't really overload. Why are we building an RFP? And that's I think the a lot of products LED software right now is, is sort of leaning into because they can build it so fast.
BRITNI44:45It doesn't take weeks. It takes a few hours. Yeah. So something from a company perspective and a product perspective is really making sure we know what that ICP is and what do we want to really dig into. Because I think in my opinion, the companies that are going to succeed in this world of AI or those niche companies that know who they are, that know where they play well at and really dive into that, vertical software as well.
BRITNI45:15Because if you're trying to be everything for everyone, again, you're really nothing for anyone. So yeah, that seems to be a theme in some of the things sharing today, but it is just so important to remember because it's not you actually aren't making customers happier by just giving them everything that they want. You have to remember what is your long term plan and what is it really that you're trying to build for who?
BRITNI45:41Yeah. And that's even for internal.
RACHAEL45:44Yeah. So and so I want to make sure that we talk about this a little bit before before time's up. What what are some of the numbers that your proudest of so far at meter tech in considering like the AI implementation when it comes to that?
BRITNI46:00We haven't fully gone there yet, but attacking that $5 million like overlap in sales or software is maybe going to be one of those things that I, you know, talk about for the rest of the time. Like we have already saved several million and there's still more to go. I think the other thing is looking at different pieces of software that are outside the box and thinking about how we're working at, you know, outbound and thinking about outbound differently, because every like I, I delete every single call that comes in that I don't know.
BRITNI46:35And, you know, but still telling an outbound team to go call every single executive like, it's just you can't keep doing the same thing and expect different results. Like, we can't do what we did ten years ago that worked so well ten years ago and expect it to work well. Now. People are just different when it comes to buyers, and it's we're just so different as companies and how we run things.
BRITNI46:58And so, you know, some of the other numbers that I've been really proud of to is just the efficiency in which our sales teams are spending more time actually doing their job rather than doing admin, which someone could argue, saying that like admin is also their job. But that's not what salespeople want to do. Like
BRITNI47:19you're not hired to go and spend 15 hours a week to just update software.
RACHAEL47:25It's just.
BRITNI47:26Like, that's expensive. It's not what we like. Most salespeople want to go and talk with other people and support them and whatever their problem is, so that it can be solved. That is where salespeople thrive, is like building those connections and relationships and then obviously making a good paycheck because they're implementing that support for those companies. And so we've increased the efficiency of the time that they're spending not doing that.
BRITNI47:57Then initial numbers is 25 to 30%. I think we can get it a lot higher. And and yeah, I would say those would be the, the biggest one so far. I am sure there's a lot more, but those are the ones that I'm probably most proud of.
RACHAEL48:15Yeah. And I want to go back to that $5 million in tech overlap. Is that what you came into the company seeing, or did that happen while you were at Mixtec?
BRITNI48:24That came in as a yeah. No, I, no one had known that that was what was going on. It was a conversation that I was having with a few different folks, and I got access to an Excel spreadsheet, the love, Excel, Excel of like what all Safari had and who owned it and how much we were spending on it.
BRITNI48:48And when it gets, you know, I got very lucky to be able to get my hands on that. And it was very clear very quickly how much overlap we had. And it was sort of like a asterisk of something for me to go look at. But it became a much bigger piece of responsibility when it was a very clear number that we needed to attack.
RACHAEL49:09Yeah. That's great. So you found this overlap and you were able to consolidate it all. And let me get make sure I'm correct here.
BRITNI49:17All of it. We're not there yet but okay.
RACHAEL49:19Are you working on it okay. And then the idea is once it's all consolidated, saving the company $5 million in redundant tech.
BRITNI49:29Yeah, and it could be higher than that. But it also is. It's it's getting us out of all of these silos. Like. We at the beginning had seven Salesforce instances. Let's just period.
RACHAEL49:44That period.
BRITNI49:47Yeah. Yeah. Let alone everything else. And so it's just impossible to really work quickly when you're going in and out of different instances. Not only is a sales team or sales leadership, but just in general, like trying to get different marketing or marketing teams or our finance team to be in all these different places is it is paralyzing.
BRITNI50:08It's there's no other way to describe it. And so, it was part of the implementing AI. It's part of making sure that we can all work a lot more effectively. But it also was a part of when it comes to everyone's motivation and what drove them the most nuts. And what is the one thing they wanted to solve?
BRITNI50:30Like all of those questions that I was asking, it all came back to that, like essentially to that which made it really clear to dig into, and to be able to solve it. And it's there. I'm sure there are numbers out there that we could pull. I haven't pulled it of like, how much more efficient are we from just on operational business because we are, consolidating that and because all of the teams are communicating a lot differently and a lot better because of that consolidation.
BRITNI51:04I haven't run those numbers, but I'm sure it's significant.
RACHAEL51:09Well, even just I mean, being able to consolidate all of that, if you're able to save the company $5 million, like, that's an insane return on investment. You know, just looking into this and we.
BRITNI51:23Change, that's for sure.
RACHAEL51:24Yeah. No kidding. And like we talk about the the ROI of go to market ops all the time. Right. Because it's like go to market operations. And a lot of, you know, executives, CEOs, CFOs before they bring us on to help with this kind of stuff, they're like, you know, what's what's going to be the return on this, you know, what's what's the ROI.
RACHAEL51:45And it's like, it's always very frustrating because it is impossible. It's it's really it's a question you can't really answer. Or either you can't answer it or it seems so obvious that it doesn't need to be answered because it's something like that, where it's like we're going to save the company, like significant amounts of money if we just fix these issues or it's like, oh, we can't calculate the ROI with a starting number, that's not even accurate.
RACHAEL52:12Like if like we're saying the closed rates and stuff, like, how do you calculate the ROI of fixing bad data? You can't because the bad data that you start with is bad. So yeah, the math doesn't work.
BRITNI52:26That thing and.
RACHAEL52:27Yeah, it.
BRITNI52:28it's so interesting because I would agree with you like you how you answer that question
BRITNI52:33when you know, what we were sharing earlier is you can't just use one data point. You can't just look at the 5 million. It's not we're saving 5 million here. It's how is it affected everything truly. And how do you pull all of that, all of those pieces of data?
BRITNI52:50And how are we as a team working better together, and how are we going to market quicker with something that's happening? It's just it's something that sometimes you can't put your, you know, your nose on, but it's yeah, it's obvious. Yeah. I mean it's like it's obvious. Yeah.
RACHAEL53:14I'm with you. Yeah.
BRITNI53:17when we.
RACHAEL53:18Think about bringing reporting and dashboards to board meetings and presenting, you know, what's going on in the company, in your opinion, how well do most boards actually understand the software their company runs on and what that means for the numbers that they're seeing?
BRITNI53:38I that's a hard one to answer because I, I,
BRITNI53:41I know what my board sees and what they ask, but I can't say, you know, this is how everyone is because the conversations I've had other boards are, you know, far more sophisticated in some ways and far less than others. And, and I think it's at least for us.
BRITNI54:01It's making sure that at least for me, I'm coming prepared to answer any question that they might be asking from an efficiency standpoint and an AI standpoint, because I essentially own the AI implementation. So what type of things are they going to ask me when it comes to that? Now? They actually might think implementing AI is just chat, you know, custom prompts.
BRITNI54:30So part of it is also education on what is great out there and what influences are they having my other people that they're interacting with. So it's also, you know, I'm I'm a sales person. I'm sleuthing all the time. Like, who are they connected to? What situations are they getting into? Who are we? Who are they? You know, adding into their team and what might they care about?
BRITNI54:53And all of those things essentially affect, you know, how we should show up to it also depends on how data driven the company or the board originally was. That that all plays into it. And the reason I'm being a little soft in that is just making sure that, you know, at the end of the day, I think the answer is making sure, like, as a sales executive, that your job is not only to implement those changes, but also to educate, because I've probably have a lot more experience when it comes to AI and implementing it and seeing it and than others, and trying to help educate those that are investing in us in a
BRITNI55:43way that's obviously safe and fair and not condescending, is also a big part of, you know, what my role is and do.
RACHAEL55:53And so what are the questions that a board should be asking when they're shown reports and forecasts that they almost never do?
BRITNI56:01Yeah. It's
BRITNI56:02what.
RACHAEL56:03Are.
BRITNI56:03We looking at from a multi level perspective for from a you know we should not be asking you should not be asking if I'm talking to the board. The one number we should be making sure like how is that affecting this this this this it should, it should be multi-level answers and questions for any data point. And I think a lot of times, at least in my experience, the board is really what's the word really trusting, which is great.
BRITNI56:47But I also think that it should be more aggressive and like. But what does that mean that that seems so simple. But I my experience is they're not asking that question. Like what does that actually mean? And that is something that I noticed, especially in my days at sales, like analytics to one company could be completely different to another.
BRITNI57:11Like, it sounds so simple analytics should be a very similar definition, but everyone sees everything wildly different. And I think the question that I would love boards to ask more often is, and what does that mean? And then can literally continue to do that as they're, they're diving into, you know, different data points because I've seen a lot of we're just taking it at face value and just making it essentially what we think that means.
BRITNI57:42And, AI helps us be smarter and dig in deeper. And even if we don't know the questions that we should be asking, preparing for these meetings like we should be, we should have, like, you know, AI agents that are like pushing us in every which way, which should also be the board doing the thing to us. I just haven't experienced it as much as I, I would anticipate.
BRITNI58:11So anyway.
Speaker 358:13And so yeah.
RACHAEL58:17And so for this question, we don't advocate for anyone doing this, but just for fun, if you're an exec who wants a hard question from the board to go away and you don't have to answer it. What do you put in front of them?
BRITNI58:31Alcohol and candy.
Speaker 358:34Yeah.
RACHAEL58:35A little hard when you're remote.
BRITNI58:36But yeah, I know right. There is definitely ways you can ship out call to people. Yeah. Definitely. It's it's it's it to me, it's just. How do you.
BRITNI58:50If I want a question to go away, that just means that I have something to hide. And so and I don't I don't want something to be hidden. And I, I'm a leader that likes to be transparent.
BRITNI58:59And that is going to mean that, like, hey, I have downfalls or I, hey, I made a mistake or hey, there's something like this going on, and I'm probably more widely transparent than others. I'd rather we all have the right information and the real information we get all attack the problem together rather than, yeah, I just want that question go away and I'm going to hide it and I'm going to manipulate it.
BRITNI59:24Because that you should.
Speaker 359:27You should.
BRITNI59:27Have something in the back of your mind that's like your fail safe, like, why am I feeling that way? Why do I want that question to go away? Yeah. And they're probably a real answer to that. But yeah, I found alcohol and candy. Really?
RACHAEL59:40Oh, yeah. Although reason I asked that question is kind of a cheeky way of asking, like, what are some telltale signs that an exec doesn't want you to dig deeper?
BRITNI59:54Oh, I mean, they're deflecting. Yeah. There's so many ways. I mean, it's and maybe because I'm in sales and I love psychology and I love understanding, like how people respond to things. And I'm constantly observing what the situation looks like and how people just I am a student of psychology, and to me, it's very clear when someone wants to deflect or doesn't want to answer something, they deflect or sort of like casually answer, and hopefully somebody will pivot because they're not giving like a super detailed answer.
BRITNI60:32But yeah, there's there's lots of tales, but a big part of it is like, how are they answering the question, are you are they even answering the question?
RACHAEL60:40Yeah. And so I don't know if you've ever actually dealt with this, but if you have, how do you navigate dealing with execs or, or managers who would rather fly under the radar than expose things that are going wrong in the organization operationally in order to try and actually fix it?
BRITNI61:00I mean, it's different if it's someone who's a peer versus a leader who works for me or, you know, whatever. But I, I, I'm from and born in Seattle, but I found working with people in New York are just so direct to just get to the point. Those are my favorite kinds of people. So when I'm talking to people on the West Coast, I have to remind people that, like, hey, I got a little bit of New York and me, and it's just being direct.
BRITNI61:29It's just like, hey, this is what I'm seeing. This is my observation. This is the perception that I'm having based on what I'm seeing here. Like, walk me through if I'm wrong or, or what can we do to solve this. And it's just being just transparent and not being rude about it and not being judgmental about it. It's just I found that just being direct and and or sharing, hey, here's the a perception that I'm having based on these data points that I'm seeing.
BRITNI61:58Is there something else that should be added into this equation so that it changes my assumption of what's going on? And a lot of times that's the case. And if it's not now we can solve it. We can solve it together. I've noticed that not only with, you know, internal peers and leaders, but also with prospects I can see or hear when they're starting to push back or starting to dig their heels in, or they're starting to get feisty with me, and I'll just stop a conversation and be like, hey, like, I'm sensing this, like, am I right?
BRITNI62:33And here's why I'm assuming I'm sensing this. Let's talk about it. And nine times out of ten, it like breaks that tension wall and it it makes people feel like they've been seen. And it's, it's been things that like someone had just gotten a divorce and he was super pissy with me. And I was like, something's going on.
BRITNI62:56And I know it's I don't think it's me, but like, I just want to make sure you're okay. And man, we did a lot of work together. It's just those simple human pieces, that are so impactful and that's only going to get more and more and more impactful and more and more and more important as AI becomes more and more prevalent.
BRITNI63:19Because the only thing we have is being human. And it's and to just call out those things that we see, because that's how you stay connected as a human, and that's how you stay aware and present in the current moment is, you know, hey, shit, hit the fan. Sorry, I don't know if I could swear, but, you know, it happens.
RACHAEL63:40I think so, yeah. I think we have in the past.
BRITNI63:43Well, good. If you need to cut it out, it's fine. But you know which hits the fan. Like how do you kind of work at it together rather than, you know, throw someone under the bus? I've been in a situation where I had bosses or others that, you know, use situations and threw me under the bus, and that never feels great.
BRITNI64:01But if you can be aware of your situations and like, hey, you know, it happened, let's figure it out. We've learned from it. It's never gonna happen again. Let's just go. It's hack it. I have found that people are actually so much more honest with me, and so much more transparent and much more forthright in sharing when those things happen than if we try to hide it, or if you come at it from a negative perspective.
BRITNI64:25I just I have found that all human and we all make mistakes. You're no better if you've got a title in front of your name or not. I try to be as humble as I possibly can in the sense that, like, I will try to take on or take responsibility off someone else because, hey, the more I do that, others feel like they can trust me.
BRITNI64:51And not only from people that work for me, but also peers and others that like, hey, I'm not going to throw you on to the boss. We like all of this happens.
RACHAEL65:00Absolutely. So yeah, I love that answer to you because, like, it comes up a lot when you're trying to fix tech and AI and go to market operations and like the stuff that's underneath the data, because, you know, if something did go wrong at some point and that person maybe didn't realize it, you know, or, you know, maybe they did, I don't know, a lot of people can be worried.
RACHAEL65:25You know, somebody comes in and opens the hood and sees that, you know, am I going to lose my job? Am I going to get in trouble? There's a lot of really human layers that goes in that go into that, and a lot of fears that go into that. And like you said, it's so important to stay on a human level with those people that you work with and make sure that they know, like, listen, no one's I mean, I can't speak for every situation, but like, no one's going to get in trouble here, you know, like, we can fix this and it doesn't mean it's the end of the world.
RACHAEL65:55But the longer that things stay broken and hidden, the worse is going to be for the company overall.
BRITNI66:01Yeah. And it just becomes the culture like it comes. That culture of we hide things and it's okay that we hide things or, you know, it's all about the culture that you're trying to build. And some cultures within companies that fear.
RACHAEL66:19Works well for them.
BRITNI66:20Then in those companies, it's not a place I want to say. You also see people turn over really quickly. I've also seen where you're just too soft and you're you've got a lot of people that are probably doing, you know, 50 to 80% of their capacity because everybody just wants to be nice and everybody, yeah, doesn't want to, you know, hurt feelings, but you're not hurting feelings if you're just sharing what's going on because you're likely sharing with somebody and it's just an gossip and it's just festering.
BRITNI66:52And to me, it's so important to just share what's under minds and not be judgmental and not, you know, assume everyone has the best intention. And even if the best intentions just still assume everyone has the best intention and give them those opportunities to go change. Because, you know, the thing that I wonder from a long Stem perspective is, how are people going to learn?
BRITNI67:25A lot of stress, a lot of BDS are becoming more obsolete. How are we going to train our salespeople in the future? What is that going to look like? How are we treating our, you know, to the executives, if we're not teaching them what works, what doesn't, why this is wrong? You know, we have to use those things as teaching moments, because otherwise, how do people learn?
RACHAEL67:48Exactly.
BRITNI67:50Yeah. So it's, that's just something that I. That's just my philosophy. I've found
BRITNI67:55if I run that, my teams just run through walls with me, and I haven't always found it at my peer or executive level. So it's nice to have a team that leans in with me and.
BRITNI68:11That believes in that holistically, too. Because at the end of the day, being soft or being too hard is it just doesn't get us anymore fast at this point.
RACHAEL68:21Well, we're a little over time here. I just wanted to ask one more question. What is a good AI ecosystem look like to you, and what are the critical layers, tools and workflows?
BRITNI68:34Yeah, so a true autonomous revenue engine is you've got to make sure you've got your data layer. And a big piece of that is like, where is that data lake? Where is that data warehouse. Whatever that is, you've got to have all of that in one place that can be able to be, you know, all of the data can consistently go in and all of it can be analyzed coming out.
BRITNI69:00And so it's to me trying to keep this answer as concise as possible, knowing where over time is, you've got to have that base layer where the data lays. You've got to have the the governance and the ability to pull, you know, that data, whether that's like,
BRITNI69:25I won't give it, I won't give names, but you've got to have the data, got to have the governance, got that governance level. You also then have to have certain pieces, whether it's your CRM, whether it's your call recording, whether it's those type of things. To me, if you could have all of that in one place and I'm just talking like a sales perspective, that is would be the most efficient, infrastructure.
BRITNI69:57Now, how do we figure out what that is specifically? We the holistic we I don't know if we've all found with that perfect one is. But I think perfect is going to be different for every company and every vertical. And that's what makes it so complicated, because it's there's just so much out there to leverage. And it's changing every single day.
BRITNI70:20Yeah. So as a company you have to make sure that again. Can you answer your ICP? Can you answer what is it that you're really trying to solve, and how can you consolidate so that we're not overlapping software? Because it's so easy to do these days. So. Yeah. Yeah. So hard question to answer. Yeah. Great. One for any leader, especially in strategy or red ops to really think about,
BRITNI70:50and you know, what can you live with and what can you live without.
RACHAEL70:53Absolutely. Yeah. That was perfect. Thank you so much, Brittany. And thank you so much, everyone else for listening. And, Brittany, if people want to follow you and see what you're thinking, what you're what you're doing, where can they do that?
BRITNI71:04I am the only Brittany Borelli that's out there because my first name is very weird and the second is not terribly weird, but you can find me on Brittany really pretty much on any platform except TikTok. I have. I know young kids. I just can't do that.
RACHAEL71:21Fair enough. Yeah.
BRITNI71:22And everywhere else you can find me on Brittany. Brittany. Really?
RACHAEL71:26All right. And just for the people who are just listening in their car now, that's Britney. That's why it's different than most Brittany Spellings. And we'll also have the link to Brittany's LinkedIn and tech in the show notes as well. Thank you so much.
BRITNI71:40Yeah, thanks.
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