#096 ForceMetrics | Go Head First Into the Bad

Speaker A: Police officers dispatchers are making life and death decisions with less data than your Uber driver.

Speaker B: Welcome to the Mid Stage Startup Momentum um, podcast. Each week we interview up and coming founders of some of the fastest growing mid stage startups across the world. Your host is Roland Siebelink, who will share some of his own experience helping startups scale from 10 to 1,000 people in a few years. Here is Roland,

Speaker C: and welcome to the Midstage Startup Momentum podcast. My name is Roland Sibelink and I'm a coach and ally for many of the fastest growing startups in the whole world. And today we are very honored to have with us a former FBI agent. It is Andre McGregor, who is the founder and CEO of Force Metrics. Hello, Andrej. How are you?

Speaker A: I'm, um, good. Thanks for having me.

Speaker C: And did I get that right, you're a former FBI agent? Because I do not want to get in trouble with the authorities.

Speaker A: I a.m. a former FBI special agent. Yes.

Speaker C: A special agent even. Wow. I've never had a special agent on the podcast before. So that is a first today. But we're not here to talk about the FBI, or at least not, uh, directly. Right. Uh, we are talking here about Forcemetrics, your startup. So, Andrej, first question is always, uh, what is Forcemetrics doing? What are you bringing to the world that is of value to folks? And how are you making the world a better place?

Speaker A: ForceMetrics is, uh, a precision policing platform. Essentially, we sit on top of large data sets of public safety systems. So think your 911 dispatch systems, police reports, jail reports, traffic tickets, body cam videos. Police departments collect a lot of information and it's just oftentimes ineffective for them to get it from multiple systems. So we're a data integration, but really when you think about it, we're kind of like Google Meets Zillow for public safety data. So the idea there is, at the end of the day, an officer is trying to figure out a lot of questions in a short amount of time. Are you going to kill me? Are you going to kill someone else? Are you going to kill yourself? And then why am I here? What are the issues that you're dealing with? Domestic violence, PTSD from the military, autism, dementia, and doing it with a positive outcome at the end. We synthesize all that information into a very easy to, uh, format smartphone app and it's accessible to thousands of officers daily.

Speaker C: Excellent. Okay, so if, uh, a shooter is targeting the police officer, they just pull out their smartphone and they look at the analysis that you guys provide is that how I should imagine it?

Speaker A: You can if this is television and NCIS and CSI, but in reality you're going to call 911 and someone that you've never met before is going to uh, uh, you know, pick up the phone and ask you some questions. And honestly, calling 911 is a very scary moment for most people outside of actively giving birth. It's usually the worst moment of someone's life when they're calling that number. And so you're panicking, you're speaking loudly, you're speaking quickly. Um, you may not tell me where you are. So there's a lot of information that the dispatcher is trying to get. That's the first point. Then we're going to send someone there to actually deal with whatever you're going through. And they've never met you either. What are they going into, what previously happened there. So when you think about public safety, I like to do it in percentages. 90% of it is administrative boredom and 10% is sheer terror.

Speaker C: That is actually probably very similar to the startup founder's life, right? Uh, 90%, maybe not boredom, but at least like all the, all the bad things that happen to you or the times you want to give up and then the 10% of elation and big breakthroughs that you may experience. How has that been so far? How long have you been a founder by now? How long ago was it that you left the special, uh, Special Forces?

Speaker A: Um, it's been four years so far. M. I transitioned from being a gun toting special, uh, agent to uh, going back into Silicon Valley. I was at Brown University after graduating Goldman Sachs and Cardinal Health and then became an FBI agent, uh, but always wanted to go back to my engineering roots. And so you know, I, I turned the badge and gun, um, decided to go to Silicon Valley building cybersecurity Software. And then 2020, 2021 was tough years for everyone. My Academy classmate was shot and killed in a routine search warrant.

Speaker C: Oh no.

Speaker A: And we later found out that there was information that the guy that killed him and his partner Laura wanted uh, to kill law enforcement in a blaze of glory. But it was lost in a paragraph in a report of a bunch of reports that would never surface, quite frankly.

Speaker C: Oh no.

Speaker A: So through that trauma and a lot of tears, it was, how can we bring context in a very quick but accurate way to the people that are answering the emergencies of all the communities and so forth. Metrics really spawned out of the ability for me to combine not only my engineering abilities, my understanding of data and Databases, but then also having arrested people, having used force, knowing what it's like to arrest someone and how to investigate a crime and then doing it in a modern platform like an Apple iPhone.

Speaker C: And not the least also that personal trauma that you went through, uh, and uh, understanding the real impact you can make on the world, if only that data would be better available, I guess, right.

Speaker A: You have to think about it, that, you know, police officers, dispatchers are making life and death decisions with less data than your Uber driver. And that's unacceptable. Right? We need to be providing that information, you know, in droves in a way that's easy to understand while they're driving to that call, while they're interacting with someone. And you know, AI is a, uh, big component to a lot of this because it's streamlining and making it easy to digest that information. But the whole idea for me is I just want to take what I learned from chasing cyber criminals in the FBI to now chase inefficiencies in public safety. And you know, we're, we're in 35 cities and counties in 12 states. We continue to grow and we're, you know, saving lives every day.

Speaker C: As I mentioned to you, uh, Andre, in the, in the conversation before we started the recording, we are typically in the business of hunting for breakthroughs for startups. So I guess you just described the first breakthrough, that insight that got you going on the app. Right. Did that take you a long time to decide to go there? And what, what really spurred you to take this step as opposed to just

Speaker A: thinking about it starting, starting a company, especially for the first time. I'm a very risk averse person and you know, to get investment money, uh, it's all about de risking. And so, you know, we had to identify that there is a problem worth solving. Which I think at that time everyone understood that public safety, you know, concerns were high in communities. There were communities that were on fire because of protests. There were, you know, concerns around just safety in general. And so that, that was easy identifying the problem, but, but solutioning was a little bit harder because you have to be right all the time, you know, so we are very focused on getting it right the first time. So it took about two, two and a half years before we actually deployed our application. We want to make sure the application worked first and worked consistently.

Speaker C: Um, and uh, how would you figure out whether you were on the right track during all that time? Because two and a half years is a very long time to keep developing. Um, I'm sure that that was not after, after two and a half years that you first exposed it to potential customers?

Speaker A: No, we actually. Good question. Um, our first exposure was putting engineers in cop cars around the country doing ride alongs and saying, go pull people over, go sit in a dispatch center, actually go into a domestic violence call and understand not only what the technologies they use today, what are the information points that they need, but also what's the perspective of not only the officer, but the victim and the offender. And so now you can start to understand those pieces. And so think of it like agile development on steroids that were constantly sort of like building the app and then getting into a cop car, testing it out, rebuilding the app off feedback, getting back in a cop car, trying it out. And then over time it's like, okay, it's ready for prime time, let's give it to a couple of departments to use. And we have um, you know, three departments that, that were our first beta users. And then from there it's just been significant growth.

Speaker C: So those are really like design partners in a way, like those, those FBI police departments. Whichever services you worked with. Right. How did you persuade them to even try this out while it was in such an early stage?

Speaker A: I, I, I ended up going to a conference for evidence based policing. So you end up getting a lot of data, uh, conscious data minded researchers, analysts and even police chiefs. And there were a couple police chiefs that spoke about research projects that they had done within their department. And at the end they said, hey, we're open to ideas or anyone that wants to reach out and see how we can work together. And I just cold called these police chiefs and said hey, I just watched your presentation and would love to talk about this idea. And they said, well why don't you get on a plane and fly out here and learn about our department. And the rest is history because they opened their department to us, opened the SWAT team, the K9 unit, the mental health co responders, the dispatch center. And when you start to look uh, at the onion that is public safety. It touches most of society, right? You gotta touch in the parks, in the schools and the hospitals. The uh, police department knows what's happening in a community probably better than you because they're information, uh, coming in. And so we started to be able to paint a picture of not only safety but, you know, ways that they can be more efficient. And I think that's when we started to realize the ROI aha moment was data. We have a lot of police departments that understand now that data is important. They don't necessarily know where to apply it all the time. So some departments can do some back of the napkin math and say, okay, I have, you know, I can pay X amount of money for two crime analysts, which would be limited to these particular functions. But, uh, with this application, for the same amount of money, I can make all of my officers and employees analysts, or I can up level my analysts to be data scientists because they don't have to do mundane data projects anymore. You have some people that are like that. On the other, when you start to think about the efficiencies we gain, we have some agencies that, uh, have reduced their time on domestic violence calls by 15 to 30 minutes.

Speaker C: Okay, wow.

Speaker A: Back and forth to their car, having information immediately available in their hands. And we have some departments that have reduced their time using their traditional research tools by an hour to an hour and a half per officer per shift. Those are full time employee hours that you're giving back to the community, especially at a time when you can't hire enough police, uh, officers.

Speaker C: Talking back a little bit about your founder journey, like, what would you say has been the one moment that's felt most like a breakthrough in your startup journey?

Speaker A: Some people joke and say I'm the investor whisperer, but being able to actually understand how to communicate to a, uh, prospective investor and to your current investors. Right. As a new founder, I remember my first dozen pitches and they were awful in comparison to what they are now. But I didn't really understand all the pieces of what they have to evaluate me on in terms of determining if this is a reasonable investment that can return the right amount of equity back to their LPs, I had no idea about this stuff. So being able to sort of like understand how an investor works and then being able to dissect that in a way to say, what's the story of my business and how we're going to make it not only a very impactful social business that save lives, but, but also return, um, the investment back to the LPs in a way that is meaningful. Was sort of that leap that I took.

Speaker C: Um, you know, as you were struggling with that, uh, was it more a question of like, this investor asked me about pricing, so now I have a pricing slide. And then the next investor asked you about tam and then you added a TAM slide, or was it more like just keep going and after 10, 15, 20 pitches you're like, okay, got to rework the whole thing now.

Speaker A: Good question. I would say in the process we started having just general conversations, which I think was not the right pathway because people want to be helpful, which I appreciate. And they're like, here, I'll make an introduction to this vc. And you realize that, oh, wait, I wasn't ready for that vc. And they're at maybe a different level than where I should start. So sometimes it's better to, I don't want to say start, um, with uh, not your top VCs or, but essentially identify the VCs for which you're, you're hoping to have good traction. But if they say no, you're not going to be absolutely devastated. And so, you know, at the conversations with some of the VCs that were able to come back and give advice, like, hey, great idea, but I don't understand this, I don't understand that, I don't understand these different pieces. And so taking notes and then to your point, I added a slide. Now, okay, like explain the TAM a little bit better. Let me explain how we're going to reach product market fit. Let me explain how we're going to, you know, have world domination. That's the other term that they like to use. Exactly, yeah. Uh, and world domination, um, we're on

Speaker C: path to both going back to the breakthroughs like this and other breakthroughs you may have experienced in Force Metrics. How has that over time changed your understanding of the role that you have as a founder and what the company needs most from you?

Speaker A: Yeah, I would say my journey has definitely gone from being a founder to a CEO in many ways. Because as a founder you're in the middle of everything. You're doing a lot of stuff. You're the cheerleader, uh, and the first person to pick up a broom. Um, and then you start to add more team members and more team members. And as a, as a result, you know, we're, you know, 40, 40 person company now. We have, you know, dedicated teams and leaders in those roles. And so I'd probably say, you know, 30, 30% of my time is investor relations and having conversations not only with my existing but with prospective investors. Uh, another 30% is with customers, both current and future customers, because, you know, they still want to see me or they still want to know that they're attached to me as the CEO, uh, of the company. If they have questions or an idea that I want to. I've learned to be like a lawyer where I probably say no more than yes. Because if you say yes too many times, then in this industry we're trying to build a car, but they've asked for so many requirements that It's a, uh, 7:47.

Speaker C: Yeah, exactly.

Speaker A: We were just driving a car. But yeah, but add this and that's. We definitely are, uh, the one with

Speaker C: the ultimate decision power. Right. So, uh, that's what I think many founders learn. Like, never ever be the one in the room that is forced to say yes when there's no higher authority that can veto you.

Speaker A: Right, which is why my sales team has all forbidden me of giving, pricing out, and a variety of stuff I'm not doing anymore. You know, I used to say things that are like, don't say that, don't say that. So, no, same, uh, on the product side, when I was the last word,

Speaker C: when I was at Rocket Fuel, uh, one of the three scale ups I went through that grew from ten to a thousand in three years. They had a president and a head of product who were both excellent at pre selling what wasn't there yet. And they definitely learned very quickly never to have both in the same room with a customer because then they started bidding against each other, and before you know it, like, they would cut out of the meeting. Like, I think we closed it, but

Speaker A: what the hell did we sell? So the nice thing is that we do take a different approach of under promise and over deliver. You know, we want to make sure that, like, hey, once you get it, it like, works and works much better than you thought it was ever going to be. Um, but then also when we do get a customer that has a good idea, like I'll give you an example. You know, we had a customer that said, hey, we want to incorporate license plate reader data, and we want it to be searchable and force metrics. So my response was, do you want millions of data points just to, uh, be available in a search result? And they're like, well, no, like, what we're looking for is when we, when we have a license plate reader in our city, we'll get 3,000 hits a day. But we can't go after 3,000 cars. We want to find the ones that are the most violent or the ones that are the most concerning. And, uh, we need to cross reference that with the data that you have to see what that is. I'm like, well, that's a different story. You want an integration that later that tells you like a green, yellow, red. Okay, let me give you a product manager to sit with. Exactly right? So I don't say, yes. I say, tell me more.

Speaker C: And very good life lesson in general, I would say, right, yes. And maybe, uh, talking about life lessons. So from what you all the stuff you've learned in the last four years, in particular as a founder, what is if you had to distill like a principle or a lesson from that experience, something that other founders could also apply, what would that be? Andre?

Speaker A: Say, don't overcomplicate things.

Speaker C: Uh, what? But we're founders, we're engineers. Like, come on, that's all we like doing, right?

Speaker A: I mean, I'm sure everyone says that, but it's like, it's so easy to overcomplicate things or overthink. And I think at the end of the day, to your point, in terms of, you know, was it, you know, two and a half years before you actually had any people using it? No. Like, you know, it's like, how fast can I get something out the door and start metrics and testing it out and iterating and changing, but also doing that at the people level, right? Like, you know, you're, you're managing risk. There's people risk as well as there's technology and economic risks, right? And so, you know, break it down to the simple principles because usually it can fit in those buckets and then, you know, make a decision, but oftentimes you'll, there's paralysis with, with indecision or paralysis with complexity.

Speaker C: And uh, and I actually like, like to apply that to startups themselves as well, because what you just said is like, in a way, reduce complexity rather than add to complexity. Right? Simplify things for, for the folks that are working for you, for example. And I also found in working with startups that just one of the levers we pull most often and it helps them the most, is just variable reduction. How do we actually take all this complex thinking into, like, well, what matters most and what do we need to decide on right now? All the rest. And Reid Hoffman's words are fires we can let burn. Right?

Speaker A: Although in law enforcement, maybe that's the

Speaker C: wrong analogy to use.

Speaker A: Well, it's funny because we'll get a lot of, uh, agencies and departments that will say, well, can you add this data set? Add this data set and add this data set. And I say, so who's going to use this? Because now you've added all these different variables. Uh, who's going to be able to understand what they all mean and be able to sift through it? And so they're like, well, you're right, yeah, like you're making it for one person, and that one person is going to leave you at some point and then you're going to wonder why you have this thing that sounded great. Again, the 747 that you wanted to be a car and now you have a. You don't know where to park your 747.

Speaker C: But it's so common in tech companies, especially those with more enterprise, uh, focus. Right. That when you get too dependent on one customer, uh, you start adding all the bells and whistles and before you know it, you don't really have a product anymore, but a custom solution. Right.

Speaker A: Um, that and not all customer feedback should be included. Meaning. And I'm a big, uh, proponent of Ray Dalio and Bridgewater Associates and the principals and a, uh, principal earned the right to have an opinion. Like I can have an opinion on cybersecurity, on law enforcement, on technology. I don't have one. On, you know, trains and a variety of things like that. Right. I haven't earned the right to have an opinion. So early off we had like one agency where we had one officer that said, you know, it'd be nice that in your app with the phone number when you show it for a person that if I click it, I can call it. And I'm like, well, that makes sense. Right? Because you want to. You're finding a person and then the number of other officers that came back and said, that's a bad idea. I don't want to call my subject, I don't want to call this one person. Great idea. The rest of the people, we had to get rid of it.

Speaker C: When you're too much in the weeds as a founder, it's so hard to get out of the complexity. Right. Do you have tips for people? Like how do you keep that perspective, to keep things simple and simple in the eyes of the customer, not only your own eyes.

Speaker A: Yeah. It's interesting because one of the things that we'll do with our application is when we go to a new agency and the way that we sort uh, of. We're fast and we're easy not only on the UI UX side, but also on the implementation side. We have a very small data engineering team. We can get an agency going in hours and days versus like also very fast. And we're ingesting tens of millions of records from a lot of these agencies when we do it. But then when we do early user, uh, adoption, we will go to agencies and we'll say, give us your saltiest officer that is gonna hate whatever. Like we want that person. Why? Because he's gonna give us feedback immediately. Uh, and then either we're going to iterate and change on it to make sure it works, or we're going to learn the culture that we need to work towards and then we're going to win them over. So for us, go head first into the bad. I'm not saying this person's bad. I'm just saying that they're going to be the detractor or the naysayer. But when you do that, you actually see a lot very quickly. You're not waiting months and months for something to surface. They're telling you on day one, like, hey, you got to change this or this ain't gonna work.

Speaker C: Okay, so, uh, Andre, like, how big could this become? You're Talking about about 40 people on your team right now. You know, uh, don't need to share revenue numbers, but how much bigger can this be? How much, how much, uh, how much could your team grow? Like, how much of an impact do you actually want to have with force metrics over long term? Long run.

Speaker A: I mean, in the long run, uh, every police agency, every fire, ems, you know, animal control needs to have this data at their fingertips. So for me, getting it into the, you know, um, 16,000 law enforcement agencies in the U.S. the additional law enforcement agencies in other countries is where my focus is compared to like, roughly how

Speaker C: many you have now, if I may ask.

Speaker A: Uh, Cool, Cool.

Speaker C: So good enough to not be dependent on one of them. Right?

Speaker A: So, well, and, and we've only been selling for about a year.

Speaker C: Pretty good, right?

Speaker A: So. So, you know, as we kind of like continue to grow, it's, you know, we're gonna, we're gonna see those numbers. But for us, like, you know, the team's gotta grow. And, and the interesting thing is our, our engineering team is, is slim and lean. And right now our priority product because as we need to go out in the field and actually build some of this stuff and get requirements, um, our go to market and m. And, and um, customer success side. Because we have to always be good to our customer. Because if we're good to our customer, then they tell their neighboring agency and then. Right, so you can't sit on your hands or sit on your laurels and say, okay, we're fine. Like, no, we have to actually be out there in the field with them. Be in the cop car with them, um, be. Sit in the dispatch center, bring the donuts. They do eat donuts. That's not a myth. Then, yeah, they get mad. They get mad because they're always on a diet. But like, they'll eat the donuts.

Speaker C: Last question. What's the breakthrough you're chasing the most right now, something that's just out of reach but that you're determined to crack.

Speaker A: I would probably say how best to leverage, you know, an audio AI assistant in all of the data that we're collecting and really being able to do in a way to, to get right back to the beginning statement, uh, that you said in the podcast, which is, so I'm going to be out with a subject and I'm going to pull out my smartphone and I go, well, no, you're not. I want to be able to just have something that I can speak to that's actually, you know, digesting that. Ah, what my ask and then spitting out what it expects that I need.

Speaker C: Almost like they now have.

Speaker A: And that means your earphone, where they

Speaker C: could talk to central, but instead they would just talk to their phone, for example.

Speaker A: Yeah, they're talking to talking.

Speaker C: Excellent. Okay. Very cool. I love that vision. Uh, very cool. Well, we are out of time, so. Andre McGregor, founder and CEO of Force Metrics. Really loved having you on the podcast. Really engaging conversation and I learned a lot about, uh, law enforcement and how tech can help them.

Speaker A: Yeah, thank you for having me. It was a great conversation and hope, looking forward to coming back and letting you know where, after the last question

Speaker C: is if any Ford law enforcement department is happening to be listening or anyone wants to get in touch, where do they go? What do they download? Other than just asking me for an intro, which I'm happy to provide as well.

Speaker A: Of course, uh, they can go to forcemetrics.com um, they can also email me@andreorcemetrics.com and we'll definitely get, uh, them the right resources or get them connected with a peer in their, you know, in an agency to answer their questions.

Speaker C: Thanks again, Andre McGregor, for being on the Midstage Startup Momentum podcast. And for our listeners, we will have a new episode next week, so stay tuned, everyone.

Speaker B: Like what you heard? Subscribe to this podcast and leave a review. Tune in next time for more hot startups and interviews with some of the highest momentum startup founders in tech today.