We sat down with Max Feinberg, our Chief Technology Officer, and Micah Jackson, our senior software engineer to talk about why technology is important as we pave a path to understanding risk and quantifying culture.
Max, Micah, welcome! If you don't mind, tell me a little bit about your journey to Ledgestone.
Max: Yeah, so my backgrounds originally in aerospace and computer science. Most of my research focused around applying AI to helping robots see and move. I worked on a NASA program called Astra V, which is a free flying robot for the space station, an assistant to astronauts. I worked on that until it launched in 2017 Around that same time, I founded a commercial cleaning robot company. I did the whole Silicon Valley startup thing, raising money from venture capitalists and cleaned a bunch of offices in San Francisco and San Mateo and Oakland. That wasn't growing quite as fast as I wanted, so in parallel with that, I started doing consulting. Part of that was working with pharma companies. I worked on water projects, doing data analysis for water quality and algae blooms, across the entire United States. I had originally met Austin (Ledgestone’s CEO) in 2015. We got reconnected under the concept of trying to use alternative data to change the way that people think about risk. Insurance really is one of those industries that is stuck in the past. And it's using blunt instruments to deal with a problem in a very reactive way. Now we are working to take this fundamental issue of risk management and use data to come up with solutions.
Micah: My background is in math and statistics. I ended up going to grad school for stats, and had several projects across various industries. I worked with Toyota Racing to help them exactly look at the risk of taking pit stops. And when they should do that, or when they should not. After that, I joined a senior living community. Well, technically I didn't join the community, but I joined the company that ran a bunch of communities that were focused on memory care, specifically dementia, and worked on a few business homes there. We did research to try to quantify that their communities actually helped the seniors more than the competition. From there, I actually went into pharmaceutical consulting, where I ended up meeting Max. There I built a bunch of economic models for clients, as well as building web apps that they can host for various users.
Max eventually reached out to me to see if I would like to come aboard and work on building these products that actually help people and empower companies and stuff. And so I was definitely hooked after hearing that. And now here I am.
You mentioned the somewhat archaic nature of the risk management world and this tendency to be a little stuck in their ways. How do you see the role of the technological developments and the tools we're building and kind of shifting the industry mindset towards risk?
Max: The way that I think about it is sort of bifurcated into two primary segments. The first segment is process automation and it is somewhere that I think it is a lot easier to see results as they are objective. Many small agencies still do a ton of their work on paper. There is also a lot of work that is intensive data entry. Service teams do a lot of work that is very repetitive. Before I go further, I have to be careful because it is a touchy subject. When I worked on cleaning robots, I can't tell you how many cleaning people were scared and saying something like “Oh man, this machine is going to take my job.” But fundamentally that just isn't the reality.
I think it's hard for people to see that the primary purpose of process automation is to change the types of work that people do. One thing that I firmly believe is never going to go away is the human, relational component where you need people to manage relationships and navigate claims. There is no future that I see where that goes away. But the monotony of filling out 130 fields for a document and emailing it to someone, or transcribing some information over the phone and copying it into four different systems can be automated. We really want to make it so that all human effort is truly valuable and meaningful instead of relatively meaningless monotonous tasks.
To summarize, the first role technology can play in this industry is automation, not to replace humans, but to allow them to focus on their highest output tasks that can really drive value for their team?
Max: Exactly. The things that are of highest value, more meaningful, and drive the things that really matter.
Micah: Process automation can take a four hour process and turn it into 30 seconds. Or you could take something that could take a full time employee the entire week and cut it down into less than five minutes. It saves money, it saves time, it saves energy, like personal energy and motivation that we can use for, as I said, higher value targets or higher value tasks
So what is the second part of tech’s role in the future?
Max: The second role technology and data will play for us is a little bit squishier.
We're trying to collect all this data on essentially human relationships and behavior. That's really what culture is. This data will help us understand and try to use that to understand problems within a company and how those things connect, and try to provide insights. It starts by collecting and visualizing data on topics that many business leaders just don’t think about.
If you would have asked me three or four years ago what I thought about culture, I could tell you that every single like successful entrepreneur says, oh, culture is so important, I can literally imagine Brian Chesky, the CEO of Airbnb, talking about how good Airbnb is, how culture is the most important thing, and brought them all this success. But honestly, I didn't believe it. I thought that's something that you can say, when you have all that money, and everything's successful. But even in smaller organizations and startups, I think culture really is important, because it impacts how people feel and believe as they work.
Culture can be a bit of a nebulous term, how would you define it?
Micah: In a sense culture is the aggregate of all of your employees and all of your company's interactions. And you hope that each of these interactions are moving the ship in a positive direction. Now how you define positive can vary. Whether that is helping people, if it's making money, or whatever your mission is, the goal is to have a culture that drives toward that missional goal.
Max: I think if I had to succinctly define it, I would say that company culture is how the people within an organization communicate with one another, as well as how they think and feel about the organization and its goals.
Do companies care about culture?
Max: I would say that the thing that makes me believe in it the most is all the conversations that I've been a part of with one of our clients or prospective clients. This message of organizational health and trying to tackle these problems within culture, really resonates. It is truly endemic in that it touches every single industry. We go into these meetings and there are times where people bring this huge binder of their insurance stuff. But people don't have problems with their insurance, people have problems with their culture like employee retention or safety. And because we're able to meet these people where they're at and present ideas that people have never really thought about before. This idea really engages business owners and I think it will be really transformative.
Machine learning and artificial intelligence impact some of these projects and sometimes people have some misconceptions about what ML and AI really do. Could you give us a basic explanation of their role in all this?
Max: I think the best way to put this is that with traditional programming, what you're doing is you're trying to encode some algorithm. When I say algorithm, a lot of people shut down. But an algorithm is just a sequence of steps, right? For example, the steps that you take to make a peanut butter jelly sandwich would be an algorithm. Traditional programming takes some algorithm and encodes it in a computer and computers are really fast at doing certain things. Because of that you can make tedious tasks like we mentioned before much more efficient and fast.
When you look at artificial intelligence and machine learning, a lot of people really just draw from movies when they think about it. But at its core programming is a person telling a computer instructions that it follows. Machine learning is allowing a computer to learn its own rules based on data. So instead of us telling a computer exactly what to do it tries to figure it out by looking at the data.
The reason that is so important to this space is because there's a lot of times where human biases come into play. I'm not even talking about intentional bias. I'm talking about completely unintentional things where people design a system with good intent, but the context of their lived experience and the lens that they see the world informs how things work. This manifests in lots of areas that can be impactful on people's lives like credit scores or deciding who gets a loan,
But as you begin moving towards decision making that's based on data, instead of human intuition, there's a lot less subjectivity in it. And I think that that is the foundation for more fair and equitable systems. And that's why I think AI is important, because when you look at things like insurance you are considering risks? And oftentimes, companies that look like low risks are actually high risks, and they've just gotten lucky due to the biases built into the scoring. Data allows us to have a more objective lens.
Fairness is an important foundation for healthy companies and communities. To close us out, what is something you guys are excited about that is coming down the Ledgestone tech pipeline?
Max: I'm excited to have users actually start getting to use these awesome process automation tools that we have built, and the upcoming cultural tool as well.
Micah: I'm kind of in that same boat, right. We have built an awesome tool and now we just need people to share that goodness with. I think it's also exciting that we're branching out this cultural impact into several different industries now. That growth in itself is fun and exciting.
Not too many people have even tried to quantify culture, and I am excited to build more tools that can take cultural data and really help companies across different industries.
Well thanks for your time guys, we are excited to see what the future of tech, culture, and risk management looks like!
Max & Micah: Anytime!