Originally posted on HighDrive.tv on March 20, 2018
The importance of analytics may be mostly understood today, but many operations don’t realize just how powerful it can be. Quantworks, a custom software development company, focuses on the creative—and thoughtful—implementation of analytics and big data. Volpe & Ghitelman believe it can be a gamechanger for any company.
Russ: Hi I’m Russ Capper and this is BusinessMakers USA, brought to you by Insperity, inspiring business performance. Checking in today once again from the Research Triangle, talking about Raleigh Durham, North Carolina, and I have the Co-founders of Quantworks with me Nick Ghitelman and Anthony Volpe. Guys, welcome to the show.
Anthony: Thanks for having us.
Nick: Thank you.
Russ: You bet. Well, tell us about Quantworks.
Anthony: Quantworks is a custom software development company. We specialize in software that requires or needs very strong analytics and big data competency. And we build this software for companies of all shapes and sizes, everywhere along the maturity curve, across a variety of industries.
Nick: I think the most important thing from my perspective is we’re a self-funded company, we’re 2 years in, team of 25 – an excellent team of 25. We wouldn’t be where we are without them so I want to add that.
Russ: Self-funded, growing to 25, that’s pretty cool; these days it is. But give us an example of a customer and what you do for them.
Anthony: A customer might be a large enterprise retailer for example. And what we would do for them is they have a very specific need around how do we more precisely manage our inventory. So the question is how do we not only create a model that can help them make some decisions about inventory one time the way a consulting company might or a data scientist is inclined to do; here is a model that solves a problem. We actually want to build the software around that model so that model can be tuned, updated, parameterized every single day across their entire inventory so this becomes automated and part of their everyday process. Our idea is not to just do a one-time ad-hock analysis but to transform the business through the use of analytics.
Nick: I think the idea of applied analytics is really the piece where we get on the soapbox and start to shout. Analytics did once, never productized, is a research project. We want to make sure that people are taking advantage of the data they have and taking advantage of the analytics that we build. And so how things get used is really important to us.
Russ: It makes sense to me but it seems to me it might be a challenge though to go up to somebody and convince them that they need it.
Anthony: Well it might have been 10, 15, 20 years ago. Some of us old-timers have been doing what we used to call quantitative methods, quantitative modeling; the fact that we have the word analytics and it’s known pretty much by everyone now – we watch sports, we’re into politics – analytics shows up in anything and everything we read. So I think there’s a great awareness of the power of analytics and what data can do. I think there’s still some misunderstanding about how to actually make it work for businesses large and small.
Russ: It seems to me that you might show up at some prospects and they’re actually doing it okay already, is that possible?
Anthony: Yeah, I think a lot of companies are doing okay with it. I think the question is how can you really make it a strategic differentiator in the marketplace that you’re in. I think there’s a real tension between do I hire data scientists into my organization, do I bring heavy-duty software that’s coming from the community – the third-party community. What balance do we strike across those different dimensions to make analytics happen?
Russ: Okay, so is it usually the CTO or CIO that finds you and says hey, come look at what we’re doing and see if you can help us?
Nick: I think at the enterprise level that it’s at that space. I think Anthony mentioned that there’s a spectrum of customers that we deal with, both early-stage and established companies and I think it depends on where they sit on that spectrum.
Anthony: So I think, as Nick mentioned, in enterprise more and more it’s the business stakeholders; it might be a brand president. It might be the owner of the supply chain or the Chief Marketing Officer that is now seeking analytics. I think 10 years ago it was the CIO, it was the CTO. But no longer because it’s the business P&L owners who recognize the value of analytics and they want it to impact their bottom line.
Russ: So where do you typically find that the data lives?
Nick: I think enterprises large and small have data all over the place. We were talking earlier about unstructured data that sits out in the web that you could tap into. There’s obviously the structured data that exists in your own data warehouse. And I think it’s the fusion of that data that to us is really the Holy Grail. When you begin to combine data into streams that are active and flowing you get results that you wouldn’t have 10 years ago, 5 years ago or if you’re simply focused on the structure data of your enterprise.
Russ: Are you actually maybe even using AI in the process?
Anthony: Yeah, AI – artificial intelligence – is a way that we use data. I mean we generally think of data as an ingredient. How we treat that data is a form of cooking. AI might be one technique or one method we have of cooking with a particular set of data. We hear terms these days like machine learning, AI, deep learning; these are all – they’ve gained traction recently. They’re not as new as many might think and yeah, of course we use that along with other methods.
Nick: I think to use the cooking – to extend that one step further – you could knead dough; people have been kneading dough for centuries. There’s a sand mixer, it can do it faster. You let it go unsupervised and you get a dough that no longer resembles the thing you need to actually make bread. So our view of it is it’s a tool if you have it, it can still be a recipe without it.
Russ: Do you find that after you come in and design the perfect system that there’s potentially extensive training required too after that?
Anthony: No. I think one of the biggest differentiators we have is that we understand how to bring analytics to people who don’t really want to use analytics. Early on in our career we were challenged with helping 22 year old graduates of fashion institutes get a hold of analytics and help them do their jobs better, make better decisions in the fashion industry and I think if you think about the challenge there, what we’ve learned is that analytics needs to be accessible to everyone, understandable by everyone and really that comes down to creative implementation. Nick mentioned earlier it’s about applied analytics and from our point of view there’s a lot of creativity and thoughtfulness that has to go into that.
Russ: So take us back to the beginning. What triggered the idea for you guys to come in and do this on your own without investors?
Nick: We met in a former life and worked together solving some awesome analytic problems for large companies. We both went our separate ways, I to the small end of the business spectrum and Anthony to the large end of that spectrum and we both saw opportunities that suggested maybe there’s a way to borrow from the large and borrow the scrappiness of the small and put something together that could benefit both and that is the DNA of what Quantworks is.
Anthony: We haven’t talked a lot about another type of customer that we serve. We mentioned that we serve both large and small but the startup customer is also very important to us. And what I mean by that is we’re bringing the products to market that small companies are out there marketing and selling. So you can imagine two or three physicians that are world leaders in a particular disease community, they have a lot of interesting data. We help build the software as a service so that physicians around the country or around the world can access that data, they can use the models.
Nick: Contribute their own data.
Anthony: Right, contribute their own data, but the point is those are entrepreneurial companies, those physicians in this example, we build the product for them that they take to market. And I think what we believe is what we’re learning working in that entrepreneurial sort of marketplace. Taking that type of hustle, agility, flexibility to the enterprise space is really, really compelling. We use words that in your show we use all the time, MVP. Take MVP to a large tier 1 company, a Fortune 100 company, they’ve never heard the term. So we’re doing things from the startup space with these large companies and they’re blown away. At the same time the credibility we have from working with Fortune 100 companies, globally recognized brands, that gives us credibility with our smaller partners, the startups.
Russ: Really cool, really cool. So what kind of people are they? Are they all developers, designers, coders, big math guys; what are they?
Anthony: It really takes a range of skillsets. We do have of course the traditional data scientist roles and backgrounds; those are the mathematician, statisticians. People brag about having chemists and physicists, anyone who’s quantitatively inclined. We’ve got that. But again, the secret sauce comes from creative use of those type of skills and models surrounding those people with thoughtful design of software. So we have a lot of computer engineers or software engineers. We also have thoughtful business analysts and again, we run this like a portfolio. As I mentioned we’re investing in these small startups. We think we have some of the skillsets a fund might need to have in order to recognize is this a good use of our time and our resources to partner with those physicians going back to that example. So it’s a wide range of skills.
Russ: So where would you like to see the company say 3 to 5 years from now?
Nick: 3 to 5 years from now Quantworks is still around doing what it’s doing. We’d love to see some of our early stage companies hit the next track of success.
Russ: Meaning your customers.
Nick: That’s right, that’s exactly right. That’s how we think about them and we’re partners with them so we want them to be successful.
Russ: Really good. Nick, Anthony, thanks a lot guys.
Nick: Thanks Russ.
Anthony: Thanks for your time, appreciate it.
Russ: You bet. And that wraps up my discussion with the Co-founders of Quantworks Nick Ghitelman and Anthony Volpe, and this is BusinessMakers USA.