Let’s go technical! It may be a higher value to build your analytic software solution than it is to buy from an enterprise software vendor. Dhruv has been designing and building software for over fifteen years, and has worked with a variety of organizations across the public and private sectors (B.C. Government, Yukon Government, Change.org, Apple). In 2016, he founded Real Folk to help build the next generation of digital services across government and industry in North America.
Let’s dive into part 1 of 2 of our conversation with Dhruv about buying vs. building software, where we’ll look at the evolution of software and our interactions with it.
[00:01 – 05:23] Opening Segment
[05:24 – 14:36] Analytic Applications: What Changed
End of Part 1
Connect with Dhruv:
Connect with Dino:
Announcer:
Here’s an experiment for you. Take passionate experts in human resource technology. Invite cross industry experts from inside and outside HR. Mix in what’s happening in people analytics today. Give them the technology to connect, hit record, pour their discussions into a beaker, mix thoroughly. And voila, you get the HR data labs Podcast, where we explore the impact of data and analytics to your business. We may get passionate and even irreverent, but count on each episode challenging and enhancing your understanding of the way people data can be used to solve real world problems. Now, here’s your host, David Turetsky.
Dino Zincarini:
Thanks for listening. As a reminder, this was part one of two in my conversation with Dr. Dang. Please come back and download the second part to hear the full podcast. Hi, everyone. Welcome to the next episode of the HR data labs podcast. This is Dino Zincarini, I’m filling in for David today because he’s off doing adventurous exciting things. But we’re gonna have some adventure as well. I’m really excited to be talking to my friend today Dhruv Dang, who I will admit I met at a dog park, our dogs became friends before we did. But we have since bonded and have very interesting conversations at the park. And this was one of them. So I think we’d like to share it with all of you welcome Dhruv to the podcast.
Dhruv Dang:
Thanks for having me, Dino.
Dino Zincarini:
Awesome. And what we’re going to do today is maybe go a little bit more technical than we have in the past, we’re going to be talking about building versus buying software. And in particular, we’re going to be focusing on the building side of things Dhruv has a company he founded his own company to do custom software development has been very successful at it for several years now. So Dhruv, why don’t you tell us a little bit about what you do and your company? Sure.
Dhruv Dang:
So my company Real Folk has been building custom software for about five years now. And we work primarily with the government of British Columbia. And the government of BC for those that aren’t aware is pretty notorious for buying enterprise software. And it’d be doing that for 20 years. So when we came in and started working with them, building them custom tools, I think it reshaped the discussion for them. And we’ve learned a lot in the process. Our approach to software is a little bit different from what you might find in the industry. It’s about building things that are sustainable, and solve problems in a meaningful way that can adapt to change. So I’m looking forward to chatting with you about it today. Dino
Dino Zincarini:
You’ve already used some words that I didn’t usually use in the context of software like meaningful and adoption and, you know, full transparency here I’ve worked my whole career pretty much on the enterprise software side of things, which means the the buy side of the market. So for me when we first started talking about the idea that maybe building software is a viable option, building custom software, especially for analytic solutions is a viable option. I was a naysayer, and I probably going to be a bit of a naysayer, while we talk today for the sake of playing the devil’s advocate. But you’ve definitely shifted my thinking. So I think we want to share that today with the group. But before we get into that we have a tradition on the podcast, which is I have to ask you some awkward question that is that is special and different about you. So what’s something you can tell us that most people don’t know about you that you would like to share on the podcast today? Oh,
Dhruv Dang:
I probably don’t have any interesting things. I’m probably the only person in the world that doesn’t have a fun thing to share.
Dino Zincarini:
Everybody says that practically. So I’m gonna say you may have heard a slightly weird accent from Dhruv. But that’s because he has a slightly weird background. No, I’m kidding. He actually is Australian, but then went to Singapore for a while and then moved to Canada. And now his accent is all diluted and weird. So he has a really cool background, when we’re not talking about technology and dogs. we’re usually talking about food because he’s lived in some pretty great foodie places like Singapore. I don’t know if anybody has been to Singapore. But I don’t think there’s been a place in the world I’ve been to that had better food than that place.
Dhruv Dang:
So you know, it’s funny that you mentioned that you’ve inspired me and reminded me of something that might be a little unique. And how I actually got that strange accent was I was visiting family in Texas, and grew up in Australia, but I’d never had Wendy’s and I was really excited to try Wendy’s. So I went to order a burger. And you know, I just gave the number because people are having a tough time understanding me then and I asked for some tomato sauce, which is how you say ketchup in Australian. And I remember getting the most confused dumbfounded look at what I was saying. And it was at that moment where my accent started to change into what it is today.
Dino Zincarini:
Oh my gosh. Yeah. See, there you go. He said you didn’t have a good story you just did. Yeah, somebody’s asking for tomato sauce, wood. I don’t even know what I would do. That’s just weird, but good. you’ve adapted you’ve, you know, ketchup is a is a food group here in Canada in the US. So I’m glad that you figure that one out. Let’s get into the topic beyond just condiments here, we want to talk about analytic applications. And the story for the last while but a lot while I mean, the last 20, or 25 years since I’ve started working in this industry has been that you go out and you buy a tool, right? You want to do analytics, finding an analytic vendor, you buy that thing, they all do roughly the same thing. They do it in slightly different ways, or some features here and there. There’s definitely differences in the technology stack. But fundamentally, they all do the same thing. And I don’t think there’s really been any serious questioning of that process of going out and finding a vendor and buying the technology. Certainly, since I’ve started working. In the early 90s, there was a bit of custom development work, but usually ended up being super expensive, took a long time, you had to hire these big consulting firms to do it, because it was nobody in your company who knew how to do this stuff. And then by the time you got it, it was usually out of date. So what’s changed over the last, especially the last 10 years, and we’ve seen emergence of cloud technology with change in the technology landscape that may have balanced the scales a bit here between buying and building?
Dhruv Dang:
It’s a really great question, you know, and I’d like to start by just saying that software as an industry is really young, you know, we’ve only been around for a short amount of time. And if we compare software to let’s say, carpentry, which has been around for 1000s, of years, and probably has some really ancient stories about how it was founded, software has been around for maybe 40 years in an enterprise context. And what that means is that we’re learning a lot as a community, and we’re changing quite rapidly. And we’ve all seen this happen. And in the last 10 years, we have seen an incredible change in many areas. And one of that is software literacy. So everyone who has technical and non technical is now a lot more comfortable with using software and computers, there was a time where there was a desktop computer in a household, and that was the only place to use software. And only maybe the kids in the house would use it, you know, the grown ups wouldn’t, you’d have to use a dial up internet connection, and no one would be able to make phone calls. It was a whole affair. But nowadays, you know, we all have iPhones smartwatches we have access to software in such a meaningful way. And and that’s that’s had a huge impact. It means that people when they choose to build or buy software, are speculating less they have once and needs when they want to go ahead and build something. And it’s not about what I might need. It’s about Oh, actually want to solve this problem. Now, it’s not true for everyone. We’re still young, and we’re still growing and changing. I would say that is probably the biggest change that we’ve seen. That’s a great point. First of all,
Dino Zincarini:
I suddenly feel young. I mean, yeah, the way you put it was, it’s obvious. Now, of course, I’m just young in my industry, because it’s not 1000s of years old. But I think that was a great point. Like when I started out in school, you know, computers were this exotic thing. You know, this was the 80s. There’s not like it was the Stone Age, but it was an it was an exotic thing. It was an elective. If you wanted to get into it, you can get into it. Now, I think every kid who’s coming through at least in kindergarten, they’re already using technology. By the time they’re in grade school, they’re probably doing some basic work in encoding. So you’re right, like the skill set here, we lose perspective, I think the carpentry example is great, there is no comparison here, the skill sets that have been emerging and changing, the pace of change is remarkable. So you’re right, the average person coming out of school, every generation every year probably has a better skill set than the year before.
Dhruv Dang:
Exactly. An interesting side effect from that is this idea of expression. And you often hear that word a lot in for people who design programming languages. But it’s actually quite a useful word to use, describe how people interact with software. And we can think of buying software as a way to purchase a tool for you to express what you want to do in your business. So for example, if you want to understand the way HR works in your company, or what employees are doing, or why they’re leaving, or where they’re switching jobs, right, you are using some kind of tool to express a way to understand that question. In software, we use this word quite a lot, because writing code is an act of expression. It’s expressing what you want the computer to do. And what’s happened as people have gotten more aware of software and more comfortable with it is that these tools that you buy are becoming more and more complex. Because the needs to express complex requirements. Are there things like no code tools are effectively ways of writing code without actually writing the code.
Dino Zincarini:
You’re right. This is interesting, because I don’t usually think that layer below, right I’m, I’m interacting with the software. And that’s all I’m thinking about, right? Where is that feature? I need what menu is it under? And how do I do this thing? I’m not really thinking about how the idea came to be and how that was materialized how to get out of somebody’s head and turn into this application. But that hadn’t happened. And there’s a there’s a difference between the people who build the software, the people People who build the software to build the software, right? They thought of these expressions that can be used. And every year, this gets more sophisticated, and that set of expressions gets more developed. So even the tool set becomes richer, deeper and more expressive to use your word that we didn’t have even like a couple years ago. So that’s a great point.
Dhruv Dang:
Exactly. Exactly.
Dino Zincarini:
And, you know, I think you mentioned to me before, too, that, you know, competition as well is, is a dimension here, right? As soon as you innovate, and you do something you think, is pretty special. Within a year or two, everybody else is doing it. Right.
Dhruv Dang:
Exactly. And, you know, I think this is also reflected by the enterprise software industry, if you put yourself in the shoes of a large tech company, you know, they’ve, they’ve got to build enterprise software to sell to companies like yours, they’ve actually got to sort of do their own research and speculate what problems they’re trying to solve. So when it comes time to buying and using that software, you have this choice between these different ways to solve your problems. But if a bunch of different companies are using that same tool, they’re all solving the problem in the same way. And that just makes competition a lot harder, because everyone is equipped in the same manner. And the idea behind this is that companies that build software that you buy, are solving universal problems, problems that affect everyone, because that’s the incentive of that business is that if I can get this software in more hands, get more people to use it, the more money I’m going to make. Whereas with custom software, it’s completely different. It’s a lot more flexible, and less rigid. So you’re solving problems that are unique to you. So for example, if you have a very unique business where you’re trying to compete in an extremely competitive market, let’s say it’s a perfectly competitive market, but you do some research, and you build some IP, and you want to sell it, it’s very likely that there’s no existing software out there to help you do your job better, is a very high chance that you’re gonna have to find something special to company.
Dino Zincarini:
Yeah, I mean, I’ll admit some guilt here. As a product manager, when we talk about things like addressable market, that is the total set of customers that might be able to buy what it is you’re making, that is actually a process of homogenization, I’m trying to build something that is generic enough that it will appeal to a large enough community while balancing that with delivering something that might deliver a competitive advantage. And so over time, I think the result of all of that competition is, is ironically, a move to the middle. And it takes a startup to come in and sort of knock that out of place, because the startup has nothing to lose. And that’s why you see the process that we do in enterprise software, where the big vendors start to all look the same. And they focus more on brandy to differentiate as opposed to the products, and then you have some startup that comes in disrupt that market. And then you know, within five years, that startup is now the one consolidating all the features. And this process continues and continues over and over again. And it’s all symptomatic, I think of what you’re saying, which is that the innovation stops serving the customer, it starts serving the vendor at some point. And therefore that adds cost and burden to the customer of the enterprise software without necessarily delivering value. And that’s the key word is value. It’s an interesting thing. We’re basically saying here that the industry is relatively young. And there’s a lot of change happening and that the pace of change in this industry is remarkable given how young it is that the skill sets have been changing. And the the general comfort and knowledge of technology and software has been growing exponentially even year to year there the difference and that the tool sets available to technologists who work with and build software have become more sophisticated and more expressive as a result of this general increase in the skill set. And that the competition between vendors, yes, it does create innovation. But that innovation is usually targeted mostly towards market growth. And not necessarily towards always towards value doesn’t mean that the customer doesn’t have value. Like you said, it’s not about solving a unique problem. It’s about solving a more pervasive problem. That’s the only way a an enterprise software company can ever be profitable. So that’s a great summary and a good setup for the next part of our conversation. Hi, everyone. This is Dino. my conversation with Dhruv went a bit long. So this is part one of two, please make sure to come back to the HR data labs podcast list and get Episode Two in order to hear the full conversation.
Announcer:
That was HR data labs, please visit Turetsky consulting.com forward slash podcast to review the show. add comments about this episode, or add new ideas about upcoming shows you’d like to hear. Feel free to be creative, but please be nice. Thank you for joining us this week on the HR data labs podcast and stay tuned for our next episode. Stay safe.
In this show we cover topics on Analytics, HR Processes, and Rewards with a focus on getting answers that organizations need by demystifying People Analytics.