Ep # 111: Mastering Talent Retention: Revolutionizing HR Tech with CandorIQ ft. Haris Ikram (Co-Founder, CandorIQ)

Adil Saleh (0:00:03) - Hey, greetings everybody. This is Adil, your host again and thank you very much for this time and this opportunity that we get to speak with these people. One of the best brands in the tech for I would say the last ten to 15 years. If I just recall you, we previously spoke with Lee to ship a deal that was also a real good conversation. Today we have another compensation management software. Actually he's the co founder of Candor IQ Haris. And prior to that he was more into product management. One of the significant roles that hit me hard, the kind of journey that he had at Salesforce. It started as a product director of content team that is more focused towards working with teams on the content program that they had. And then he ended up as a senior director of product manager that was more served towards digital experience platform that he helped the ride reaching to 400 million in business. So that experience was something that we're going to be talking about today as well, after all. Thank you very much, Harris. It was long awaited for taking the time today. Haris Ikram (0:01:25) - Absolutely. Glad to be here. Adil Saleh (0:01:28) - Love that. So, Haris, I mean, we came across people that have like, they try to desperately try to connect their prior backgrounds with the products that they're doing, like products they're founding. In your case, I see that your prior background was more towards product management. You did a degree in entrepreneurship, which is good. Now you're co founding a platform that is more slightly different from an outsider perspective. You will expect somebody from a product management background to build something like June, something like product analytics platforms. What was that story like? What made you think like that? And what was the inception of Candor IQ and your prior journey? A little bit as well. Thank you. Haris Ikram (0:02:15) - Yeah, absolutely. I'll start by what's Candor IQ? And kind of walk you through the story. So Candor IQ is a platform for companies to manage compensation and headcount and ultimately hire the best talent, reward the best talent, retain the best talent. That's the goal. And the reason why I went into this space versus many of the other things we could have done is a few reasons. One, post Salesforce, I was the head of product at several unicorn companies like Checker as well, and blend Labs where I managed pretty sizable teams, about 100 people in product and engineering. And the more people you manage, the more operational work you kind of have to do as well to kind of get those organizations going and effective. Right. And as a chief product officer, to be successful, you obviously have to have product strategy be able to execute. But all of that is hiring and retaining the right people. So that was the reason. There's many reasons and many inputs to hiring and retaining the right people. One portion of it is like helping them understand the career ladder, understanding pay, all of those things. And for that problem I had to use spreadsheets or we used many different systems who did little bits of different things. You get budget information from finance, you get benchmarking data from HR, you build your own models. And as I went from company to company, had to do this manually every single time and ultimately kind of saw this as a problem that all leaders kind of face and started a company in the space. Adil Saleh (0:04:02) - Very interesting, very interesting. I have one because we have teams that listen to this podcast and a lot of them, they're either if not directly product manager, but they're working with product teams if they're like GTM teams. So now thinking of Haris joining Salesforce in 2015, working with the product management and everything, how is it different than with AI evolution everything today, like how people see product management and how it evolves in what spectrum it's going. Haris Ikram (0:04:38) - Sure. Postulating here with the impact of AI, I think some of it's yet to be seen or will change a lot because the space is changing. But I will say that the job of the product manager doesn't necessarily change. You want to build the right things for your customers and you want to think strategically. You want to think about the business side of things, think about the technical decisions as well. So the end goal you want to achieve is the same, right? But with AI, some of the things could evolve quite a bit. For example, how you get customer feedback and input might change because you might have tools that instead of manually curating feedback requests, it can index all the data that's coming in and then sort it for you and prioritize the things that come out. That's an example. Or if there's bugs in the story, instead of having logs and having an engineer dig in and figuring out what's wrong, AI could be used to help people stitch together bugs and issues as well to help the triage process. So from strategy and roadmap prioritization to all the way down to bug fixing, I think there's a lot of opportunity for AI to come speed things up, but I think ultimately that's a good thing. What that should do is help speed up the ability to understand the situation, speed up the ability to make decisions. Maybe you can also use AI to kind of write some of the requirements as well to speed up the process. So less manual work and more time spent on the thing that humans do really well. Right. Which is cross team collaboration, presentation, working with customers, working with your teams, thinking about strategy and less time in Jira's and spreadsheets. Adil Saleh (0:06:34) - Yeah, absolutely. And a lot of this in the past, they get just lost in translation and everybody's banging their head. And until the customer churns, you get to know, okay, these are the reasons, okay, these are the things that we should have followed earlier. Now we're just slightly too late. So now, talking about this talent retention, you're in the Silicon Valley. You know that on average it's not more than six weeks, sorry, six months, which is what I read last year, the report that came out. So the average retention is not more than six months of employee. How do you see it changing for better? Of course, it has so many moving parts and so many reasons in so many different things in Silicon Valley. Talk about from a startup to a company that has a unicorn status. So how do you see it if you are to just give your view on how this employee retention is going to be as a problem for this b two B test? Haris Ikram (0:07:38) - Yeah, I think in tech in general, employee retention is probably only going to get worse. In general, yes, there's ups and downs. Last year the economy was slower. That kind of met, and retention did go up to some degree. But for the best talent, they can always move around. That's one and versus a decade ago. Now all industries are tech industries. There's a war for talent, tech talent in every sector. It's not just at software only companies. I think the jobs and the roles in the tech industries are just going to be more and more competition for it. And so I think at a macro level, I think the war for talent is only going to get worse and the best people will have the ability to move around. Having said that, there's a lot of things that companies can do. Be creative about where you hire. Think about remote work. Yes, I live in San Francisco and there is a high concentration of talent here. But there's great talent in New York, where you are in all parts of the US and outside the US as well. So I think the workforce is just going to become more global because you're going to go where the talent is going to be more flexible. And also, I think the companies can do a better job of understanding what they want, like set up career ladders and what skills they need and what the level structure is. Understand what the market pay is so that they can hire the right talent can, or IQ can help with some of that when it comes to global compensation data and figuring out what the right skills and levels and tiers are so you can pull in the right talent. But yeah, I think it's a broader wave and problem statement. Adil Saleh (0:09:30) - Okay, interesting. And I was slightly curious because this last week I talked to also a product that is more towards, like people Gen AI, they're tracking patterns and how people are interacting outside work, sitting at work. It's not something like they're shadowing, it's just that how they're spending time and how likely a company is to retain them, like their interest in the job and interest development and all of that, their motivation and all. So are you thinking at Candor also about getting some external data sources to make sure that this employee retention can be mitigated as much as possible? Haris Ikram (0:10:11) - Yeah, that's a great question. Right. So I think a few things. One is people think pays or managers is the only way to only inputs on retaining talent. But actually, as a manager, you need to understand a lot of different pieces. One, you need to give your team members, like exciting work, help them understand their career, help them grow performance management, help them see the career ladder. Trust and relationship is always important. So there's many different factors to being able to retain talent. It's not just exactly how much you pay, and it's not just like the manager. There's many different things. Right? So with Candor IQ, we try to marry that. Yes, we have global compensation data in 100 countries. You have millions of records, which kind of tells you how much different people are getting paid. But also then we provide information on what the different levels are like senior engineer versus lead engineer, or AE versus senior AE, and what the skills and expectation are of those people, so that managers also understand what they should expect of the team. Along with we'll pull in data from performance management tools, we'll pull in data from your payroll system. One, we put all lots of different types of data to help answer these questions. Number two, we try to be proactive and leverage AiML and other automation. So we'll surface when an employee who's a top performer has their equity vested, or we'll surface if an employee seems like they're a churn risk because their pay hasn't changed in three years and their performance will. So we try to, instead of having managers go seek information, we try to proactively surface things to pay attention to for HR managers so that they can, hopefully then it's up to them, and hopefully then they can do a better job of retaining people it's usually too late. Once someone's saying they're about to quit, it's usually too late. You kind of have to do this on a continuous basis and that's what we hope. Adil Saleh (0:12:25) - Yeah, that's what I was going to ask. Because it's not always like for SMB to mid sized companies enterprise. They have registered recruiters and that's a different, you can say they have different motion when it comes to hiring, but when it comes to SMBs and mid market, of course it's always good to have a players, but over time you need to nurture those people. You're not going to have a players on your team all the time, and all of your players will be doing wonders. And they are kind of like a players like Steve Jobs said. But it's all about nurturing and all. So the analytics that I see for these people, teams and managers, what kind of analytics that we think that are super powerful, like you can say like power analytics that identify the journey of an employee or maybe help managers understand those employees on different, smaller or big use cases. Haris Ikram (0:13:21) - Yeah, a few things. One is, I think that the definition of airplayer can also vary. Right. So one is someone who's great at a big company might not be as effective at a startup and vice versa. So I think every company define what are their expectations, what's right for them, and it really kind of varies. That's one comment. But in terms of the analytics, there's many different things we can surface, right? Like which employee is a top performer, which employee is a top performer, and how are they paid versus their peers? How are they paid versus the market? When's the last time they had a paid change? When's the last time they were promoted? We can collect a lot of that kind of feed information and surface it to managers as ways so that you can one look at the company level, maybe department level, team level, job function level, and see how that employee is doing. Whether it's, and this is across salary or equity or bonuses, there's different compensation types as well. And so there might be a different mix of those things. Maybe some companies are less cash heavy, and so that really varies. There's no one right answer, but there are some general out of the box suggestions, and every company can tweak a little bit on what they care about in terms of measurement of employee happiness. Adil Saleh (0:14:56) - It also changes within different teams as well. For development teams, like product teams, for customer facing teams, it's different. So how you guys are successfully able to help these of your customers to formalize this across the organization. Haris Ikram (0:15:14) - Yeah. One, we'll give them data on what's the expectation career frameworks for different types of jobs and that kind of information, and then work with them so that they can define what's right for them in terms of competencies and skills and pay and across different geographies as well. And departments. Okay. But it's also up to the company to decide, hey, what do we want our staff to focus on? What's our performance score? What do we value in terms of performance? What do we not value as much? And how do we create the right behavior, training and education? But also how do you create the right financial incentives to get people to do the right thing? And that varies from company to company. And even department by department. Sales teams versus engineering teams will have different incentive structures for that very reason. Adil Saleh (0:16:15) - Cool. Understand it now. So thinking about your go to market, like what kind of segment are you trying to penetrate? Of course you're not too early, so you've been there for quite some time. It's been about more than how many years? Like three years almost. Sorry. It's almost a year. I'm sorry on this. So how you're approaching your go to market this time? File the ideal customer profiles. What segment are you after? Haris Ikram (0:16:43) - Yeah, so we've been around for about two years. In terms of customer segment, we're focusing on tech or tech adjacent companies with complicated compensation like salary and variable bonus and equity. So like SaaS software, healthcare, health tech, fintech, et cetera. That's one. And in terms of the segment, we target companies with 100 employees to 1000 employees. That's kind of our sweet spot. Another way to think about it is maybe series A or series B and above up to the growth stage. That's our target segment. Adil Saleh (0:17:26) - Very interesting. And regardless of any industry, it's just the headcount. That is what you're identifying your customer segment as of now, yeah. Haris Ikram (0:17:37) - So industry matters less because, one, the tool is built to work across any use cases. And number two, we have data for every industry and segment as well, like compensation data, for instance. So yeah, we're a pretty flexible platform. Adil Saleh (0:17:56) - Cool. And of course not going to talk about too much about competition, but you have players in the mind that they're competing big time in this category. So what is that you're thinking that of planning this year basically have a unique proposition or maybe standing out of the competition? Haris Ikram (0:18:17) - Yeah, I think two big bets for us. One is going much deeper into headcount planning and headcount management. A lot of things kind of fall between the cracks when there's collaboration between departments, in our case between finance and HR. So helping bridge the gap so these orgs can work together, I think that's a big bet. And then, like with maybe many other people, AI is going to be a critical part to what we do too. I think we can drive a lot more automation and create a much better experience as well with AI. And there's a number of interesting things that we're kind of working through right now. Adil Saleh (0:19:02) - Very interesting, very interesting. Just last conversation, going to have like three or four more minutes from you, if you love. So now talking about making it self served. Of course, it's not possible as of now because you're working with range of different customers, they have different use cases, different geographies they're hiring in. So how you're gearing towards more investing into keeping your onboarding self served and then making sure time to value is as fast as possible. Haris Ikram (0:19:35) - Yeah, that's a great question. We're not a PLG product necessarily, so it's not 100% self serve we have to do set up, but especially I think time to value is super important. Right. And so there's a bunch of things. We've built several internal tools and workflows to kind of onboard customers more quickly. We're building capabilities so customers can self serve and configure more things themselves versus using us as well. And then having out of the box kind of like templates and suggestions and recommendations where possible as well, so that we can provide those customers with more guidance. So those are some of the ways we reduce time to value for these customers. Adil Saleh (0:20:24) - So are you guys also investing into customer education? I'm sure you have a blog and also the community side of like you have. Haris Ikram (0:20:33) - That's a great one. Yes. So we do also have content. We publish blog posts every week or on social media as well. So we'll provide updates on social media, we'll put blog posts for new things, providing information, whether it's about the product or about the industry. We also have newsletters that we send out every month. And so quite a few things that we do outside of the product itself to make it more self serve and to educate the customer base. Adil Saleh (0:21:09) - Wonderful. Haris Ikram (0:21:10) - Yeah. Adil Saleh (0:21:10) - It was so interesting to meet someone like Candor after a long, long time. And the way you guys are trying to position yourself with having AI into it and external data sources and people gen AI, that you're thinking along those lines, which is really good. And I'm so looking forward to following your journey folks, this is Haris Ikram. You guys can find him with Haris first name, Ikram I k r a m on LinkedIn is pretty much active. I love his, the kind of feeds that he shared. And that's why my team reached him out for this episode. And it's so pleasure to have him today. And it's going to be super excited to see some of the features that you're working this year. Haris Ikram (0:21:54) - Yeah, thanks so much. Thanks for having me. It was good to connect. Adil Saleh (0:21:57) - Yeah, absolutely. Thank you.