Jeff Furst, founder of FurstPerson, was a recent guest on the TechnologyAdvice Expert Interview Series to share his insight on the intersection of sales, marketing, and technology. The series, which is hosted by TechnologyAdvice’s Josh Bland, explores a variety of business and technology landscapes through conversations with industry leaders.
In this episode we discuss everything from how technology has evolved since 2000, the importance of workforce analytics, and how international markets handle human resources.
Below are a few highlights from our conversation:
TechnologyAdvice: What it's been like to see not only web pages develop, but technology and software change in the past 17 years since you've founded?
Jeff Furst: There's been some major changes and shifts. You think back to the time we started, and depending on your listener's perspective and age, it will be interesting how they think about this. Back in 1999, 2000, 2001, access to the internet was limited. For the most part, you really had a dial up connection.
This is when AOL was mailing discs to everybody to set up. You'd load the software on your computer, and set up the connection. Versus where we are today: you can be walk around with a device in your pocket that's infinitely faster than anything you had back in 1999. You think of that as a starting point, and how do you reach candidates? Back then the technology we focused on was more phone-based.
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We would use an integrated voice response system (IVR). It had a 1-800 number, they call that number, then you had questions the IVR system would deliver to them over the phone. And they'd punch a number to answer that. And you were limited to what you could ask, because obviously you couldn't really evaluate somebody too in-depth because of the nature of that interface.
And then we would, if they were successful, we'd have them come to the office and we'd do computer-based testing. And you had to have computers - lots of computers - in your office. And run testing on a local computer basis. You'd have to look up each score individually, and then basically keep a spreadsheet of overall results and such.
As you moved into now the early 2000's, access to the internet improved. And then you started to have more candidates who had reliable internet access. It might be very slow compared to what we have today, but you were starting to have the ability for candidates to test from home on the computer. You still had a lot of people come in the office. It was really, at least in my opinion, back then it was more about the connection. It wasn't necessarily the software, or their user interface, or the experience. It was can they connect or not?
And then you move into the 2005, the 2008, 2009 period. Here the Internet's a little more developed, a little more fully developed. Access is a lot easier. You now have web-based tools to collect data at a high level across multiple channels and such. You're able to aggregate that, and start to do some analytics, and tie that back to performance data at your company.
I'd say over the last couple of years, with the growth of apps on people's mobile devices and consumer-driven software, you see more focus on the user interface, from a candidate perspective, along with the business side. I think as we see in the HR space, at least, companies are spending more time on that interface and development dollars are going towards that versus ten years ago.
It was really about, in our world, the assessment and the quality of the science and how predictive the tool was, that was a buy decision. And now it's a combination of things, and not only do you have to have good content that actually predicts job success, but the overall software interface. How well it works. Security components are really important now. Yes you have a wide range of things that have just slowly progressed.
Now the ability to quickly access data, and tie that back to other data sets to drive an analytics driven process has reduced time. It's made it more affordable. You're able to bring solutions that maybe only the Fortune 500 could use five or six years ago, down to a smaller company now, because it's easier to deploy that.
You see more opportunity for those smaller companies to take advantage of different tools. And then the ability to design software that can simulate jobs, for example, makes a much more engaging experience. The predictive strength of the tools has improved because of that.
TA: Could you talk a little bit more about how companies are beginning to use analytics to drive decisions in HR?
Furst: Finance, or IT, or operational investments had a lot of quantitative components to, "If we make this investment decision, here's the business case." And there could be a tangible link back to some type of improvement in an outcome within whatever component the business is related to. HR couldn't do that. It was a lot of feel good stuff, and compliance, and administration.
Now today, it's a really good thing that with the advantage of having access to information, and being able to tie that to an analytics driven process, you can say we designed this higher process in a certain way for recruiting software. We're going to hire people that are X percent more likely to stay on the job and perform at a certain percentage above the baseline.
Which means we're able to drive additional sales per interaction, or a better C-stat experience, or better net promoter scores. Which translates into a financial gain. And you can quantify that. For the human resource component, that’s a great thing. Now they're kind of on the same footing as other areas within the corporation.
That will only continue as we discuss how do you link the hiring process to onboarding, to production, to employee engagement? You really need a closed loop concept, where you're pulling data from these areas, and you're using that to reinforce other areas to basically do a better job at identifying candidates, and hiring them, and helping them be more engaged as employees. Because we know that employee engagement's really important.
On the pre-hire side, there is potentially a downfall, where it's one thing to just have two data points, and they intersect, and there's a statistical relationship, and you say, "Well now I've cracked the code. Here's why people are successful." The question is: can you replicate that tomorrow?
The skill is understanding the story of the job. Why is somebody successful in the job? What are those inherent components around performance, ability to perform, motivation to perform, skills to perform? What does that job look like? And the ability to measure that, and understand that in a more conceptual way, and then you can bring the data story underneath that. You can measure those components and such.
A lot of companies are missing that, which ultimately will limit the success they'll have around improvement in hiring, because you have to have that consistency and that narrative understood. It's not just two data points working. Don't get me wrong, analytics is critical to driving everything, but a lot of companies don't spend enough time around that front-end. Do diligence around what work looks like, and be able to define that narrative story.
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