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Hosts Stacey Harris and John Sumser discuss important news and topics in recruiting and HR technology. Listen live every Thursday at 7AM Pacific – 10AM Eastern, or catch up on full episodes with transcriptions here.

HR Tech Weekly

Episode: 64
Air Date: March 31, 2016


This Week

This week John and Stacey discuss:

  • ElevatedCareers (eHarmony HR solution) » Link
  • Mercer and Thomson Online Benefits » Link
  • Plansource » Link
  • Uber Recruiting engineers with random games » Link
  • Topics: #HRAnalytics, #HRBenefits, #Recruiting

About HR Tech Weekly

Hosts Stacey Harris and John Sumser discuss important news and topics in recruiting and HR technology. Listen live every Thursday at 7AM Pacific – 10AM Eastern, or catch up on full episodes with transcriptions here.

HR Tech Weekly Episodes




Begin Transcript

John Sumser: Good morning and welcome to HR Tech Weekly, one step closer with Stacey Harris and John Sumser. We probably should have had, “When I’m 64,” as the theme song because this is our 64th show. How are you Stacey?


Stacey Harris: I’m doing well John. I’m doing well. 64 shows, we’ve made it. We’re not quite halfway through our second year now. Doing fairly well, keeping the show running on a week by week basis.


John Sumser: Yeah, what a thing. We’ve hit it here. What’s in your mail bag Stacey?


Stacey Harris: It’s been somewhat of a quiet week, not a ton of big news going on. I did have a couple of interesting articles, and I know you went to an event so we should probably take a little bit of time to talk about the event after talking through some of the articles. The two probably biggest announcement that I caught this week had to do with benefit. Mercer and Thomsons Online Benefits announced I think it was yesterday or the day before, that they have entered into alliance to expand their offerings to multinational organizations. I think this is more of a, we’re going to help each other, partnership. It didn’t sound like they were investing in each other or do anything like that. This is more of a co-sales model. Mercer’s going to continue to provide their global benefits brokerage and consulting, those things actually going together sometimes can be a bit conflicting but for large multinational where Thomsons Online Benefit is going to be offering the technology. That’s an interesting story to talk a little bit about.


Plan Source, another benefits organization, is launching their Voyager release. They do two releases a year and this is one is a pretty big release so they’ve made some big noise about it. Plan Source is the technology that’s behind many of the brokerage firms and many of the large consulting firms who offer benefit solutions. There’s some conversation there. Then we have some updates on what people are saying on the learning space, including I had a great briefing with an organization called, which I think throwing into what’s happening in learn. Then some conversation about the labor organization, the labor department launching an online tool to help companies recruit people with disabilities, and Uber using gamification in a very unique way to hire engineers. They’re sending games to people in certain regions while they’re taking rides in Uber cars through their app. There’s a lot of stuff to talk about. Do we want to start maybe with your recent events you’ve been traveling to? Then we’ll get into the articles today.


John Sumser: Let me tell you about the thing I was at this week. I went to the launch of a service called Elevated Careers. Elevated Careers is for as long as there’s been an eHarmony people in recruiting have been offering products called the eHarmony of recruiting, where you figure out whether or not somebody matches the company based on some sort of eHarmony style approach. Actually I didn’t know this but eHarmony has changed, observably changed the quality of marriage in the western world. If you meet somebody through eHarmony and you get married you have a significantly higher change of avoiding divorce. Very interesting, very interesting. The data is robust and validated, so eHarmony is a better way to meet somebody. Now they’re trying to take that to the work place and after all these years there’s an eHarmony product.


Stacey Harris: What’s it called again?


John Sumser: Elevated Careers.


Stacey Harris: Elevated Careers, okay.


John Sumser: Elevated Careers. It’s a multivariate analysis of your skills, values and personality versus the company’s skills, values and personality. There are I think 16 core cultural values and 30 … God, I don’t remember but it’s tons, way more sophisticated than anything that I’ve seen in its level of analysis of the question of how does person X fit into the organization? What are the predictors of success inside of that organization? It’s close to 50 different elements that they look at. More than I can remember, more than anybody could remember. They don’t ever really ask you to remember all of that stuff. They give you a simplified infographic presentation on the elements of your fit, from either the company’s perspective or your perspective, in the output part of this process. [crosstalk 00:06:03] Go ahead.


Stacey Harris: Are you putting in a profile and then they’re finding companies for you or is this still, there’s a job [inaudible 00:06:10] that you’re applying for? Is that still the model?


John Sumser: That’s still the model because, I don’t know that this will last, but they are currently actively trying to not be a Glassdoor. They have accumulated, it’s very interesting, they have accumulated cultural maps of 2 million companies that have more than 20 employees. That’s pretty interesting.


Stacey Harris: Yeah.


John Sumser: They’ve done it by going out to the web and finding all the information that’s available and doing a very heavy statistical analysis against what they find out about those companies. They’ve got that as the library but you can’t go and say, “Which company do I fit?” I think this is a carry over from their days as a dating service, they were not Ashley Madison so they didn’t give you profiles of married people who you could have a good relationship with. They will only give you profiles of single and available people for a, quote, regular relationship. They have that same sort of thinking here. You fill out a profile, you give them the profile and then give you jobs in companies where you’re likely to fit.


Stacey Harris: Interesting, okay. What’s all their analysis? One of the challenges with all this data analysis that we’re seeing in the market as a whole is that organizations are looking at who they currently are and then hiring more of the same people that fit into that picture. Is that a risk do you think with something like this?


John Sumser: I think it’s very definitely a risk. In the course of the briefing we had an extremely detailed conversation about that question. There’s some very interesting stuff, the raw non-HR literature, the IO literature, according to the people of eHarmony the non-HR literature about what makes a group better, he used a term, actually I’m going to look it up while we’re talking, homogomy, H-O-M-O-G-O-M-Y. Homogomy is something like homogeny, something like everybody’s the same. They were citing literature that said the more sameness there is in a company, the better the company is.


Stacey Harris: Okay.


John Sumser: I’m going to get the cites, I asked for the cites. I’ll have that in the weeks to come. That’s exactly the opposite of the contemporary HR point of view. That’s exactly the opposite of it, right?


Stacey Harris: Yeah, and having a done of [OD 00:09:53] work in the past, there’s two thoughts. Which is create a team that will work together, or build a team that will work together. Picking a team where all the people will work together because you have all the right ideas, and helping people learn how to work together are two different dynamics in OD. What they’re saying is we’re going to pick the team that’s going work together best, versus telling people how to build them.


John Sumser: I think that’s a great [launch 00:10:28] into what we could spend a lot of time on this show talking about. I think that we’re starting to see a separation of those two ideas. The first idea is, if get everything in all the same, they’ll be okay so why doesn’t really matter. The first 1 we want to get the team just right so we’re going to take an active interest in building complementary roles, and why matters there. On the 1 hand the pure statistics view is causality shouldn’t really matter if you have enough correlation, and the opposing view is, what are you an idiot? Of course the actually meaning of things matters.


Contemporary statistics can be so intense now that you can find hints of correlation in the tiniest of places and the operating theory in a lot of these services is the more of those hints of correlation you can accumulate, the better able you are to predict the performance of the person in the job. It doesn’t matter than there’s a specific source of that, if it’s that they have a dot in their email address that’s enough, that’s okay, that’s fine. It may not have anything to do with anything but if it seems to predict success hang on to it.


Stacey Harris: Part of what scares me about all this, it scares or it might be just a matter or repositioning our thinking on all of this, but when we look at what’s happening, many people who know me personally know there’s been a lot that I’ve dealing with from the pharmaceutical side of things in my personal life. Looking at how we’ve dealt with scientific and medicine decisions right now, in many cases the scientific world has gone down this very similar road of trying to figure out how we can either cure things or deal with symptoms and we haven’t really taken a really good … and spent a lot of money in many cases, on causation because of this exact conversation you’re having. Which is if you can get all the correlations then we can 90% of the time cure anything that might come up, or 90% of the time pick the right people. But what it doesn’t allow us to do I think is create or build, or at the beginning figure out what people need to be doing, to really get to that next level. It’s a bit scary don’t you think?


John Sumser: I’m trying to sort that out. I believe that using the pure statistical approach, and it’s an approach that was developed in big pharma. Using the pure statistical approach you can predict everything as long as it’s exactly what happened yesterday. You can predict with certainty that what happened yesterday will happen today, except for when it doesn’t. The interesting and complicated thing about being human is the only time the predictions matter really is when it doesn’t happen the way that it happened yesterday. This is the big complaint that people are having with the way that drugs are proven, quote, to work. Taking that technique and applying it to human beings in their roles in their jobs seems like it might be a recipe for some problems. Now I’ve got to tell you that the people at eHarmony never once said that what they’re doing has anything to do with methods perfected in big pharma, but if you go around the rest of the analytics world that’s largely assumed to be a fact of the latest movement in analytics.


Stacey Harris: I think this is something that we’re seeing throughout the HR technology space as well. The two articles that I pulled today on the benefits space is an interesting confluence of what’s happening in benefits. We’re seeing a continued increase over and over again of the amount of investment and technology and rethinking of what we would consider as the benefits space these days. When we take a look at what Mercer’s doing with Thomsons Online Benefits, Mercer is a broker of benefits, a broker of the various levels of benefits that organizations might want to purchase or buy. They are also a consultant on what type of packages would work well for various organizations.


Then you have Thomsons Online, and I’ve had some great meetings with Thomsons Online because Thomsons Online does benefits technology for everyone except basically the US because they feel there’s enough people in the US market doing online technologies to manage benefits that they feel that doesn’t really fit their niche, but they’re doing it for all 146 other countries around the world. Basically what they’re created is one of the most flexible cloud platform I’ve ever seen to allow people to manage this myriad of benefits that people now are managing from [inaudible 00:16:45] to housing investments to long term and short term investments. It really is quite massive. This relationship between these two groups is really about managing risk with your employees, right? Managing the data that’s going to be happening on a day to day basis from that risk perspective and building it all into a technical system, right?


John Sumser: That’s interesting, say more.


Stacey Harris: Part of what I’m watching in the benefits space is this explosion of more technology to manage more complex benefits options, both here in the United States and internationally as well. Thomsons Online is one of the tools [inaudible 00:17:32] doing that. Now another version of that is Plan Source. Plan Source announced the Voyager, their product Voyager, which has a Spring product release of their technology. Basically what they’ve put into their new release is implementation and data exchange dashboards, click to chat support, document management workflows, billing reconciliation services, the idea that you can see some of this stuff all in one. Again Plan Source is the technology that is basically sold by brokerages and other consulting firms, basically for people access their benefits. Again it’s not good enough anymore to have a single screen, you have to have all this stuff aggregated and viewed at an aggregate level for your organization and everybody wants individualized benefits because all of the risk that they’re dealing with are very personal right now, right.


John Sumser: Right. Right, right. As benefits become more personalized the complexity of managing them goes up and the risk associated with offering them goes up. Is that what you’re saying?


Stacey Harris: When you look about the data analytics that we were just talking about, the idea that we’re going to try and manage symptoms, we’re going to try and manage risk. We’re not going to try and get to causation issues. That seems to be a symptom of this.


John Sumser: This is probabilistic thinking again. I guess the question is if you can figure out the odds of a card table, why wouldn’t you just count cards. That’s becoming a management theory.


Stacey Harris: Yeah.


John Sumser: The question is, is that smart or is that dumb?


Stacey Harris: I don’t think that we have an answer on that yet, but I think it’s worth watching as we look at all this technology and packages, services that go along with the technology. Benefits is this place where you get that, but you’re also seeing that at other HR tech spaces. Learning and development is now not just an LMS technology but it’s also the algorithms that go into learning how people learn. That’s a service that’s part of that system. The whole idea that what we’re purchasing, what we’re buying is data on how to better understand how we learn, or how we’re going to use benefits, or how we’re going to manage our own lives, right? That could be good. It could also be risky in the fact that we’re not looking at some of the challenges like where we should be learning and why we should be learning, right?


John Sumser: It’s such an interesting [thing 00:20:29] because the reason that I lose money when I go to Las Vegas and try to gamble is because I don’t have a shred of probabilistic thinking. I don’t know how to do it so I always lose. I could do with being better at it, I could do with being less concerned about the core meaning of things and more concerned about the likelihood that my decision is the right decision. I could use some improvement in that area personally, but I can’t imagine effective human systems that are divorced from that. That’s a lot of what’s being put forth right now, is that it doesn’t matter.


The underlying meaning doesn’t matter. From some pretty intense perspective I think that that puts contemporary diversity issues right square in front of the table, because if you are looking at the historic probability that somebody with a physical disability would reduce productivity the answer is liable to be yes. The fact that you have to make accommodations for people suggests that in the [raw estates 00:21:58] there’s a productivity loss before you get the value, and if you’re in the business of predicting what’s productive and what’s not productive then that’s what you’d hit. The systems are going to have to get corrected I think so that they don’t do that.


Stacey Harris: Yeah. I think that’s going to play in all of these systems that are doing data analysis, even things like benefits where they’re aggregating to see where the biggest hits come or which benefits are being used the most or which are not. There’s going to have to be some correction in our thinking because I think that data’s going to draw us maybe to conclusions that could be diversity issues, could be [ELC 00:22:40] issues, could be a lot of other issues, right?


John Sumser: Yeah. What I’m about to say is only lightly discussed in the circles where people are trying to figure this stuff out. I’m going to say it in an emphatic way that may be a little over the top. That is, probabilistic statistical calculation driven systems for making decisions with human beings always amplify the bias that’s already in the culture. They may not introduce bias but they will always amplify the existing bias that’s in the culture, and every culture has bias.


Stacey Harris: Yeah.


John Sumser: I got invited last minute, I’m not going to be able to go, to something called [Sci Op 00:23:35] where there’s a paper being presented about how you [control 00:23:39] for this particular variable through a technique called objective modification. Objective modification is so new that you can’t find anything about it on Google. This is the state of the art of this stuff.


Stacey Harris: This is cutting edge.


John Sumser: Yes, the new definition of cutting edge is you can’t find it on Google.


Stacey Harris: [Definite 00:24:04]. I think it leads to a lot of the articles that we picked up this week, is this idea that data is the underlying currency behind all of these things that we’ve been talking about on the system side as we know. But the conversation now becomes what do you do with that data? Is that data used for the end users to make [inaudible 00:24:26] their own better decisions? Is that data used in an aggregate [level 00:24:28] for the company to make some decisions that are connected to correlations versus maybe causations, or is it used to dig deeper and get to causation? If that’s the case then is there a financial or a environmental or a ethical outcomes that’s valuable from getting to the real systematic issues? It’s a big conversation.


One of the other items I pulled today was the article about Uber. I pulled this article up and I knew Uber was doing some interesting things, and I’ve seen this from other organizations, but never quite done this way. Uber is recruiting engineers by randomly sending a coding game to play during rides. They’re randomly sending this to areas like Seattle, San Francisco obviously, and there were some other, I think Austin, a couple other areas they listed in there. They’re saying they’re basing this not on any individual profile but to people in those areas.


Now there are some people who are engineers who have gotten these games while they’re riding and they’ve been sort of, “This is creepy, how do they know I’m an engineer? None of my engineer stuff is connected to my Uber profile.” Uber says it’s just a shot in the dark. They give them 60 seconds to complete these Code On The Road challenges. If they pass they’re said, “Would you be interested in applying for a job here?” What do you think about that John, and all the stuff we just talked about? Is this more of the idea of, we’re going to find all of the causal issues, or probably more we’re going to find all of the correlations where people should be who are engineers and that’s where we’re going to start looking? Not really identifying issues that we have enough engineers maybe in the places we need them, right?


John Sumser: This is actually precisely the current recruitment advertising puzzle, which is how do you reach people in places where nobody else is trying to reach them? Because everybody, everywhere has this … Between the time I got on the plane late yesterday afternoon and this morning, I got another hundred pieces of email that came through all of the filters. It’s a hundred pieces that I have to do something with and I’m having trouble keeping up with the flow. I’m having trouble keeping up with the flow. If you sent me a really valuable piece of email for something that I wasn’t immediately plugged into, so it wasn’t from you or somebody that I value or somebody that’s a client, but it was from somebody who might be interesting, I’m more likely to miss it and people who send that sort of mail, early relationship introductory stuff are desperate to find ways to reach me that are not all cluttered. Reaching me in the backseat of the Uber is exactly a great way to do it, and if they spam a few people it’s not any worse than getting a LinkedIn mail. I think we’ll see more of it.


Stacey Harris: Yeah. It’ll be interesting to see, and I was [inaudible 00:28:10] What I was really interested in is the gentlemen who they interviewed here said, “Yeah, I tried it,” and his comment was, “I think it’s a crap chute either way, [inaudible 00:28:22] answering this 60 second quiz in dark Uber car would tell that I’m the person for doing anything.” He tried it, he went through the process. He wasn’t looking for a job and he said they didn’t follow up after he said, “Yes I might be interested in contacting.” There is also an issue here of how much time are you spending on some of these things, right? I think that’s going to become a challenge every time as well.


John Sumser: But at the same time, particularly in the market place that has engineers for Uber, they’ve been using billboards with contact information so that as you drive by them on the highway you can text in to the billboard or you can go to the website or whatever. This business of catching people as they’re driving by isn’t new and the idea that you can do that to them while they’re in the car, instead of having to put a billboard up. It’s probably a more accurate prediction.


Stacey Harris: [inaudible 00:29:27] Yes. We have wrapped up our half hour John.


John Sumser: What a fantastic conversation. I think what the audience might be noticing is that statistics and analytics are becoming a bigger part of HR technology than they’ve ever been before. I think you and I might be the only people who are actually covering that.


Stacey Harris: It’s a big topic I think that we’ll probably get into a lot deeper throughout the year but I think the challenge with it is that I don’t think we have good definitions for what it looks like yet. It can be a confusing market I think, so our conversations are think are a great way to maybe get people to start talking about what the definitions are, what they should be looking like.


John Sumser: Yep I agree. Thanks so much for being here again Stacey. Thanks everybody for listening.


Stacey Harris: Thanks everyone, have a nice week.


John Sumser: Yep. You’ve been listening to HR Tech Weekly, one step closer with Stacey Harris and John Sumser. Have a great rest of your day. Bye bye now.


End Transcript