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Hosts Stacey Harris and John Sumser discuss important news and topics in recruiting and HR technology. Listen live every Thursday or catch up on full episodes with transcriptions here.

HR Tech Weekly

Episode: 231
Air Date: August 22, 2019


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Important: Our transcripts at HRExaminer are AI-powered (and fairly accurate) but there are still instances where the robots get confused (or extremely confused) and make errors. Please expect some inaccuracies as you read through the text of this conversation and let us know if you find something wrong and we’ll get it fixed right away. Thank you for your understanding.

John Sumser
Stacey Harris


[00:00:00] Today’s Show is brought to you by the human resources executive Magazine’s HR Technology Conference and Exposition held October 1st thru 4th at the Venetian in Las Vegas. Join me and thousands of your colleagues at the world’s largest exhibition of HR Technology, act now using the code HREX and you can receive a $300 dollar discount on your ticket.

[00:00:39] Thanks. We’ll see you there. And by the way, don’t miss the women in technology.

Good morning and welcome to HR Tech Weekly [00:01:00] One Step Closer with Stacey Harris and John Sumser. How are you Stacey?

I’m doing well. Podcast Radio Show personalities that you have to sometimes do your radio shows and unlikely places and how about you dare you cast radio show personality. I think you should put that on your business card.
[00:01:33] We’re actually yeah, very you know it even in this effort. I’m really interested this year and what we’re finding out about the deployment model. We were just having a conversation if you want to go about through this interesting Dynamic is changing and how organizations are deploying their HR technology and this year.

[00:01:50] We went a little deeper than we’ve done in the past. We asked about things like posting and whether or not people are posting in public or private Cloud environments and what that might mean [00:02:00] some differences. Either their own course on-premise or licensed environments that they have him or what it might mean if it’s applied based solution.

[00:02:07] So that’s kind of interesting. We’re going to be diving into some of that. So we’ll have some did on that the break coming up at the conference to be a church at conferences you decide about when we launched the report and then also get into a little bit this week analyzing data on in a workforce planning that’s going to I think be another topic that we’ll have a lot of data on this year.

[00:02:28] Workforce planning really is coming out as conversation about sort of what you do with the data and how you leverage your HR technology data in a way that’s probably most effective for your organization those organizations who aren’t doing any press workforce planning don’t seem to be getting as much out of it as those who do I will have some data in there as well.

[00:02:47] So since one week just from analysis perspective. How about you you’re deep in the writing and you’re getting into any topics that you think everyone should be watching for what we call you back to work for aspiring for a second and I’m [00:03:00] concluding from the work that I’m doing that it’s not possible to have an HR strategy without a dynamic and detailed Workforce plan because without that you don’t know where you’re going.

[00:03:12] It’s all right. I’m pretty excited to see what you’re learning there. I would imagine that people are starting to figure that out. But it’s an HR Tech kind of thing. It doesn’t really Bubble Up in the show room view of the world. And so I’m going to be fascinated by what you discover there. Yeah.

[00:03:29] No, I’m not surprised that in your work and you’re finding that the strategy and the plan are so tightly tied. I think a lot of people have an HR strategy. Yeah, just like we’re going to transform the organization make it more digital right you hear that all over the place but idea about how you want your technology where coefficient maybe want to be the best at is the workforce plan is the present ties you to the business.

[00:03:50] It’s what they need to run the business day. And that’s I think would get you more respect gives you more better outcomes. It’s more than just thinking about how we’re going to maybe change over [00:04:00] our technology and and. It’s a much bigger conversation. Right and you’re right. You don’t hear talking a lot about I think that conferences that don’t talk about data and you know, when you need data, you don’t have the technology to get data any of them tied together for also that that research that we do.

[00:04:15] That’s right. So for my stuff, I just finished the ethics section of the report, which is about the big four page ethics question is biased and so there’s some pretty interesting stuff about bias in the report. But what I’m starting to believe is that the next generation of management is going to have almost full-time attention on the ethics question.

[00:04:39] And the reason for that is we’re not going to see scary monster AI. Running wild stealing people’s jobs and taking over the world, but we are going to have a whole lot more math Enos in our work. We’re going to be employing lots of little bitch of [00:05:00] worker look like a machine and those things is they don’t have consciences.

[00:05:04] They don’t have compassion. They don’t have empathy. They don’t have intuition and that means that that unless they’re. Monitored. Bill skewed towards solutions that that may not be the most sound solution for sustainable relations with the human Workforce. And so it seems to me that the questions of Ethics will become common as a way of navigating where we’re taking the company over time and that gets you into privacy and transparency and understanding what.

[00:05:42] Good for the company versus what’s good for the workforce? And what’s good for the machines? It’s a complicated set of questions that I think it’s going to take up a lot of time for management over the next couple of generations. Yeah, I think what you’re saying is going to be a little less Terminator, but maybe a little bit [00:06:00] more iRobot maybe right?

[00:06:01] Yeah, that’s the machines might start to tell us what they think is better for us. Right but it’s a very subtle and how they do it, right? Well, so there are these great questions out there. What we’re doing right now is largely. We’re automating the way that we’ve been doing things. So imagine that this is that I hope this is a ridiculous example for the audience.

[00:06:23] But imagine this is Lucy and Ethel on the chocolate wrapping assembly line, right and what most of the tools that are being recommended do is try to automate that process precisely. And the truth is the chocolates made better other ways. So so that particular way of making chocolate is stupid and there are more interesting ways that you can make chocolate but machines don’t know how to figure that out.

[00:06:56] And so the first thing. If we lost Lucy and Ethel and that [00:07:00] great comedy, but that would be really sad thing to so just keep that in mind if you’re deciding how you want to make a chocolate. And so I don’t think it’s either of those. Scenarios it’s more. Like if you’re not attentive, you can lose control of the car.

[00:07:20] It’s sort of like, you know, and a lot of the early talk about automated cars. There was a lot of emphasis on keeping your hands on the wheel because you couldn’t predict what car would or wouldn’t be able to do and there’s that element 2. What’s happening with automation right now is you need to keep your hands on the wheel and when the car is pretty good at driving itself.

[00:07:41] It’s kind of hard to remember to keep your hands on the wheel. And so that’s where the problems really start. I saw a very interesting piece about the next layer of problem with self-driving cars and that is every self-driving car has been [00:08:00] vetted and tested in America. Every one of them and so if you take these things and you try to put them in traffic in Egypt or India or Beijing or Tokyo the rules of the road are very very different.

[00:08:15] Oh, yeah. Well, I’m not sure how close you could drive to the car next to you or in front of you and whether what’s a safe distance to get in and out of a gap in the traffic and when you can use your horn and all these things are all very very different shame car. Shame wheel same engine, but the actual social engagement.

[00:08:38] That constitutes driving is different. And if you think about that model on being a big national scale for cars. It’s exactly true about the little scale of companies. So when you see a firm that says it can give you predictive information because it’s got a large body of customers. [00:09:00] It’s just like putting an autopilot American car on a road in idiot.

[00:09:07] It’s not going to work. I think that’s the thing that basically and we told people all the time that what you need to understand nowadays what benchmarking you need to be part of because you can’t afford not to be part of these data sets, right? You just have to figure out because if you kind of put your head in the sand and say well I’ll just wait until it gets better.

[00:09:28] If you’re not part of it’ll never have some connection to you or or look like you in any way from a predicted perspective, right? So is that. Do you feel like it’s going to have to be a region by region conversation or industry by industry or a little bit of both to be able to get that through the array Company by company company by company and the large data set is going to completely ignore cultural context and cultural context.

[00:09:57] It turns out from what I can see the [00:10:00] actual very definition of work is contextual. You know some companies think that going to meetings all day is work they really do and they make a lot of money out of it. They tend to be companies that have billable hours, but they take going to meetings very very seriously and that’s where the work gets done and some companies think that going to meetings is a complete waste of time and inhibits work and so they don’t allow very many meetings.

[00:10:24] And those places do work but a software engineer in a place that’s meeting intensive and a software engineer in a place. That’s not meeting intensive or two very different jobs. And so what you need to know to understand if the data about Shopper Engineers applies in your company’s is there’s more than one but the scale of meetings to know meetings that matters.
[00:10:49] The batteries in it, huh? Yeah, do you think some of this can be resolved with you know, we’ve had this conversation before about how technology a lot more conversations about [00:11:00] finding a software that Taylor’s to a certain type of cultures and maybe they’re exactly like yours, but at least the culture the line a little bit better than if they had end and making sure that that’s the kind of company that you that you work.

[00:11:16] I think cultural alignment is a piece of the question and it’s a very divided my guess is that the software that’s good at diagnosing and implementing stuff culture. The culture is decade away because because culture is it is a sophisticated and complex problem set. It’s not. How long does the greeting Hub last in your company?

[00:11:44] And that varies, you know, the places I go where they don’t touch each other and their places I go where the the introductory hug takes 30 seconds. Yeah, that’s a broad [00:12:00] variation in social behavior. In some in some companies you’re allowed to tell the truth engagement surveys and then many companies you’re not and it isn’t written down anywhere which makes it hard for a machine to figure out what’s going on because there’s not necessarily data that shows it easily.

[00:12:21] You have to know what you’re looking for it to begin to see it is the date. If this is the challenge that we are facing in the future, you know, will you have some guidance in your reports that talk a little bit about what kind of decisions they should be making now in preparation for this world that we’re heading into.

[00:12:40] Yeah, culture based organization yet or culture or enough of assessment in some level from from a vendor to sort of really get the cultural conversation. You have to be able to make some level of decision today. Right? So you’re so you’re saying that she’ll have some of that right? Yeah. I think the biggest thing there are multiple things with the biggest thing is [00:13:00] understanding the ethics of your company and what ethics really means.

[00:13:03] I hate the word because it’s because it sounds ownerís and full of rules ethics. Really means deeply considering the consequences of your decisions, right? So an ethical organization and ethical 21st century organization will be slower to decide because it’s trying to suss out what all the implications of the decisions are and we’ve had you know, a hundred years of go fast go fast go fast go fast go fast.

[00:13:32] But now that we’re managing work forces that are part human part machine. It’s going to be very very important to get a good handle on what this might mean and and you know, if you think about the stuff that’s popping into the news all over the place these days. There’s an awful lot of If Only They thought bigger before they decided.

[00:13:54] This is the Boeing 737 problem. Right? It’s there wasn’t [00:14:00] enough ethical decision making based in and it can be done without it being a lot of people in black suits with frowns, you know, they can be done with joy and Delight but you have to get into the groove of doing well and I think you also have to build a business model that supports it to I think that’s the other conversation that we’ve had in the past, which is.

[00:14:23] I think a lot of times people think about ethics and they also think about it as as a constant you to write no can a sustainable business being ethical business at the constant conversation and many types of Industries and business and technology is going to be the same conversation, right your grandchildren listening to a table.

[00:14:42] This is going gosh back in the day. They thought that the choice was between ethics and money.

[00:14:54] Pragmatic on this one done. I agree with you totally but I think there’s a [00:15:00] pragmatic issue is that if financially be I think that make then then you have to figure out other ways to manage and monitor it right because people will do a lot of things if it works out financially right, but when it doesn’t work out financially then they’re going to have to have other mechanisms to sort of guide them in that direction General.

[00:15:20] Well, it’s such an interesting thing because Boeing certainly made short-term financial decisions that seemed to be profitable. And they may well have tanked their business doing that. And so the question of sustainability from a financial perspective this ties into and I hope we get to the news but this week the Business Roundtable, but which is the top 500 CEOs in the world said the idea that companies should be devoted to shareholder value is a bad idea and that company should be devoted.

[00:15:57] Well, no, that’s really only a 20 year-old [00:16:00] idea. It was not the way the business is run before the 1990s the idea that shareholder value is the dominant goal of an Enterprise creates the kinds of thinking that you’re talking about where if the dominant model of the Enterprise is short of the enrichment of employees and customers or the satisfaction of employees and customers.

[00:16:24] Which is what they’re saying, then you get a different a different set of things that you wouldn’t you wouldn’t ship a Boeing 737 with defective software if you cared about your customers because you’re focused on an outcome. That’s about what that customer is getting out of your product.

[00:16:42] Obviously Safety and Security is a big part of what they’re getting out of your product as well as having a. I get experience in the environment. But if you’re worried about your shareholder price that ship two completely different conversation, right? This is not a new conversation though. I guess the question is as well.

[00:16:57] Yeah, [00:17:00] exactly. Exactly. So let’s hop into the news before we run out of time. So predictive HR required an RPO. What do you make out of that? What do you make out of that? It seems like we’ve been talking about at least as far as you know, we’ve seen a lot and a lot of service companies picking up technology and
[00:17:31] call a little.

[00:17:39] And it’s all about the technology and they picked up a service business is this I mean, I don’t know if you know message three a RPO, but to me this seems like the. The opposite direction we’re seeing a lot of other organizations go where most technology organization themselves are trying to let go of their services where the services businesses are trying to pick up technology.

[00:17:59] [00:18:00] Is it unique to you to think they’re just because maybe there are more of an analytic software companies there helped a little bit of a different standard or this just a matter of bringing together their customers who maybe are already working together. This is the same company that also went out in July with a partnership with engaged talents to offer sure to vote and even broader platform.

[00:18:19] Can I get both internal and external employees? So this particular has been doing a lot of moves like recently. So yeah, I think this must be something pretty interesting because it makes my head hurt. You know the idea of an analytics company providing the services that it’s analytics dictate, right?

[00:18:38] That’s an interesting puzzle. And if you use 20th century models most things that combined recommendations Plus. The technology that was being recommended had to divest those things, but I’ll be very interested in seeing what goes on the phones and predictive HR very forward-looking and their [00:19:00] relationship with engage Talent is sort of an example of that.

[00:19:03] They have the capacity to do all sorts of science-based predictions. Somebody’s going to have to give me a deeper explanation about what the integration of an RPO and that means. Yeah, I’ll be interested in finding out if their plan is to maybe trying to build a better mousetrap try and do a better job and maybe fixing the RPO for us is a lot of what we see is the RPO processes by these Technologies to make their existing processes more efficient.

[00:19:30] It would feel to me like the predictor the predictor major that I’ve sort of seen there. You know that maybe they’re trying to take their data and do something different. We don’t know until we get a deeper dive. But yeah, it’s very good. There’s a big Trend that I’m seeing RPO style companies becoming technology providers and they do it because they have a different business model.

[00:19:53] Right? So in our po can sell technology on a transaction basis and they don’t have to bother with all [00:20:00] of the subscriptions and blah blah blah and so they have different price points and the RPO companies are all trying to automate sourcing so this could be kind of a different way of doing that.

[00:20:11] That’s my thinking because I think you know what we’re seeing from OC rpos is they’re trying to automate how they do their business already. Right? What would be interesting is is are we going to try and do our po differently, so
[00:20:27] that would be interesting. Yeah, there’s a lot.

Yeah, and you know, what? Is there some other interesting thing? I think you know, most of the news this week is all about recruiting. I couldn’t find a whole lot of other shirt. Big announcements going on elsewhere. We also saw a fetcher and smartrecruiters, which is another two big groups of big names that are getting space.

[00:20:51] They’re combining around there. It’s just a partnership. It looks like but they’ve integrated they’re there to systems to create a better. I guess they’re [00:21:00] coming up next Generation outbound recruiting platform and little bit like this is going to be a mixture of. JJ and high volume and now they can do more tailored recruiting based off of the conversation they’re having here.

[00:21:11] But again, it’s this idea that the recruiting tools need to be combined in some way that if they they’re good enough in and of themselves, but we’re seeing more of this conversation, right but they have to have some actions to each other. Yeah. There’s a lot of flailing around going on out there.

[00:21:29] I’d like to start with Business review article about predictive recruiting. Right. How do you how do you know who’s going to quit without getting any inside information from the company? It’s such a good idea. It’s such a good idea. I think the car I think there’s already been engaged Talent here.

[00:21:45] But the idea that you can accurately predict who’s going to leave a company so that you have a better chance of having a coherent conversation with them about taking a new job. That’s what the the Harvard Business Review piece is about and it [00:22:00] looks like there’s actual science and validation here.

[00:22:03] Well, they gave out a survey is what they did to a group of people based off of. I think they had the idea of who would be no possibly rest and then I gave a survey out of who would be interested in looking at job opportunities and so follow through those two and most likely versus least likely say this is a mixture of serving like validation through survey plus taking the data that has been analyzed and giving a sense.

[00:22:27] But if you can’t get back to your earlier conversation this works in this kind of companies. Analysis has been done in right but there might be other type of somebody or cultures that it might not work in right? So this is very much a cultural conversation. I would think so. That’s an interesting idea.

[00:22:42] I don’t know how you tell that but but but of course, there’s cultural variation. That’s a really astute notion. And Gordon cuz they’re talking about they have a sample about 500,000 individuals who they’re doing this with that’s a lot when it comes down to your headline validated. What kind of industries that I got in there.

[00:22:58] What type of Workforce types do [00:23:00] I have in there is 500,000 and up in a world of seven billion people. I don’t know if the major all the questions that have to be asked but yeah, it would be interesting to see the data in the same Bahamas because they’re doing a lot more. That’s right. Okay. And is this the last one how to make I don’t know.

[00:23:16] Let’s see. Where do you want to go next? We got room for one more. Well, I think there’s some interesting stuff going on in the VR who want to switch gears a little bit away from than what’s going on in the recruiting space if you’re watching with happening and learning a lot right now, but. But winning space is heating up with virtual reality.

[00:23:36] Lots of virtual reality going into preparing organizations that there was a big story this week about Walmart partnering with one of the VR headset groups and they’re going to be doing unfortunately but shooter preparation, right it were all of their Walmart employees. We were virtual reality environment and they’re thinking that could save thousands of lives and situations that like we hang out Paso.

[00:23:58] This one in particular [00:24:00] is a VR. That is developed with a employee that you’re letting go. So it’s a practice firing process and the employees personality demeanor what they say how they say changes based off of how you interact with them and the things you say and so it’s not just a pick and select.

[00:24:22] It’s an actual Talking virtual reality. And this to me is getting to really know it goes back to their using AI in this and is to make them some training examples and some really interesting presort of Assessments about how people might react to certain situations. And this is next Generation training.

[00:24:43] I’m not exactly sure though at this point if we’re comfortable with the fact that. This artificial intelligence can do as well for predicting how people would react to certain thing as we think it can but this is where it’s heading right now.

Well, yeah, and and so I’ve spent a fair amount [00:25:00] of time talking with Kyle Jackson who runs tailspin, which is the company that produces this product and what I’d say is couple things one is you don’t have to have the perfect rendering that’s what’s interesting.

[00:25:13] If you get close what matters in this simulation isn’t necessarily what the simulation does but how you respond. And so there’s a fairly narrow range of responses to the situation and this provokes them and so it’s because in difficult conversations like firing somebody the question is how do you do it effectively and gracefully and with compassion and that has to do with how you the training is how you manage your emotions and your responses in that circumstance.

[00:25:52] Right. And so that may not require a complete High Fidelity full range set of responses. It may be that they’re only 10 or [00:26:00] 15 points that matter in that I don’t know but but that’s the kind of thing. We’ll get to look at isn’t it? Exactly I guess for me and this is the first step towards and so we are seeing a lot of this stuff coming out of this is not the only one there’s multiple story.

[00:26:14] And the last month about the virtual reality training and I think the more and more we get into and didn’t get into the same situation. We’re getting into with the recruiting situation in which if someone doesn’t react the way your program said they would react when you use the language you said you’re going to use how does that you know, you’re starting to get into this gray area of what I’m teaching you and what you’re experiencing and then all the sudden you get into the real world situation and if it doesn’t quite match up, Are you able to make the switch pick up or change how you’re doing?

[00:26:45] Things big enough is the system training you to something. That’s not quite right. We don’t know yet until we get through. All this process is right. So it’s better than nothing obviously right now, but it’s an interesting I think things will be watching and calibrating. Are we doing the right thing with this virtual reality?

[00:26:59] Because it puts you [00:27:00] in a much more realistic and heightened environment than if you’re just answering on a piece of paper or something like that or is that. Yeah, I think part of what you’re getting at is what happens with all of this stuff. Once you start really studying an arena in a way that allows you to introduce intelligence into it.

[00:27:18] You start to have questions that you didn’t know you had before so, you know, you know the question that I have when you say it doesn’t cover all of the circumstances ends up being well, how would you know what all the circumstances are and the really interesting thing is if you start training with tools that actually learn you can start to discover what all the circumstances are in the past.

[00:27:44] All you had was somebody’s theory of what they were. And now you can have a date now. You should have a data-driven view. But that means in the beginning the training is going to be less effective than it will be in the end and I think my questions coming down to while we’re getting to that training [00:28:00] period is there a point at which being in such a hyper realistic environment and maybe learning that the perfect way of doing this does it have more of a negative impact than being in a different type of environment and I don’t know the answer.

[00:28:13] Good morning. We put people in situations which are emotionally charged in one way or another the more you might end up with a things happen that you don’t expect right both for the people who is being trained and for when they get out into the real world. So it’s what happens anytime we go through a transition like this and need to develop more training and more experience and a lot of interesting stuff going on.

[00:28:33] Okay, so another great show under the belt. Thanks for making the time in your busy trip to Ohio, and thanks everybody for tuning in. You’ve been listening to HR Tech Weekly One Step Closer with Stacey Harris and John Sumser and we will see you back here next week.

Bye. Bye now.

Thanks everyone. Bye.

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