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HRx Radio – Executive Conversations: On Friday mornings, John Sumser interviews key executives from around the industry. The conversation covers what makes the executive tick and what makes their company great.

HRx Radio – Executive Conversations

Guest: Jim Stroud, VP, Product Evangelist at ClickIQ
Episode: 322
Air Date: April 12, 2019




Important: Our transcripts at HRExaminer are AI-powered (and fairly accurate) but there are still instances where the robots get confused and make errors. Please expect some inaccuracies as you read through the text of this conversation. Thank you for your understanding.

Full Transcript with timecode

00:00:14:11 – 00:00:32:01
Good morning and welcome to HRExaminer’s Executive Conversations, I’m your host John Sumser and today we’re going to be talking with Jim Stroud, who is the eternal industry veteran. And these days is hanging his hat with a company called ClickIQ, how are you Jim?

00:00:33:00 – 00:00:34:11
I’m doing fine sir. How are you?

00:00:35:01 – 00:00:43:21
I am on top of the world. The sun’s out For a moment. The California rains have stopped and so things couldn’t be better.

00:00:44:12 – 00:00:49:11
I get the image of a Disney movie with birds singing and dancing animals that kind of thing.

00:00:49:24 – 00:00:59:13
Yeah exactly exactly. It is California and Disney is just a reflection of what it’s actually like to live here. And so few people really understand that.

00:01:01:25 – 00:01:04:28
So, introduce yourself, tell people about Jim Stroud.

00:01:04:28 – 00:01:33:05
Sure sure. Well I have been in the sourcing and recruiting world for two decades which is hard for me to believe and I’ve been fortunate enough to work for such companies as Google, Microsoft, SiemensRandstad Sourceright and quite recently now I am the V.P. of product evangelists for North America for ClickIQ which is a automated job advertising platform startup in the UK which is now branching out to the U.S. because we’re taking over.

00:01:33:06 – 00:01:43:17
It’s great. It’s a lot of fun to be on one of these world-bending things. So tell me a little bit more about how you got to work. What do you do, Jim Stroud?

00:01:44:16 – 00:01:49:05
That is a good question. The question I my family asked me all the time is it.

00:01:49:12 – 00:02:20:19
Well they are in my present role. I evangelized click IQ by talking to good people like yourself and also potential clients and you show them the virtues of our product how we can save them time and money on a job advertising but also operate in about leadership capacity where I. Speak at conferences. Teach people at different events about the world of work feature work in particular as well and also produce content that draws people’s attention to click IQ and the things that we have to offer when not doing those things. I

00:02:20:19 – 00:02:32:11
I am speaking at source code so I can see why I’m writing a book. Or on producing a podcast of my own or a video series. All about the future of work or a feature of life and everything in between.

00:02:33:02 – 00:02:45:23
So how does one get on your list. What moves about where are these podcasts and books feature like movies or Netflix series reside.

00:02:46:12 – 00:03:01:02
Yeah. Everything and anything that I’ve made it can see on my website with Jim Strout JM and Ciara. Jim Strout that cop followed me there. Get to connect with me on Lincoln which is also a good place. Or on Twitter at Jim Stroud.

00:03:01:09 – 00:03:08:02
Jim Stroud OK so now we’ve done the June shouting. Tell me. Q What’s the deal with you.

00:03:08:09 – 00:03:12:17
Sure well look I you know I get smart.

00:03:13:15 – 00:03:46:16
Oh well not quite not quite click I as an automated job advertising platform it sits on top of you. ATF takes your job and posts out for you. So it’s sort of like a central hub for all of your media. All of your job advertising distribution is also a central hub for your media spin. So if you have relationships say with Indy you zip recruiter and several others you can sort of manage it all from one place. You also can manage how much money you’re spending on different job boards one place and it also will optimize your spend.

00:03:46:21 – 00:04:17:13
So essentially you valuable to us if you wanted to distribute your jobs to 100 different job boards and you are getting the clicks and applications you need. There is no need to spend extra money because you’re already getting what you need from the organic placement of the jobs. But if the jobs are not performing you’re not getting clicks an application then those trials will move to the next level where it goes in the premium spots on different job boards. After that. It would go to social. So your job adverts would appear on Facebook and Instagram where people can engage with a chat bot

00:04:17:24 – 00:04:41:26
And if for some reason you still are going to cuts in applications then it would go out to Google where people can see it through different Google at so your job advertising will be seen and it will save you money because it is working on one job board and it’s cheaper than the other. Well we’ll keep showing it on a cheap spot save you money while getting the clicks and applications that you so desire so you get clicks repetitions.

00:04:41:27 – 00:04:47:08
How do we know if the application is really good. Does that matter. Or is it just volume that you’re after.

00:04:47:23 – 00:04:58:19
While the quality of the applicants. I can’t judge you per say because once they’re in your TSB they’re sort of out of our. Reach to monitor. So I can’t really speak to that.

00:04:59:01 – 00:05:03:28
But I can’t speak to getting you to clicks and applications from your other clients. Certainly.

00:05:04:12 – 00:05:20:03
That’s interesting so it takes an administrative work away from somebody who would buy jailbirds but it’s sort of more work to do evaluating transaction. So yeah I guess you could say that I can see that

00:05:20:14 – 00:05:34:01
But you can also we also have different rules you can put in place as well. So let’s say that you only want 20 applicants this week so you can say OK once you hit a number of 20 applicants take the drop out. You certainly have that control as well.

00:05:35:16 – 00:05:41:04
We should have a long conversation you probably have a pretty interesting idea about

00:05:41:24 – 00:05:57:06
Whether the cards discrimination in hiring is legal today. You can measure quantity but could you account for the varying levels of access you know women tend to not apply as quickly as men for example

00:05:59:24 – 00:06:06:09
If you have a hard time line then it might be that you get more men than women. I don’t know.

00:06:06:17 – 00:06:39:23
Yeah definitely I don’t know. But then decide what kind of time limits you put on a job that I mean or how many applications because you could say leave a job up for 100 years and in the hundred and first year. Three women would have applied. So that means it’s discriminatory because you cut her off at one hundred a year but you know you got a hundred applications. So to speak rather I’ve said I’ll have to use applications rather and then once you cut it off at a hundred applications then you know the one first person may have been a blind and deaf minority woman.

00:06:39:23 – 00:06:46:05
I don’t know if that’s really hard to sort of. Qualify but it’s an interesting question altogether though I don’t know.

00:06:46:22 – 00:06:48:25
Well a great offering. Are

00:06:48:25 – 00:07:00:27
Are you following the evolution of intelligent tools elsewhere in recruiting besides you. Yeah yeah yeah I see I see a lot of activity in this space and

00:07:01:23 – 00:07:20:18
They sort of all fall in two different categories. And without mentioning any names for some that I’ve seen and some that I can’t say that I’ve seen. Different categories we sort of put these A.I. tools in would be a I for silver medalist. So I call it. So I can be modeling yes for people who interviewed well but didn’t get hired. To do some other

00:07:20:26 – 00:07:28:13
Well qualified candidate. This trend would. Find people in ATX who were. Super medalists in one realm

00:07:29:00 – 00:08:03:06
Didn’t get the job or perhaps their ideal for another role. And I’m seeing a lot of tools around that finding. The gold in rather the silver. In the ATF. Then I’m also seeing a I for had bias so I don’t see a lot of that. All this developed to fight unconscious bias which of course a huge topic last year still sort of a huge topic issue. Because of all the diversity inclusion. Conversation going on. Seeing a lot of a eye for candidate engagement. Because nobody likes the black hole resonates that it has become

00:08:03:23 – 00:08:36:18
So you’ll see a lot of chat bots was going to create a divide between candidate screening and application status. And also well I don’t see a I’ll call it because in marketing. To a lot of that as well. Application of marketing best practices analytics multi-channel use targeted messaging that kind of thing. That. A lot of the A.I. tools that are out there even the ones that are not A.I. but kind of playing the way. They can be one of those kind of categories and that’s what I see a lot. It’s sort of. As. I see it all if that is the wax poetic for a minute

00:08:37:00 – 00:09:07:22
I see it all very interesting from the standpoint of I like seeing a lot of new technology out there doing a lot of different things especially if it takes away repetitive path. But I think there is a danger. Well thank you. A word of caution from promote a tool. Because I think there is a chance of people becoming overly reliant on those tools rather than human judgment. So I think no matter what A.I. to use or any kind of super tech to you

00:09:08:08 – 00:09:38:21
You have to have a human in the loop. Otherwise you opening yourself up for Terminators to come. Case in point I was reading actually podcasting about this. Recently. About. The predictive algorithm that IBM has. Where they have. Said that they can be with 90 percent accuracy he going to leave the organization. So once the magic algorithm says that John is going to leave the organization for whatever reason. Let’s go ahead and reach out to John now offer him a promotion make a little extra money

00:09:39:07 – 00:10:09:13
Maybe give him some sweet assignments to work on. So we can keep him. In the on the payroll. A little bit longer and sell. That’s fairly cool. If it can indeed predict a 95 percent accuracy. But on the flip side of that it makes me concerned because I’m wondering. If the machine says John is going to leave. Let’s go ahead promote him. Or maybe if the seen said John is going to leave. Let’s not. Worry about advancing his career because the machine says he’s gonna be leaving us soon anyway. Instead let’s

00:10:09:23 – 00:10:21:00
Let’s focus on John because the algorithm says he’s going to be here for a long time. And let’s go ahead and give him better opportunity. Yeah. So yeah that’s a little bit of a rant there. What do you think of that.

00:10:21:00 – 00:11:08:26
Well you know there is one of the interesting things about the technology is that there’s no consolidation of resolve. So this is the evolution of and recruiting into a science but we don’t have peer review of this stuff. It’s relatively clear that in some of the more advanced technical environments flight risk forecasting is prohibitive and flight risk forecast to use prohibited because the only result you can correlate with having for it forecast is increasing attrition because you do exactly that kind of thing that you’re talking about you get a report about somebody you see they’re going to leave and then you start treating them differently whether you work to keep them or work to let them go.

00:11:08:26 – 00:11:40:15
You treat them differently once you get the report and because you treat them differently it’s not more. This is your relationship with that employee. That’s the only thing that happens. The whole organization understands you know when somebody stops giving assignments that something’s wrong and people don’t make long term commitments to project with people they view as short time timer’s the consequence of having a flight risk forecast can be devastating.

00:11:40:18 – 00:12:06:16
And because there’s no sharing of how these things work in the various environments there turns to them then we don’t get a coherent learning about it. So my guess is that the flight risk forecasting stuff that IBM is peddling right now won’t last very long. As soon as people start catching on and practitioner organizations start sharing information about what works and what doesn’t work.

00:12:07:08 – 00:12:26:11
Yeah. Two points on them to do a protocol there. So on a pro side of the algorithm. Another thing that IBM does in concert with that thing called my T.A. stance remarks something I forget I say advancement I’ll go I don’t know that it’s called my fiancé. Not to be confused with wait and see. What it does is it looks back

00:12:26:28 – 00:12:29:18
It will be forever confused with body OCA for

00:12:31:12 – 00:12:32:13

00:12:32:26 – 00:13:03:03
Yeah. So what it does is it looks at the trajectory of the company and the different projects the company will be implementing to get to where they want to go and then they will look at a skill set of the workers at the company and then they’ll send out an email or notification of some sort that says hey John our company is moving towards the north and you’re here in the south. What’s your take on some projects like one two and three that’ll give you the skills you need.

00:13:03:09 – 00:13:42:07
So that by the time we’re ready to move more towards the north you’ll have the skills to go to North West. I’m oversimplifying it but that’s essentially what it is. And I have read recently I think of CNBC which is why I got this information that some big percentage of the promotions were as a result of that algorithm things like 12 percent or 18 percent or something like that or something like that. So I can see how the algorithm in that case benefits in sort of a win win. But on the flip side of that I have to wonder to your point what if I am a IBM worker and I don’t get the plum assignments and I’d say IBM anywhere who’s using an algorithm like this.

00:13:42:09 – 00:14:16:09
I’m not getting the plum assignments. And so I decide to leave and Agrium does pick me up and then I’m going to leave. So you don’t pitch to me and offered anything like that. Right. So then I go I leave the company you are about to leave the company. Did I find out the reason why my career had stymied the organization is because some machine said that I wasn’t going to stay. And so I could get mad and say well what did the machine say about me. Can I see the data you’ve collected about me because maybe I can explain this in a way that a machine didn’t pick up but a human being would say so do I.

00:14:16:10 – 00:14:48:27
And do I have control of the data you’re collecting on me or that confidential to the company and only H.R. people can see it and I can’t see our permanent record so that’s why to what if I get really indignant and I decide to sue the company and say you know what this company has discriminated against me I’ve been discriminated by algorithm would you probably be a future legal term or something. The machine said I was going to leave so the company did not give me a fair chance. So I’m going to sue the company because the machine discriminated against me.

00:14:48:27 – 00:14:55:29
This is you own the machine and I’m suing you. So that’s something else I think could possibly happen in the future. What do you think about that.

00:14:56:00 – 00:15:01:03
That too far. Let me take the last call you just figured out I have a visual.

00:15:02:03 – 00:15:45:16
Yeah I really can see in the future a future job or rather a future business. So is this thing looking for a hot startup to fund b become an algorithm auditor you know go to these companies that say we use a machine to make sure we’re not bias. And then you go and you audit the machine. And test to see if it truly is unbiased. Or maybe go to. Law enforcement offices and say Let me check your magic algorithm machine that matches people’s faces with felons in your database because quite recently I thought his team quite recently the ACLU did this study where they tested some machine to see how well it identified it identified felons

00:15:46:01 – 00:15:51:29
And a ACLU gave them several politicians pictures from Congress

00:15:52:06 – 00:15:55:29
Right. And so the machine said about twelve of them are crooks.

00:15:56:01 – 00:16:13:24
Now these are politicians that have the machine was correct. I know of a search that it took 12 or so people that did not have criminal records but the machines that these are in fact stolen. So someone who is an algorithm auditor could do stuff like that. It’s hard to make a bazillion dollars overnight.

00:16:14:03 – 00:16:39:00
Oh there’s already we’re I’m already getting sort of requests for that kind of work. That’s coming for a record a week. Yeah. Well part of the problem is biases or bias is an interesting thing. There are kinds of voters are illegal and those things we need not do those things because they’re illegal. There are kinds of voters that ought to be illegal

00:16:40:05 – 00:16:52:12
And they are women still or are entitled to equal rights or constitution. And so. There is a level of bias there that is legal still and shouldn’t be.

00:16:52:16 – 00:17:13:03
But then there are other kinds of barriers that are necessary and important and absolutely necessary and important that we understand that we’re an electronics company not a retail store. And so the people that we hire are good and the electronics they’re not behind the cash register customer service.

00:17:13:16 – 00:17:56:24
And that is our bias of hiring. And we wish to get better at that. All right. Every culture is an expression of bias and there is a challenging thing that I’m sure you know more about than I do in diversity remove collusion that is diversity is the opposite of cultural diversity is the celebration of difference in culture is the celebration of sameness. So the idea that you don’t want the celebration of sameness is all about bias the celebration of differences about the opposite of bias and the right answer for every individual company is some blend of those two things not the elimination of bias.

00:17:56:25 – 00:18:11:11
And so you know it’s like it’s like we got the discovery of the hair cutting razor and we’re going to give everybody a number to buzz now because of the razor. The truth is some people need long hair

00:18:13:21 – 00:18:29:19
you know. So this is a tricky area business. The commercial tendency to jump to conclusions is starting to interfere with our ability to get things done. I think so. Do you see recruiters are going to be replaced by machines now.

00:18:29:24 – 00:18:39:19
No that I’m a big proponent of the Tony Stark model where she’s going to augment our abilities that they won’t take away our ability.

00:18:39:21 – 00:19:00:24
They will take away jobs that they did sort of take away different functions. You know when I see something of course being automated and becoming part of the robot world like you know a resume a collection and passing into these scheduling that kind of stuff. But there are certain things that I think that are intrinsically human so that. Because of that recruiters don’t have to worry about it.

00:19:00:27 – 00:19:06:08
For example I could see recruiters being very good. They already are closers and negotiators

00:19:06:24 – 00:19:38:17
Negotiating with the hiring manager negotiating with candidates negotiating over salary. That kind of thing I don’t see a machine being able to do that. I see recruiters becoming more like brand agents. You know. So it’s one thing to say this job is awesome these companies often come over here and work for us but then when a candidate researches that Astral that same recruiter. They should be able to see on their LinkedIn or on their Facebook or Twitter something some sign that they actually believe that they work for a great company.

00:19:38:17 – 00:19:41:25
Otherwise they may come across as just a used car salesman to a candidate.

00:19:42:11 – 00:19:48:15
So a recruiter has to be really good knowing how to champion their company and their company’s culture.

00:19:48:15 – 00:20:20:04
I see recruiters also being released great marketing strategies. The same way marketers create a persona of the person they want to sell to. Same way they build an ad campaign. Same way to make you an email campaign. Same way they may do an advertising campaign. The same skills that recruiters need to have as well. And so I don’t see although some of that can be automated of course like to click I keep for example. But not all of it. You know this took the skills that take your imagination to teaching thought problem solving those kind of thing.

00:20:20:04 – 00:20:53:27
Those kind of soft skills you definitely need a human being for and those are things machines can’t do. And so by virtue of all that I don’t see robots taking recruiters jobs away you know just make it easier for recruiters to actually be more human because it’s the humanity that we have that can’t be duplicated by machine. And that’ll make us more valuable which is interesting to me too from a standpoint of every different scholarly papers and I’m really feeling really nerdy reading different articles about how. There is the millennials are losing interpersonal skills.

00:20:53:28 – 00:21:29:13
I read articles about that I read articles about how there. Is a lack. Or a seemingly lack or a downward trend in emotional intelligence. So I think a lot of people of a certain generation. Are losing the ability to look someone in the eye and talk to them to. Give a cohesive argument as to why they like or dislike something and the loss of those skills would make it harder for them to be a recruiter. So I think if a recruiter wants to stay valuable. From this point for. They really need to focus on building up their interpersonal skills and one of few ways to do that

00:21:29:21 – 00:21:35:03
Is to volunteer. To go to church and. Serve in a soup kitchen

00:21:35:11 – 00:21:57:21
You know go to no folks home as we call it senior living this is an amazing facility and good with people and talk to them and you will quickly discover how good you are with people in general. You interact with people I guess. The best way that I could say that. Joint organization like Toastmasters Sydney used to standing in front of people and talking. And actually if you are single

00:21:57:28 – 00:22:02:11
Is sort of weird. Listen. Yes. But I understand it works

00:22:02:25 – 00:22:34:00
If you are single go online and do a search on t a. Can you a sense or pick up artist forums. In those forms. You’ll see different tips and tricks on how to build a profile on the type of person that you want to pick up so to speak the type of language you can use to refer the person to you. And then using that information you can. Fall in love or something similar. Although the aim is different in the. The basic skill sets are still the same.

00:22:34:06 – 00:22:42:12
You’ll learn how to look at people how to pick up on non-verbal signals and that’ll help you when you’re interviewing people and talking to folks in that kind of thing. I

00:22:42:12 – 00:22:56:00
I feel like I’m I’m well. Well you’ve heard it here first. Jim Strouse recommends recommended mastery apply for a single bars as a way to become a better recruiter. That’s what recruiters should do.

00:22:56:01 – 00:22:59:08
Nice. It’s perfectly happy with rejection too.

00:23:02:27 – 00:23:17:16
So we are blessed. This has been a lot of fun. We’ve blasted through our time together. Take a moment and reintroduce yourself and if there’s something we should dwell on from all of the wisdom you’ve been dispensing here what is it.

00:23:18:10 – 00:23:39:03
Well look me up on my website. JimStroud, www J I M S T R O U D, Jim Stroud dot com, you can also look me up on Linkedin and connect with me. And if you are a talent acquisition manager or an H R leader and you want to save money and optimize your job advertising definitely look up clickIQ or actually you know what, send me an email you can reach me at Jim at ClickiqUS, C L I C K I Q U S dot com

00:23:46:06 – 00:23:49:04
And I’ll talk to you about that their.

00:23:49:14 – 00:23:50:18

00:23:50:26 – 00:24:11:09
Thanks for taking the time to do this Jim. It’s been fantastic to talk with you. You’ve changed my mind abuot a couple of things, now I’ve got to go learn some pickup lines, That was great. That was very very memorable. Thanks for doing this. I’d love to have you back to do this again sometime.

00:24:11:21 – 00:24:11:24
Any time sir.

00:24:13:03 – 00:24:37:07
You’ve been listening to HR Examiner Executive Conversations and we’ve been talking with Jim Stroud who is a raconteur man about town and the vice president of evangelism at ClickIQ which is a programmatic advertising company for recruitment. Thanks for tuning in this week and we will see you here same time as usual next week. Bye

00:24:37:07 – 00:24:46:28
Bye bye now.


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