Exploring the Role of AI in Hiring

Paul Weiss 1:28
Alright, so welcome to Bluewave’s webinar series The Current. It is a continuation of our conversations on the demystifying AI topic.
This webinar series is designed to provide information on the latest technologies and how they can help solve your business’s challenges.
When we look at ROI opportunities for our clients, we look at the building blocks of technology, people, performance and experience all in service of company efficiency and driving revenues.
Today we will be exploring AI and how it can drive positive impact in the people part of that equation and more specifically in hiring.
If we can all agree that how we start impacts, how we finish, then we can all agree that the hiring journey and its successful outcomes are most critical to company success.
Along those lines, today we invited our strategic partner, Daniel Ash, CEO of Journeyfront, to be our guest and today’s conversation, I will be your moderator.
I am Paul Weiss, vice president of solution advisory here at Bluewave.
Welcome Daniel.
It is nice to see you here today.
Thank you for joining us.

Daniel Ash 2:41
Paul, good to be here.

Paul Weiss 2:43
Excellent.
Today will be an open discussion based on some simple question and answering and we hope that all of our viewers find value and can take away some good insights from our conversation today.
Daniel, before we dive into the questions, please feel free to introduce yourself to us a bit about Journeyfront as well.

Daniel Ash 3:03
Yes.
So first of all, great to be here.
I’m proud partner with Bluewave.
I am the CEO, founder of Journeyfront.
We are an intelligent hiring suite that helps companies improve hiring.
Speed and accuracy.
Our specialty is particularly around volume hiring, so we work with organizations, call centers, warehouses, manufacturing where they’re hiring a lot of people in a given period of time.
Often these organizations really struggle with turnover, keeping those people on the first three or six months driving performance out.
It comes associated with with that massive hiring process that they manage.
So it’s good to be here looking forward to diving into some interesting topics.

Paul Weiss 3:47
Excellent.
Well, thank you, Daniel.
So a few questions for you.
Let’s start kind of broadly with large language models like open AI and chat GPT, creating universal awareness of AI and basically every commercial you see on TV now from Amazon and IBM and everybody else that has their brand, that AI, that is an expression of AI, a version of AI, but not really very specifically the utility of AI solving specific use cases like someone like Journeyfront may.
And so there’s probably as much confusion as there is excitement about AI in the general, both kind of consumer and business marketplace.
Do you, from your experience, from what you’re seeing and from the businesses you’ve already impacted, do you believe that AI and specifically Journeyfront’s expression of that can fundamentally change how organizations hire and track the performance of their people and continually improve the hiring process?

Daniel Ash 4:52
The answer is absolutely.
Whenever you go through a technology wave like this, it unleashes new opportunities to drive ROI in areas by an order of magnitude.
Hence, organizations need to be taken this seriously.
Umm my perspective is, however, that the fundamentals of let’s say hiring, which is what we’re talking about today, still apply.
So in that sense, at the end of the day, the value props that AI is driving are not new.
They’re the same value props that have always been driven in an as it relates to hiring.
Certainly hiring will be transformed to drive improvements in speed, efficiency, accuracy, achieving levels not possible before AI.
But to be clear, those have been the goals prior as well.
So yes, I think order magnitude more potential now than there’s ever been, which is exciting also can create probably some anxiety for a lot of organizations because that means you need to not be sleeping on this opportunity.
However, all of it comes down to still fundamentals.
Understanding the problems you’re trying to solve, the ROI you’re trying to drive, and in what areas.
And so I think as is the case with any new technology where it’s, you know, the shiny new object, you still don’t want to stay grounded in, in the objectives and the value props that are fundamental to in this case, we’re talking about hiring and what the focus of it should be.

Paul Weiss 6:22
It’s very interesting that you say that and with the broad perception of AI possibly being offered a prompt and it tells me things or creates content or creates images and that’s the experience with chat, GPT and open AI to your point, organizations have been seeking automation, have been seeking acceleration, have been seeking, learning faster or aggregating data sets for a very long time.
You know not to overcook the hiring conversation, but I actually like to use the analogy of hiring an employee as to thinking about the utility of AI in an organization.
We believe that it is always an augmentation conversation, a Better Together AI, and humans and AI’s going to bring skill set to the table that maybe humans by ourselves cannot and the same is true in in reverse as you consider where the utility of AI is in your organization, you think about and.
And I would believe it to be exactly like this.
You’d write a job description for what is the the work I need done.
What is my expectation of the impact and outcome of that work?
How could I measure the success of that work being done, and how would I budget economically to fund that hiring of that employee?
And we really view the implementation of AI in exactly the same way in any organization considering where AI can affect it.
Maybe that’s an simple place to go.
Think about where in your organization automating accelerating generating content getting better, moving faster, whatever it is, can benefit from AI.

Daniel Ash 8:16
If you’re.

Paul Weiss 8:20
Start there.
Think about the job.
Think about what the outcomes are.
You’re seeking what you would budget in connection to those sought outcomes and make great decisions.

Daniel Ash 8:30
Yeah. OK.

Paul Weiss 8:30
What we’re finding then with Journeyfront is that you’re doing exactly that really right in the challenge of the hiring practice and for those involved in the operation of hiring, they’re well aware of those challenges.
Many of us that we that sit here today may not be as aware of not just the challenges of accurate and efficient hiring, but also the significant benefits of improving both the accuracy and efficiency of hiring.
So let’s talk about that, Daniel, from your experience, how is journey fraud and you’re AI being used by leading organizations to drive faster and more efficient hiring?
And then we’ll talk about the accuracy of hiring.

Daniel Ash 9:20
Yeah.
UM first, if I if I could just draw on that analogy, use, which I thought was a great one.
If you were deploying AI akin to, you’re creating a job description, you know, how would you approach that?
Best practices around creating a job description are around you.
Start with the end in mind.
Like what are the outcomes that this person in this job will have to achieve and the reason you start with that end in mind is because if you do not everything you you write around the traits this person has to do, or even the activities we choose to emphasize or that they’ll need to engage in during the job, maybe off target with the ultimate end in mind, right?
And then the second now, uh, aspect to that analogy, drought is AI is not going to be cheap.
It’s a sophisticated technology that has massive ROI, so there will be costs associated with it, not just the cost of let’s say, a solution that you’re purchasing, Journeyfront or otherwise or building something your own.
But even just the man hour cost of implementing it, because that cost is so high, akin to any role that you were hiring for, where there’s a high cost.
Umm, it’s going to be all the more important that you’re really focused on the ROI this this thing will bring and you’ve called out the first area which is faster or more efficient hiring that certainly is one of the ends within hiring in general, right?
You have to have a certain speed of that process.
If you’re hiring process takes a year by the end, the time you get to the end of it, there’s no candidates left.
They’ve already gone elsewhere, right?
And data shows that top candidates are off the market very quickly and some cases research shown in within 10 days efficiency, right?
It does matter how much this hiring process costs your organization.
You could throw 1000 people at it and probably have a good outcomes, at least as relates to hiring the right people.
But it is a very expensive process if you don’t invest in being more efficient with it.
So certainly AIS focus areas automating of most tedious or costly.
In some cases, the most important tasks associated with that hiring process can go a long ways to driving ROI for the business.
So we’re talking automating candidate screening, which is Journeyfront specialty in the evaluation of the candidate or the different ways we can speed up that process, improve the efficiency of that process.
Certainly AI is being used to automate a lot of the candidate communications and interaction chat bots and so on.
I’m automating things like recruitment, marketing, you know, scanning large sets of data on job boards.
What have you and pulling that in but at the end of the day, it’s all about.
Let’s take this hiring process with all the steps that it involves and all the cost associated with that and.
And how can we use the automation the AI brings to dramatically reduce the cost of those things?
One other area, which is one of my favorites is AI, and we’ll get to this when you talk about accuracy.
Can also identify parts of the hiring processes aren’t needed at all to begin with, right?
There’s nothing more efficient than not doing something then taking something you were doing and no longer doing it at all.
Right.
And certainly if there’s a step in your hiring process that’s unnecessary, think of it like a manufacturing process.
Of course you should remove that process because there will be savings accordingly, but at the end of the day, that is one of the value props.
When you go back to your job description analogy, that AI should most certainly focus on is, yeah, deficiency speed of that hiring process.

Paul Weiss 13:10
There are thousands and thousands and thousands of organizations.
Everybody hires at various volumes for different roles and reasons, and every single one of those organizations may or may not have visibility into the efficacy of each particular step in their hiring process.
Is it adding value?
Is it simply creating lag or wasting time?
Is it in some cases even Contra indicative of a good hire?
Am I getting bad information or bad output from a profiling exercise or something else that may otherwise inform how we hire and how would we ever know that and that that tracking the life cycle of an employee back to how they were hired and learning continuous improvement is something that I think is huge value Now I’m getting ahead of myself because right now we’re talking about the faster and A and efficient hiring and these benefits tend to be, let’s say more immediately realized right hours spent in each step.
So talk a little bit little bit about just some specific examples.
You gave us a couple, but walk through a typical hiring practice, practice and show us where I can find immediate benefit in reducing man hours of effort or increasing the ability to scan and decide on candidates.
So I don’t lose great candidates as well.
Talk a little bit about that and then I want to shift to the accuracy discussion.

Daniel Ash 14:51
Yeah. So.
Organizations are different in how they manage the workflow of their general process, but generally speaking, it’s they source applicants, often across a variety of channels called could be social media, could be LinkedIn could be a job board like indeed or what have you could be employee referrals.
They’re often coming in from many sources.
Not all sources are created equal.
Some are cost more, some lead to more effective candidates, which we’ll get into when we talk about accuracy.
But there’s certainly a sourcing stage there.
Some organizations have automated that that’s the whole point of a lot of these job boards and technologies, right?
You don’t have to go out and call people all day long.
There’s places where people looking for jobs are already right, so that sourcing stage number one second, there’s a whole process of reviewing all those applications.
3rd, there’s some kind of phone screening process where a recruiter or in some with large call centers, BPO, they’ll call them off and screeners will be calling those people right to actually schedule the phone screen even prior to uh.
And then finally, the some kind of final interview around a final interviews.
If you were to and I would strongly suggest every organization do this.
If you were to look at what is the amount of time is spent that spent doing each of those stages of the process.
It’s it’s going to be the most expensive during the phone screen and the interview cause now you’re spending meaningful time.
I’m talking to these applicants and there’s a dollar cost there, right?
But the reviewing of manual applications as well is it can be very costly and really sucks up or recruiters time.
And if you have recruiters doing a lot of that, you’re going to need more recruiters, and that’s not going to scale well either, by the way.
So the areas that technology and AI can be much more effective is actually helping automate a lot of that reviewing of applications.
So I’ll give you an example.
So we have a client that they’ve they post a job and they get 1000 applicants like in a day and they’re recruiters would try to filter this down where they would say.
All right, let’s look at the employee referrals, right?
And maybe that grabs you a small subset of that those applications, and then you start with them and you move them through the process, but then they would just start reviewing applications that requires a person to actually read every single statement.
Maybe there’s some knockout questions about, you know, work relevant work experience, or right to work in the geography you’re hiring them for.
But largely, it’s just reviewing applications and resumes, and so you’ve got to take a step back and think how effective is reviewing an application in a resume.
Truly at identifying a top candidate because as the effectiveness of that highly manual process worth the fact that it takes you a lot long time to do it, and often by the time you get done with candidate 900 before moving people through the process, candidates one through 800 are already gone, right?
So there’s certain ways technology that same client I just referenced, now they can set up.
I’m a an assessment language proficiency assessment, a job simulations and skills test, some automated screening questions that all score the candidate on the back end as soon as they answer, and it’ll immediately stack ranks all candidates top to bottom and with the push of a button sort all applicants move them into the next stage.
So it’s gone from taking them a whole week.
I would say down to instantaneously the same day they apply, they’re making decisions and moving them through, right?
That’s just the reviewing applicant phase.
The more effectively you do that, though, back to that comment that if you were to map out your costs across each stage, you’re going to see that most of it’s in the phone screen and especially interview stage just due to you’re spending now 20 minutes, not 2 minutes reviewing an application 20 minutes or now 45 minutes in an interview, the more effectively you can go from 100,000 applicants down to that 5000 that you do a phone screen on and let’s say 2000, you do an interview on that is going to drive the bulk of your ROI.
From a hiring efficiency and I would say speed standpoint.

Paul Weiss 18:59
It’s a I have an allergy for that and an allergy.
I should say we at Bluewave.
Excuse me when we interact with our clients in their efforts to improve technology in any number of different areas, whether it’s cybersecurity, contact center, AI or the like, companies have a general practice, right?
What do I need to put together a bid spec?
Go to market, perhaps an RFP and then the time bloats.
I have to review all the RFP’s I have to now pull in stakeholders and operators to sit and 90 minute demonstrations with vendor after vendor after vendor only to with the always the intent of disqualifying until you get to a finish line and the challenge with that process is that there are so many wasted hours interviewing applicants or providers that will never have met your needs and it takes too long to figure that out.
So in the benchmarking and the database and the experience of working with all of these vendors, moving companies along faster so they commit the time where it’s smart to be spent and they don’t waste it where it doesn’t need to be wasted very much.
The same dynamic.
The more we know, the better decisioning, the more we can trust our data, the more we can make the right decisions and move along and not linger in waste time on applicant and phone screen reviews.

Daniel Ash 20:11
Mm-hmm.

Paul Weiss 20:18
For folks that maybe never had a chance to work here anyway, right?

Daniel Ash 20:22
Right.

Paul Weiss 20:22
Same type of process.
So now let’s talk when we talk about the accuracy of hiring, folks may say, well, what does that really mean?
It’s simply hiring the right people for the right job as often as possible, and those efficiencies or the benefits they are, tend to be, let’s say, lagging indicators around turnover reduction and tenure and graduation rate.
But it’s a continuous improvement effort that if efficiency and speed on the front end Dr immediate benefit, these lagging indicators Dr even more significant benefit.
So talk a little bit about examples there.

Daniel Ash 21:02
Yeah.
So this is so important because organizations need to take a step back often when they’re so siloed.
Focusing on, you know, we got to get people in seats tomorrow.
You know, there’s so focused on speed and accuracy and or excuse me, speed that they forget the whole point in the 1st place is to hire a person that achieves a sufficient level of ROI in that role to have justified all the costs of getting that candidate to the higher point and then all the costs of training and onboarding them in many of these organizations, especially where there’s high volume hiring taking place, you’ll see organizations that have turnover of.
I mean, I’ve seen organizations that lose 25% of candidates in the first seven days or 25 or some of them.
They don’t even show up.
They one uh, certainly 1020 thirty 4050% of candidates in the first three one month or two months or nine months.
Right.
And yet they still have hires, by the way, that will last a year.
Two years.
Five years.
I was recently at CCW speaking at a fireside where I raised my hand and said all right, earliest turnover person.
What is it they said?
Daisy Row or Day one longest tenured employee in your contact center.
What is it?
And people were still have their hands raised when it got to 20 plus years, right?
So the ROI of a hire and I’m just talking retention, let’s not even talk about like performance vary so much across hires that if you’re only focused on improving speed and efficiency, we’ll then geez, skip the whole hiring process, what’s more efficient than hiring process that takes the first person that raises their hand, you might as well, right.

Paul Weiss 22:54
Umm.

Daniel Ash 22:55
The whole point of it all is to achieve a minimum threshold of quality of candidate that achieves the outcomes you care about, and that’s what accuracy is about.
It’s about are we accurately hiring people that achieve that minimum level of retention, if not much greater that we need to recoup all of our costs and hopefully make some profit on it?
And are we?
Are we achieving a higher that achieves that minimum level of performance as well?
And the reason we use the term accuracy and not just quality of hire is because quality hires the metric, right?
So it’s the goal in metric in hiring, it’s the one that matters the most.
The reason we use accuracies to run remind people it’s not just about quality people out there.
There’s plenty of quality people out there that might be able to work in a contact center and do well, but they’re not willing to.
They don’t want to.
They wouldn’t stay.
Accuracy helps us focus to your point, the right person for this specific job.

Paul Weiss 23:48
You know, there’s something else that we haven’t talked about it.
It just kind of came to me as we were speaking here.
The hiring process is in fact A2 way.
Courtship you also have to have the candidate decide they want to work for you, and how many excellent candidates might you have identified that choose to work elsewhere?
And sometimes that may be straightforward on the package or the geography, but also perhaps impacted by the hiring experience in the 1st place.
And if I get a sense of engagement and collaboration and effectiveness within that process, maybe I’m more likely to want to be hired by you and you are my selection.
That could be a ohh let’s say a lost cost in the hiring process that had just felt piece of meat.
Ish or haphazard?
And maybe I don’t want to work here and so I think there’s a that’s another additional benefit.

Daniel Ash 24:49
Right.

Paul Weiss 24:53
It is the collaboration and engagement because it is in fact A2 way conversation always in hiring.

Daniel Ash 25:00
Right.
Yeah, I’m the the experience, the candidates having does matter.
Umm, the extent to which they’re expectations align with the job.
You know you can’t hire somebody against their will.
They may say yes, they may sign your offer letter, but in today’s world where they can go across the street or get another job the next week, you do want to make sure that this aligns with what the person wants and needs and really at the end of the day, it’s fit right?
There’s a lot of these volume hiring organizations that stress about the candidate who never completed anything in the application, and they spent a lot of time going after that candidate trying to get them to respond right, calling them up, spending more and more money, trying to get them to respond.

Paul Weiss 25:33
Umm.

Daniel Ash 25:42
Well, that’s one way to think about it.
But at the end of the day, what if that person applied to 1000 jobs on indeed, quick apply?
They’re not interested in you?

Paul Weiss 25:51
Umm.

Daniel Ash 25:51
Umm, I don’t focus on that candidate.
That doesn’t isn’t interested when you can build a process that identifies the people who are and that fit and moves them officially, quickly through the process, and you have data to suggest they’re inaccurate match.
Let’s move forward.
There’s no need for us to have like a 30 to one or 100 to 1 applicant to hire ratio if we can more accurately and quickly identify the ones that are one to one.

Paul Weiss 26:17
So with the what I think are fairly clearly illustrated benefits of faster, efficient and more accurate hiring and all of the ROI that can deliver in reducing attrition in reducing hours spend and simply finding people to perform their jobs more effectively for longer for your organization, why isn’t every organization picking up their phone and calling Journeyfront first, right?
And the answer to a degree.
I’ll step ahead and answer it, cause we talked to companies every day.
Companies that make decisions sometimes based on triggers and sometimes based on intents, and if the trigger is where am I feeling?
Obvious pain companies react to that, but unfortunately that’s not always the biggest measure of benefit.
Sometimes even a process with an organization that is not obviously painful might could be significantly improved, even more so than the painful process.
Perhaps so forming intentions to your point, when you hire with the end in mind, think about the benefit of outcome.
Most organizations have some clarity on the things they know aren’t working well.
Maybe a little bit challenged on causality or how to solve for those challenges, but a lot of companies still do struggle with the benefit of outcome and part of that is paralysis by analysis.
Part of that is uncertainty or lack of awareness of what could bet.
What better could look like?
And as fast as the marketplace is moving today, there’s just a lot of, we don’t know what we don’t know.
So along those lines, with all that you can deliver to organizations and have delivered to organizations, what is your feeling that that is stopping companies from leveraging an AI based platform like Journeyfront in a tiring?
Is it lack of awareness?
Uncertainty on the how and why governance, compliance concerns.
Where are you seeing the impediments?

Daniel Ash 28:27
Yeah, I mean it’s lack of awareness, right, we’re a venture backed VC backed early stage startup technology that everyone’s heard of Oracle and ADP and maybe some of your legacy assessments solutions we’re kind of like a, umm intelligent hiring, sweet means there’s an applicant tracking suite compared to component of it, but also in an assessment in an analytics component of learning from umm organizations just haven’t heard of us yet, lot of organizations but.

Paul Weiss 28:57
And they’re so steeped in the usuals that that they just don’t recognize it can be different and better.

Daniel Ash 29:00
E.
Yeah, I would say that there is an urgency in hiring where they have to focus on executing and perhaps no one taking a step back and saying is there a way to optimize this further.
And the answer is that there is if we had.
If we had a lot of uh people in an audience in front of us and you ask them, umm, how many of you are actually tracking quality of hire, you know, in a consistent manner, let’s say with each hiring cohort, very few would raise their hands now.
Now the leading organizations would, and I’m proud to report that every single organization using Journeyfront is now tracking this.
But the biggest and most and lost opportunity within hiring is that everyone’s.
Really investing in these hiring processes and hiring these people and there are no mechanisms in place to take the data being collected on candidates that we are using to drive decision making.
Now data could be in a resume.
It could be organized in a more effective manner, like Journeyfront helps with, but nobody is taking what data we have on these candidates and comparing it to the actual new hire, retention and performance associated with those candidates.
And that’s the fundamental innovation that journey fence technology brings.
It’s a feedback loop akin to the feedback loops that are already commonplace in marketing or finance, and all these other worlds where it’s a no brainer to you build a budget and then track actuals against the budget and finance.
You spend marketing dollars and then you track the ROI return revenue associated with those marketing dollars any time where you’re spending lots of money and doing things over and over again, you should be tracking the efficacy that feedback loop is the efficacy.
So there’s many organizations that don’t even realize that they’re playing make believe in their hiring process.
Sorry to be a little up front about it, meaning they don’t even realize that a lot of what they’re doing in the hiring process is not leading to outcomes that they actually care about.

Paul Weiss 31:00
Umm.

Daniel Ash 31:09
You could skip this process, or you could certainly those seven questions you asked in the phone screen.
Only two of them are actually effective, and the other five are noise that actually lead to worse hires, not better hires, you know, so the funnel mental innovation that we are pushing it, journey fund is kind of a leader in this area is the importance of hiring should be a data driven process.

Paul Weiss 31:21
Umm.

Daniel Ash 31:32
There is tons of data.
We’re just throwing it away once we hire the person and forgetting what we thought about and compared to what actual outcomes we see with them later, certainly in any way that we’re certainly we’re certainly broadly, I’m saying not journey from and our clients, but broadly like throwing away that the effectiveness of that data when in reality that data and AI by the way is really good at pattern recognition.
That’s the innovation we can now put forth for the world is you can identify patterns just by continuing to focus on hiring like you’ve always done.
It unfortunately had to do with the hiring goals you have and let technology identify patterns around what from hiring is most predicting retention and performance and what is not at all and could be removed from the process.
So you can take that data and improve efficiency by removing things that aren’t predictive and you can improve accuracy at the same time by emphasizing and using that data to predict outcomes associated with candidates for the things that are predictive.

Paul Weiss 32:30
So that that was powerful and it my next question and you might have answered it in advance with what is the biggest takeaway that you would like viewers to having heard what we’ve talked about today to start thinking about or recognizing or realizing and I’ll give an answer and then rely on your even better answer.
But with what?
You just said data is what do we want to call it the new oil, the new gold, right?
Everybody wants to make effective, best decisions on good, clean, accurate data.
It across every aspect of an organization.
Most folks are thinking about that and the perspective of their customers, right?
And how do I communicate to them?
How do I drive their experiences?
Understand their journeys and, you know, convert them, sell them, keep them.
Maybe not as often as they could or should, about how they hire and then create the employee experience from day one.
And so the idea that all of this valuable data is evaporating in most businesses day-to-day operation is, is both frightening and encouraging because it’s solvable.
And Journeyfront is helping to solve that, that, that that for me is the takeaway and if we look at it as a data challenge then efficiency and speed and accuracy are obvious benefits.

Daniel Ash 33:51
Umm, right.
Hmm.
Yeah, that date you should let data drive a lot of that decision making.
Umm, because again, without rooted in evidence.
Like if you say is it a?
Is it more efficient to drop the phone screen in the hiring process?
Well, if we’re not optimizing for anything else, of course, like I said earlier, it’s more efficient to drop everything and hiring because the ultimate goal hiring is to hire somebody who stays long enough to recoup the cost to you associated with hiring and ramping that person up, right.
And to achieve some type of benefits why you’re willing to pay their payroll and benefits, right?
So data can drive decision making in a much better way than opinions, right?
Without opinion and there’s a without a person without data, you’re just another person with an opinion.
That’s one of my favorite quotes.
Another one is without data.
My opinion is always better than yours, right?
Like or your opinions always better than mine.

Paul Weiss 34:59
And.

Daniel Ash 35:00
We’re just, we’re just guessing and arguing, but data gets us all on the same side of the table to really effectively Dr decision making around what can be removed from the process speed up from the process, what needs to be most focused on during the hiring process.
And you asked what to lead people with if you were to and I’ll give you a real client example because we do this with our clients.
You can quantify the cost of your entire process.
We have a client that hires about 4000 people a year.
We went through all the man hours involved, end to end, source to hire and it was about $1.8 million in actual cost.
Now 1.2 of that was sourcing costs.
Indeed costs whatever paying these job boards and ad campaigns, only 600K of that was the actual process of the of the selection process.
But theoretically, if you automated 100%, which I agree isn’t necessarily possible per se, but if you can get pretty close by the way.
But if you automated the whole thing, you’d have 1.8 million in savings.
The whole thing now.
We then looked at.
That’s the cost that.
So that’s the cost of hiring an efficiency 1.8 million.
We then looked at what’s the cost of their turnover is about 39 million and without getting the details of how we did this, we also looked at what’s the cost of low productivity and it’s about 33 million.
So hiring people that turn over or that or they aren’t productive had a cost of 71 million compared to that 1.8 million of hiring an efficiency.
So the cost associated with hiring and accuracy are about 40 X if you include the sourcing costs but 120X the cost of hiring an efficiency if you just include the process of the hiring process itself.
Meaning the ROI from driving hiring accuracy is by orders of magnitude of magnitude greater than the ROI.

Paul Weiss 36:40
Well.

Daniel Ash 36:46
I’ve just hiring efficiency.

Paul Weiss 36:48
With without even thinking about the potential of how those inaccurate hires might impact customer experience or have other residual effect.
I left you because I had a bad experience in dealing with this, less than perfect employee, so the ramifications of bad hires go well beyond even just that cost of attrition and the like, but also the experience, the impact they may have on other employees and or customers within an organization, all things Debbie thought about so well.

Daniel Ash 37:04
Umm.

Paul Weiss 37:21
Thank you so much Dan for your time today.
We again, this is our Bluewave webinar series, the current continuation of our demystifying AI conversations, Daniel Ash, CEO of Journeyfront, helped us I think, learn an awful lot and think really hard about where Journeyfront is driving value, where AI is making a difference in an area that some organizations may not be aware presently that AI is making the difference that it can.
And so we certainly appreciate everyone here who will have watched this video, Daniel, for your time today as well and we look forward to future conversations.

Daniel Ash 38:04
Right.
Thanks, Paul.
Great to be with you.

Paul Weiss 38:06
Thank you as well.
Alright, take care.

Daniel Ash 38:08
You too.