Home > Podcast > Recruiting Future with Matt Alder > Ep 532: Data Driven Talent Acquisition

Ep 532: Data Driven Talent Acquisition

June 28th, 2023

Employers have never had so much data to inform, innovate and optimize their talent strategies. However, understanding and extracting value from this data is something many organizations are still struggling with.

So how should employers be thinking about data, implementing data-driven talent strategies and planning for a future of data-based decision-making?

My guest this week is Grant Telfer, Business Development Director at Textkernel. Textkernel has long specialized in bringing machine learning, AI and data-driven intelligence to talent acquisition, and Grant has some great advice, use cases and future insights to share.

In the interview, we discuss:

• The current state of talent markets

• Magnified skill shortages

• Extracting value from data

• What are the most important data sets employers have access to

• Skills taxonomies and internal mobility

• Upskilling and succession planning

• Data & APIs

• The dangers of not using data to its full potential

• The role of AI

• Example use cases and outcomes

• What does the future look like, and how should we plan for it

This episode is supported by Textkernel:

Textkernel is a global leader in AI-powered recruitment solutions, delivering multilingual parsing, semantic search and match, and labor market intelligence solutions to over 2,500 corporate and staffing organizations worldwide. Our innovative technologies help companies better connect people and jobs.

See how you can connect people and jobs better, request a demo: https://hubs.ly/Q01VLGr40 
Visit our website to learn more about our solutions: https://hubs.ly/Q01VLFnW0

Listen to this podcast in Apple Podcasts.


Matt Alder (Intro) (2m 16s):
Hi there, this is Matt Alder. Welcome to episode 532 of the Recruiting Future Podcast. Employers have never had so much data to inform, innovate and optimize their talent strategies. However, understanding and extracting value from this data is something many organizations are still struggling with. So how should employers be thinking about data, implementing data-driven talent strategies, and planning for a future of data-based decision-making? My guest this week is Grant Telfer, Business Development Director at Textkernel.

Matt Alder (Intro) (2m 59s):
Textkernel has long specialized in bringing machine learning, AI, and data-driven intelligence to talent acquisition, and Grant has some great advice, use cases, and future insights to share.

Matt Alder (3m 13s):
Hi Grant and welcome to the podcast.

Grant Telfer (3m 16s):
Hi Matt, great to speak to you.

Matt Alder (3m 18s):
An absolute pleasure to have you on the show. Please could you introduce yourself and tell us what you do?

Grant Telfer (3m 23s):
Sure, so my name is Grant Telfer. I’m Business Development Director based in UK and Ireland at Textkernel, and Textkernel as a company. Our mission, if I were to paraphrase it, is to connect people in jobs better. So it’s all about helping organizations, whether they’re in the staffing, commercial, or government space to make sense of data and find the right talent effortlessly. What does that mean at a functional level? So it’s deep enrich CV and job pausing. It’s enriching the data, so pausing non-CV type data and extrapolating from there. It’s been able to search and match for vacancies and candidates both internally across your database but also externally in terms of candidates.

Grant Telfer (4m 4s):
We also offer labor market intelligence that’s used in two ways. For corporates, it’s really good to see what’s happening in their market sector, who’s posting jobs, what companies are asking for in terms of skills and experience. And then for staffing organizations, they use it fully generation as well in terms of new companies that they want to build a relationship with. Add to that, new ways of communication like WhatsApp, because LinkedIn and email, yep, they’re fine, but a lot of people are using those. And the ability to actually redeploy people in terms of temp staffing and put them onto new contracts. So that’s probably enough about Textkernel. We’ve been operating for 21 years, and we’ve been leveraging technology, particularly AI and machine learning for a long time now to help recruiters and help the candidates that they’re looking to place and hire.

Matt Alder (4m 51s):
Fantastic stuff and huge amounts of stuff there. Lots of interesting things that you are doing. It also makes you the perfect person to ask this first question to. So we know that we’re seeing a lot of volatility in the market. Markets are different from country to country and sector to sector. What are you seeing at the moment? What are you seeing from the data that you’ve got, and what your clients are doing?

Grant Telfer (5m 13s):
Yeah, it’s really interesting right now. And I’m gonna chuck in a couple of reports and stats as well because I think they’re useful. Not ours, which again is good because they’re independent. But the first thing I would say is that hiring is and remains business-critical. You know, it has to be right up front and center in terms of organizations and their goals. And people are saying it’s difficult. Josh Berson, who’s well known in the HR space in terms of providing analyst reports, said that more than 80% of the companies we’ve talked with worry about not being able to hire the right people. Well, we know that, you know, there it is in black and white. And it’s really interesting because before COVID people were talking about the skill shortage and talent shortage.

Grant Telfer (5m 57s):
Afterwards, and it’s magnified it. So it hasn’t gone away. It’s exacerbated. And the thing is, people also used to talk about, well have we got the right data? Have we got enough data? People have mountains of data, and they’re finding it really hard to consume. It’s complex to access sometimes, and people need to think about a balance of internal external data. So just to put that into context. Accenture did a study for 190 US execs. Apparently, only 32% of companies can extract tangible and measurable value from data and only 27% consider data analytics projects to be fully actionable.

Grant Telfer (6m 38s):
Those numbers aren’t high. So yes, there’s a skill shortage. And I know there’s a balance of corporate and staffing companies that are listening now to the podcast. But one thing that has come into play as well is not just looking for external candidates that was certainly already in play, but Bullhorn do an annual report and the grid report and in 2023, certainly for the staffing companies in the audience. They said that winning new business, finding new organizations to work with is important. But Matt, there’s one other thing that I’m seeing going on. Again, I’ll back it up with some statistics. I’m gonna call it schizophrenia and loyalty, which maybe sounds a bit strange but I’ll explain.

Grant Telfer (7m 21s):
So page insights if you haven’t seen it. And by the way, I’m not paid to plug these. It’s just reports that you’re reading and we’re looking at the industry trends, but they’ve done a talent trends 2023. They say that 86% of all employees are open to new opportunities. So whilst companies are struggling to find the right candidates and hire them quickly, a lot of people are thinking about, “Well, am I open to new opportunity?” And the answer is yes according to this. But here’s the weird thing for me. What is the most important thing to talent in deciding on the next role? Well, the rankings that they gave was that, first is salary and compensation and sixth is work-life balance and company culture.

Grant Telfer (8m 3s):
And then under the top 10 reasons for resignation. First is work-life balance and company culture, and fifth is not satisfied with the current salary. Maybe they tie up that they leave for a better salary, but it’s almost the inverse of each other, which is why I say schizophrenia. And it’s clear that, you know, the loyalty is something that organizations will continue to need to work on. And things like employee satisfaction will be really, really key.

Matt Alder (8m 30s):
I think that’s really interesting because you know, I’ve seen lots of reports, and lots of people have sort of come on the show and talked about the issue with employee engagement at the moment and how it’s an all-time low? And how approximately sort of 20 to 30% of the working population are ready to jump ship at any moment. And I suppose it just illustrates what a complicated situation it is and the complexities that people have with their relationship with work. So yeah, that’s really interesting. Digging into what you were talking about in terms of data there. I thought that was very interesting in terms of that Accenture report that companies have huge amounts of data but are not using it effectively particularly, which seems a massive missed opportunity, particularly at the moment.

Matt Alder (9m 15s):
Just to sort of go through that step by step, to take a step back, I mean obviously data and analytics is a critical part of any talent strategy. You say that companies are swimming in data. What are the most important data sets that employers are likely to have access to?

Grant Telfer (9m 33s):
Yeah, look, I’ll touch on some of those. And I’ll also touch on what are some of the reasons why they need it and how they can better use it as well, if I may. So I think there’s lots of data. HR organizations you’ll know that you’ve got so much data but it’s accessing it. And the HCM solutions that people are using, they’re rich in data. The applicant tracking systems, they have data as well. But there’s other things. What about things like performance appraisals? What about the data around past and present candidates? CVs extraordinarily good, particularly for internal mobility in terms of actually allowing employees to build their profiles and set those up.

Grant Telfer (10m 18s):
Also, if you’re a staffing organization, of course, you need to have the latest and greatest CVs. Vacancies, you know, there’s rich data in the vacancies as well, which will allow you to do quite a lot, particularly in conjunction with CVs. And then people should have if they don’t. Taxonomies, particularly around skills and professions. So what people are talking about now is not just looking at how you hire around roles. You know, that’s almost become a little bit passe. It’s important to know what that role is, but you need to understand skills. And you know, I’m not the first to come on your show or the first in the market to start plugging. You need to be able to look at skills and professions. E-learning as well. There’s lots of data there and you want to be able to use that data and tie up the data you have around employees and candidates by looking at, what e-learning capability might they have, how do they enhance their own profile?

Grant Telfer (11m 12s):
And then there’s external data, whether that’s using data like LinkedIn or whether it’s using something like Jobfeed, which is our labor market insights solution. You know, there are a number out there. So it’s important to be able to have the right sources. And you know, I said I’d touch on what are these used for? So it’s interesting. Because probably around about, and some organizations will have been looking at this earlier. But certainly, you know, 2016 or 17 onwards people were talking about internal mobility. And I think people have really embraced that it’s hugely important to help people and help people in their careers. By having access to this data and looking at the skills you can start to use that data and help them to plan their own careers and keep them in the organization.

Grant Telfer (11m 58s):
And I’m shocked at how many people sort of immediately talk about external candidates when they’ve maybe not looked at the internal candidates because they either can’t access the data or can’t trust it. Upskilling. I’ve talked about that in terms of linking to the e-learnings solutions, but you know, it’s useful for two things, which skills do employees need and how do we help them get those skills? But also if you do need to go externally, are the candidates that maybe have all the right attributes and the right attitude but they’re lacking a few skills and can they be trained up because that’s an obvious place if you’re looking externally to try and reach and bridge the gap between the skills gap that people talk about.

Grant Telfer (12m 41s):
Succession planning. Who else in the company could do a job? Cross-functional project-based initiatives. I think this is quite important because you know, the surface of work is changing. And typically people were put in projects based on roles. But people now need the ability to spin up and spin down projects. So I might be working in a project with a finance director, an HR director, and myself in terms of sales or business development, which sounds like the first line of a joke. But we are seeing a lot more of these things spinning up. and people being on a project for a period of time because they have the right skills and attributes rather than, what is my title? Recently, unfortunately, we’ve seen that people have been made redundant.

Grant Telfer (13m 21s):
Obviously, there’s been a huge cry about oh we haven’t got enough talent we need to hire. But some of the bigger organizations and technology space, which I’m in have been for years there’ve been some big companies who’ve been unfortunately having to let people go. So there are things like actually giving people access to labor market insights and giving them the opportunity to see what organizations are hiring, what skills they’re asking for? So if you are having to let somebody go, you’re at least giving them a helping hand into their next role. So I think, you know, I’ve talked about some of the data where it sits, but also some of the reasons why people need to rethink the recruitment processes.

Matt Alder (14m 3s):
It’s very clear that data really sits at the center of this. It’s perhaps also clear though that despite all of these sources of data employers are struggling to make data-based de decisions. I mean, what are the key elements of data-based decision-making? How can employers effectively use the data that they have?

Grant Telfer (14m 29s):
Yeah, so, it’s absolutely true. It’s not, the data isn’t there in many, many respects. We talk about understand, connect, and analyze. So what does that mean in layman’s terms? First of all, understand. Know your data. Know where it is. Know what the data is that you want to use. And then once you’ve considered how you are really going to use it, use it to connect the two elements of vacancies and candidates together. And whether that’s internal or external vacancies and candidates, obviously external vacancies is more relevant to the staffing companies who are listening. But for the corporates certainly every other element counts. So, understand what those are and use it to actually analyze what’s going on in the market, make placements more quickly, and then automate the process around it.

Grant Telfer (15m 20s):
You know, you really want to automate it just for the sake of it, but for your recruiter’s sake and to give them a better day but also for the candidates as well. Make things easier for the candidates. So, one thing I would say is that there used to be this divide or debate around, well, should I go with an integrated suite or point solutions? And I think the answer is definitely a hybrid. But people need to be able to use APIs. So it’s important that whatever you are using in your estate, that there is API access so that you can actually sync the data between the systems and solutions you are using and it needs to be modular I would say as well.

Grant Telfer (16m 1s):
Certainly, that’s the approach we’ve taken. So whilst we would like our clients to take every element of the Textkernel stack, that’s not always the priority for them, but there may be some really good ingredients that just help glue things together to allow ’em to work really more effectively. So, I would say, that those are the key elements at a very high level.

Matt Alder (16m 19s):
We’ll dive back into the technology part of this in a second because obviously, that’s absolutely crucial. Before we do though, what are the dangers to companies who aren’t using their data to their full potential?

Grant Telfer (16m 32s):
Yeah, I mean I’ll go back to what I said at the start, which is hiring is business-critical. So, it’s gonna be very difficult for people to effectively manage their current workforce and the recruitment process as well as they might be able to if they haven’t got access to the right data and aren’t leveraging it properly. And that will have a negative impact on things like employee satisfaction, on things like career progression, and it will make workforce and succession planning a lot more difficult to achieve effectively. Now, providing that they have looked internally and haven’t found the right candidates as well. I mean, obviously, people are gonna look externally. Again, if you haven’t got data and aren’t using it to its full potential, it’ll be really hard to get the best candidates before one of your competition does.

Grant Telfer (17m 21s):
Worst case and I don’t want to sound overdramatic, but some companies effectively, if they haven’t got not harnessing data to full effect will potentially go a business.

Matt Alder (17m 34s):
That makes sense. [unintelligible] I think that’s dramatic at all. I think that’s just the way that things are on the way that things are going. And that does take us nicely back onto technology. You were sort of starting to describe the role of technology there. Go into a bit more detail for us, I suppose specifically around the role that AI will play in all of this because it’s actually illegal in many countries to have a podcast interview and not mention AI. So, I think we should make sure we mention it.

Grant Telfer (18m 3s):
Yeah, AI. It’s brilliant, I love it in many respects, but I think it’s important to remember that AI was already in existence. It’s nothing new per se. In fact, I think AI started to be talked about in the 1950s and then sort of every now and again each decade or maybe every 20 years, you know, AI is back in its shining. So look, we’ve been using AI capabilities such as machine learning, deep learning, larger language models for quite some time now depending on sort of what’s been available. We also have quite a specific approach. So what we do is highly oriented around data-driven AI. And I raise that spec specifically versus behavioral AI.

Grant Telfer (18m 44s):
So the context of behavioral AI is that it will — let’s say I’m Grant’s hiring manager, which I obviously do, in terms of hiring people and have done in the past, in terms of teams. I have a fairly set formula of things that I measure people against. Obviously, I’m particularly looking at things like culture. I may do that job reasonably well, but if technology or AI is mapping everything I does, I does, I do even that won’t necessarily be the right answer for what’s needed in terms of diversity inclusion, getting the right mix, and the right candidates across an organization. In fact, it can be quite dangerous.

Grant Telfer (19m 25s):
We already know, and I’m not going to talk about sort of previous reports of people who have used behavioral AI and come unstuck. And there’s a new element, and this is the shiny one, the whole ChatGPT, GBT sort of Bard conversation. Generative AI, it’s hugely exciting. So, if you think back to when mobile phones and the iPhones came into play back around 2006, it changed the way that we actually operate in both our personalized and business. And you got a huge flip in the market between personal applications, actually, being the driver to change business applications because we got so used to it easy nice to use applications. It’s like right businesses.

Grant Telfer (20m 5s):
We want this in terms of our everyday work and you’re going to get the same drive and push I think with generative AI. What could it be used for? Things like job descriptions. We know that it can put things like that together. Candor and rejections. We have an innovation week we do each year, which is probably my favorite time of the year where we basically get people to suggest and nominate their top ideas within the company in terms of what we might do and how we might innovate. We then vote to come up with the top 10 to 12 ideas, and we all fly into Amsterdam from all over the world. We’re about 200 people in the company, and we split into teams.

Grant Telfer (20m 46s):
And these are cross-functional teams, so it’s not all the sales guys in one. We actually get people across these various projects that we nominate ourselves for because we think it’s a really good idea and we spend a week innovating. And at the end of the week we present in a bakeoff, and you get five minutes, and then we vote for the best idea, and we take that into play. Last year the one we looked at was around candidate rejections. So, first of all, how do you generate a job description? Secondly, how do you make sure that people aren’t hearing nothing when they’re not selected from an interview process or aren’t selected from submitting their CV?

Grant Telfer (21m 26s):
Well, you can start to generate those things, and you can start to even suggest skills that they might work on to bolster their own profile so they’re more successful next time. But I think we all do need to be aware, as exciting as this is, and it is definitely going to impact and bring in change. It is costly at the moment, and it does have risk particularly around data and compliance, and security. And we need to be pretty careful that there aren’t hallucinations so that it’s not the AI isn’t suggesting things that actually aren’t accurate or correct. You’re still going to need people who have sufficient intelligence and knowledge to be able to look out for that type of thing.

Grant Telfer (22m 6s):
So, yeah, AI its already there. It’s big, it’s going to get bigger, lots of exciting things and then also things to just look out for.

Matt Alder (22m 14s):
Yeah, absolutely. I couldn’t agree with you more on that one. To kind of summarize a little bit, you’ve talked about lots of different use cases around data, how companies can make database decisions, the dangers of not doing it, some of the sort of the technology considerations that are involved. What are some of the sort of the best sort of real use cases you’ve seen and the outcomes you are are seeing from, you know, maybe some of the people you’re working with?

Grant Telfer (22m 38s):
Yeah, so we’ve got a real mix of government, corporates, and staffing agencies. In fact, seven out of the top 10 staffing agencies use our technology. So they’re using it for deep parsing. And I say deep parsing because there’s lots of parses out there that people can select. What we are talking about is that whoever you select and go for, make sure that you are really getting good experience and skills data because that is what you need to remove bias and to do the richer matches. Things that we are looking at though, just things like semantic prompts. So when people are typing things in rather than everybody needing to know bullion, it is coming up with sort of auto prompts for what somebody might mean save a bit of time, whether that’s candidate or recruiter.

Grant Telfer (23m 19s):
You can also do things like, you know, our clients are looking at, “Well, if I’m a candidate and I submit my CV back the data, which I can then review on a company’s website where I’m applying for the job, why not prompt them for additional skills and say, Grant people with your skills also have skills like these. Are any of these the right ones for you in terms of your profile?” And I might select some, I might not do, but give people that choice. Also look at things like non-CV data, can you pass that in? So, if I’ve got a certificate or if I’ve got a letter of commendation or referral letter or again if there’s performance appraisals where I think there’s something specifically good, you need to be able to pass that in, get it in easily so that that data can then be stored and shared.

Grant Telfer (24m 3s):
And then the other thing that people are looking at particularly because of the issue of getting the right skills is, how do I correlate using skills and professions to actually look at what jobs somebody has been doing, what skills they have, and whether they can bridge the gap either into a new role in a different industry? Or whether they can bridge the gap because they’re already in the right industry. And as I mentioned earlier, they just need a couple of additional skills. You know, is it worth an employer saying they’re the right candidate and I can’t find a better candidate, but I’m just going to invest a little bit of time upfront to just upskill them so that they’re really ready. So, they’re doing that, we have commercial clients, particularly in the sort of investment banking space, who’ve built internal mobility solutions so that their employees can look at what they would like to do next in advance.

Grant Telfer (24m 57s):
We’re seeing some interesting things as well in terms of the ATS solutions, particularly on the staffing side. So it may be something that is becoming more prevalent across the industry and will be hitting corporate organizations as well. There seems to be quite a big investigation and investment in terms of Microsoft versus Salesforce. So, on the staffing side you’ve got quite a few Salesforce-based platforms. In terms of the ATS world. And then you’ve got Microsoft-based platforms as well. And if organizations have a leaning to those, that’s just putting an interesting spin in the market. And the last thing that I’ve mentioned in terms of what our clients are doing are private data feeds is something that we’ve spent quite a lot of time on recently where people have an index that’s very, very data rich and it goes back to the theme of this podcast.

Grant Telfer (25m 44s):
That’s great, but how do I access it? So we are actually providing them that data feed so that it’s accessible. So that if they want to, they can couple it up with external labor market insights, whether it’s ours or somebody else’s. And they can analyze supply and demand looking at what they’re seeing in terms of themselves as an organization, and what’s actually happening, and what’s been asked for in the market.

Matt Alder (26m 9s):
So, final question. It’s becoming very obvious that we’re on the cusp of a great period of change in recruiting and talent acquisition. Where do we go from here? What do you think talent acquisition is going to look like in a few years time?

Grant Telfer (26m 24s):
It’s always a bit of a crystal ball moment and obviously, there’s going to be a degree of subjectivity. But yeah, I’d love to sort of take that. I think you’re going to see a continuation of what’s already emerged as trends. So the skills side of things is obviously going to remain in place. But I think the four-day week will become a real thing. It’s been tested. Governments are looking at it. So I think that will definitely be something that will come into play. I think there’ll also be a focus back on the over-fifties. And if anybody’s seen my profile photo or looked at my history, I fall into that bracket I think.

Grant Telfer (27m 4s):
But I think the governments are talking about, well how do we make sure that we retain and keep people in the economy? And I think organizations are beginning to think we do need to recruit and hire people who’ve got the experience. And there’s plenty of people in that category who’ve got lots of energy, lots of knowledge. One of my favorite clients from last year focuses on role sharing. They’re called role share. That’s going to take place more and more I think as well accompanied with the points I’ve just raised. So what that does is it allows maybe two candidates to apply together for a permanent, for a role that’s for one person. It allows people to apply individually for a role.

Grant Telfer (27m 45s):
It also allows organization to say, “Well, I’ve got some good talent.” They don’t want to work five days a week, but I don’t want to lose them. So, I’d be prepared with another organization to actually share and pull some of the resources. So, I think that’s a very exciting initiative that will particularly fit in with the over-fifties, with parents who want to split their time in terms of the children with people studying. And there’ll be a number of other reasons why people want to do some role-sharing. And then the final point I was going to make was sort of a hundred-year life. Really fascinating book, which is all about the change from the generation that I’ve grown up in where literally you had your education, whether that was school or whether you went to university, then you worked, then you retired.

Grant Telfer (28m 31s):
And even with my generation it changed from the previous one where you didn’t join an organization for life. Well, that’s now pretty rare. It’s changing massively. So, the new generation, and here’s a couple of more interesting things. iCIMS have just recently released a report. The class of 2023, which is about Gen Z year 2000. You know, how do they see things? 28% apparently of Gen Z in the UK identifies members of the LGBTQ+ community, which a really high figure. I was quite surprised by that. But that needs to be thought of these types of things. A third of them are also specifically looking for a diverse workforce that’s represented in employer pictures on career sites and social media pages and also a third of final-year uni students have used an AI bots, write their CV or cover letter, or are planning to.

Grant Telfer (29m 23s):
So there’s already elements of change. I think the one thing that will continue to mean that — I think the recruit list recruiting, I think Alin who you had on the on on the podcast in May talked about it, and some of those elements are going to come true. Automation bots and generative AI will definitely lend itself in certain circumstances to recruit us or near recruiter-less recruiting. But I think the human touch, the human element, just to wrap up in terms of culture, which is quite hard to identify and is very particularly to an organization or a candidate that’s looking at an organization means that there’s still going to be that element that needs a very human focus and touch on it.

Grant Telfer (30m 7s):
But there are going to be some big shifts in the market.

Matt Alder (30m 11s):
So lastly, tell us where people can find you.

Grant Telfer (30m 14s):
You can find us on www.textkernel, T-E-X-T-K-E-R N-E-L.com, and LinkedIn. And also we are gonna be at RecFest in Knebworth Park Island 6. So if you’re there, please come and share what you are seeing. Come and share what you are doing.

Matt Alder (30m 30s):
Thank you very much for talking to me. My thanks to Grant. And if you are going to Rec Fest on the 6th of July in Knebworth Park, I’m going to be there as well. And you can find me on the hiring without boundary stage at 4:15 in what promises to be a very interesting fireside chat with the title Will the Recruiter exist in 10 years? So if you’re going to be there, and you’ve got some opinions on that topic, I’d love for you to come along and join the discussion. You can subscribe to this podcast in Apple Podcasts, on Spotify, or via your podcasting app of Joyce. Please also follow this show on Instagram.

Matt Alder (31m 10s):
You can find us by searching for Recruiting Future. You can search all the past episodes at recruitingfuture.com. On that site, you can also subscribe to our monthly newsletter, Recruiting Future Feast and get the inside track about everything that’s coming up on the show. Thanks very much for listening. I’ll be back next time, and I hope you’ll join me.

The post Ep 532: Data Driven Talent Acquisition appeared first on The Recruiting Future Podcast.

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