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Ep 478: Developing Talent Intelligence


Talent Intelligence is on the rise, with an increasing number of TA teams putting data at the core of their strategy. However, do employers genuinely understand the full potential of TI, how do you get started, and what is the business case for building a specialist resource?

My guest this week is Toby Culshaw, Talent Intelligence Leader at Worldwide Amazon Stores. Toby is one of the global pioneers of talent intelligence, having built teams and Philips and Amazon. He has also recently released his first book, “Talent Intelligence – Use Business and People Data to Drive Organizational Performance” Suffice to say, this is a must-listen interview for anyone who wants to know more about the development of talent intelligence.

In the interview, we discuss:

• What is Talent Intelligence, and how is it developing

• The business outcomes and value of TI

• What areas of TA is data intelligence being applied to?

• Where should TI sit within the organization?

• Maturity model

• When TI isn’t TI

• What skills does a TI function need to be successful?

• Building capability

• What will be possible in the future?

Listen to this podcast on Apple Podcasts.


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Matt Alder (1m 19s):
Hi there. This is Matt Alder. Welcome to Episode 478 of the Recruiting Future podcast. Talent Intelligence is on the rise with an increasing number of TA teams putting data at the core of their strategy. However, do employers genuinely understand the full potential of TI? How do you get started and what’s the business case for building a specialist resource? My guest this week is Toby Culshaw, Talent Intelligence Leader at Worldwide Amazon Stores. Toby is one of the global pioneers of talent intelligence having built TI teams at Phillips and Amazon.

Matt Alder (2m 1s):
He’s also recently released his first book, Talent Intelligence Use Business and People Data to Drive Organizational Performance. Suffice to say, this is a must listen interview for anyone who wants to know more about the development of talent intelligence. Hi, Toby, and welcome to the podcast.

Toby Culshaw (2m 21s):
Hi Matt. Thank you, man. It’s good to be here.

Matt Alder (2m 23s):
An absolute pleasure to have you on the show. Please, could you introduce yourself and tell everyone what you do?

Toby Culshaw (2m 29s):
Yeah. Toby Culshaw, I lead Talent Intelligence at Worldwide Amazon Stores, which is essentially the Amazon business that we know and love,, and all of the mechanisms to get that to your door, so the airline business, the robotics, the warehousing, logistics, and then right through to everything associated with the retail business. Anything you buy from us, that’s the world I inhabit and got the Talent Intelligence for.

Matt Alder (2m 57s):
Fantastic. You’ve been a big figure in Talent Intelligence for quite some time. You’ve written a book on it, which we’ll talk about. For people who aren’t fully familiar with the concept, tell us what Talent Intelligence is, where it’s come from, and how it’s developed.

Toby Culshaw (3m 14s):
Yeah, so the definition is still somewhat fuzzy of talent intelligence. There’s a few different variations going out there, which was one of the triggers for me to the book. I cobbled one together from various different sources. Essentially, it’s augmentation of internal and external people data and then you’re applying some kind of technology or science, insights, intelligence to it to then help drive business decisions and business outcomes. Generally, you’re gonna be looking at things like the people, the skills, jobs, functions, competitors, geographies, that thing. It’s essentially essentially looking at labor market data to help the business, make the business have better decisions, and the decisions they’re making.

Toby Culshaw (3m 58s):
That’s relatively new in its current, guides. The reason being, historically, there’s a couple of different guides to it. We can talk the differences there as well, but historically, the platforms from a tech side were very raw data driven. If you go back 10, 15 years, you had to be heavy data savvy to be able to get these data sets and make sense of it. You’re basically looking at being a business analyst, business engineer, or economist. It was quite hard from a user interface of it. The stickiness of the pick up was slow. Roll through another 10 years and suddenly we had this generation of late market intelligence platforms.

Toby Culshaw (4m 39s):
That really lowered the bar in terms of barrier to entry to because the user interface was so much easier and they were doing a lot of the heavy lifting, heavy work of analysis on their end and that’s really exploded things. You suddenly have platforms like NZ or Drop or Talentneuron Strategies, HorseFly, LinkedIn insights, obviously a big one for the massive. There’s a lot of these visualization tools that are suddenly making it far more approachable and far more digestible. Then you had Covid taking in and the sides of the economy through that period, which then as a concept really drove Talent Intelligence in a much, much more aggressive way.

Toby Culshaw (5m 23s):
You suddenly saw it becoming a business priority. Historically, a lot of TI teams were formed within Talent Acquisition and they were essentially sourcing intelligence on steroids. Some bits would tend more towards exec research, but generally, you’re looking at that sourcing intelligence piece ramped up a little bit. Through that Covid period, you saw a lot of teams pivot and say, “Well actually, we can’t affect the business enough by purely working at the requisition end of this journey. We have to get upstream. We have to get to get earlier into this decision phase and affect the strategy and the decisions so that we can actually make our lives easier downstream at a TA level.”

Toby Culshaw (6m 4s):
Through that period, you’re seeing a lot of teams starting to pivot and move further upstream earlier in that decision cycle.

Matt Alder (6m 11s):
I suppose to dig into that just a little bit more, talk us through the business value that it creates. What type of decisions does it help with? What are the outcomes and the results that an employer would get from investing in Talent Intelligence?

Toby Culshaw (6m 27s):
Yeah, great question. The offerings are somewhat similar from most teams. You’re essentially gonna have a core around location strategy. Obviously, location is becoming somewhat location agnostic, but at the same time, you do have location hotspots for talent. Location strategy is really big for most teams. You’re looking up on average about 60 to 70% of teams is around location in some way, shape, or form. Competitor intelligence, competitor insights, talent flow, analytics. Understanding who’s going where and why they’re going there. DE&I intelligence is a really big thing in all its it’s forms and guises. Talent sentiment and what people are saying, why they’re saying it.

Toby Culshaw (7m 9s):
What’s the perception of you as a brand, as an organization? How’s that handling in the marketplace? Really, we’re doing a of the work around future intelligence so looking to five years plus out. One of the big trends that are gonna impact us as a workforce that we need to start addressing ahead of time. Then I’m seeing much more so developing around recruit marketing, recruit marketing intelligence, and persona insights. Obviously, the actual span to market as well. That’s ramping up. You have some teams that are cutting right into strategy, MNA, and working with those teams to say, “Well actually, if we’re looking to land and expand this company or buy this company and expand it aggressively, is that even feasible?

Toby Culshaw (7m 49s):
Is that possible? Are we about to buy company that we can’t expand because it’s skillset is not in the market, the location isn’t correct for that, or the leadership team has got a toxic reputation so we can already struggle to hire the people to expand in the way you wanna do?” I think, depending on the maturity of the function, you’re seeing a slightly different product offering essentially and who their customer base is internally, but by and large, it’s anything to do with external market data. What are your key drivers as an organization? What are you trying to achieve as an organization? What’s gonna stop you from getting there? If you ask any CSU, what’s your biggest asset? Every time, it’s your people. If you it’s them, what’s the biggest risk for the future?

Toby Culshaw (8m 30s):
It’s not having access to the right talent. It’s bringing that talent data to that decision point to say, “Well, where are we trying to get to in the future? What’s the risks we’re exposed to and how do we mitigate those risks?”

Matt Alder (8m 41s):
You mentioned that it was a function that perhaps a traditionally grown out of Talent Acquisition in the last few years. Does it naturally sit somewhere within the business? Is it within Talent Acquisition? Is it somewhere else or does that depend on the employer and their priorities?

Toby Culshaw (8m 58s):
Yeah, it’s great question and I think honestly, there’s a few directions this could go. This is one of the elements we discuss in the book in the final chapter, the future state. In terms of the current state teams sit, you see a lot of teams, as say, within TA, some within recruiting for two different reasons. TA generally, you’ve got the pain point. You’re feeling it on the ground. You’ve got the volume so using market data to try and mitigate that, to try and solve some of those problems you’re feeling on a short term. Exec research, you find it gets tied into there because they’ve generally got the relationships of the senior leadership team.

Toby Culshaw (9m 39s):
Those decision points, whether it’s competitor analysis, whether it’s strategic guidance, they’ve got the essentially route to customer or route to market senior leaders. Interesting from the talent benchmarking survey last year, although just over 70% of all TI teams sat within Talent Acquisition, over 80% thought that was the wrong function to be sat with them. They wanted to pivot out. Where they wanted to pivot to varied massively. You had some teams wanting to sit within HR analytics, people analytics. You had some teams wanting to sit directly up into the C-suite. You had someone sit within ops or within strategy. A huge variance within there, but when I look at the future, I think there’s a few directions the function could develop.

Toby Culshaw (10m 24s):
I think there’s the overall merging of people analytics, HR analytics, and Josh Pearson said something recently and was talking about this also where you essentially see a combination of HR analytics, people analytics, talent acquisition analytics, talent management analytics, Talent Intelligence, all into this workforce intelligence type function. I think you actually referred to it the Talent Intelligence function. I think it would probably be accurate to the workforce intelligence function as one centralized HR science team essentially. I think personally, that is probably the most likely route it’ll go, but I actually think the more interesting route is to say, “Well actually, if we look at Intel as the offering, and it’s just happens that our intel offering aims towards labor market talent, you get some really interesting situations when you start merging Talent Intelligence work with say marketing intelligence, business intelligence, or strategic intelligence.

Toby Culshaw (11m 21s):
When you look at it as a centralized intelligence function and you then have the sub-specializations within, you then look at competitor intelligence for example in a very different way. You’ve got the marketing intel guys looking at the share of the market, the share of the wallet, the product offerings, but then from a TI perspective, you can start looking at how these companies pivoting? How are they changing their hiring needs? How is that an early predictor for what that company might be doing in the future and how can that affect our market share or share of wallet? I think you can start doing some really interesting things when you start combining Intel functions across. That’s another route. It’s a centralized intelligence function, and then the third possibility I think could also happen slightly more optimistic in my mind, but I am incredibly biased.

Toby Culshaw (12m 7s):
I could see a time where you have a Talent Intelligence function akin to a marketing intelligence function in a marketing, big intel function that supports both of the strategic and the operational level. I can see TI being a whole COE in of itself within organizations where you have a talent management, Talent Acquisition, and Talent Intelligence. It’s a whole separate COE that’s there to bring that science edge to the rest of the HR function and really be a COE in itself.

Matt Alder (12m 36s):
One of the things that I’ve noticed certainly over the last 12 months is lots more employers, heads of Talent Acquisition are talking about Talent Intelligence. I was at conference a couple of weeks ago. I saw five or six presentations from Global Heads of Talent Acquisition. I think probably three or four of them mentioned Talent Intelligence as part of their strategy. We’re obviously seeing raising awareness, more adoption, and all those kind of things. In your book, you outline a maturity model path that the companies can take with this or have taken with this. Tell us a bit about that.

Toby Culshaw (13m 15s):
I’m politician . I’ll cover that. I think note though is you see of talent intelligence advertising, a lot of people pushing Talent Intelligence and they don’t know what it is. In my mind, it’s essentially sourcing. It’s new clothes. We’re calling it Talent Intelligence because it’s a trendy thing to call it and it’s a hot topic, but when you actually look at the key responsibilities and roles, you’re seeing a lot of roles that are Talent Intelligence by name, but the job responsibilities are driving talent pipelines, creating long list, or doing talent mapping. That’s all valuable work and it’s incredibly important work. In my mind, that’s sourcing intelligence.

Toby Culshaw (13m 56s):
I think the purist in me for the TI side of things, it’s more around how we’re using that intel to drive business decision and the business impact. I think that also does tie them into the maturity model where you’re seeing a lot of teams initially starting up these SI type roles and the sourcing type roles that are TI by name but then, as the people are starting to get into those roles and looking to develop, you do see the actual TI capabilities start developing throughout. Initially, it might be an individual, and in the book I talk around the jack of all trades. First, you’re just trying to do anything. You’re getting demand all over the place as soon as you start to do anything from a late market perspective, the business will snap it up because they haven’t had this before.

Toby Culshaw (14m 43s):
It’s super exciting, I think you’ll you see this initial scrappiness when a Talent Intelligence provider just delivering the work, but you’re trying to get across everything. As the offering develops and matures, you’ll end up through the problem solving through insight generation. What you really want to be is that TI trusted advisor and really working with the senior leaders as a trusted advisor to really drive business transformation, business change. I think there’s some parallels also with HR analytics and maturity model. You have a lot of, in HR analytics, the core maturity curve. You have manual reporting, automated reporting, and dashboarding, forecasting, prediction, et cetera.

Toby Culshaw (15m 28s):
I think there are some some elements there that run across and you do see that run through into TI. I think the big difference though is that HR analytics generally will go through that curve and look to have self-service as one of the core items. You’re hitting a scale on the self-service piece and then, as an aside, they’re developing the consulting offerings to have more more specialist deep dive. I think TI is generally moving in the opposite of that. Yes, we have some tooling, but most TI functions don’t really want to push self-services and offering because the data’s so much more contextual. If you look at a location feasibility, yes, you might have the demand, supply, the comp data, et cetera.

Toby Culshaw (16m 12s):
The reality could be the location might be the wrong side of a toll road. It might be that the location has really bad restaurants nearby. It might have a really terrible infrastructure and no bus stops or train stations. That information is really hard to get into an automated self-service dashboard. That human element and that human contextual element is really, really important. The maturity scale I think is slightly different within TI where you have some element of self servicing, but just to scale and to make it accessible for many. The highly consultative nature, that trusted advisor relationship, I think that that’s really gonna be where a lot of teams focus their time and energy.

Toby Culshaw (16m 55s):
It’s to really build out that relationship and build out the trusted advisor model.

Matt Alder (16m 59s):
You mentioned that the technology and the resources available have changed dramatically and have really driven the development of talent intelligence. You don’t necessarily need to be a data scientist or an economist to be able to do this anymore. What skills do you need though if you were advising a head of Talent Acquisition, for example, on how they might develop a TI function? What kind of skills do you need to do that effectively?

Toby Culshaw (17m 31s):
Yeah, it’s a great question. I think there’s probably two different elements with this overall. There’s gonna be some harden skills that you’re gonna need across. You see that a lot with, once again, when we did the benchmarking study. There were were teams that had certain skill sets they wanted to push. Initially, it was data visualization, predictive analytics, data analytics, strategic consulting, data engineering, that sort of stuff, and skills they wanted to remove and see. Equally ironically, there were some bit around sourcing, some bits around what was planning, some bits around data engineering. I think the key for me though is more the technical skills, the hard skills you can train.

Toby Culshaw (18m 13s):
I had no issues around that. The platforms are relatively straightforward. You have to have data appreciation. You have to be comfortable with data because wherever you go within the TI world, there is gonna be data. People have to be comfortable with data, comfortable with playing with it. You don’t have to be data scientists. You just have to understand what you’re looking at. I think the core thing for me would be the softer skills around things like problem solving, critical thinking, having creativity, and innovation at your heart. There’s a lot of this stuff that is very new and there isn’t a well problem path. You’re finding a new reach, creating new roots. Having that innovative thought process, tying in that dealing with ambiguity, it’s a very messy world out there for a TI perspective.

Toby Culshaw (18m 56s):
Your business leaders don’t necessarily know what questions they’re gonna be asking for. They don’t really know the problem statements. They don’t really know the data sources are gonna be available. You may not what data sources available if you’re going into new markets. There isn’t a world path for this so really, under being to work in that ambiguous space is really a key. I think also, for me personally, I think thinking is really, really cue. That’s Amazonian piece, but being able to look at the work you’re doing and saying, “This is great, but how do I turn this project, this one off project, into an ongoing program of work? How do I scale this so that rather than doing this work 10 times over 10 different stakeholders, how do I build this into one program that’s gonna address all their needs on an ongoing basis?”

Toby Culshaw (19m 40s):
Looking for those mechanisms to try and solve future problems and get ahead yourself rather than just solving for today. I think honestly, the two biggest ones are proactivity and passion. Arguably, some of the hardest to interview against so it doesn’t really help anyone. Apologies for that, but I think proactivity is really vital in the state maturity TI’s in. You have to be hungry, you have to push. Your stakeholders aren’t gonna necessarily know what this is, so you’re gonna have to be pushing with them. Your broader customer base if you’re in TA, you might wanna work with the business. They’re not gonna necessarily open the door for you immediately. You have to be proactive. You have to get out there. You have to push this stuff.

Toby Culshaw (20m 20s):
You have to write papers that’s no one asked for just to show the capabilities and the possibilities within TI. You have to really be very proactive and just basically run with it, and equally have all the passion. There is no set place for this. People have to find their feet. They have to find their direction with this work. You have to be passionate about it. No one’s gonna give you a standalone TI team out of the box and say, “Here you go. Go with it.” You have to be passionate and really fight for it.

Matt Alder (20m 51s):
Looking to the future, you’ve already talked, structurally, how TI might work in organizations moving forward and what some of the possibilities and the options are. In terms of what intelligence might be able to deliver for businesses, things that it can’t do now, what are you looking forward to be able to do in the future?

Toby Culshaw (21m 13s):
Do you know what, some of that I think’s gonna be relatively straightforward but exciting. I think at the moment, most organizations have a fairly decent handle on their internal data. They’re getting a better handle of the external data. It’s still messy. There’s still lots of the data points that are confusing and taxonomies that are confusing. Overall, TI landscape is still hard to unpick sometimes, but it’s getting better. They’re getting data sets, getting data points. It’s starting to work together. I think, short term, what I’m most excited about is bringing the internal and external much close together from a data perspective. For example, if you’re seeing your employer brand or your sentiment data is terrible in a certain location, how does that compare with your internal employee engagement scores?

Toby Culshaw (21m 58s):
How does that compare with your Talent Acquisition metrics? How the funnel conversions happening through that location? What’s the referral rate like in that location? Is that increasing your cost per hire? Externally, you’re not getting applications. The toxic management means you’re not any referrals coming in so have to hire an agency. Your cost per hire is going up. Suddenly, you’re looking for things much more holistically rate spking because your brand is terrible and everyone’s leaving. There’s no one coming back in so you’ve got this huge attrition issue, which means your recruitment process is slowing down. interview, etcetera. Combining the internal dataset with the external into a holistic view, I think super exciting and I think that’s gonna give us some very different perspectives.

Toby Culshaw (22m 46s):
Tied into that also, I think is using that human capital data in with business facing data. I mentioned the marketing intelligence and tying in those other functions to say, “Okay, what are you trying to achieve at an organizational level and how does this work together? I think overall, when I look to the future of the function, I’m super excited where it’s going, but I think that’s also the point where I’m thinking we have a moment in history at the moment where we get to control the evolution of talent intelligence. There’s very few functions where you get that moment in history to really set the standard of what this function could be. I think we’re at that moment in time now.

Toby Culshaw (23m 27s):
I think we’re at a moment where we can look at TI and say, “Well, do we want to be sourcing intelligence? Do we only want to support TA? Do we want to tie in with strategic workforce planning and really give that the external lens and external firepower to look much more strategically to the future? Do we want be a strategic function tying in with strategy and MNA or real strategy, et cetera? We’re at that moment in time where we get to control that and we get to control the narrative and build the future. I think it’s important that because if we don’t, either it won’t happen and you’ll see TI revert back and almost pull within its shell and become much more towards sourcing intelligence again.

Toby Culshaw (24m 9s):
Particularly, tougher economic times at the moment as that market switches back on and companies are super aggressive in hiring again, it’ll be very easy for TI to retract back and go into sourcing intelligence mode because you have to get those hires. You have to get that names generated. How are we gonna find those candidates? I think it’d be very easy to get to pull back into that SI world, which as I say, it’s still very, super important. I think it’s really important function. I don’t think it’s necessarily where TI should be heading. I think we’re at an interesting cross roads at the moment and I think the overlay, before we jumped online, we were talking about different work methodologies. We’ve got things like the metaverse kicking in and I think with that comes a whole different type of TI and a whole different type of labor market, intelligence, and strategic workforce planning.

Toby Culshaw (24m 53s):
Are you looking at individuals? Are you looking at skillsets? Are you looking at units of labor? Are you looking at RPA, outsourcing, or offshoring? All those types of models and that creative way of thinking about work and how work is done, I think we’re at a prime crossroads to help with that for the business.

Matt Alder (25m 12s):
Final question. Tell us about the book. What’s it called, who’s it written for, and where can people find it?

Toby Culshaw (25m 18s):
Yeah, so it’s fairly straightforward name, Talent Intelligence, and then the subtitle, Using Business and People Data to Drive Organizational Performance. You can buy it at usual suspect places really. Amazon, obviously Google Page website. Anywhere you buy a book should hopefully be available. It’s really aimed at people that want to set this stuff up and set a good foundation. Some of the elements of it, we get slightly more advanced TI type work, but really it’s aimed at people that are saying, “I want to set this up. I don’t really know what it is. I don’t really know who to ask. I dunno what’s out there.” This will give you that really good foundation in place of this is what a TI function is.

Toby Culshaw (26m 1s):
This is where it came from. This is how you set it up. These are the systems, processes, tools to look at. This is the structure. These are the things you need to think about in terms of if you’re doing an intake meeting. What could that look like? What questions should you be thinking about right to the maturity curve and the skills to have within the function, what career patch you can expect within the function. Hopefully, should give a really good foundation, whether it’s somebody within Talent Acquisition, whether it’s somebody within HR, whether it’s somebody within the business that’s thinking, “Actually, I need a better handle on my human capital Intel here.” Yeah, hopefully it should give people a handle to get started and sets the functions up.

Matt Alder (26m 40s):
Toby, thank you very much for talking to me.

Toby Culshaw (26m 41s):
Thank you.

Matt Alder (26m 42s):
My thanks to Toby. You can subscribe to this podcast in Apple Podcasts, on Spotify, or via your podcasting app of choice.

Matt Alder (27m 21s):
Please also follow the show on Instagram. You can find us by searching for Recruiting Future. You can search all the past episodes at On that site, you can also subscribe to the mailing list to get the inside track about everything that’s coming up on the show. Thanks so much for listening. I’ll be back next time and I hope you’ll join me.

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