Data is power, or more accurately, smart insight derived from accurate data is power.  Once organisations have experienced the clarity and confidence that talent intelligence provides, they invariably want to continue to have talent intelligence as an element of their strategic planning and hiring.  Katie Chevis, People & Culture Partner delves deeper with Alex Martin, Talent Intelligence Managing Partner, including talent intelligence’s role as ‘glue’ between strategic workforce planning and talent acquisition and how this relatively new discipline is supporting skills-based hiring.

Katie: Could you share with us the context and purpose behind Savannah’s development of a data-led talent intelligence function?

Alex: The use of data to understand our environment has increased rapidly over the last ten years. From the health trackers on our watches to spending breakdowns on our banking apps and screentime trackers on our phones. Our thermostats at home are digital. Cars give us detailed data on everything from energy consumption to tyre pressures and the apps we listen to music on can tell us how our music preferences compare to the rest of the world. With such a societal shift to surface and utilise data in decision making in all areas of our lives, it’s only natural that the demand for using data would apply to the business environment. In marketing, we have metrics that help us optimise our marketing spend, measure campaign effectiveness, brand awareness and more. In technology, we have user data on product behaviour and infrastructure usage. In finance and commercial, we have reports on our P&L, cashflow and forecasting. And in human resources, we have data on our employees. So why not apply the same approach to understanding the hiring market? Global spend on recruitment and human resources services is around $600bn per year. So given we’re spending all that money on hiring people, if you had better data on that market before you started hiring, would that lead to hiring better people?

We think it would. But in the past, getting that data has been difficult. The availability, consistency and categorisation of data for leadership roles has been limited. Recognising this trend, Savannah saw an opportunity to apply data science and analytics in our work on leadership talent acquisition to enable more effective diagnosis, design and delivery of leadership solutions.

The platforms and techniques we’ve developed now allow us to combine a wide variety of public and private data sources including social media platforms, company websites, job boards, government data, annual reports and private databases with advanced labelling and categorisation techniques. We can process millions of data points in hours or days rather than the weeks it used to take. This has created an ability to quickly draw conclusions on questions as specific as ‘is there anyone else we should be considering for this hire?’ to questions as broad as ‘which countries and locations should we build our future workforce in?’. It’s a pretty amazing capability that the business world is still waking up to. It’s a bit like the story behind the film Moneyball where Brad Pitt plays Oakland Athletics’ General Manager Billy Beane, who used statistical analysis to assemble a competitive baseball team in a world where decisions up to that point had been based on gut feel. All of a sudden, we have this ability to see into the market and know how many people have the required blend of experiences, who those people are, and where else we could look. Or compare the way other organisations have built out and structured capabilities that you are looking to add.

Katie: Is talent intelligence mainly a data retrieval function for human resources or talent acquisition teams?

Data retrieval is of course an important part of the job, but talent intelligence should not be thought of as just a data retrieval exercise. The context of a scenario is always different and therefore the choices that you make about how to approach answering it will vary. No one platform has all the answers and each approach has pros and cons. For example, when looking at country level data, governments and universities record different statistics or have different categories depending on location. So you need to standardise between those locations. Or when looking for data on a specific job title, you need to consider the wide variety of titles for the same job in different businesses and organisations. So you need to know all the different relevant job titles and seniority levels that you should be including in your analysis.

It’s the job of a talent intelligence team to consider all this, understand the specific business challenges and devise the best approach to build the data sample which will answer the problem statement in the most robust way. After that decision comes the data retrieval, and then you need to categorise the data, visualise it to spot patterns and outliers, determine conclusions and present the information in a clear and engaging way. So the skill sets within a talent acquisition team include consulting, data analytics and recruitment research, and the talent intelligence function should be a strategic partner to talent acquisition, strategic workforce planning and functional, divisional and senior leadership teams.

Katie: Who benefits most from talent intelligence offerings and where does the greatest value lie?

At the moment it’s organisations that naturally value data-driven decision-making. Think private equity firms, technical businesses like technology, manufacturing or insurance and larger more complex corporate organisations that are already well-versed in using data across various functions. For these businesses, it’s a natural progression to utilise talent intelligence to enhance their recruitment processes and overall workforce strategies.

One immediately obvious demonstration of value is in helping hiring managers understand how different hiring criteria affect the size of candidate pool for leadership or executive roles.  In a lot of cases, the layering of criteria results in tiny candidate pools. There is a bias that exists where because you know someone or used to work with someone who has a specific blend of experiences, you think there are many more people just like that. In some cases that might be true, but the more senior the talent pool gets, the more career paths diverge in different ways.  It is helpful therefore for hirers to know that if they are looking for, say, a diverse finance director with FTSE 250, Big Four consulting and commercial experience, there are a handful of people that meet that brief. That’s not to say you can’t land one of them, but it’s a tight market and the odds of you catching someone at the right time are reduced. Or at least be prepared to overpay. Knowing this upfront enables helpful conversations at a briefing stage to align expectations and provide solid data on how big that market is and which specific parts of your criteria are restricting the talent pool the most. That gives the best of all worlds, it means we can rapidly identify the people that meet all the criteria and go and approach them. But also agree on the elements of the brief we can flex to widen the talent pool sufficiently.

It is worth noting that some leaders struggle to relinquish reliance on gut-feelings and everyone has biases, particularly in hiring scenarios. Part of the job of talent intelligence, particularly when applied to recruitment, is to present a range of candidate profiles that meet the brief but also push the thinking about who should be considered. Often this challenges pre-held beliefs and that can be uncomfortable. But it’s the path that leads to building more diverse and future ready teams. It will take time for all organisations to embrace the benefits of using data as a core component of leadership hiring decision-making. But again, I think of the analogy of Billy Beane in Moneyball, the companies and leaders that lean into the market data and keep an open mind will gain a talent advantage over those that don’t. Now, every team in US Major League Baseball uses statistical analysis to pick players.

Katie: How does talent intelligence relate to strategic workforce planning?

They should be closely linked. Strategic workforce planning is often, perhaps unfairly, criticised for its theoretical nature, detached from the market realities of recruitment. And talent acquisition is criticised for being an operational function without strategic foresight. This is where talent intelligence plays a pivotal role. Talent intelligence can be the glue between strategic workforce planning and talent acquisition teams. Helping the strategic workforce team test hypotheses before a direction is chosen and provide them with recruitment quality data on a market. In turn, talent intelligence can also help talent acquisition teams get realistic briefs and good guidance from hiring managers and human resources business partners.

Katie: Some clients are exploring skills-based hiring as an option. What is this and can talent intelligence help?

Skills-based hiring places a primary emphasis on the specific skills a person has rather than on job titles, roles or organisational experiences. Today, the remit related to a particular job title is changing fast. Relying on historic job title naming conventions and organisational experience based on the companies someone has worked could mean overlooking people not covered through this approach. Another merit to a skills-focused approach is for the employee who can get exposed to a broader range of career options. And for many organisations, the skills they need for the future are not in sufficient supply in the talent market. So something needs to be done to develop people with the skills they need.

Organisations moving to this model start by building internal skills frameworks to identify and catalogue the skills they have within the organisation and map against the skills they need. This is usually relatively easy to do using data available on human resources’ systems.

The challenge comes when bringing internal people data together with external people data. The external talent data is more fragmented, less standardised and less complete. So how can you decide whether someone has the skills you need? The most common way is to use a skills library. But this presents problems. Firstly, skills listed on a person’s profile are self-reported which means they may be either over embellished or missing entirely.

The alternative is searching for keywords that suggest someone may have a skill. Once again you are relying on a person accurately representing themselves and on knowing all the different ways that skill could be described.

Savannah Group’s perspective is that job titles still hold the key, but to look at them alone is limiting. The key is in understanding job title (function and any specialist capabilities) seniority (size of role) and organisational environment (what the company they work for does, how big their team is vs other similar organisations, how big is the division or region they work in vs the whole etc). From that we can create a skills framework which we believe is a more reliable and consistent indicator for the potential transferability of a person from one role to another. Using talent intelligence you could also consider the frequency that a move from a particular functional area to another happens and whether or not these moves are usually successful. Or the transferability from one industry to another. There is a lot that talent intelligence can offer in relation to the skills-based model transition.

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