Measuring the ROI of your talent engine

Any leader with P&L accountability knows that tracking margin (ie the difference between your revenue and what it costs you to earn that revenue) defines your unit economics.

How can you quantify the unit economics of your talent engine (the incremental cost of each new hire and the value delivered to your organisation from that hire) to ensure you are delivering best-in-class ‘talent’ unit economics?

Global data suggests that annually, organisations invest at least USD$350 billion pa* in acquiring talent. For many HR teams, the recruitment team represents the largest headcount and most significant cost within the HR function, so measuring ROI is critical to running a commercial function (especially since HR is a cost centre and as such, every unit of ROI impacts the bottom line).

Recruitment teams and HR teams are often challenged with not being commercial enough, so let’s take a commonly used set of metrics in another sector and apply them to help guide ROI quantification of your talent engine.

‘CAC’ (customer acquisition cost) and LTV (lifetime value of that customer).

SAAS Metrics for Recruiting

SAAS companies pay attention to two key metrics that speak to ROI of effort - ‘CAC’ (customer acquisition cost) and LTV (lifetime value of that customer).

No SAAS business will survive for long if it's acquiring and then churning customers. That’s like burning cash. Similarly, no recruitment team is going to be seen as high-performing if they are hiring and then churning employees.

In a high employment market, there is a lot of talk of hiring anyone capable of ‘fogging a mirror’, almost an excuse for teams that are hiring and churning.

Recruitment teams seem to be valuing more the speed and efficiency with which they can deliver replacement hires than stopping to examine why their churn is above benchmark (which based on US stats is around 20% for best-in-class companies). Now we all know that people leave for a lot of reasons. But, for any churn less than 90 days, that’s 100% on the recruitment team for not doing enough to qualify for fit

Recruitment has to be more than filling a seat with a warm body. Time-in-seat matters otherwise you are ignoring LTV which is the longer-term ROI measure of success in hiring.

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Applying these metrics to your talent business model can help identify where to invest your HR budget to drive better ROI.

●????? Look at your CAC as your candidate and talent acquisition cost. How much does it cost your business to hire one person, taking into account the direct and indirect costs of hiring?

●????? Think of your LTV? as the long-term value of your talent. How long do your new hires stay in the business? How many of your leadership roles are filled by internal talent which is a lower acquisition cost than external recruitment?

LinkedIn has the best data to analyse this at scale per company, per industry, and over time. To my knowledge, they haven’t shared the analysis if they have done the work.

Let’s do the math

A simple model below shows the costs of bad hiring. CAC can be as high as $53,000 under this scenario which would imply an incredibly ineffective talent engine. Plug in your own numbers to work out your company’s CAC LTV becomes redundant in this scenario. It's zero given the churn If these were the numbers for a SAAS business they would have long since gone out of business, quickly having burned all of their available operating capital without being able to make a compelling case to raise more.?

So, instead of optimising for speed of throughput, optimise for CAC - Just like in a SAAS business where speed of customer acquisition can also be seductive as a success metric. If you are losing those same customers 6, 9, 12 months later, then you are throwing money down the drain. Longevity matters in every sector especially when it comes to hiring.?

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AI can massively drive DOWN your Candidate Acquisition Costs

4 factors drive your CAC:

1. Direct recruitment costs ?(i.e. how many recruiters do you have on the tools)
2. Indirect recruitment costs, eg the hours invested in interviewing by people leaders or hiring managers.? This is typically the least understood and often the biggest cost. Minimising the number of interviews per offer is critical.
3. ?The productivity and speed of your recruitment team (that is, it’s scaleability)?i.e. the number of candidates they screen in an hour, a day, a week, a month, etc.
4. The layers of assessment in your recruitment and their costs?(i.e. are you doing CV screening, phone screening, video screening, 1:1 interviews, panel interviews, group assessments, coffee chats?)

All of these layers of assessment, some with some science behind them, most with no science behind them, add to your CAC.

AI can automate all of these to a full or partial extent. You can expect between 90% reduction in CAC by using the Sapia.ai platform to automate screening, interviewing, candidate feedback, and interview scheduling.

AI can massively drive UP your LTV

Lets deep dive into LTV in the context of recruitment

We analysed LTV for our customers comparing their ‘old’ recruitment process to a new world where they use our AI to do their screening and assessments.

The results are stunning.

One large UK retailer was struggling with extremely high turnover (77%) prior to implementing Sapia.ai’s automated recruitment tool aimed at finding the best people for the role (which they measured by time in role, ie LTV).

With a large upfront investment in training and development of new employees, reducing churn was a priority - in effect CAC payback was longer than usual given the high upfront investment in training.

By relying on Sapia.ai to shortlist the best candidates, this retailer cut their time to hire from 21 days to 7 and reduced churn from 77% to just 29%. Thus, they achieved a significant reduction in CAC and also an increase in LTV.

Both are important for building a strong talent engine.

Automation of a bad process will come at the cost of LTV which is often a much bigger cost to a business when you take into account the cultural impact of employees churning.

Similarly, a large financial institution was facing heightened turnover in the years prior to implementing Sapia.ai. With the help of our platform, they are now seeing turnover rates of only 21%, compared to over 60% turnover in the roles where Sapia.ai is not being leveraged. Specifically, Sapia.ai helps them quickly identify good-fit candidates who are more likely to stay in the role. 68% of the longest active hires came from the YES recommendation and 84% came from the YES and MAYBE recommendations. Additionally, 80% of candidates who received a YES recommendation were medium-long stayers. Again, measurable improvement in LTV.

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*Linked In search 14 October 2023 shows 350,000 people with 'recruiter' in their title. Assuming the average fully loaded cost of 100,000 gives you 350bn.

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