Sevenstep Blog

Talent Acquisition Leaders Seek Predictions That Matter

By Amy Bush, President

 


 

The turn of a year brings prognosticators out in force. In talent acquisition (TA), many macro-level predictions by analysts and solutions providers will attract attention. These forecasts draw sound conclusions based on real data, yet few will pass the “so what?” test for decision-makers. If a projection about talent or the economy is too broad, there is little a TA leader can do about it.

Now, that is changing.

Can You Predict if a Requisition Is Going to Age?

In 2023, our organization embarked on an initiative to better forecast the road ahead for our TA solutions clients. Historically, our technology innovation team has dedicated much of its efforts to building predictive analytics into our proprietary integration platform, Sevayo® Insights. Our clients and delivery teams apply that technology to accurately forecast everything from hiring volumes, talent supply and market conditions to the number and type of resources needed to deliver on time and within budget.

For this new project we addressed one of the most stubborn TA challenges: reducing and eliminating aging requisitions. Even in the best talent operations, problem vacancies can arise. If left unaddressed, they create outliers that can skew the performance of any TA function and leave the business without the critical talent it needs.

In setting our business strategy, we did not just want to predict a market or make a general statement about the future to slightly influence general ideas about hiring or budgets. We wanted to make predictions that:

  • Informed decision-making with detailed and relevant insights

  • Delivered a measurable level of reliability

  • Offered a path to a specific action that could influence or change business outcomes for the better

Considering these parameters, the recruitment remodeling initiative focused on three fundamental questions:

  • Can you predict whether an open requestion will likely age (remain unfilled past its time-to-fill objective) before it even goes live?

  • What can you do about it?

  • Can you create and demonstrate positive outcomes from your results?

Developing and launching this initiative involved business, TA and technical expertise. Our innovation team applied machine learning to analyze historical data from multiple clients in our Sevayo® Insights platform, ranging from six months to several years (including up to 12 years from a long-term client).

The platform learned from that data to predict when a role was at risk of aging. We identified factors contributing to that risk, set thresholds to monitor current open roles and then structured specialist resources to deploy specifically against high-risk openings. By predicting and addressing problem areas, we:

  • Reduced aging from roughly 40% in a challenging clinical talent hiring effort to 6%

  • Cut overall time-to-fill by 18 days

  • Increased the hiring manager Net Promoter Score (NPS) to 90%+

Better still, we have applied this predictive modeling practice across multiple clients to drive greater results for organizations in our portfolio.

Can you predict whether a requisition will be at risk? Can you do something about it? Can you achieve a positive impact? The answer to all three questions is “yes.” With forward-looking intelligence, TA leaders see the hazards ahead and can steer around them and build a more reliable strategy in the process.

Building Predictability into Your TA Function

The work in this successful TA process enhancement highlights advances in predictive analytics that reshape employers’ expectations of their talent solutions partners.

If you are establishing expectations for a solution that will build data-driven predictability into your TA function, you are not alone. Our report based on an Everest Group talent decision-maker survey finds:

  • 93% of respondents rate predictive workforce intelligence as important or extremely important to their organizations

  • 88% expect their RPO or MSP solutions to help them adopt this technology

Raising your expectations is critical to the effective use of analytics. Remember, the technology involved depends on more than simply reporting data. It relies on the breadth of data, the integration of sources into one environment and the predictive analysis of that information to deliver detailed projected outcomes.

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That same report outlines fundamentals to consider as you evaluate your technology or talent solutions partner options.

  • Stop looking for technology features and focus on empowering human decisions instead.
    Workforce intelligence is not about improving data; it is about connecting data to decisions. The features of our technology are advanced, but they are valuable because they directly impact the decisions we make.

  • Adopt ecosystems, not one-off applications.
    Data comes from many sources, and even the most advanced analytics solutions are only as accurate and relevant as the data they can access. There is a reason that we emphasize the fact that our Sevayo Insights technology is a talent data integration platform. It does make a difference when you derive your intelligence from all data sources. It takes a robust analytics capability to do that.

  • Metrics do not solve problems. Humans do.
    The recruitment remodeling initiative is an example of how a provider can put data to work in a way that pre-emptively tackles risks before they turn into real challenges. Technology alone will not create the solutions, but our people could not do it without technology.

Making Forecasts That Matter

Our company comes together with a problem-solving mindset that makes our innovations immediately practical to our clients. Employers expect this from their talent solutions partners, and our clients depend on that mindset to tackle challenges that an uncertain market inevitably brings. Our clients’ challenges never get easier, so our industry cannot afford to stand still when it comes to innovation.