Succession planning and leadership development are tough for Human Resources (HR) and Learning and Development (L&D) professionals, who must anticipate business needs and offer proactive strategies to drive performance.
Yet, because most HR teams lack empirical tools to evaluate an individual’s capabilities or likelihood of future leadership success, their decisions are often based on gut instinct, personal perception, and personality. And despite their best efforts to remain objective, it’s simply human nature that personal biases come into play when making these business decisions.
Using Science to Strengthen Leadership
The use of scientifically valid and objective leadership assessments allows HR to cut through the subjective fog of talent decisions. By providing data-based insights, objective assessments help companies use behavioral metrics to minimize bias; make better, more confident promotion decisions; and avoid overlooking hidden potential.
In fact, data shows that those who can proactively surface leadership talent, HR “Anticipators,” consistently deliver higher quality and more successful leaders for their organizations. It’s no surprise that these successful “Anticipators” are 2.1X more likely to use objective assessments in their hiring, succession, and development—clear evidence that empirical assessments are key to success.
What makes data-driven assessments so powerful? Here’s how they contribute to better outcomes for your organization and your team.
- Behavioral data tops all. Effective leadership assessments must be based on how a person behaves, not only on what they know or how they’re perceived. That’s why things such as 360s, personality inventories, and IQ tests only give us part of the picture. Not only do some people just “test well,” but 360s are limited to the perception of the individual performing the assessment at that time. And IQ tests are simply insufficient. One organization found executives scored high on one IQ test and low on another. Which one should they trust?
Behavioral assessments reveal how that person actually shows up—how they respond in the moment as a leader and whether they can put into practice what they know, not just get the right answer on a test.
- Validity = accuracy = equity. Many people think of data validation as some laborious process of statistical analysis. But it really just means making sure the data is accurate. Data-driven assessments ensure that decisions are based on empirical evidence and that we’re giving people a fair shot by removing as much bias as possible from the decision-making process. This eliminates gut instinct and reduces adverse impact by establishing criteria, guidelines, and validity. It increases the likelihood that a participant’s evaluation is due to their capability rather than their gender or skin color.
- Objective data is actionable. The value in conducting assessments isn’t to merely get the data—it’s what you do with it that matters. Valid data enables you to identify next steps and chart a path for improvement. It can be tied to performance and growth to measure whether coaching, training, or mentoring is moving the needle. If an initial assessment shows that Adam is two years away from readiness to take a director-level role, and he’s still two years away 18 months later, that’s a problem. Empirical data can pinpoint those gaps.
- Data is nonjudgmental. When it comes to people skills, we often default to using flowery words to describe abstract concepts, and leaders sometimes tiptoe around criticism to avoid hurt feelings. Objective assessments give us a standardized language and an empirical score that adds consistency and provides a foundation for integrating other perceptions of the participant’s job performance. This gives L&D leaders a nonjudgmental way to assess and discuss gaps and opportunities. Instead of Adam deciding that Mary needs training or coaching, the data shows it to be true.
- Stretch and predict. Data-based assessments allow HR leaders to benchmark prospects against established metrics for a specific leadership level across industries, organizational demographics, or globally. Once you know how an individual stacks up, then you can bring your specific business context into the equation to stretch them up one or two levels. Empirical data makes it easier to assess experience needs and predict performance in the context of current business drivers and future initiatives. This strategy can optimize the development approach to focus on future needs rather than current skills and performance.
A Word About AI: Proceed With Caution
Of course, artificial intelligence (AI) can be a game changer for sifting through large sums of data quickly to identify patterns and connection—but only if it’s trained and incorporated effectively. The key is to be smart about AI use. Identify where AI strengths can be leveraged to extend value and ensure solutions have processes for establishing validity, managing drift and hallucinations, and looping in humans at the right times.
Data Drives the Business—HR Is No Different
The fact that every other business function relies on empirical data—from financial analysis, productivity, and quality metrics to lead gen and sales—proves that valid, objective data is essential for making smart, strategic, and defensible decisions. Your HR and leadership development strategy should be no different.
Before deciding on any strategy, HR leaders should always start by asking what problem they’re trying to solve. Is it a leadership gap? A training void? A succession shortfall? Next, identify what data is missing, then start gathering and analyzing it. Otherwise, you miss out on verifiable metrics to prove HR’s strategic value.
