Evidence-based HR practices are no longer constrained to internal or historical data. Combining internal data with external talent intelligence has enabled HR decision-science to become future focused, big picture and benchmarked against competitor activity. Using newer and more powerful analytics, HR can uniquely bring a holistic talent perspective to business decision-making.

Industry guru Dave Ulrich warned earlier this year that HR needs to wise up to the potential and drawbacks of evidence[1]based HR. Delving a bit deeper into his advice, he suggests that HR needs to look forward and not backward, to attend to patterns rather than events and to use information to make knowledge productive. Critically, he challenges HR Directors to ask themselves, ‘what do I uniquely bring to a business discussion to help deliver results that matter?’ This is the crux of decision science and evidence[1]based HR and the answer to this question is the one that will ensure HR is not only at the table, but that it’s a first port of call for strategic decision making. Although HR has made advances in terms of people analytics, there are still too many instances of the practice only being able to present part of the picture, looking at individuals rather than trends, looking internally without a lens on the external market and looking at specific events, rather than patterns in the data.

While many companies now have a mature internal people analytics team, increasingly more are starting to bring in talent intelligence – which we can view as external people analytics – inhouse, as bigger and better data becomes widely accessible. When the two teams of people analytics and talent intelligence work together to combine internal and external data-driven insights, the data is incredibly powerful. Plus, it’s more relevant and more necessary than ever in the post[1]pandemic world, where working patterns and locations are in constant flux. The critical role of steering people strategy has never been in more evidence than over the last 22 months and HR is in the limelight like never before and, as we rebound from the pandemic, people are at the forefront of the rebuild. So, in an increasingly data-led era, how can data guide future talent strategy, without having to become an expert in every application of internal and external data analytics? A healthy relationship with data is one that enables HR leaders to inform the board about the latest trends, keep an eye on competitor talent strategy, build a compelling EVP, enable the business to attract diverse talent and future skills and centrally, answer the questions that only HR can answer.

During the pandemic, many businesses surprised themselves, by their capacity to turn things round in days, that before would have taken months. For them, this is an awakening of potential. The fact is, people don’t ask the right questions of the data, they look at data to provide evidence of what they think they already know. Although the pandemic was in some ways an epiphany for data analytics, in order to maintain the head of steam, HR needs to take a more thoughtful and sophisticated approach to data. Now is the time to capitalise on the headway that analytics made during the crisis, to move away from a mindset of using data to affirm an assumption, towards one where data proactively supports decision-making. Those teams and organisations that are thriving have won trust through accurate, credible, accessible data that can be used to answer questions at tactical and strategic levels. Moving towards data-led decision making requires investment in technology and building the business case for a talent intelligence team is a challenge for many who struggle to demonstrate value from the outset. To start with a broad answer to how this can be achieved, illuminating the answers to these three questions is a key aspect of highlighting the strategic value of data: What are the big challenges your organisation is facing? Who needs to be involved and what data do you need to answer those questions? Importantly too, what are the pain points for your stakeholders?

Once these questions have been well researched and answered, try splitting the challenges into tactics that can be addressed by data at three levels; battlefield, tactical and strategic. Turning focus on stakeholders pain points, at the strategic level, they will likely cover areas such as, a lack of skills availability, real estate optimisation, diversity and workforce composition. At a tactical and battlefield level, this might translate into time and cost to hire and employer value proposition. Once the business case is built, it’s essential to translate stakeholder requirements into key performance indicators (KPIs) for the team. One of the most important questions is, how do you know whether the team is successful? How can you prove that investing in the tools that make data-evidenced HR possible are saving the business money, making the business money and mitigating risks? The success of the team cannot be measured by tactical and battlefield level KPIs alone, KPIs must be strategic and linked to business decision making. By setting strategic and focused KPIs, you can demonstrate how the team is achieving, avert the cost of poor decisions, reduce consultancy spend and accelerate the speed at which the business can access insight. As examples, these might include cost avoidance, such as hiring an external specialist versus the cost of the internal team, repeat business from customers, decreased time to hire, decreased cost to hire and increased quality of hire. They can also include project-related metrics such as; maintaining project over run at less than five percent or team utilisation at over 85 percent.

Once the team is delivering on its KPIs, the next big consideration is how to demonstrate ROI to the business. You know your team is delivering value, but it’s hard to prove the value of not doing something. If a team is saving the business the cost of poor decision making, how can you demonstrate it? Again, the ROI of an HR analytics team sits at three levels: Battlefield, for example attrition rates, retention rates, competitor moves; Tactical, for example growth rates, the cost of unfilled roles and time to fill roles and Strategic; understanding the skills you are hiring for compared to your competitors. ROI at the strategic level can also include scenario modelling to measure the cost of not acting on intelligence, or the cost implications of the wrong decision, including lost market share, decreased revenue and increased competitor advantage, to name but a few. Joining the dots between challenges, stakeholders and data at all three levels is the first step to building the business case for investing in data-based decision[1]making. From tactical measurements such as attrition rates, or losing talent to competitors, or strategic measures such as lost market share or risks mitigated, there is indeed a strong argument to be made that data has the potential to help organisations see the whole picture when it comes to talent.

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