Gaining actionable insight from HR and People analytics isn’t always easy.
If your business is finding it a challenge, rest assured you’re not alone.
Over 90% of HR leaders said that they struggle to gain strategic insight from their HR and People data, according to our research.
Enter: People Science.
People Science means applying data-driven approaches to improve workforce visibility and how you both manage and engage your workforce. It’s about understanding employees and their behaviour in your company and generating more actionable insights to help you make better business decisions about your workforce.
People Science is more than just HR analytics, however. In practice, it means not just mining data and reporting it—but analyzing it and gaining actionable insights to test hypotheses and identify solutions.
We’ve blogged before about how People Science is a journey: companies must start with data collection, then progress to reporting, then analysis, then insights and finally People Science – the end goal.
HR and People teams can’t expect to become People Science experts overnight, and often naturally follow this journey to truly impact business performance.
For those companies in the middle of their journey, though, how can you use reporting to develop actionable insights? How can you move from the ‘data collection’ part of your journey, to the ‘analysis’ and ‘insights’ part? Here’s three steps to help you along the way.
Firstly, People KPIs need to be derived from business KPIs. The most important People metrics vary considerably across the phases of a company’s business lifecycle, so it’s important that your KPIs reflect current and realistic goals.
As an example, rapidly growing companies need KPIs focused on talent acquisition and retention to supply the headcount needed to enable that rapid growth.
Whereas a mature organization might be looking for its next market move. In this case, they might be considering a focus on their talent and performance management KPIs.
On the flipside, companies which may be in an economic downturn will need to rationalize and maximize the efficiency of their workforce, with a watchful eye on labor productivity and costs.
Just as a business has short and longer-term goals, HR and People teams need to both assess performance today and prepare the workforce to meet the business needs of tomorrow. This involves measuring the current ‘lagging’ metrics, as well as ‘leading’ metrics also.
‘Lagging’ metrics are outputs of an event. They confirm long term trends, but do not predict them. They are often easy to measure, but hard to influence.
For example, turnover rate is a lagging metric measuring a company’s performance on employee retention. It is often used in workforce planning to estimate how many employees will leave in the future by assuming the current rate of departures continues.
However, to truly predict the risk of an employee leaving or how current initiatives will impact future departures, ‘leading’ metrics are needed.
Although lagging metrics can confirm patterns and trends, it’s only with ‘leading’ metrics that HR and People teams can influence the data and do something to change trends that are emerging.
Employee engagement is closely linked to employee retention, with highly engaged employees less likely to leave. As a result, changes in employee engagement are leading metrics indicating changes in retention. A company trying to improve retention can monitor the success of their efforts by measuring changes in engagement.
There is a difference between KPIs and other metrics HR and People teams may need to track. A KPI is a measurable value that demonstrates how effectively a company is achieving key business objectives.
However, measuring KPIs alone is insufficient. For each KPI you also need to determine other metrics that impact or drive it. KPIs measure how well you are performing, or have performed, and these additional metrics should help explain why you are performing at this level.
For example, talent acquisition KPIs would be the number of hires and the quality of those hires, both of which are lagging indicators as they measure previous performance.
However, improving performance starts with understanding what impacts or drives it, and therefore what drives the quality of hire. So in this example, explanatory metrics might also include recruiting process metrics, such as time to fill, along with sourcing and employment brand measures.
Fascinatingly, companies at the highest level of People analytics maturity reported 82% higher three-year average profit, compared to those at the lowest level of maturity, according to research carried out by Deloitte.
Yet only 37% of companies are using data and analytics to make decisions, according to Sage People research.
For those who may be collecting data but are looking to take their next steps on their People Science journey to gain better workforce visibility and actionable insights, these three steps may help.
Find out what stage of the People Science journey your organization is in. Download the ebook ‘Five secret steps to greater workforce visibility’.