Making the Business Case for Data-Driven HR: 9 Steps to People Success
Gut feelings and best practices you've been using for a decade won't cut it in the future of work. At least not these alone.
Instead, organizations need to get geekier about the people side of the business to gain a competitive advantage.
Data-driven HR decision-making has become increasingly important as organizations expand their global footprint and face new industry pressures. Companies can gain deep insight into workforce dynamics through predictive analytics to inform more intelligent decisions and drive business performance.
This guide makes a case for data-driven HR in your organization.
- The benefits of using data.
- Some key considerations when developing a data-driven HR strategy.
- Practical tips for implementing yours.
📊 What is data-driven HR?
Data-driven HR refers to the practice of using data and analytics to inform decision-making processes within the human resources function. By leveraging data, HR professionals can make more informed, objective, and strategic decisions that impact various aspects of the organization and solve talent management challenges.
The process starts with collecting valuable data using surveys, assessments, review metrics, and predictive analytics on topics such as:
From here, you'll identify patterns and trends as the foundation of strategic decision-making to drive business success. This positions your organization to be proactive and create solutions for forecasted roadblocks.
For example: if staff survey data reveals that employees are disengaged, HR can act on the data by offering individual growth opportunities to prevent a wave of resignations.
🕵️♀️ Status check: The potential of data in HR remains largely untapped
The term "big data" emerged in 2005 when Roger Magoulas, Director of Market Research at O'Reilly Media, struggled to handle an extensive data set using traditional business intelligence solutions.
Since then, companies have relied on data analysts and dedicated tools to crunch the numbers and make meaningful decisions that improve sales and customer relations while streamlining operations.
In his book, Data-Driven HR: How To Use Analytics and Metrics to Drive Performance, Bernard Marr explains how people teams view the people function and processes.
"HR traditionally is seen as being very people oriented, and not so much about numbers and data. A lot of HR data analysis comes in the form of key performance indicators (KPIs) measuring factors like absenteeism or number of training hours per full-time employee, sometimes because these metrics are easy to measure or because they are what other companies measure."
But many HR teams have yet to track these metrics or expand into other areas.
As a result, "The State of the HR Function in Small to Mid-sized Businesses" report reveals that:
- 54% of HR teams take a reactive rather than proactive approach to people-related data.
- 25% fail to use people data at all.
- Only 26% of respondents use people-related data to achieve actionable recommendations on the next steps or address people activity trends before they occur.
🗄️ Why has people analytics yet to take off in HR departments?
As we've seen, many companies haven't yet dipped their toe into the world of people analytics.
Here are four common reasons why HR professionals shy away from data.
1. Cost of implementation and training
An obvious drawback for small to mid-sized companies is the budget issue, especially during implementation.
As Sylwia Smietanko, HR Specialist & Recruiter at Passport Photo Online, tells us:
"People analytics has seen tremendous growth in the past few years, but I've yet to implement the technology into my practice. The reasons why I haven't done so are mainly due to the cost associated with adopting such a solution — it requires extensive training and is quite expensive for many organizations. The majority of people analytics software is also tailored for larger enterprises which can lead to complex implementation for mid-sized companies like mine."
2. Concerns about bias
Growing awareness of bias and how it can unconsciously influence decision-making in the work environment may also dissuade HR teams from becoming data-centric.
Karolina Kijowska, the Head of People at PhotoAiD, told us:
"Like all data-based approaches, people analytics can be prone to biases. Especially harmful is confirmation bias, where analysts only look for data that supports their previous assumptions. For example, suppose an organization believes younger employees are more productive than older ones. In that case, they may only look at data supporting this belief and ignore data contradicting it."
The way to overcome this barrier is to include diverse voices in the decision-making process and consider a wide range of data points when forming conclusions.
3. Retaining human approach to people management
At first glance, statistics presented in stale charts, graphs, or raw percentages certainly seem far removed from human people processes.
And this is the top reason why Grace He, People & Culture Director of teambuilding.com, has opted to steer clear of data-driven HR. She told us:
"While data can provide insightful information on employee behavior and engagement, relying solely on it may lead to a dehumanization of our workforce. Our employees are not just numbers; they are real people with unique circumstances and needs.
Therefore, we must balance our use of data with empathy and intuition to create meaningful interactions that acknowledge their individuality. This is especially true in small and midsize companies like ours, fully remote workforces especially. In such an environment, the human connection becomes even more critical to make employees feel a sense of belonging and to feel valued by leaders."
4. Difficulty tying people data to business goals
According to UKG's aforementioned report, 71% of organizations admit it's challenging for business leaders to tie people data to larger business goals and initiatives.
HR professionals must demonstrate how people analytics can improve employee productivity and engagement, reduce turnover and absenteeism, enhance recruitment activities, and much more.
Again, this is where a combination of data-driven insights and a human-centric understanding of people comes into play.
Translating people insights into actionable strategies that help achieve business objectives is key to making a case for data-driven HR.
📈 7 Reasons to implement a data-driven HR model
But savvy companies look past these obstacles and recognize the value of using numbers to support their key people processes.
Here are seven compelling reasons to embrace a data-driven HR model.
Increase workforce productivity
Key insights into employee behavior support HR teams in optimizing how they manage their workforce, ultimately improving output.
For example, HR data analytics can identify high-performing employees who contribute significantly to the organization.
From here, companies can reward them with incentives and recognition programs, increasing job satisfaction and motivation to perform even better.
Boost corporate agility
Organizations using people data achieve 82% higher-than-average corporate profits over three years compared to their low-maturity counterparts.
A clear understanding of what your future and current employees need to perform effectively helps HR teams make more informed, agile decisions in times of uncertainty.
Prepare managers and HR for the future
Successful managers must always look at the next one to five years to forecast what resources their team may need.
By analyzing employee data, businesses can identify the characteristics of their current top performers along with their power skills, experience, and performance management metrics.
This information supports workforce planning in areas such as learning and development and hiring process decisions.
Funnel high-priority resources into impactful business areas
Data provides answers as to which of your processes has the highest ROI.
Your organization might be stretched and can't commit to every initiative on the table. In that case, data will identify which areas are most effective and worth investing in.
By doing so, you won't plunge time, money, or resources into areas that don't produce results.
Identify talent programs' efficacy
Measuring the business impact of an existing talent program enables you to make improvements where necessary. Track metrics such as:
- employee retention;
- promotion rates;
- employee satisfaction.
Take regular snapshots and compare them against the original program objectives.
As far back as 2015, the Wall Street Journal published an article on "The Algorithm that Tells The Boss Who Might Quit." And this is the essence of what retention analytics are.
The software takes employee feedback or performance data to highlight which employees are considering leaving the organization because they're disengaged or dissatisfied with their work.
Enable intelligent recruitment practices
An analytics-driven HR team can run assessments to ensure they're hiring the most suitable candidates for the job. By leveraging skills tests, video interviews, and background checks to capture essential data points, HR teams can save time and money by quickly narrowing down their recruitment pool.
Data will also spotlight a lack of diversity and inclusion in your workforce. Utilizing various recruitment channels will address these gaps and create a more diverse and inclusive team. Plus, businesses will tap into multiple perspectives and experiences, leading to more innovative ideas.
💡 Design a data-driven HR strategy in 9 steps
A logical strategy is a perfect complement to traditional people-centric processes.
Follow these nine steps for success.
Define your business problem
Collecting all the data without a clear goal is a recipe for disaster.
You'll quickly become overwhelmed with numbers you don't know how to act on.
So instead, begin by selecting a specific challenge or goal to work towards. This approach ensures you'll create value from all your people analytics projects.
Lead with a hypothesis
Incorporate humanness into your people analytics by creating a hypothesis, then checking to see if the data supports your theory.
Example hypothesis: Providing greater career opportunities and career framework transparency decreases turnover.
Inventory available data
Start by taking stock of your current data.
If you're missing any obvious opportunities for feedback, consider implementing them to capitalize on these actionable insights in the future.
Remember: Always use a range of data types to eliminate the incidence of bias.
Choose data-driven HR tools
The right HR analytics tools will help you to collect, analyze, and interpret people data. Research solutions that fit within your budget and skill level and always ensure data privacy is a priority.
Analyze your data collection
Review all of your data sources to identify trends and correlations. Look for cause-and-effect relationships, such as how changes in hiring practices correlate to changes in employee retention.
Here are some analysis techniques you might use:
- Text analytics: extract value from large volumes of text data such as emails, survey responses, job applications, or performance reviews.
- Predictive analytics: use artificial intelligence to estimate the likelihood of future events based on historical data.
- Voice or speech analytics: analyze audio recordings to gain an overview of the topic or specific words and tone used
- Video analytics: rely on CCTV footage to extract valuable information, such as if your construction crew adheres to health and safety regulations by wearing the correct safety gear.
- Image analytics: use pattern recognition to extract information from graphics or photographs.
- Sentiment analytics: understand attitudes by working with text analytics to uncover the nuances behind the employee experience.
Reveal helpful insights
The next step is to tell a story with the numbers, adding plenty of context before presenting it to an audience. Bernard Marr explains:
"These days, most HR teams are already data-rich, but that is not the same as being insight-rich. To be insight-rich, you need to turn the data you collect into valuable insights that answer your strategic questions and deliver your strategic goals."
The aim is to craft a narrative they can easily understand, regardless of their preferred learning style. Incorporate visual aids such as charts, pictures, or videos to illustrate the statistical evidence you're displaying to keep your audience engaged.
Devise a strategic plan
Start planning how you'll put your strategic insights into practice. Remember to involve stakeholders in the decision-making process as you create a plan. This will ensure they buy into your strategy and understand how data-driven people decisions benefit the overall organization. Your plan should also include:
- implementation steps;
- progress tracking.
Empower your team with workforce analytics training
The key to making data-driven HR decisions is giving your people team access to the right tools and resources.
Tip: Invest in learning experience platforms, microlearning, workshops, or seminars to ensure your team is comfortable using and applying the data strategically.
Incorporate data-driven decision-making into your HR mission statement
To be effective, data-driven decisions must be a priority in your organization.
Revisit and update your HR mission statement to reflect a commitment to data-driven decision-making.
Your statement must be transparent about how you collect employee feedback, with an expectation that you will use it to inform your HR strategy.
➡️ Drive strategic and data-driven people processes with Zavvy
Collect the data you need to power your people processes with Zavvy. Our suite of tools includes:
- Analytics: customize our complex dashboards by hire date or department, providing key data such as compensation statistics, attrition rates (viewable by tenure, gender, or reason for departure), manager stats, headcount, average tenure, and the average age in the company.
- Pulse surveys: gain regular employee sentiment snapshots enabling you to identify trends and act on them.
- Performance feedback: analyze valuable data on L&D goals, feedback conversations, and productivity.
- Onboarding: collect engagement data on candidates and new joiners, ensuring they feel welcomed and have all the resources to start contributing to your organization's success.
- Learning management: understand training completion data and learner engagement and spot opportunities for improvement.
Ready to leverage the power of data? Test-drive Zavvy by booking a free demo of our suite today.
What do you mean by data-driven HR?
Data-driven HR is an approach that uses people analytics and data to inform decisions made by the Human Resources department.
Data-driven strategies are based on HR metrics that measure people-related activities, such as employee engagement, retention, and performance.
What is one way HR can be more data-driven?
Onboarding is one aspect of HR where collecting and analyzing data can be beneficial. Ask new joiners to complete pulse surveys at regular points during onboarding. Then use this data to identify areas for improvement, measure how quickly your new hires become productive, and analyze the attrition risk.
Is a data-driven approach toward human resources necessary?
Data isn't the only way to power an HR department, but it is the future. A data-driven approach ensures you make the most informed business decisions possible, leading to better results and greater success.
Put simply: if your HR professionals don't use data, you are likely to fall behind competitors that do.