Big data. Two small words with huge implications. But is this really the business differentiator it is hyped up to be? Or is it just more meaningless industry jargon?
The answer depends on how you use it. When applied correctly, big data can lead to better conversion rates, faster production and a bigger bottom line.
Companies that implement data-driven decision-making are five to six per cent more productive than companies that don’t, according to 2014 research from the MIT Center for Digital Business.
The benefits of using big data in the human resources function are also significant. Human resource managers can use big data tools to hone their recruitment process, avoid costly skill mismatches and more effectively retain top talent.
One in six Canadian employers “always” or “usually” use analytics as part of the recruitment strategy, according to a 2014 survey of more than 400 Canadian hiring and HR managers released by CareerBuilder.ca.
Of these employers:
•70 per cent said it lowers the cost per hire.
•66 per cent said it lowers time to hire.
•49 per cent said it helps them hire more candidates for specialized fields.
But these benefits only scratch the surface of big data’s potential. HR leaders have a lot of data at their fingertips.
In addition to internal data gained from pre-employment assessments, employee engagement surveys and applicant tracking systems, there are a variety of tools available that leverage government and online recruitment data.
These tools crunch millions of data points — resumés, job postings, labour force surveys — enabling human resources to locate the areas where the greatest supply of qualified talent is most concentrated, find out the going salary rates and see which organizations are competing for the same candidates.
The overwhelming supply of data available is both a blessing and a curse for HR managers. While data can unlock the keys to proper workforce planning, effective employee engagement and a strategic recruiting strategy, knowing where to start is a battle in and of itself.
The mere idea of mining all of this information can be overwhelming. The good news? It doesn’t have to be complicated.
One of the biggest misconceptions about working with big data is the idea you have to work with every data point available. Not only is this overwhelming and virtually impossible, given cost and time constraints, it is also unnecessary.
Here are some steps to navigate the vast amount of HR data available to you.
Know the difference between data and metrics: A metric contains a single type of data, such as the number of applications or employees. Not all data matters, which means not all metrics matter in terms of a particular organization and its specific needs and goals.
Work with the right data: If you are working with unreliable or irrelevant data, the results will be inaccurate and your resulting approach to reach those goals or solve challenges will be misguided.
Define goals: The goals will tell you which metrics, or data sets, to look at. Once you have determined which metrics to focus on, you can measure the impact of your effort to reach those goals and adjust accordingly.
Focus only on the metrics that matter: Collecting data and calculating metrics is time-consuming and expensive, so focus only on the metrics that matter for your business goals. (This is why having clearly defined goals is key.)
Below are some common HR goals and the metrics to track in order to evaluate the elements within these goals.
Enhance workforce productivity: To measure the current level of workforce productivity, look at the costs associated with wages, benefits and other HR expenses, and compare that to overall company revenue.
Boost employee engagement: If the goal is to improve employee engagement, the scores from employee satisfaction surveys can help you assess where you are now.
Other metrics to consider include money spent on recognition, training opportunities versus the number of employees who take advantage of them, and employee performance levels.
Increase retention rates: Look at both overall turnover and turnover in specific job functions, across departments and under specific managers.
Improve recruiting effectiveness: To assess the current level of recruiting effectiveness, start with the sources of hire. Consider how many of those applications convert to interviews, how many of those interviews convert to hires, and the average tenure of those hires.
Here’s where you also want to take advantage of those tools that leverage government and online recruitment data (mentioned above) in order to get a sense of where the supply of available and qualified talent with the skills you need is most concentrated.
These metrics will help set a benchmark against which you can measure the results of any changes or adjustments made as a result of the findings.
Once you know where you are, you can adjust your efforts accordingly. For example, if the goal is to find more qualified applicants for hard-to-fill positions, by looking at the supply and demand of talent in a specific area, you may decide to reallocate recruitment marketing efforts or offer relocation compensation or more competitive pay to lure these candidates — or perhaps even adjust the role requirements.
After these adjustments have been made, go back in a few months and measure again... and then again.
Constant measurement is crucial to this process. It will help you understand where you are making progress and where there is room for improvement.
Remember, the key to working with big data — and making it work for you — is knowing which data sets to work with, and that starts with knowing your goals. Only once you’ve identified the right data can you begin to mine it to solve a specific problem, overcome a particular challenge or meet a targeted goal.
Mark Bania is managing director of CareerBuilder Canada in Toronto. For more information, visit www.
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