Big Data and a big problem: Crunching the numbers on retention
It’s almost worse than tax season. That sinking feeling you get when one of your more experienced CPAs comes up to your desk and utters those dreaded words: “I’m leaving.” The only thing that could make hearing that news worse is if she delivered it during tax season!
Unfortunately, you may be hearing more declarations like that this year. According to the 2017 Global Tax Market Assessment from Tax Talent, job seekers will be in the driver’s seat as retiring Baby Boomers create vacancies and a projected increase in turnover puts pressure on compensation levels.
But don’t panic just yet. “Big Data” benchmarking and predictive analytics tools may help your firm weather these impending talent tempests and reach the goal of attracting and retaining the best talent available. These tools also might help further differentiate and grow the firm’s service offering as a strategic advisor by providing its clients with valuable insight to attract and retain top talent.
Benchmarking can give an accounting practice the ability to compare its employee data with current industry averages – including compensation, turnover, productivity and other workforce metrics.
For example, if a firm is faced with the departure of a key employee who just gave unexpected notice, a recruitment manager may need to refine the firm’s compensation strategy. But what if the HR organization’s compensation data is nearly a year old? Typically, recruiters have to “age” compensation data to accurately estimate a competitive salary and avoid losing out on top talent. That’s because traditional compensation data surveys publish their results annually; publishing more frequently would be overly labor-intensive and cost prohibitive.
An associate’s departure isn’t the only reason to keep tabs on compensation trends, however. The same challenge can arise when a firm moves to a new location or creates a new position. Accurately “pricing” job openings can vary greatly depending on geography, job composition, or the amount of bonus or overtime pay a position carries with it, among other things.
While benchmarking can provide a window into broad workforce metrics, predictive analytics can specifically help identify those employees most at risk of leaving and help identify likely hotspots of attrition within an accounting firm. That could mean that before a key team member even reaches your desk to resign, you already may have identified them as a flight risk, addressed their needs, and helped prevent their departure.
Turnover probability identifies the likelihood of voluntary turnover across an organization, within job types, locations, teams, as well as for individual employees. It analyzes combinations of factors related to job characteristic, organizational dynamics, compensation elements and employee demographics that impact the likelihood of employee turnover. And it allows organizations to compare their turnover risk against industry benchmarks to see if they are more or less at risk of losing talent.
In addition to benchmarking and turnover probability, there’s another talent management dynamic that data analytics can address.
Accounting firms (and their clients) need to prepare for new pay equity reporting requirements, which expand EEO-1 reporting requirements for private employers with 100 or more employees by requiring them to provide summary pay data and hours worked in addition to information regarding employee gender, race/ethnicity and job category that they already are required to provide.
As they prepare, many firms may want to dig deeper into their pay practices to gain a better understanding of potential pay gaps and identify specific groups of employees for further analysis.
Data analytics can help accounting firms do this by:
· Identifying potential pay gaps in jobs being performed by people in specific EEOC Protected Classes.
· Examining and addressing potential pay equity gaps at the intersections of race, gender, location and job to determine if further analysis is required.
· Delivering “decision-quality” benchmarking data that helps ensure pay is not only equitable, but is also market-competitive.
Armed with accurate and timely data, firm leaders and HR professionals can proactively build retention plans, coach managers who have higher-than-usual team turnover, or dive deeper into their compensation or engagement practices to identify areas for improvement. Data analytics can also help firms enhance their role as a strategic advisor to their clients, providing them additional understanding into their own trends. But the ultimate power of data is in its ability to provide organizations with actionable insights that can inform decisions, keep and attract top talent and help lead to business success.