Key Takeaways
- Despite initial doubts, analytics programs can yield substantial cost savings, with potential projected savings as high as $500 billion for government agencies.
- Building an analytics team may seem daunting, but agencies can tap into existing talent or outsource until they can budget for dedicated specialists.
- Analytics isn't about quantity but finding the right data, which often lies unused within an agency's existing systems, presenting valuable insights for decision-making.
Demand for workforce analytics continues to rise in the corporate world as business leaders recognize the value of data-driven insights for finding, hiring and retaining the best talent. According to a report from Bersin by Deloitte, three in four companies believe using people analytics is important, and CEB found that 95 percent of HR leaders plan to increase their investment in analytics in coming years.
The private sector still has a long way to go — the same Bersin report found that only 8 percent of companies think their analytics efforts are strong — but it's time for the public sector to join the big data journey. Compared to companies, the majority of government agencies have yet to even start exploring the potential of HR analytics.
"There are some astute government leaders who are taking the next steps around predictive analytics to drive the future of HR in government," says Jim Gill, vice president of Government at Cornerstone. "But, in general, the public sector is still lagging in the adoption of data analytics."
At a time when agencies' budgets are shrinking and the talent pool is limited, data-driven decisions can help optimize workforce management and generate long-term savings. While there's no denying that analytics programs require a significant investment of time, money and resources, many government leaders overestimate the challenges of implementing analytics in their workforces. A closer look at the obstacles compared to the opportunities reveal that even the most basic of an analytics program can pay off substantially.
One reason that senior leaders forego implementing workforce analytics programs is often the upfront cost versus the actual cost savings. Many executives doubt the financial impact of an analytics program — only 31 percent of federal IT execs believed big data solutions would deliver efficiencies, according to a MeriTalk survey. However, MeriTalk also found that agencies could save a projected $500 billion if they fully embraced big data to increase efficiencies and enable smarter decision-making.
Another common obstacle to an analytics program is building a team — many agencies do not believe they have the necessary skills or talent to start HR analytics. While an analytics team does require specialized positions, such as a workforce behavior expert and a data scientist, organizations just beginning analytics can often tap into these skills from existing employees, or outsource the work, until they can demonstrate results and budget for a dedicated team.
Government leaders will also often react to the idea of analytics with, "We don't capture enough data yet." But the goal of analytics isn't to have the most data — it's to find the right data, which is often readily available and sitting idle in your system archives. For example, if an agency's biggest challenge is retaining good talent, an answer is likely buried in the unused exit interview and turnover data from years past.
Overall, analytics enables agencies to do more than make blind guesses about whether their strategies will be effective. From deciding whom to hire, to measuring flight risk, to tracking performance, the opportunities for improving talent management processes are vast. As Gill emphasizes, "The key for agencies is to ask the right business questions they want to solve, and understand what data is needed to unlock that answer."
Learn more about how government organizations can leverage HR tech to improve workforce agility.
