the value of the insights you gain will be well worth the effort
I often see organizations challenged by growing complexity. It slows their ability to forecast and react to market shifts, hampers their competitiveness and puts them at risk for non-compliant practices. Talent analytics can help.
Today’s workforce complexity requires increasingly sophisticated analytical solutions, ones that not only provide insights into past and current practices but also the ability to predict future developments.
But you may already know this. If implementing predictive analytics is on your radar, but your organization hasn’t yet pulled the trigger, don’t panic; you are not alone. According to a recent Harvard Business Review (HBR) study, only 9% of companies surveyed use predictive analytics to inform their workforce decisions. However, 57% have plans to employ analytics using data integrated across multiple systems. If you’re among the 9%, kudos to your foresight. If you’re among the 57%, best of luck in your efforts. If you are among the remaining few on the sideline, what are you waiting for?
The linchpin of analytics is, of course, technology, but the challenge is choosing the right one for you and integrating it into your HRMS. Many organizations see this as a significant barrier, but it shouldn’t stop you from implementing a robust analytics platform. There are many reasons why you should. Some key points to consider include:
- Business agility. Talent scarcity is so severe for some skills that companies report their businesses are negatively affected. Analytics solutions can help you identify the skills your business leaders need well before it becomes a problem.
- Operational efficiency. With the kind of real insights that predictive analytics offer, you can better identify gaps in your talent strategies and execution, leading to greater efficiencies.
- Cost reduction. Accompanying those efficiencies are significant cost savings. Knowing how talent spend is occurring within your organization is the first step to developing steps to reduce and optimize your resources.
- Organizational transparency. Securing headcount is hard enough, but are you able to quickly capture your company’s use of various types of talent? Do you know who is coming and going in your operations?
- Workforce planning. In Randstad Sourceright’s 2016 Talent Trends Report, more than half of talent leaders surveyed said they use analytics in workforce planning to align their efforts with the goals of business leaders.
a clear vision for analytics
The reasons for deploying talent analytics are compelling, but to achieve the best results requires effort. I believe you need to rigorously consider a number of factors before you dive in head first, starting with identifying your goals for gaining greater insights or why you are measuring. This helps you to draw a straight line from current state to desired future state so you can reap the rewards more quickly.
Talent analytics typically fall into three types: operational analytics, predictive analytics and business outcome indicators.
- Operational analytics: are key to performance feedback; it’s why we measure metrics such as time-to-fill.
- Predictive analytics: build on operational data to support your desired outcomes, such as determining talent needs for a particular division next month.
- Business outcome indicators: provide strategic intelligence based on operational and predictive data, i.e., what will it take to ensure you have the skills to support a new product launch next quarter.
Clearly establishing your goals will help you prioritize your deployment of the types of analytics you need.
Keep in mind that meaningful analytical results involve context. Being able to quickly pull up data points on a dashboard is great but without context it is next to meaningless. I like to use the example that if one of your divisions reported filling 150 of 180 open positions last month, was it a successful outcome? That depends on the context, doesn’t it? The percentage of fills may have exceeded previous benchmarks but if the roles that didn’t get filled were revenue-producing, then the impact is significant. Similarly, if the vacant roles were operational in nature but impact delivery of services to customers, there may also be an associated business cost. Analytics have the power to put things in perspective so you can assess the business outcomes of your talent strategy.
Finally, don’t be misled into thinking that good technology is all you need to achieve analytics nirvana. Robust tools are just one part of the equation. To get the most from your investments, you still require data science expertise and active, continuous human involvement. Finding these niche skills can be highly challenging so don’t underestimate the effort you need to put in to securing these resources.
When I explain to clients the power of robust talent analytics, I see the wheels spinning in their heads. They start to think about all of the useful ways this insight can be used. But when I further caution that a turnkey solution requires quite a bit of internal work and dedication of key resources, their enthusiasm seems to fade a bit. I’m here to tell you that after the hard work is done, the result is well worth the effort – especially when the insight derived can be turned into measurable impact and outcomes.
