In 2004, I was a newly-hired consultant for CLC Metrics, the joint venture partnership between the Corporate Executive Board and the Infohrm Group that provided technology and consulting on workforce analytics to a membership of HR organizations.
An early assignment was coaching an HR manager to deliver analysis on the “State of Diversity” to executives at her financial services firm. Improving diversity was a high priority, one to which numerous resources were devoted. After aggregating, studying and publishing the data, the manager presented it to her leadership team. I subsequently asked her how the discussion unfolded and whether the group was planning to take action on the insights, given the critical nature of the topic. Her response was stunning, being along the lines of “they didn’t even look at the data – the graphs need to be outlined in black, as with their non-HR reports.”
“While we in the analytics community speak often about “data-driven decision-making” in HR, I would estimate that at least 80 percent of the analytics efforts undertaken by HR never comes close to driving a decision”
Admittedly, this is anextreme example of how talent data can be swept to one side –even under the most promising of circumstances, such as an engaged executive team, high-visibility issue and money to spend – but I doubt it is unique.
While we in the analytics community speak often about “data-driven decision-making” in HR, I would estimate that at least 80 percent of the analytics efforts undertaken by HR – metrics reporting, dashboards, ad-hoc analysis, etc. – never comes close to driving a decision. Insights into workforce trends and transparency of root causes are important, yet are failing to change behaviors.
A recent survey at the SAP SuccessFactors user conference in Sydney asked HR leaders, “What is the biggest analytics challenge for your organization?” Options included generating integrated data, building standardized metrics and sharing dashboards that provide context on talent trends. The most popular response, at 30 percent, was “delivering insights about the workforce that are compelling.”
For all of the data that challenges assumptions about the workforce, identifies problems and educates managers, there is an execution gap between the goal of using compelling workforce data to make better business decisions and the likelihood of that actually happening.
Why? The causes are multi-faceted and range from the very technical (inability to aggregate meaningful data) to the strategic (under-staffed HR departments struggling to adapt to the time- and resource-intense nature of analytics investigations). This latter hurdle often results in HR scrambling to provide dashboards with flavor of the month metrics without necessarily taking action. Of course, better analytics technology can help overcome both of these challenges, and others, but so can changing how HR identifies, prioritizes and influences strategic decisions to which data is applied.
Strategic Decisions: Using Workforce Data to Improve Competitive Advantage
On one hand, it would be interesting to ask, “What percent of your managers make a major decision at least once a year and that involves at least 1 percent of your workforce?” It would certainly assist in orienting your analytics agenda towards those decisions with the greatest cost or risk to the affected workforce.
On the other, we can be more circumspect and seek out truly impactful decisions where the value of data is highest. In his Harvard Business Review article (“What Makes Strategic Decisions Different”, November 2013) Phil Rosenzweig posits that the term “decision” may be applied to any kind of choice – “routine as well as complex deliberations, to both small-stakes bets and high-stakes recommendations, and to exploratory steps as well as irreversible moves.” However, the most valuable of these are strategic decisions, ones in which:
1.The decision-makers can influence the business outcome (through ongoing action)
2.The company seeks to improve performance relative to its competitors
3.There is a high-degree of complexity, requiring adaptive thinking and data insights
Let us apply these three criteria to a couple of talent management issues. With 10,000 retirements every day, many organizations – particularly those in healthcare, energy and the public-sector – are facing an aging workforce. This is a common topic for workforce analytics and planning. We can contrast that issue with one originating from the CEO’s office – a new product launch will require a workforce possessing skills very different to those available today. How would an executive at this firm evaluate the strategic importance of each issue?
As you can see from the table above, it isn’t obvious that the aging workforce issue will be a high priority for workforce analytics – the business outcome is unclear, there isn’t a compelling argument about how this issue improves the firm’s competitive position, and the decision on how to replace the aging workforce may be relatively simple. As such, workforce analytics data might not offer tremendous business value.
In contrast, the new product launch could be the right opportunity for workforce analytics – by using data to identify and hire people who fit the new product profile, HR reduces decision-complexity (by eliminating some of the risks associated with acquiring new skills) and has a clear line-of-sight into how its actions create competitive advantage for the firm.
To illustrate this further, I recently spoke with the head of workforce planning at an energy company about the two types of planning his function does:
1. Replenishment Planning – HR leads a process to identify future workforce gaps stemming from retirements and terminations. Business conditions and scenarios are an input to this process
2. Disruptive Planning – The business is venturing into new service lines that will disrupt a significant portion of the workforce in terms of skills required, operating procedures and how they engage with customers. Much is unknown about the future.
In both cases, workforce data should influence the talent planning process. However, the strategic decision to launch new service lines, which could create competitive advantage for the firm but is fraught with complexity–especially around very different talent requirements–offers the best opportunity for HR to maximize the impact of data.