In the world of workforce analytics and predictive planning, organizations are looking for answers to the following frequently asked questions;
- What is the most important metric I should be tracking?
- What does it indicate?
- How do I know when corrective action should be taken? and lastly,
- What action should I take?
As a former CFO with 15 years in finance and 8 years conducting analytics and workforce planning as an employee at several high profile organizations and as a consultant leading companies on the journey, this set of questions usually comes up. Unfortunately, the answers are not that clean and simple. In fact if they were then we would not be having such a conversation. There seems to be timeless wisdom in the phrase, “if workforce measurement, analytics and planning were easy, everyone would already be an expert doing it”. The real answer is that, yes, there are certain measures that are always important. The workforce is complex. Taking a single metric point and attempting to diagnose a solution is highly uncertain at best and disastrous at worst. At a minimum one is likely, taking the measure out of context, or worse, misdiagnosing the issue and making things worse. Simply put, the need for a simple answer is overriding our sense of caution. Distilling data and analyzing workforce issues to get at root cause factors, making decisions based on those factors and successfully implementing interventions is, in fact difficult.
There are good reasons why metrics selection, root cause analysis and crafting interventions is hard when it should be less so. HCMI will reveal and explain these difficulty and complexity factors in its’ upcoming blogs and in our Human Capital Chronicles™ stories. Human Capital Chronicles
Think of it this way. If you went to a medical clinic, would you really trust your doctor to diagnose and recommend a treatment based on just one metric? What if the doctor was recommending surgery based on nothing more than say your body temperature? Would you not want your doctor to review your medical history and gather real time information such as height and weight, blood pressure and heart rate? Would you not feel more comfortable if a battery of additional tests and data supported the diagnosis and need for a surgical intervention such as testing blood and cholesterol, or taking urine samples and more? Would you not want to know what alternative interventions exist such as drug treatments or lifestyle changes as alternatives to surgery? To be sure, an elevated body temperature is an important metric, one that every medical practitioner should take and reference in decision making. But is it enough to make decisions about your life and health with?
A realistic example would be going to your doctor complaining of recent chest pains and your doctor, forming an initial hypothesis or preliminary diagnosis that you may have suffered a heart attack, decides to operate immediately. This could in fact be the issue however, without testing and additional metrics to confirm the preliminary diagnosis, the doctor may be putting your life at risk needlessly. You may in fact have been suffering acid reflux or a severe upset stomach rather than a heart attack. If a doctor did that and was wrong, which is a significant possibility then they would likely be called incompetent and face a multi-million dollar lawsuit. Is it then any wonder why HR lacks respect in the eyes of their functional peers.
When HR focuses on a single measure like employee engagement, diagnosing and prescribing interventions for an issue, without adequate analysis and testing, then, just as in the case of the doctor and the high temperature, several things are likely to happen. First, the organization will likely only be treating the symptom (lower employee engagement), with no real proof as to the root cause issue. Second, the treatment administered is as likely to further lower employee engagement as it is to improve it. Third, and this one may sound hauntingly familiar, HR, in failing to improve engagement, loses credibility and may also lose their voice thereby having additional interventions thrust on them in the future by management since HR “can’t get it right”.
The point here is not to debate the importance or criticality of a single metric but rather, much like a doctor diagnosing an illness, that the right metrics, used together, provide the deeper understanding and context for diagnosing a workforce issue. The next step is to aggressively test the diagnosis (or hypothesis), with statistical analysis to seek to isolate root cause drivers. Once root cause drivers have been identified, the organization should have candid discussions, much like the doctor and patient, about different types of interventions and their respective pro’s and con’s. There is usually more than one intervention method to address a workforce issue. The right one can be slightly different for every unique organization or business unit.
In other words, the workforce, like the human body, is complex and the sooner that HR accepts and understands this, the sooner they can begin to educate the rest of the organization.
HR needs to build a comprehensive web of measures that, when used in combination, effectively guide workforce issue and root cause identification.
This could finally put HR and workforce analytics at the proverbial decision making table and ultimately recast HR less as an administrative support role but rather more as a key strategic value add. Such an HR organization could truly guide the workforce to create value improving productivity, lowering costs, increasing stability, and enhancing employee engagement among other outcomes. HR could finally be the workforce doctor they have always aspired to be with the tools, processes, and success stories to back them up.