Having met several professionals responsible for workforce analytics at our recent Evidence-Based HR Exchange -- hosted at Kaiser Permanente's headquarters in Oakland, California—the answer for the majority of companies is clear: they are only just beginning. With technology, data storage and the long overdue realization that HR should look at people data the same way most other departments analyze their own hard data converging, these are exiting times with great potential for organizations to gain serious competitive advantages through their workforce analytics strategies.
But you're reading an article about workforce analytics, so you may have already noticed which way the wind is blowing. i4cp has recently shared how to get your workforce analytics engine humming, so in this article I'm going to focus on the phases of a workforce analytics engine, according to one of the Forum's speakers, the head of analytics at a major Silicon Valley corporation. There is nothing revolutionary about these phases, but you can't make progress if you don't know where you are.
Level I. Reporting
While simply doing reporting is less sexy than conducting analysis or developing workforce models, it is the foundation on which everything else sits. The mantra "start small" applies here: don't try to address the entire organization, or even the most important metrics. Focus on one business unit and determine a few metrics its leaders want, even if those metrics are basic and not entirely helpful. Once you've manually developed a reporting structure, you can look at systematizing similar reports for other units.
Aim to develop a dashboard of reports and maintain a continual focus on a few key metrics—ideally metrics that people outside of HR care about—to gain visibility and develop broader support for deeper analysis.
Level II. Analytics
That's right. Analyzing workforce data is only the second phase. Once you have the reporting foundation in place, drill deeper by segmenting information (i.e. examining turnover rates by critical job function, by department, etc.), determining probabilities of certain scenarios (attrition probability) and identifying drivers of problem areas (what causes short tenure attrition?). Of course, seek to answer questions that:
- Are applicable to your business
- Will result in an outcome, action or decision (for example, determining the drivers of short tenure attrition could result in better candidate profiling to reduce recruiting and onboarding costs).
Level III: Workforce modeling
Workforce analytics will only get you so far. Workforce modeling is where real business value starts to come into play. With a streamlined workforce analytics engine humming, you can focus on broader workforce scenarios. For example, a company could have a policy of buying a certain job skill from the external market versus building that position from within. Is the company spending more but making more as a result, or is money and internal potential being wasted? This kind of buy versus build question, among others, can be answered at this phase.
Level IV: Strategic workforce planning
i4cp member organizations know we strongly encourage an emphasis on strategic workforce planning, which is why in addition to our Evidence-Based HR Exchange we also host a Strategic Workforce Planning Exchange, which focuses on building a robust platform that enables the business strategy to meet growth targets.
As our exchange speaker explained in his presentation, strategic workforce planning is less about specific numbers than it is about understanding the business strategy, modeling the workforce to support that strategy and then using the resulting information to determine how the business is going to beat the competition.
Strategic workforce planning is the last stage of workforce analytics evolution.
So again, the question: where are you on your journey?