A comedian once chuckled that 78% of all statistics are made up on the spot. But that’s the ambiguous nature of data. Data by itself is inert – so the important questions are where are we getting our data, is it relevant, and what are we doing with it? After all, with Big Data, quantitative, vs. qualitative, ordinal vs. nominal, numeric vs. discrete, etc., it’s a very big, hairy jungle out there. And it must be simpler and more useful than what we often see.

The Good

Without ignoring the value of both human instinct and intuition (and they are different), data is what drives the decision-making process in most businesses. Or at least it should. As one senior executive shared with me his organization’s mantra: “No data, no decisions,” he emphasized, mitigating emotion as much as possible. Setting strategy and prompting change is often best executed when the basis is more objective than subjective.

Workforce strategies and solutions are no different – they need intelligible and actionable data. Critical performance and cost metrics like on-time fill, turnover (which is subject to more than one methodology), overtime, headcount, assignment length, and assignment completion, along with a few more, are fundamental. This type of data, correctly calculated, interpreted and addressed, can make or break the decision process related to a company’s contingent workforce strategy and talent supply chain’s quality, responsiveness, and cost effectiveness.

The Bad

Data for the sake of data is not usually helpful. One of the more prominent Vendor Management Systems (VMS) claims to have literally thousands of reports and will create more if needed. But should you brag about that? I doubt it. How much of that data is actually pragmatic and useful to managing your contingent workforce, processes and suppliers? I have a mental image of an HR Manager unable to open his office door enough to get to the plant floor and engage his employees because of reports stacked on every inch of the floor – reports that he would never have enough time to read, much less rightly interpret and act upon. Have you ever heard the phrase “paralysis by analysis?”

Often one of the major shortcomings of workforce analytics is an obvious lack of thoughtful interpretation. Numbers on a page (or screen) don’t tell you much unless they are translated into meaningful patterns and, where there is an obvious issue, a root case analysis is conducted. For example, knowing that local wages are increasing and internal turnover has spiked doesn’t mean the factors are necessarily correlated. Working with metrics is more nuanced than that. Although it’s imperative that we keep data and analytics relevant and simple, it’s wrongheaded to think that the interpretation and application is easy.

The Ugly

Bad data or data wrongly interpreted is usually worse than no data at all. Many poor business decisions are made when data is mishandled, unreliable, or not properly translated. Knowing the numbers doesn’t create solutions – that’s where a circumspect analysis is pivotal. Numbers don’t leap off the page and miraculously form an action plan, especially when an overabundance of data seems to point to conflicting conclusions. The professor in my statistics class often used the acronym KISS – Keep It Simple, Stupid – to remind us of the need to stay practical and of the often negative results of overcomplicating metrics.

I think a good rule of thumb is to only review data that is going to be acted upon to improve processes and partnerships. If you don’t need it to better run your business, don’t look at it…and certainly don’t keep it. I’m reminded of an HR Manager that compiled EEOC-like information on his company’s worker population for years, yet never acted on it. When they were hit with a hiring discrimination lawsuit he wished he had never created the report. Sometimes data can be dangerous.

Common Sense Data and Analytics

As I consult with my clients I’m seeing a shift in the way data is used. And it’s a positive shift. They don’t want most of their employees inundated with meaningless reports they won’t read or often can’t understand. They don’t want their key decision makers acting as data analysts instead of strategists, leaders and visionaries. They realize the importance of rightly interpreted and acted upon data to drive sound business decisions and workforce strategies. But they also see that the data pendulum had swung too far one way and much of their reporting and analytics were creating little value for their organization and their talent acquisition initiatives.

Want to learn more? Please contact Linden Wolfe, PHR, CCWP at lwolfe@excelsiorstaffing.com