of the nearly iconic television
spots you've seen that promote the efforts of nonprofit
dedicated to combating hunger worldwide. These commercials invariably
show stark images of children who have suffered the ravages of
malnutrition and lack of medical care. Thinking back to those
commercials, what do you recall? Is it the specific statistics
regarding hunger the voiceover mentions or the images of the children
and the stories told about their circumstances? For most of us,
the latter, and it's not because the numbers aren't
because our brains are wired to react more strongly to emotional cues
rather than to dry facts.
As HR professionals, we obviously
facing problems as critical to humanity as world hunger, but I use that
example because the people who design those campaigns know human nature
and understand that statistics alone aren't enough to sway their
audience. And although the decisions we make at work may not solve
problems on that level, they can have a profound impact on the people
with whom we work and their families, so the stories connected to the
numbers are just as vital to communicate.
It wasn't all that long ago
that it was difficult for HR to get basic measures such as headcount
and demographic information. But as technology and techniques became
more sophisticated, so too has our ability to capture and quantify data
about abstract concepts such as engagement and commitment. Now we are
sitting atop a mountain of data, with statistical proofs in one hand
and probability models using predictive analytics in the other,
shouting percentages of likelihood and blabbering on about correlations.
And nobody's listening.
That's because statistics can
be overwhelmingly complex, confusing and dry, and storytelling is a
difficult art that doesn't come naturally to many of us. At a
recent meeting of i4cp's Evidence Based
HR Exchange hosted by Cisco, I noted that an overwhelming number of
participants were preoccupied with the idea of how to turn data into
actionable information. And in a recent survey conducted by i4cp (to be
released later this year) on behalf of the EBHR Exchange, 51% of
respondents indicated that they have encountered "difficulty
interpreting or finding the story within the data."
Obviously if this were an easy
problem to solve, it wouldn't be such a prominent issue. However,
the consistent advice suggested by those who are most successful at
communicating data meaningfully is to always remember the human aspect.
This is the one advantage HR has over almost every other department
when it comes to data; there are nearly always examples of the data
that involve individual people.
Here's an example: imagine
you have data showing that 23% of your employees report being unhappy
with recent changes in your organization's flex-time policy, and
the policy has resulted in only a minute improvement in productivity.
That may be slightly interesting, but if you put a face on the story,
say, longtime employee "Monique," who was a high-performer
but left the organization because her new work schedule made it
impossible to pick her son up from day-care on time, you might have
more people thinking about how these policy changes affect the
employees, and how that in turn can impact the company.
Granted, it's time-consuming
to interview employees and difficult to get people to speak candidly
about their workplace experiences, but a blend of qualitative and
quantitative data is sometimes necessary for effective storytelling
purposes. We see this concept in action in every political season and
especially in national elections. Presidential debates often degrade
into volleys of statistics thrown out by both sides, but it's the
anecdotal stories that resonate and that we remember. Case in point:
the "Joe the Plumber" phenomenon that emerged during the
2008 elections. Bottom line: people remember characters and stories.
Ron Gier, VP of Human Resources at
Sprint, recently spoke with i4cp and expanded on this idea in an
example from his own workplace. "Our survey might tell us that we
have 75% [favorable] score on job opportunity, but a lower score on job
satisfaction. These scores might sound conflicting, putting the
credibility of your whole survey at risk. To help our team best use the
data to make decisions, we try to describe the results in a way that
resonates intuitively and resolves the conflict."
description," Grier continued, "is that an employee could
see their job as a great opportunity and be enjoying it, but also see a
lot of stuff around here that he/she finds needing improvement. Can I
imagine 20% of my workforce looking around their office and thinking
those same things? Yeah, I can. I can get it. Now I can paint a picture
of what the data tells me that improves decision making -
capitalize on the strength of the job opportunity and focus improvement
efforts on some of the day-to-day things that employees find
That's the other part of the
equation for overcoming data issues. You've got to paint a
picture with it. My favorite common data conflict is the perception
around pay satisfaction being critical to retention. Managers generally
conclude that if there is low pay satisfaction there will be turnover,
but most research suggests that pay satisfaction is not predictive of
turnover. Managers struggle with this counterintuitive twist, and often
need a more illustrative example to grasp it. I suggest that they
probably know someone who never complained about their pay, but left
anyway. They also probably know someone who complains about their pay
all the time, but never intends to leave. By painting those mental
pictures for people, they will tend to be a little more open to what
the data are telling them.
Naturally, there will always be
some data that doesn't lend itself as readily to telling a
compelling story, but then again, not all data requires action. Just
like data from any department, not all HR data is useful. But in the
cases of data that should be acted on, look for details from the data
set and try to get some actual examples of how it plays out in
practice. Not only will the stories help form the narrative, they may
help explain the causes of the results.
Storytelling may not be a skill
that all of us were born with, but as it is with many things, it can be
improved with conscious practice. Developing this capability is an
imperative, because people are behind every number we crunch and the
stories we tell help to effectively communicate the messages that are
most critical to our organizations. To get started, focus on the change
you want to promote, have strong statistical backing, and above all,
remember to give your audience a relatable and human story that will
motivate them to care about the data, the issue, and the people it
Cliff Stevenson is a Human
Capital Researcher for i4cp. Anyone who is interested in learning more
about hunger in the United States, including where to donate, can
follow the link here.