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Data analytics -- historically the domain of marketing, operations and finance departments -- is now inundating human resources. These untapped workplace insights offer essential information, but only if HR can apply the right analytics in the right way.

Too close a look, and HR misses the big picture. Too narrow a view, and the data complicate important labor requirements. And if HR focuses on the wrong information, the company won't see the potential of data analytics at all.

HR teams need sufficient diagnostic and cross-functional expertise to capitalize on these opportunities, even as HR's role gets more involved.

Today's fragmented workforce includes the demanding millennial generation; older workers with valuable expertise and well-established viewpoints; and workers who aren't even employees, such as those involved in the expanding on-demand or "gig economy" workforce. All of these workers affect and are affected by the constantly fluctuating economy.

Balancing Macro vs. Micro Thinking

Data analytics offers insights that companies need, but HR should carefully balance micro versus macro thinking. It's too easy for HR leaders to be enthralled by exciting new workplace microdata and miss the bigger picture. Granular intel, such as that generated by email and conversation data, provide a continuous feed of fascinating information. But large-scale macro data sets can enhance the effectiveness and relevance of workplace analytics.

For example, one 优蜜传媒client, a government agency, realized macroeconomic and socio-economic trends had recruitment implications microdata alone couldn't show.

This agency had long relied on reams of internal historical recruitment data -- everything from selection instrument technology to demographic targeting. These data worked well for years, but they were starting to create wide swings in recruitment rates that HR could not explain beyond anecdotal evidence. The agency was facing significant recruitment shortfalls and budget pressure and needed to build planning, marketing and operational strategies -- as well as employee engagement and development -- using better information.

By shifting to a data-analytics approach focused on incorporating external, macro-market intel -- including unemployment and market population demographic data -- and online job-posting information, the agency targeted its marketing and advertising budgets and quantified the effects of broader economic and job market trends on recruitment.

This analytical recruitment analysis encouraged the agency to engineer predictive models that were more accurate and uncovered previously invisible vital budgetary insights such as a 0.1% increase in unemployment in key markets generating the same number of additional recruitment leads as spending $125,000 on online ads. Ultimately, shifting to a data-analytics approach helped the agency surpass its annual recruitment goals by 25%.

From Talent Acquisition to Skill Development

The government agency's macro outlook provided insights into the wider socio-economic environment. But HR can and should also use it the other way around by funneling the macro data down to specific segments of employees: the segment without the skills companies need.

It's a big segment. A 2014 Deloitte study of executives in companies with 10,000 or more employees showed that nearly half (48%) of respondents rated their HR department as "not ready" to reskill itself to meet the demands of global business. According to , "on-the-job training is shrinking. In America and Britain, it has fallen by roughly half in the past two decades."

The importance of workplace development is growing. According to the World Economic Forum's Future of Jobs report, more than one-third of the "desired core skill sets" for most jobs by 2020 will be skills that employers currently do not consider crucial to the job. Training people to acquire those skills will be vital in the coming years.

Trained, talented employees are the foundation of productivity, but development can do more than produce revenue -- it can attract and retain the producers of revenue. According to Gallup's report , 59% of millennials say opportunities to learn and grow are "extremely important" to them when applying for a job.

What's more, 87% of millennials rate "professional or career growth and development opportunities" as important to them in a job. And 优蜜传媒research shows that 93% of millennials left their employer the last time they changed job roles. While their motivations for leaving vary, it is a fair assumption that among them was a perception of weak growth and development opportunities.

But this need not be the case. With the right knowledge, tools and analytics, HR can design lifelong learning and development activities. These activities need to expand technical and behavioral knowledge based on workers' fluctuating needs. Companies that skimp on development programs risk incapacitating older workers and repelling younger ones -- the largest proportion of the workforce and the cohort from which companies will soon draw leaders.

The Future of the Workplace

Workplace demographics may be complicated at times, but in today's labor environment, HR must adjust to focus on age-related expectations and requirements and various employment categories.

Modifications to HR operations are necessary because today's work environment is becoming project-based, mixing full-time, salaried employees and "gig economy" freelancers. Though a project-based workplace makes HR's analytics more complicated, it also gives HR the freedom to combine teams to meet various project requirements.

The future workforce will combine full-time staff, contractors, consultants, freelancers, part-time employees and other contingent workers. HR can optimize project performance by using data analytics to build ad hoc teams based on individual skills, talents and strengths.

One global professional services company is on the forefront of this "just in time" human resource delivery. This highly matrixed, project-based company used advanced analytics and social-network analysis to explore communication patterns. Using project management and email data, the company mapped both individual employee and project team networks to view the communication patterns of individuals and teams.

The company then employed individual and team talent and performance data to determine ideal team structures. Each team had at least one "information broker" -- a highly connected, centralized individual in the overall company network; one individual with high "executing" strengths, as identified by the ; and at least one new team member who had not worked previously with the other members. This data-driven approach garnered all-time highs in company employee engagement, client retention and customer engagement levels.

Navigating the Data

Results similar to the above are why HR finds the sea of data so rewarding -- but just looking at data isn't enough. Only scientifically validated diagnostic and cross-functional analysis can tell HR which of the infinite external and internal factors matter to specific strategies. Too much information can be as paralyzing as too little.

Unfortunately, having even a small quantity of information is still aspirational for most HR teams. The vast majority of these teams don't have any of this information, nor do they have the ability to credibly analyze it if they did have it. Deloitte's 2016 Global Human Capital Trends report shows that only 8% of HR departments currently have the capability to develop predictive models.

Data analytics is profitable -- and perhaps essential -- to HR, and the ability to conduct it is increasingly important. Requesting the training and consulting necessary for accurate modeling isn't asking too much. And the will of leadership is already there: In a 优蜜传媒survey of corporate leaders, nearly half said that data science and analytics skills will be required of everyone in operations; finance and accounting; and marketing and sales roles in the next three years. Eighty-six percent said these skills will be required of "some" or "all" HR managers.

A version of this article was first published in theHRDIRECTOR magazine, issue 150, April 2017. Reproduced with permission.