QUESTIONS

• Compare and contrast the ways in which data are used in human resources.
• Analyze the history of HR and data analytics.
• Learn what other colleagues outside of HR are expecting from HR professionals and the data they see that have potential.

BELOW ARE 2 ARTICLES THAT NEED TO BE READ BEFORE ANSWERING THE QUESTIONS ABOVE:

ARTICLE 1

HR Leaders Need Stronger Data Skills

An old saying sums up the data skills of most HR professionals: "The shoemaker's children go barefoot."

In today's tightening labor market, HR leaders must work relentlessly to develop and recruit people who advance digital transformation across their organizations. Yet most have struggled to advance their own digital competencies. This neglect has hindered their ability to leverage data into talent strategies that can help transform their businesses.

We base this claim about HR's digital skills gap on the results of our latest global leadership survey. Co-produced by our three organizations, the survey gauged nearly 28,000 business leaders across industries about the state and trajectory of leadership. Among the findings: On average, HR leaders lag far behind other professionals in their ability to operate in a highly digital environment and use data to guide business decisions.

It comes as no surprise that this skills gap has spurred a credibility gap between HR professionals and their colleagues. Only 11% of business leaders trust HR to use data to anticipate and help them fill their talent needs. When we last fielded the same survey three years prior, 20% of business leaders felt that way still a low number, but nearly twice what it is today.

Finding ways to improve HR's digital acumen and data skills can challenge even the most well-resourced companies. HR leaders can start by upskilling their teams in areas that impact two critical business outcomes: building bench strength and tying HR metrics to financial success. To achieve both, companies can support their HR leaders in taking these steps:

Forge internal partnerships. At most companies, other departments use data and technology in ways that HR could apply to their own work. For example, HR can work with marketing for guidance on search engine optimization (SEO), a skill that can help HR improve its recruitment efforts. They can also consider partnering with colleagues proficient in finance technology for guidance about blockchain, a technology capable of transforming how HR stores and verifies private employee data. Such internal collaborations may not only help HR attain new skills, but also help to foster a data-driven culture across the organization.

Map talent analytics to business outcomes. HR should learn how to tie its data about people to performance and business outcomes. This process must begin with gathering data about the skills, capabilities, and behaviors of the existing leaders and workforce, often done through assessments. For example, a hospital seeking to improve patient safety might look to HR to discover that the highest rates of patient safety are tied to nurse units where supervisors showed specific behaviors, such as demonstrating empathy. By collecting data on employee skills and experience and tying it to business outcomes, HR can highlight key areas of risk and opportunity for the company.

INSIGHT CENTER

• Scaling Your Team's Data SkillsHelp your employees be more data-savvy.

Develop data visualization skills. Simply collecting data and analyses won't help HR leaders advance their efforts unless they know how to leverage that data to influence others. One study found that when presenters supplemented their stories with visuals, audience members had around a 40% greater likelihood of taking the desired course of action versus those who received non-visual presentations. As such, HR should learn how to create graphical presentations of data. HR needs to get more proficient with sophisticated software programs such as Power BI, Tableau, or R Studio, all of which give visual context to data.

Implement leadership planning models. Beyond using data to highlight current talent trends and gaps, HR should use it to fuel predictions about future talent needs, especially for leadership positions. HR professionals should employ leadership planning models to map a business's long-term strategic plan to the leaders it will need to implement that plan. Leadership planning models enable HR to create data-driven projections for the quantity of leaders needed, the skills they will require, and where they will be located. On an ongoing basis, these models can compare the leadership talent it has against what it needs. As such, HR can course-correct when necessary by revising or shifting its priorities among hiring, development, and performance-management systems.

Taking these four initial steps can yield big dividends. Our research shows that companies excelling in using data and analytics to drive their talent strategy are more than six times more likely to have a strong leadership bench. Moreover, those with the strongest digital leadership capabilities outperform their peers by 50% in a financial composite of earnings and revenue growth.

And when HR executives use their digital savviness to advance their companies, they often move up themselves as a result. We found that HR professionals who leverage advanced analytics are over six times more likely to have opportunities to climb the corporate ladder.

Today, unemployment stands at the lowest level in nearly five decades. As the economy continues growing and Baby Boomers retire in droves, the labor market will further tighten and increase the pressure on HR. These demographic and economic dynamics will push HR to be better, faster, and smarter about how it finds and develops the talent their organizations will need to execute their business strategy. Investing in developing HR's data and technology skills should be a top priority if companies want to win the war for talent.

ARTICLE 2:

Is HR the Most Analytics-Driven Function?

I have argued over the past decade that the Human Resources (HR) function has the potential to become one of the leaders in analytics. The key word, I thought, was potential. Not anymore. A recent global survey on which I collaborated with Oracle suggests that HR is right up there with the most analytical functions in business and even a bit ahead of a quantitatively-oriented function like Finance. Many HR departments are making use of advanced analytical methods like predictive and prescriptive models, and even artificial intelligence.

This is a big change from a decade ago, when I began to study the use of talent analytics. (Jeanne Harris, Jeremy Shapiro, and I published an article in HBR on the subject in 2010). At that time, the only really sophisticated HR analytics capability we uncovered was at Google and perhaps Harrah's (now Caesars). There was a fair amount of reporting going on, but not much prediction. Few HR organizations even had a dedicated analytics person. "HR analytics" typically meant a debate about how many employees the organization had, or the best way to measure employee engagement.

Even before the new survey results came out, I suspected that things were very different today. Most large companies have at least a small people, talent, workforce, or HR analytics group. There are many conferences devoted to the topic. It's very common for organizations today to model workforce growth, attrition, engagement, and other key variables.

The survey involved 1,510 respondents from 23 countries across five continents. It included senior managers, directors, and VPs from from HR (61%), the Finance function (28%), and general management (10%). I was hired to help design, analyze, and report on the survey. All of the executives were from companies with $100M in revenue or more. Detailed results are here.

While it's obvious that HR is moving in an analytical direction, I did not expect the very high level of sophisticated analytical activity in the survey. Here are some highlights:

• 51% of HR respondents said that they could perform predictive or prescriptive analytics, whereas only 37% of Finance respondents could undertake these more advanced forms of analytics.
• 89% agreed or agreed strongly that "My HR function is highly skilled at using data to determine future workforce plans currently (e.g. talent needed)," and only 1% disagreed.
• 94% agreed that "We are able to predict the likelihood of turnover in critical roles with a high degree of confidence currently."
• 94% also agreed that, "We have accurate, real-time insight into our employees' career development goals currently."
• When asked "Which of the following analytics are you using?" "artificial intelligence" received the highest response, with 31%. When asked for further detail on how respondents were using AI, the most common responses were "identifying at-risk talent through attrition modeling," "predicting high-performing recruits," and "sourcing best-fit candidates with resume analysis."

This level of self-assessed capability for HR analytics was high in almost every geography and every specific question, but it was somewhat lower in Asian, European, and Australian organizations. It was generally highest in the U.S., the Middle East, and Latin America. Across industries, it was lowest in the "hospitality, travel, and leisure" and "media and entertainment" categories. Particularly high industries included financial services, energy and utilities, professional services, and wholesale distribution.

Why is HR more comfortable with advanced analytics than Finance, which has always been a function based on numbers? I have noted for years that Finance organizations and the CFOs who lead them have found it difficult to move past descriptive analytics and reporting which they do very well to more advanced analytics. There are certainly exceptions to this rule, but it helps explain why the growth of advanced analytics has been faster in HR.

But no function in a business stands alone with regard to data and analytics. One reason that Oracle surveyed both HR and Finance executives is that those two functions have an increasing need to collaborate. Workforce expenditures are often among an organization's highest costs, and a company's financial situation will dictate fluctuations in the size and makeup of the workforce. The survey found high levels of collaboration and mutual respect between HR and Finance, and a growing need for collaboration. For example, 82% of respondents agreed or strongly agreed, and only 5% disagreed, that "Integrating HR and Finance data is a top priority for us this year." However, several interviews conducted after the survey revealed that there is still much opportunity for greater sharing of data and collaboration on analytics.

Of course, not everything is rosy in the world of HR analytics. I was quite interested to see that the function's use of analytical tools surpasses the ability to interpret and act on them. When respondents were asked about the area of "most needed to develop or improve" analytical skills for HR, the highest-ranking choice was "acting on data and analytics to solve issues." "Cultivating quantitative analysis and reasoning skills" and "advising business leaders by telling a story with data" also ranked highly. My experience is that these skills are equally lacking in other functions. Perhaps it is another sign of HR's analytical maturity that it is facing the same human skill shortages that have long bedeviled analytics users across companies.