By: Kip Kelly

Director

UNC Executive Development

Gene Pease

Founder and CEO

Vestrics

About the Author:

Kip Kelly is Director of Marketing and Public Programs at UNC Executive Development. He is also

responsible for the portfolio of non-degree, open enrollment executive education programs available

through UNC Kenan-Flagler Business School. Prior to joining UNC, Kip served as Director of

Executive Education at Duke University’s Fuqua School of Business where he also oversaw the non-

degree open-enrollment programs.

If you'd like to talk to the author of this paper or to any members of the UNC Executive Development

team about your talent development needs, call 1-800-UNC-EXEC or email unc_exec@unc.edu.

All Content © UNC Executive Development 2015

Website: www.execdev.unc.edu |Phone: 1.800.862.3932 |Email: unc_exec@unc.edu

Driving Talent Development

with Data

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Introduction

rganizations are increasingly relying on advanced analytics to make better, more strategic

business decisions. The “Data Revolution” is transforming the way companies operate and the

effects are being felt in every industry, at all levels, in every department – including human

resources. Leading-edge companies are already tapping the potential of advanced analytics to improve

talent acquisition, employee engagement, retention, and talent development. For example, Gild, a

technical recruiting firm, identifies highly skilled engineers by analyzing open-source code, reaching

out to those engineers who meet their “quality” threshold. Online retailer eBay uses analytics to

counter employee attrition. Beth Axelrod, eBay’s senior vice president of human resources, said in

Forbes that they use advanced analytics to identify managerial or departmental hotspots for talent loss.

“If somebody has been in a role for three years, hasn’t been promoted, and hasn’t changed roles,

there’s a far higher probability of attrition than someone who doesn’t have those circumstances,” she

says. Yahoo! CEO Marissa Mayer’s decision to change the company’s telecommuting policy was

based, in part, on analysis of computer logs which showed that remote employees weren’t logging in

to the VPN often enough.

By and large, however, most HR and talent management professionals are not applying advanced

analytics to their organization’s biggest asset—its people. For any number of reasons, human resource

professionals have been slow to embrace advanced analytics, but that is changing quickly.

Organizations are becoming more data-driven, and business leaders are becoming more sophisticated

in how they use data to drive decisions. As organizations experience success using advanced analytics

in other parts of the business, there will be an expectation that HR professionals adopt human capital

analytics.

This white paper:

Defines human capital analytics and explores how companies are using advanced analytics in

HR and talent development to drive business results;

Outlines the human capital analytics continuum and explains how organizations can start to

use advanced analytics to optimize their HR investments and improve business decisions

regarding talent development;

Offers a five step process for creating a human capital analytics measurement strategy and

explains how to create a measurement map, and;

Provides examples of how some organizations are using human capital analytics to drive

talent management and talent development practices.

O

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Understanding Human Capital Analytics uman capital analytics, also known as

human resources analytics or talent

analytics, is the application of

sophisticated data mining and business

analytics techniques to human resources data.

Collecting and analyzing data in human

resources is not new, but several converging

trends have helped to accelerate the growth of

human capital analytics. First, the amount of

data that is available to companies is growing

exponentially, and will continue to grow for

the foreseeable future. Recent technologies

have emerged to help companies capture

unstructured data and combine it with

structured data to provide new and valuable

insights. Cheaper, faster technologies have

made it more affordable than ever to collect

and analyze large datasets. Annual and

quarterly reports are giving way to real-time

decision making and predictive analytics.

These trends are all working together to create

a brave new world for human resources

professionals.

The trend of using human capital analytics in

decision making has made 2015, according to

Josh Bersin, principal and founder of Bersin by

Deloitte, the “year for analytics.” He writes in a

recent report that in 2015, “it is becoming imperative

for HR teams to invest in talent analytics….(T)his means bringing together the reporting and analytics

teams in recruiting, compensation, engagement, learning, and leadership, and putting together a plan

to evaluate (the) workforce with a holistic data perspective.” Assembling this team and launching the

process, he notes, will take two to three years for a company to complete (Bersin, 2015).

There are a number of factors driving the demand for human capital analytics. The predicted labor

shortage was delayed a few years due to the recession, but baby boomers are starting to retire in larger

numbers, and will continue to do so for years to come. With their retirements, employers will

experience significant skills gaps and a loss of institutional knowledge. In addition, there are also

widespread skilled labor shortages in certain industries, often in highly specialized sectors such as

health care and IT, and in labor-intensive positions such as manufacturing and agriculture, and at both

H Sun Microsystems Mentoring

Program

Sun Microsystems

used advanced

analytics to optimize

their company-wide mentoring program.

The goal of the program was to increase

employee performance. In two phases of

the study, 98 employees were compared

to a control group of 1,436, and 838

mentees and 677 mentors were

compared to their control group of 5,000.

The human capital analytics showed the

mentoring program to have a positive

impact on employee retention, salary

grade, and pay increases for both mentors

and mentees. The dramatic difference in

retention among participants over non-

participants translated into a savings of

$6.7 million dollars. This far outweighed

the $1.1 million cost of the mentoring

program.

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ends of the educational spectrum. These shortages will require HR and talent management

professionals to dig deeper to find, keep, and develop talent.

Unlike the labor shortage that occurred during the economic boom of the late 1990s and early 2000s

when companies invested more heavily in talent recruitment and development efforts, this one comes

in the age of a new business austerity. In response to the recession, companies have made dramatic

cuts and now demand greater accountability. Business leaders are looking more closely at data to

drive better business decisions and expect metrics to demonstrate a return on investment (LaVoie,

2014). Yet according to PwC’s 15th Annual Global CEO Survey, of the 80 percent of CEOs who said

they needed talent-related insights to make those decisions, only a small percentage actually receive it

(PwC, 2014).

Those organizations that are measuring their talent management practices have seen their efforts pay

off. A survey by i4cp, a human capital research firm headquartered in Seattle, Washington, found that

high performing companies were more likely to measure their talent management practices than were

lower performing ones. High performing companies that measure human capital focus on such areas

as:

Employee engagement

Organizational financial success

Leadership success

Management satisfaction with the talent management process

Scorecard improvement

Reduction of costs

Robustness of talent pipeline (Kuehner-Hebert, 2010; Vickers, 2010).

The survey also found, however, that like the PwC study, few (only one in five) organizations actually

have these measurements in place.

There are several reasons why HR and talent management professionals may still be reluctant to

measure human capital analytics. One reason may be, simply, that they do not understand the value of

collecting and analyzing the data (Kuehner-Hebert, 2010). To be clear, human capital analytics can

help organizations make more informed business decisions about talent which can directly impact the

bottom line. The i4cp study found that large companies which adopted a “data-driven decision

making” approach saw productivity gains 5 to 6 percent higher than those who did not (Pease, Boyce

and Fitz-enz, 2012).

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The Human Capital Analytics Continuum rganizations can use human capital analytics to optimize their HR investments and improve

business decisions regarding talent development, employee retention, engagement, and

productivity, all of which improve organizational profitability. Many organizations are already

on the path toward advanced analytics. Those who want to venture into human capital analytics may

want to first take smaller measurement steps. To do so, it is helpful to view the human capital

analytics process as a measurement continuum. Pease, Beresford, and Walker offer a useful analogy to

help illustrate this continuum in Developing Human Capital: Using Analytics to Plan and Optimize

Your Learning and Development Investments (Wiley; 2014).

a step beyond “smiley sheets.” They augment them, providing further insight into the satisfaction of

talent development activities and can be the first step toward quantifying the value of those efforts.

Scorecards and dashboards are the next level of sophistication. Scorecards are a performance

management tool that concisely summarize the organization’s talent management strategies and

associated measurements.

Dashboards are a distillation of the most important performance indicators. They allow senior leaders

to review those indicators at a quick glance. Scorecards and dashboards can leverage automated

surveys and activity data to track how the organization is executing strategy and the consequences

arising from business processes.

Benchmarks are the next level beyond scorecards and dashboards. Benchmarks use “best-in-class”

practices to compare with an organization’s actual practices. Studying the best-run companies in a

O

The continuum begins with anecdotes or storytelling. Anecdotes tell the story

behind the numbers. They personalize

an otherwise dry statistical analysis and

are a good way to get senior leaders

to understand the people

behind the numbers.

Anecdotes are

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specific area will help organizations establish benchmarks for things such as salary, training levels,

desired turnover rates, and so forth.

Correlations and causations are the next two stages in the continuum. Correlations describe the

statistics where two or more variables move together, but there is no clear reason why. For example, a

study may find that children who play a lot of violent video games are more likely to become bullies.

This is a positive correlation in which both variables—the amount of time spent playing violent video

games and bullying behavior—increase together. A correlation, however, does not prove causation. It

is possible that other factors—such as the lack of parental supervision or violent parents—have

influenced both the amount of time spent playing violent videos and bullying behavior.

Causation shows why a metric or key performance indicator has changed. In their book, Investing in

People: Financial Impact of Human Resource Initiatives (FT Press, 2008), Wayne Cascio and John

Boudreau offer the following rules necessary to prove causation:

1. Two events must show a clear and statistically significant connection.

2. One event must precede the other.

3. All other plausible causes must be ruled out.

The final stage of the continuum is optimization, the holy grail of HR measurement. Optimization

involves predictive analytics. Predictive analytics not only measure the impact of the causes, it also

helps optimize and prescribe future investments. At all other points on the continuum—from

anecdotes to determining causation—the value of human capital investment is shown by evaluating

business impact and return on investment, and this is a good thing. Optimization, however, goes one

step further and allows HR and talent managers and senior leaders to gain insight into where human

capital investments are working and where they are not, and gives organizations options for

improvement. Optimization is a proactive and future-oriented stage.

It may seem daunting to reach this final level on the continuum, but it won’t be if HR and talent

management professionals proceed sequentially through the stages. Each stage builds on one another,

and when taken in small steps, becomes a natural progression. The optimization level requires

executive buy-in, the collection of quality data starting with data HR usually tracks (employee

surveys, for example), and moving to the collection of data related to specific business outcomes.

These key performance indicators (KPIs) reflect the critical success factors of an organization, and

they differ depending on the organization. Buy-in from executives and cooperation among other

departments to amass the data is best obtained by progressing gradually and sequentially through each

stage and showing successes along the way.

How to Start a Measurement Strategy easuring human capital can seem intimidating, particularly for organizations who have not

started down that path, but it doesn’t have to be, particularly if HR and talent management M

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professionals start small. Choose one investment to measure—for example, the efficacy of leadership

training—from the design stage and use it as a pilot program.

Best-in-class organizations see measurement is an intentional process and have a measurement

strategy in place that guides the design, deployment, and analysis of each investment. A measurement

process provides a mental model for everyone in the organization to use and provides a common

language that makes it accessible and achievable by everyone involved.

HR and talent management professionals who are just entering the measurement arena should begin

with the first stage—anecdotes—and build from there for each investment they want to measure. As

their comfort levels grow, so too will the complexity of their measurements. For example, as

anecdotes about the effectiveness of leadership development investment are compiled, additional,

more direct questions naturally will arise that will be incorporated into the next investment, and so on.

While the strategy will grow over time, there are five key steps HR and talent management

professionals should use from the start:

Step 1: Drive alignment with business goals.

A well-designed measurement strategy will make the connection between human capital and business

goals. Aligning any talent investment with business goals and corporate strategy is critical, as is

aligning the necessary stakeholders at the outset of design and measurement.

Be specific about what needs to be measured and why. Identify what needs to be proved or improved.

For example, the goal may be to prove that leadership development initiatives are effective at getting

new leaders up to speed faster, thereby increasing productivity.

Other questions that can be asked to start the measurement process include:

Where are we today?

Where do we want to be?

What are our priorities?

What kinds of investments are needed?

How long will it take to get there?

Step 2: Establish business measures of success.

It is important to establish what success looks like. Stakeholders—boards of directors, senior leaders,

department heads, and employees—can help identify ways to measure if the investment is succeeding.

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They are the key to accessing the necessary data and determining the measurements that will

demonstrate success. HR and talent management professionals should consider all stakeholders when

determining appropriate metrics and timelines to achieve the initiative’s goals.

It is also critical to determine how success will be measured. Every organization is unique and

different metrics will apply to different situations. This is where the continuum can be useful to

identify the appropriate metrics. Can the information be gathered anecdotally? How will it be

quantified and reflected on a scorecard or on a dashboard? Will the metrics help to reveal correlation

or causation?

Whenever possible, HR and talent management professionals should use multiple sources of data—

anecdotes, surveys, interviews—to calculate the return on investment. Once identified, these should be

reviewed and agreed on from the outset by senior leaders. This consensus will be crucial when

reporting the findings.

A common challenge among talent development leaders is how to measure the success of a leadership

development program and to justify its expense against business objectives. The best-known

framework for measurement in learning circles is Donald Kirkpatrick’s four-level model of evaluation

combined with an expanded version proposed by Jack Phillips that added a fifth level. The levels are:

1. Satisfaction

2. Learning gain

3. Learning transfer or behavior change

4. Business impact

5. Return on investment (ROI)

An initial level (Level 0) was subsequently added to capture the basics that are tracked by most

learning management systems (LMSs)—utilization, and a sixth level—optimization—was proposed

by Pease, Beresford, and Walker (2014), to capture the predictive analytics phase in the Human

Analytics Continuum described earlier.

The Kirkpatrick/Phillips framework has helped many HR and talent management professionals to

learn valuable insights into their learning initiatives. For a refresher on each level of Kirkpatrick’s

model, please see the UNC white paper “Beyond Smiley Sheets: Measuring the ROI of Learning and

Development” by Keri Bennington and Tony Laffoley.

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Step 3: Guide the development of content that’s aligned with

business needs.

The first two steps – driving alignment and defining success - should occur before any design takes

place. It is the business measures of success that will ultimately be used to write objectives. Instead of

saying, “We want our people to be able to do X,” say, “We want to achieve X. To do so, people need

to be able to do Y and Z.”

This step is applicable to all areas of HR, but it is

critical when creating a training curriculum. For a

training curriculum to drive business results, it

must be aligned with all the tasks that contribute

to those results. This is called performance

mapping, and it provides a proven way to

systematically align training curricula to

organizational goals. HR and talent management

professionals should also use gap analysis to

identify, quantify, and prioritize performance

gaps in an organization. Performance mapping

and gap analysis can provide the foundation for a

long-term, performance-based curriculum that

targets an organization’s most pressing learning

and performance needs.

Step 4: Provide in-process

measures for continuous

improvement.

Once the investment is started, the metrics that

were identified at the planning phase should be

monitored to ensure that the program is on track.

Measuring these leading indicators of success can

be an uncomfortable prospect for leaders, but in

practice, most people uncover more nuanced

changes that help improve the effectiveness of a

program. It is rare to see an aligned investment

that doesn’t show business value.

For any human capital investment that is developed with the intent to improve a business’s bottom

line, how it is expected to contribute needs to be explicitly articulated from the outset. Learning

leaders must be able to define the logical relationship between people investments and business goals.

Chrysler Dealership Sales Consultant

Training

Chrysler

collected

data from

33,867 of its dealership sales consultants

to determine if the company’s Sales

Consultant Curriculum (SCC) had any

impact on sales volume, sales satisfaction

index score, and retention of sales

consultants. The business impact study

revealed that sales volume increased by

1.3 new vehicles per month per

consultant due to training. The retention

rate for fully trained consultants was

98.9% versus 47.8% for untrained

consultants. Turnover among new hires

was dramatically lower among the

trained consultants. This “hard” data

allowed Chrysler to guide future changes

in the content of the curriculum and for

measuring the business impact of those

changes.

(Source: Vestrics, 2014.)

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A measurement map helps to show that causal chain of evidence. Building these maps, while

challenging at first, is a skill that most learning and development professionals can develop with a

little practice.

A measurement map depicts the logical relationships between people and business strategies. It

communicates using a common language that all stakeholders can understand. And it typically fits on

one sheet of paper.

It is important that the links that create this causal chain of evidence are measurable, especially when

analyzing the impact of an investment. To build this chain, the measurement map has four connected

sections:

1. Investments in people. This is the intervention or series of interventions intended to drive

business results. It can be any type of investment in human capital—a training event, a

recognition program, a new performance management process, and so on.

2. Leading indicators. Leading indicators are nonfinancial measures that suggest whether the

program is on the right track. Leading indicators typically appear earlier in the causal chain

and provide early evidence of the quantifiable business results to come. Common examples

include employee engagement scores, performance reviews, the number of customer

complaints, the number of new accounts opened, and promotion rates.

3. Business results. Often referred to as key performance indicators (KPIs), business impact

measures are tied to a financial value. They either are expressed in dollars and cents or can be

translated into financial terms. Common examples include turnover rates, customer loyalty,

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sales volume, revenue-per-full-time employee, productivity, workers’ compensation costs,

and cost avoidance.

4. Strategic goals. These are the ultimate end results anticipated as a result of the initiative. For

most organizations, they boil down to improving financial performance by increasing

revenue, decreasing costs, or both.

Every map will be different from investment to investment and from organization to organization. The

bottom line is to create a map that represents the expected and agreed-on observable, measurable

outcomes of the investments. By defining the alignment between people investments and business

goals, HR and talent management professionals will know what to measure, and their stakeholders

will know what to expect. Then the measurable outcomes become everyone’s business.

There are five key things to remember when starting the journey to create a measurement map:

1. Involve the right people. Part of the alignment includes involving the business operations

people in these discussions. They are the ones with the expectations of what employees will

do as a result of the program. They will also have access to the business data needed for an

impact analysis.

2. Agree on the strategic goal. The idea behind alignment implies that there is an explicit

strategic goal. If there is no end goal in mind, a map won’t help.

3. Make all KPIs quantifiable. Dashboards from the functional business units offer a great

source of what is already being measured, making data collection that much easier.

4. Treat it as an art, not a science. No two maps will look alike. The point is to illustrate

alignment, to create a common language about what to measure, and to build a credible map.

If it achieves that, it’s a good map.

5. Enjoy the process. Having an explicit and open conversation about how the organization’s

people investments align with organizational strategies can be eye-opening for everyone. The

conversations help build the map and credible relationships with key stakeholders.

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Step 5: Prove and improve.

Many learning organizations invest time and effort in the basic levels of measurement, but most see

limited value in the data. The key is to develop high-quality surveys and tests that allow HR and talent

management professionals to gather insightful and actionable data—data that can prove, and perhaps

more importantly improve, the quality of training. Improving the basics of learning evaluation enables

HR and talent management professionals to increase the value of some of the easiest measurement

data they can get.

Business metrics can be used to calculate a return on investment that will pass muster in the CFO’s

office. Predictive analytics can be used by adding statistical analyses to optimize the investment and to

identify where future investments are most needed. It’s the competitive advantage needed for high-

profile, high-stakes investments.

When organizations adopt a measurement strategy using these five steps, measurement tends to catch

and spread like wildfire.

When Human Capital Analytics Pay Off t can take time (two to three years of small steps and achievements) before an organization is able

to realize the full potential of human capital analytics, but the rewards are worth it. Here are a few

examples of organizations that have successfully used metrics and predictive analysis to improve

their HR and talent development processes, to link them to business strategy, and to impact future

actions:

Google used analytics to confirm their suspicions that low-performing employees were either

misplaced or being poorly managed. They used data and predictive analytics to determine the

most appropriate intervention to help them succeed.

Harrah’s used metrics to evaluate the effects of its health and wellness programs on employee

engagement and the bottom line.

A client of Bersin by Deloitte used analytics to discover that their approach to finding sales

and marketing candidates (by going to top-ranked schools, looking at GPAs, and assessing

academic activities) had almost no relationship to success on the job (Bersin, 2015).

I

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Conclusion

uman capital analytics allow organizations to make more informed business decisions that

improve the bottom line. Retiring baby boomers, a tightening labor market, and a new business

austerity that demands data is pushing human capital analytics to the top of the HR to-do list. It

is possible—and rewarding—to gather and analyze human capital metrics that will directly improve

an organization’s performance. HR and talent management professionals must start measuring their

talent development activities to prove their effectiveness and improve their organization’s competitive

advantage.

H

ConAgra Foods Foundations of Leadership

ConAgra Foods used human capital analytics to measure the

business impact of their Foundations of Leadership (FoL)

training initiative. Over the course of 2.5 years, ConAgra

studied the performance of 600 trained supervisors and 1,600 untrained supervisors at

65 US-based plants. The business impact study revealed a positive return on

investment, positive effect on plant and individual performance metrics, and a positive

impact on supervisor turnover and retention after participating in the training initiative.

(Source: Vestrics, 2014.)

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About UNC Executive Development

Our approach to program design and delivery draws upon the power of real-world, applicable experiences

from our faculty and staff, integrated with the knowledge our client partners share about the challenges they

face. We call this approach The Power of Experience. We combine traditional with experiential and unique

learning to ensure that all individuals gain relevant new skills that they can easily implement within their

own organizations. Through action learning and business simulation activities, we challenge participants to

think, reflect and make decisions differently.

Our Approach: The Partnership: Our team customizes each leadership program through a highly

collaborative process that involves our clients, program directors, faculty and program managers. We are

dedicated to following-up with our clients and individual participants to ensure that their learning

experiences have been meaningful and impactful. This integrated approach consistently drives strong

outcomes.

Our Approach: The Results: Our executive education programs are designed with results in mind,

and we are focused on successfully meeting our clients' business and academic expectations. Below are a

few examples of the results our client partners have achieved:

Leadership refocused with new

strategy and cohesive vision

Strategic plans created for the global

marketplace

Supply chains streamlined

Products redefined

New markets targeted

Cost-saving measures developed

Silos leveled

Teams aligned

Participants leave empowered to bring in new ideas, present different ways to grow business and tackle

challenges. The result is stronger individuals leading stronger teams and organizations.

Contact Us: Web: www.execdev.unc.edu | Tel: 1.800.862.3932 | Email: unc_exec@unc.edu

About Gene Pease Gene Pease is a pioneer in the field of Workforce Optimization. He is the Founder and CEO of Vestrics, a

company helping businesses optimize their human capital investments through cutting-edge software and

consulting solutions. He is the co-author of Human Capital Analytics: How to Harness the Potential of Your

Organization’s Greatest Asset and Developing Human Capital: Using Analytics to Plan and Optimize Your

Learning and Development Investments, both featured in the Wiley and SAS Business Series. Gene speaks

regularly at industry events, most recently at the 2014 Conference Board’s Performance Management

Conference.

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Sources ADP staff (2011). Effective talent management has become an essential strategy for organizational

success. ADP. Retrieved from http://www.adp.com/~/media/White%

20Papers/NAS/ADP_NASEffectiveTalentMgmtWhitePaper.ashx.

Ahalt, A. and Kelly, K. (2013). The Big Data Talent Gap. UNC Kenan-Flagler Business School.

Retrieved from http://execdev.kenan-flagler.unc.edu/execdev-big-data-talent-gap.

Bersin, J. (2015). Predictions for 2015. Oakland, CA: Bersin by Deloitte.

Buckley, P., Ohm, J., and Lissak, R. (2013). Human capital analytics: Thinking like an economist.

Deloitte. Retrieved from http://www2.deloitte.com/content/dam/Deloitte/

global/Documents/HumanCapital/dttl-humancapital-trends13-hc-analytics-no-exp.pdf.

Coco, C. T., Jamison, F., & Black, H. (2011) Connecting People Investments and Business Outcomes

at Lowe's: Using Value Linkage Analytics to Link Employee Engagement to Business Performance.

People & Strategy, 34(2), 28-33.

EY staff (n.d.). Paradigm shift. Measuring the effectiveness of talent management remains a

challenge. EY. Retrieved from http://www.ey.com/GL/en/Issues/Driving-growth/Growing-Beyond---

Paradigm-Shift---Measuring-the-effectiveness-of-talent-management-remains-a-challenge.

Facteau, J., and Hall, N. (27 June 2011). Are you measuring the right things? Talent Management.

Retrieved from http://www.talentmgt.com/articles/are-you-measuring-the-right-things.

Harkness, A. (20 November 2014). Human capital analytic: Harness data to power business

performance. I4cp. Retrieved from http://www.i4cp.com/productivity-blog/

2014/11/20/human-capital-analytics-harness-data-to-power-business-performance.

Kuehner-Hebert, K. (02 June 2010). Metric failure. Human Resource Executive Online. Retrieved

from http://www.hreonline.com/HRE/view/story.jhtml?id=440491363.

Lavoie, A. (04 November 2014). Measure these 5 talent metrics for greater success in hiring and

managing employees. Entrepreneur. Retrieved from http://www.entrepreneur.com/article/239117.

Lev-Ram, N. (07 November 2014). A way to help HR professionals predict the future. Fortune.

Retrieved from http://fortune.com/2014/11/07/workday-human-resources/

?utm_source=feedburner&utm_medium=feed&utm_campaign=Feed%3A+fortunefinance+(Fortune+

Finance%3A+Hedge+Funds%2C+Markets%2C+Mergers+%26+Acquisitions%2C+Private+Equity%2

C+Venture+Capital%2C+Wall+Street%2C+Washington).

Marr, B. (13 November 2013). The awesome ways big data is used today to change our world.

LinkedIn. Retrieved from https://www.linkedin.com/pulse/20131113065157-64875646-the-awesome-

ways-big-data-is-used-today-to-change-our-world.

Driving Talent Development with Data

All Content © UNC Executive Development 2015 16 | P a g e

Montgomery, C. (10 November 2013). Wal-Mart: An economic cancer on our cities. Salon. Retrieved

from http://www.salon.com/2013/11/10/walmart_an_economic

_cancer_on_our_cities/?utm_source=facebook&utm_medium=socialflow.

Pease, G., Beresford, B., and Walker, L. (2014). Developing Human Capital: Using Analytics to Plan

and Optimize Your Learning and Development Investments. Hoboken, NJ: Wiley.

Pease, G., Boyce, B., and Fitz-enz, J. (2012). Human Capital Analytics. Cary, NC: SAS.

PwC staff (2014). Trends in workforce analytics. PwC. Retrieved from

http://www.pwc.com/en_US/us/hr-management/publications/assets/pwc-trends-in-workforce-

analytics.pdf.

RHR International staff (n.d.). Measuring the impact of leadership development. RHR Executive

Insights. Retrieved from www.rhrinternational.com/100127/pdf/ei/V21N2-measuring-leadership.pdf.

Sicular, S. (27 March 2013). Gartner’s big data definition consists of three parts, not to be confused

with the three V’s. Forbes. Retrieved from http://www.forbes.com/sites/

gartnergroup/2013/03/27/gartners-big-data-definition-consists-of-three-parts-not-to-be-confused-with-

three-vs/.

Vickers, M. (02 June 2010). The crummy state of talent management metrics (and what to do about

it). I4cp. Retrieved from http://www.i4cp.com/trendwatchers/2010/06/02/

the-crummy-state-of-talent-management-metrics-and-what-to-do-about-it.