USING PREDICTIVE ANALYTICS TO
DRIVE WORKFORCE OPTIMIZATION
New Insights from Big Data Analysis Uncover Key
Using Predictive Analytics To Drive Workforce
BIG DATA PREDICTIVE ANALYTICS AS A
SOURCE OF COMPETITIVE ADVANTAGE
Fortune 500 companies are investing in big data analytics for a simple reason – to save money and gain market share by understanding the real dynamics behind their business. Companies with the best analytical capabilities outperform the competition by wide margins. They are:Data is a critical business asset, just like labor and capital. The volume of data that is available and the speed with which it can be analyzed is providing companies with real-time insights into their business. What’s more, it’s allowing companies to predict future business outcomes and drive decision-making now. A recent Bain & Company study shows that adopting big data analytics is worth the invest-ment. Companies who do so are gaining a significant lead over their competitors.
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2x
3x
5x
2x
More likely to be in their industry top quartile of financial performance
More likely to execute strategic plans as intended
More likely to have faster decision making
More likely to use data-driven decision making at the C-level
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Research2 conducted by Bersin by Deloitte found similar
results. Companies that use predictive analytics for fore-casting outcomes and strategic planning gain tremendous business returns.3 For example, they are twice as likely
to deliver high impact recruiting solutions, their leader-ship pipelines are twice as healthy, and their stock market returns are 30 percent higher than the S&P 500.4 Yet, only 4
percent of surveyed companies have achieved the capabil-ity to perform predictive analytics about their workforce. Why are so many companies missing out on such an es-sential business program and source of competitive advan-tage? There are common misperceptions about applying predictive analytics to the workforce. Many companies mistakenly believe that they don’t have enough data, aren’t mature enough, or need to make huge investments in data technology.
“ From the standpoint of competitiveness and the potential capture of value, all companies need to take big data seriously.” — McKinsey5
OPTIMIZING THE WORKFORCE WITH
PREDICTIVE ANALYTICS
Data analytics is changing the way business leaders think and act when it comes to one of their most important as-sets - their people.
Workforce performance is one of the most critical business functions for any company. Poor performance drags on revenue whereas optimal workforce performance provides a critical competitive edge. Now, the selection, training, management, compensation, scheduling, and retention of employees can be optimized using big data analysis. Big data analysis of the workforce allows business leaders to factually answer questions such as: Which job appli-cants will deliver the best customer experience? How will a wage increase impact employee retention? What types of hires will sell the most product? What truly drives employee performance, training program outcomes, and management success?
The hiring, training, and managing of people has long been done by gut and intuition. Now, companies can rely on data analysis to uncover the facts and drive decisions.
“ Considering that companies spend a fortune building a workforce yet so many new hires don’t work out, using data to improve how businesses hire, retain and motivate employees can result in an out-sized gain in corporate performance.” Kenneth Cukier, Data Editor of The Economist6
BIG DATA ANALYSIS AND ACTION DRIVE
PROFIT
The benefits are clear. Adopting a big data approach to workforce performance leads to measurable improvements in net income. Big data and predictive analytics are helping companies:
s Increase customer satisfaction and NetPromoter scores s Conduct interviews and make hiring decisions 5x faster s Improve employee retention and reduce attrition 39% s Manage workload with 20% fewer employees by
improving schedule adherence
s Increase sales 10% by optimizing employee training and management
s Improve employee engagement and reduce missed work hours 29%
Driving these outcomes7 requires analyzing data across
the entire employee lifecycle, identifying the key factors impacting workforce performance, and then putting that analysis into action. And it results in tens of millions of dollars in savings.
“ We have clearly entered an economy in which talent is considered a critical and scarce commodity. When this happens, companies should get smarter about every single talent decision. Enter the world of ‘ data-driven’ people decision-making.” — Deloitte8
EVERY COMPANY CAN DO PREDICTIVE
ANALYTICS
To do predictive analytics and predictive modeling, compa-nies don’t need to make huge investments in data technol-ogy. They don’t need to hire a team of statisticians either. These are common misconceptions. The fact is, most com-panies already capture more data than they think. And one third of all enterprise data is people data.9 New technology
broadly accessible and eminently doable. The widespread use of cloud applications, the huge increase in both struc-tured and unstrucstruc-tured data, and the capacity for large-scale processing of data sets have led to the development of predictive analytics applications for the workforce.
Using big data applications built for the workforce, compa-nies can proactively manage and improve employee and operational performance. In the past, companies have only been able to look in the rearview mirror to review, assess and troubleshoot workforce performance. But unlike human resources and business intelligence tools, workforce opti-mization applications don’t just present trends by analyz-ing past data. They allow business leaders to model future scenarios and perform simulations.
“ Firms have spent many years building enterprise data warehouses and using business intelligence (BI) tools to report on the business. But predictive analytics is different – advanced statistical and machine may not reveal. Big data is the fuel and predictive analytics is the en-they gain.” Forrester 10
ENTERPRISE DATA
2/3 (240,000 PB) All Other 1/3 (120,000 PB) Human Resources
2013.
2.“High-Impact Talent Analytics: Building a World-Class HR Measurement
5.“Big data: The next frontier for innovation, competition, and productivity,” McK-6. “When the Boss Is Big Data,” Data Economy, a CNBC Special Report, April 15, 2013.
workforce optimization applications.
9. “Big Data, Bigger Opportunities: Investing in Information and Analytics,” Gart-ner Special Report, March 12, 2013.
Big Data Analysis Uncovers the Key Drivers of
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Researchers at Evolv, the leading provider of big data software as a service applications for workforce optimiza-tion, have uncovered some of the top factors that impact employee performance and tenure. What’s more, they have even measured the degree to which each of these factors influence workforce profitability.
Using big data analytics software, researchers at Evolv found that the key drivers of workforce profitability fell into five main areas:
WORKPLACE RELATIONSHIPS COMPANY PRACTICES
WORKER CHARACTERISTICS JOB CHARACTERISTICS MACROECONOMIC TRENDS
Evolv works with:
s Massive data sets, covering 500 million employee data points, 18 industries, and 13 countries
MACRO ECONOMIC FACTORS 16% WORKPLACE RELATIONSHIPS 54% WORKER CHARACTERISTICS 8% JOB CHARACTERISTICS 11% COMPANY PRACTICES 11% MACRO ECONOMIC FACTORS 16% WORKPLACE RELATIONSHIPS 54% WORKER CHARACTERISTICS 8% JOB CHARACTERISTICS 11% COMPANY PRACTICES 11%
s Top global brands, optimizing workers across 20 per-cent of the Fortune 100
s Researchers at leading universities, including The Whar-ton School of the University of Pennsylvania and The Yale School of Management
Based on Evolv’s experience working with top academic institutions, clients with large global workforces, and enor-mous data sets, these are some of the top factors that impact workers.
WORKPLACE RELATIONSHIPS
INSIGHT:
Managers Impact Employee
Per-formance and Tenure More Than
Any Other Factor—Even the
Em-ployees Themselves
Everyone can remember a manager who had a profound impact on his or her job. Data now quantifies the critical impact that good management has on employee retention and business profitability. It’s more important to perfor-mance and tenure than any other factor—including the ex-perience and characteristics of the employees themselves.
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Research examined over 2.5 million granular management and supervisory data points to study the extent to which supervisors affect an employee’s likelihood to remain on the job. The results were nothing short of striking.
The study found that the best supervisors’ employees were nearly 6 times more likely to stay than employees with supervisors who were worst at retaining staff. In fact, the study shows that an employee’s supervisor is a stronger predictor of his or her likelihood to quit than every other fac-tor combined.
Extrapolating the measured impacts observed in this study, a company with 53,000 employees could save $4.6 million just by improving the performance of its managers in the bottom quartile.
Employees with the best managers are 6X more likely to remain
on the job In addition, supervisors had a profound impact on em-ployee performance. Through analysis of data from
dispa-rate systems across the employee lifecycle, one company concerned with customer satisfaction was able to get a full picture of what was really driving the customer experience. The company used data-driven insights, including the re-sults of its supervisor analysis, to boost customer satisfac-tion by 5.2% and Net Promoter scores by 2.2%. Given the scale of the company’s operations, each percentage point of improvement was valued at millions of dollars.
4.6
Million
53,000
employees
Boosting the
performance
How can a company save millions in workforce costs? The average Fortune 500 company has 53,000 employees. A company of this size can save $4.6 million just by boosting the performance of managers in its bottom quartile.
2%
5%
Net Promoter scores customer satisfaction
DATA-DRIVEN INSIGHTS INSIGHTS IN ACTION:
INSIGHT:
Highly Communicative Trainers
Outperform Highly Organized
Trainers
Another study looked at data from 22,000 front line employ-ees, 162 trainers and 17 locations to assess the impact of different types of training styles on employee profitability. The study revealed that most effective trainers created open and active discussions in class, asked questions and checked for knowledge.
An unexpected finding of the study was that communica-tive trainers performed much better than trainers with strong time management, class control and organization skills. In addition, the results pointed to a strong link between in-training and post-in-training employee survival, indicating that trainers who are most effective during training also produce employees who are most prepared to handle the rigors of the job.
INSIGHTS IN ACTION:
The Results Companies is one of the most successful Business Process Outsourcers headquartered in the United States today. Results engaged Evolv to improve the selection, development and retention of its workforce to meet the requirements of its high-visibility Fortune 500 clients.
After launching the Evolv solution, including a trainer analysis, The Results Companies saw improvements across every facet of the employee lifecycle:
25-35%
Attrition was reduced 25-35% across key programs, representing savings and improvement to overall workforce quality.
Improvements to customer handling efficiency and adherence to schedule enabled Results to manage the same number of customer transactions with as much as 20% fewer employees. Business units focused on new business generation increased sales productivity 8-10% across key programs.
COMPANY PRACTICES
INSIGHT:
Not too much or too little –
get-ting overtime just right boosts
retention
Company practices affect workforce performance and profitability throughout the employee lifecycle. From the creation of job applicant assessments and recruiting poli-cies to the training and promotion of employees, company practices can help or hinder performance.
Researches found that, when it comes to overtime for certain job roles, there is a “sweet spot”. In order to keep employees engaged but not burned out, one to three hours of overtime a week is ideal. More or less can actually decrease tenure. It may be that workers welcome the extra compensation boost of overtime but only to a point.
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Employees stay in their jobs longer when offered the op-portunity to work overtime, analysis shows. Employees averaging one to three hours of weekly overtime showed 58 percent better retention.
Evolv analysis for a Fortune 500 company with nearly 50,000 workers showed that optimizing overtime policies would result in savings of $10 million dollars annually.
WORKER CHARACTERISTICS
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0 30 60 90 120 150 100% 80% 70% 60% 50% 90% 40%0-1 hour 1-3 hours 3+ hours
Pr
obability of
Retention over Time
EMPLOYEE TENURE BY AVERAGE WEEKLY OVERTIME
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INSIGHT:
Tech savvy employees
outper-form their peers even in non-tech
roles
Technology’s role in everyday life is continually growing. Roughly half of Americans own smartphones and globally one in five people will own a smartphone by the end of this year. Around 61% of U.S. households and 25% of global households have wifi. The proliferation of technology not
only affects the daily lives of people around the world, it also has implications for front line, consumer-facing workers. A study on technological aptitude found that tech savvy individuals performed better and stayed longer on the job. The study used three measures to estimate a candidate’s technological aptitude: technological proficiency,
willingness to adopt new technology, and technology enabled social networking.
Employees who have high technological proficiency, as measured by typing speed and responses to technological knowledge questions, are more productive. They stay on the job an additional 17 days longer on average and miss 15% fewer days of work. What’s more, they adhere to com-pany protocols and procedures better than those who have low technological proficiency scores.
A willingness to adopt new technology by choosing non-standard browsers is a powerful predictor of performance. Employees in certain functional areas that use Chrome and Firefox perform better across the board than those who use standard browsers that come with most computers, like Internet Explorer and Safari. Not only do these employees stay on the job longer, miss less work and adhere better to company protocols—just like those who are technologically proficient—but they also excel in other areas. They provide higher customer satisfaction and close more sales.
Individuals who used between 3-4 social networks perform just as well as those who use a custom browser and are technologically proficient. In other words, the use of social networks can serve as shorthand for technological profi-ciency and willingness to adopt new technology.
JOB CHARACTERISTICS
INSIGHT:
Employees who are given
the option to work at home
stay longer
Work at home policies were one of the most hotly debated workforce practices over the past year. The controversial decision at Yahoo! to ban working remotely put this com-mon workplace practice squarely in the spotlight. Here’s workforce analytics reveal about working at home.
A study of hourly workers found that work at home employ-ees have a higher probability of staying with their company. Median tenure for work at home employees is 28% higher than median tenure for their in-office peers. It isn’t surpris-ing that employees who are given the flexibility of worksurpris-ing from home stay longer.
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Work-at-home employees stay
MACROECONOMIC TRENDS
INSIGHT:
The economic recovery isn’t all
good news for business
Historically, through every recession, the number of people voluntarily quitting their jobs has declined. Then, as the economy recovers, the number goes up. According to a recent Job Openings and Labor Turnover survey (JOLTS), published by the Bureau of Labor Statistics, people are quitting their jobs at the highest rates in five years. As the economy continues to improve, analysis shows that attrition rates will keep increasing. While attrition was at an all-time low in 2008, it’s on track to return to historical averages. The implication for business is profound. Research shows that companies can expect the cost of attrition to increase 25 percent as rates of attrition return to historic norms.
For a company with 50,000 employees and average turn-over, that’s an increase of $22 million dollars in costs.
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RATE OF ATTRITION INCREASING, RETURNING TO HISTORICAL AVERAGES 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 3600 3200 2800 2400 2000 1600
Shaded regions represent periods of U.S. recession
Haver Analytics, Gluskin Sheff
Predictive Analytics is Optimizing Workforce
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Recruiting and managing talent using
proactive and predictive insights is critical
to maximizing customer acquisition,
cus-tomer loyalty, and workforce efficiency.
As such, it is essential to optimizing the profitability, com-petitiveness and overall business of companies. Business leaders have had limited visibility into the true reasons behind workforce performance. Until now.
Predictive analytics are decoding the key factors driving workforce performance. More than just data, these find-ings leverage proprietary algorithms and Evolv’s Workforce Optimization Cloud to uncover what to do with the data, why it matters, and forecast future outcomes. The result is the ability to offer companies predictive insights that inform management decisions and save millions of dollars by im-proving employee selection, development, performance, and transition—ultimately changing the way companies create and manage their workforce.
The research findings and business outcomes in this report are just the start. Evolv continues to dig deeper into the findings and companies continue to use the insights to drive performance and profit. Together with its academic research partners, Evolv seeks to answer questions about workforce performance including:
s Selecting Supervisors - Do the best supervisors have front line experience or should they be experienced managers? When looking for a team leader, should you hire from within or mount an external search?
s Employee Management - To what extent do coaching behaviors, such as check-ins and mentoring, allow em-ployees to achieve their full potential?
s Employee Engagement - Research has shown that less engaged employees tend to perform worse and leave more quickly. But do employees tend to “check out” at work before they are about to leave? If so, is it possible to predict when employees are about to leave and re-engage them before they walk out the door?
Keep up to date with the latest workforce optimization research, news, and resources. Subscribe today to Evolv’s free newsletter and find out how workforce optimization can impact profit and performance at your company.
ABOUT EVOLV
Workforce Optimization Cloud. The latest version of the Evolv Workforce Optimization Cloud, including the predictive analytics application Evolv
then utilizes that dataset to identify predictive workforce insights that -ing and workforce science, Evolv helps companies uncover the core
