1. Develop a Strategy for Workforce Analytics with Big Data
Link HR value to business performance.
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2. Our Understanding of the Problem
HR professionals who are interested in developing a workforce analytics strategy using Big Data in HR to become more data- driven, analytical, proactive, and strategic in the management of the organization’s human capital.
HR departments who want to establish the value of workforce analytics using Big Data.
Understand Big Data and its value for HR: how it can be classified, its benefits, and its challenges.
Identify Big Data workforce analytics categories and how they can be used to create value for the organization.
Business leaders who are involved in strategic goal-setting and decision-making.
IT professionals who are responsible for the management of HR technologies and databases.
Determine the organization’s workforce analytics maturity.
Develop a workforce analytics plan that will accelerate the organization’s adoption of workforce analytics using Big Data.

3. Executive Summary
HR is tasked with delivering more value to the business.
HR does not know which metrics show the most value.
Big Data seems more like a buzzword than a practical application.
Big Data is not an issue, but an opportunity. Big Data by itself has no inherent value; it is the workforce analytics (WFA) using Big Data that drives new insights to deliver benefits. Big Data WFA moves organizations away from reactive or gut-feel decision making to data-driven and predictive decision making, supported by insights gained from previously unleveraged internal and external data.
Big Data can cause “info-glut,” where HR has too much data but is not able to act on it.
Analysis paralysis is an issue as HR tries to analyze everything for fear of missing something.
HR departments do not know how to integrate Big Data into their daily analytics.
McLean & Company has observed four specific categories where Big Data workforce analytics can have the most impact for HR and the organization: Workforce Planning, Talent Acquisition, Retention, and Succession Planning.
Leveraging these categories will help HR identify specific, high-value workforce analytics opportunities, increase organizational buy-in, and reduce implementation time.
A Big Data workforce analytics program can be launched as part of your overall HR strategic plan or as its own, standalone strategy that tackles specific Big Data for your organization that is built around organizational Key Performance Indicators (KPIs).

4. Best-Practice Toolkit Guided Implementations
Develop a Strategy for Workforce Analytics with Big Data
1. Make the Case, Identify Data Needs, and Prioritize Opportunities
2. Develop, Execute, and Maintain Strategy
Best-Practice Toolkit
1. Make the Case
2. Identify Data Needs
3. Prioritize Opportunities
4. Develop Strategy
5. Execute and Maintain Strategy
Guided Implementations
Understand the facts and figures behind Big Data and why it is relevant to your organization.
Discuss and address specific data needs.
Identify your organization’s ability to analyze data and derive practical insights.
Develop the plan going forward, identifying which metrics you will track and how you will analyze them.
Plan out execution and discuss strategic maintenance plan.
Onsite Workshop
Module 1:
Identify your plan inputs.
Module 2:
Develop and execute your plan.
Phase 1 Outcome:
Identified which WFA category is most pertinent for your organization.
Identified what type of data your organization is best able to analyze.
Phase 2 Outcome:
Fleshed out strategy for Big Data.
Implementation and maintenance plan.

5. Make the Case, Identify Data Needs, and Prioritize Opportunities
Phase 1
Phase 2
Make the Case, Identify Data Needs, and Prioritize Opportunities
Develop, Execute, and Maintain Strategy
Make the Case, Identify Data Needs, and Prioritize Opportunities
Steps:
Make the case for workforce analytics with Big Data.
Identify data needs.
Prioritize opportunities.

6. Make the Case: What is Big Data?
The value of Big Data comes from connecting large amounts of previously unconnected data sets, from multiple sources, to create new insights.
The variety of data types are increasingly diverse. Structured data* often comes from transactional systems, while unstructured data comes from a number of sources
such as photos, video,
text documents, etc.
Variety
Velocity
Volume
Veracity
Value
The volume of data being produced has increased rapidly. Organizations are faced with data from numerous sources including the enterprise, the cloud, and social media.
Data is being generated at
increasing rates.
Organizations not only need
to address how quickly data is generated, but also how quickly
the data needs to be analyzed
before it becomes stale or obsolete.
Getting value out of
Big Data is dependent
on having quality data. If
an organization’s data lacks veracity, decisions may be made that do not actually benefit the organization.
*Structured data? See Appendix for some common Big Data terminology.

7. Businesses take Big Data seriously to gain competitive advantage and HR should take it seriously too
Organizations are taking Big Data seriously
“Executives look with admiration at how Google, Amazon, and others have eclipsed competitors with powerful new business models that derive from an ability to exploit data.” (Source: Barton & Court)
Businesses are striving to become data-based. A recent Wall Street Journal article reported that improvement of information and analytics is a top priority for many organizations with 85% of Fortune 1000 executives having projects planned or underway for getting more business value out of data their companies generate and collect. (Source: cited by eQuest)
HR can act now to help gain competitive advantage or later due to competitive pressures and lose out on any advantages.
The Big Data trend means business leaders will want HR to be data-driven. Ignoring data won’t make it go away.
HR should take it seriously too
Big Data is the new oil. The companies, governments, and organizations that are able to mine this resource will have enormous advantage over those who don’t.
– Pew Internet, The Future of Big Data
HR needs to embrace a “data everywhere” strategy which requires the profession to learn how to utilize all data and tools available.
– David Bernstein, VP “Big Data for HR” Division, eQuest

8. Big Data refers to the data itself; workforce analytics (WFA) is what HR does with it and where HR derives value
“Big Data is really just a buzzword for smarter, more insightful data analysis.” (Source: Davenport, Barth, & Bean)
At its core, Big Data is simply data. Value comes in its application.
Big Data technologies and practices now make it faster, cheaper, and easier to manage large data sets. This allows companies to ask and answer questions that were impossible, or prohibitively expensive, to previously answer. (Source: Visier)
As a result, leading companies are using data collection and analysis to make better management decisions and forecast what will happen in the future.
Many of the Big Data applications have been for marketing and consumer business, but there is even more opportunity to apply Big Data in HR because a large chunk of Big Data is human capital data.
(Source: Nucleus Research)
McLean & Co. Insight
Organizations have more data than they know what to do with and human capital data is no different. Big Data allows HR to take advantage of an unprecedented amount of data to conduct more powerful workforce analytics (WFA). In turn, HR can make better data-based talent management decisions and raise the department’s profile as a strategic partner.

9. – CIPD, Talent Analytics and Big Data: The Challenge for HR
Powerful workforce analytics with Big Data helps HR become better at making decisions and predictions
One of Big Data’s greatest HR values is as a predictive tool. HR can ask “What will happen if?” and “How is the business performing right now?” type questions, instead of just traditional “How did I do?” type questions.
This allows HR to support business strategies more effectively and better manage human capital risk.
Predict what will happen
Make data-based decisions
HR has traditionally relied on gut feel, personal experience, relationships, and established practice to guide human capital decisions.
This results in decisions that are less reliable and consistent compared to decisions made in other parts of the company.
A more educated approach using data provides evidence to back up assertions and results in better decisions.
Research by Evolv shows that an applicant’s work history is not a good predictor of future results.
Evolv has also found that in call centers, the quality of the supervisor is a better predictor of tenure and performance than the experience and individual attributes (i.e. communication skills and personal warmth) of the workers themselves.
IBM’s Kenexa unit has found that, contrary to common belief, an outgoing personality is not the defining trait of successful sales people. Rather, it’s a persistence to keep going even after being told no, called emotional courage, that predicts sales success.
(Source: Lohr)
Big Data is proving some traditional HR assumptions wrong
The promise of Big Data is that it almost certainly will move HR forward in terms of analysis and insights.
– CIPD, Talent Analytics and Big Data: The Challenge for HR

10. Data-based predictions and fact-based decisions bring tremendous value to organizations
WFA helps organizations
Analytics Habits of Top Performing Organizations
Percent of respondents whose organizations do these activities well or very well.
Use insights to guide future strategies
Use insights to guide day-to-day operations
Improve methods of attracting, retaining, and developing talent.
Reduce labor costs.
Improve productivity and resource allocation.
Optimize outcomes.
Connect employee data to business performance.
Increase competitive advantage and differentiation.
Visier, Inc. found that organizations that have implemented WFA experienced:
14% year-over-year improvement in revenue per employee.
20% decrease in unnecessary overtime.
2x the customer satisfaction.
13% increase in workforce utilization.
A survey by Tata (source) found that 80% of surveyed organizations reported improved decision-making capabilities with Big Data.
Top Performers
Lower Performers
This research shows that top-performing organizations were twice as likely to use analytics to guide day-to-day operations and future strategies as lower performers.
(Source: LaValle et al., Winter)

11. Google bases all people decisions – from hiring to compensation to talent management – on data and analytics
The goal of the people analytics team is to “bring the same level of rigor to people decisions that we do to engineering decisions.” – Google People Analytics Team
Industry:
Segment:
Source:
Technology
Enterprise
How Google is Using People Analytics to Completely Reinvent HR, Dr. John Sullivan, Blog Post for TLNT.com.
Situation
Action & Results
Google realized that to produce continuous innovation they needed a strategic focus on people management. To maximize innovations, they had to increase their capability to recruit and retain innovators and provide them with a supportive environment.
This realization led Google to shift from hunch-based to data-driven people management decisions and form a People Analytics Team.
Examples of Google’s data-driven approach to people management:
Retention. Algorithm to proactively predict which employees are most likely to become flight risks, which allows managers to personalize retention solutions.
Hiring. Algorithm to predict which candidates have the highest probability of success after hire, which shortened time to hire and improved retention rate.
Diversity. Analytics to find root causes of diversity problems, resulting in improvement in diversity from solving the problems.
Value of top performers. Top performers deliver as much as 300 times more than average performers. This provides HR managers with more budget and leverage to attract, hire, develop, and retain top performers.
Workforce planning and people management problems. Predictive modeling to conduct a “what-if” analysis to forecast future people management problems and opportunities for improved workforce planning.
Workforce productivity. “On average, each employee generates nearly $1 million in revenue and $200,000 in profit each year.”

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Build a high performance culture
Maintain a progressive set of HR policies & procedures
Demonstrate the business impact of HR
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