This document summarizes an article on people analytics and discusses its convergence with industrial organization, civil rights law, and big data. It notes that people analytics uses big data to quantify trends in areas like tenure, promotions, and reasons for leaving in order to develop strategic diversity and inclusion plans. However, it cautions that data must be properly interpreted to avoid ineffective solutions that do not address systemic problems. While people analytics provides useful information, interpreting and acting on the data is challenging and expensive for companies.

1. Deloitte University Press
People Analytics
Gaining speed
Written by
Josh Bersin, Laurence Collins, David Mallon, Jeff Moir & Robert Straub
February 29, 2016
Review of the Article as posed on February 29, 2016
By
R. Kimberly Grigsby, JD
Diversity, Inclusion and Equity Consultant
It is interesting to fathom how the industry of information technology has touched nearly every
aspect of human life and continues to evolve right before our very eyes. The speed of which
technology transforms the world, not only, aids in closing the gap on global business, but has had
a huge impact on society and how we as people relate to one another. Moreover, this has a direct
nexus as to how we as educators, as well as those supporting the educational movement, must
teach going forward. This article and the discussion on People Analytics is case in point.
My classical background and training has been in the area of law. I have worked in nearly a
dozen fields but I feel most comfortable working in areas that seek to bring people together and,
as well as contributing to the betterment of the world. Explaining this proposition some 20 years
ago sounded like a crazy made up task. However, now as we approach the cosmic intertwining
of the fields of psychology, law, information technology, diversity and education, we have
landed squarely exactly where I have been for years.
Civil Rights and HR Law
For many years the study of law, diversity, equality and inclusion issues seemed to be simply an
extension of the civil rights movements where people wanted to use a top down approach and
allow the federal government to administer, or dictate, changes in American culture and business
life. Fighting discriminatory practices was at the heart of the movement. It took time but some
of the more progressive companies like Pepsi, Sodexo, Coke, GE and others started on the
journey of diversifying their business culture and rectifying a lifetime of discriminatory
behavior. At the inception of the quest of these large corporations, the focus of diversity was
settled around affirmative action like quotas. The positive impact of their efforts was that it gave
diverse candidates an opportunity to participate more fully in the Fortune 500 world. The
downside was the negative backlash of the notion of quota focused programs, allowing the
perception of inferior people to take jobs away from “regular Americans”. This type of focus
was, and still remains, a concern for majority race holders as who fear the influx of minority
candidates may work to unravel the original top down, majority rule, structure. As a result of the
movement toward diversity and initiatives to reduce racial discrimination, the field of HR law
expanded from discrimination due to ethnic background and color to the eventual inclusion of
other demographic factors that were subject to discriminatory practices such as gender, age,
veteran, sexual orientation and any other group that seeks to be protected.

2. Industrial Organization
While the civil rights and HR phenomenon was growing, so too was the field of Industrial
Organization (I/O). In the early 1990’s, I/O practitioners made the switch from identifying and
fixing the ills of discriminatory practices to a more proactive stance of creating a process of
concrete standards for more dynamic and diverse environments. This movement, arguably, did
not get as much fervor as did the post-civil rights movement. This was primarily due to the fact
that there was very little by way of quantifiable, empirical evidence to show what changes have
the largest impact with the least amount of resistance. For this reason, another major shift
occurred in the area of I/O in terms of implementing proactive processes which required the
assistance of other areas. Many of the more progressive I/O practitioners have realized that if an
organization does not have policies that seek to create an inclusive environment then increasing
diversity will only be an exercise where to meet quotas and people will serve in a revolving door
capacity within the organization. The shift in I/O has created a movement in Diversity
Departments to demonstrate their expansion from simply being discrimination reduction focused
to a more inclusionary process and service delivery. This can be seen in the changes from
departments being titles such as a departing moving from the title of “Diversity Departments” to
being “Inclusion and Equity Departments”. The newly labeled “Inclusion and Diversity
Departments”, maintain a focus around policies, procedures and quantifiable data and less on the
raw numbers of diversity candidates that have been introduced to the company.
IT & Big Data
At the same time as the changes were occurring in the I/O field, the IT field introduced the
concept of Big Data. The federal government and technologist sought to stockpile information;
all types and any forms of information, including useful and superfluous information, in the
name of supporting the war against terrorism. Most can remember the first objections to the
collection of information being just a general objection, as it was against American interests in
privacy. The systems put in place to gather the data all information were not well equipped with
the knowledge and skills to separate relevant information from that which was not relevant, as
well as how to utilize the relevant information for the necessary business or safety purposes. To a
large degree this fight is ongoing but in the midst we have evolved the job of data entry
technician into a data analytic scientist. Now instead of just focusing in on data and its entry into
a massive system we have now required people to develop complicated algorithms that will
parcel out the useful information for human consumption and interpretation.
The perfect convergence
This article really sets out to draw in these three major areas of study into one new area. In this
process, one has to be a student of all three in order to understand the whole and to help direct
what the future may hold. Many HR departments have been over inundated with EEO and
discrimination claims causing legal departments and the courts to work overtime in keeping up
with the allegations that companies are not working within the confines of the law to promote an
equal environment with the non-majority employee. This causes human capital strain, as well as
financial strain for all agencies involved. In an effort to incorporate a more inclusive and equal

3. environment, I/O practitioners have developed organizational practices such as more questions
regarding protected status on employment applications, exit interviews, as well as 360 surveys
regarding workplace and environmental happiness. This has allowed data analytic scientists and
technicians to capture information necessary to quantify trends to include, tenure and promotions
of particular demographics, as well as, average tenure and reasons for saying and more
importantly reasons for leaving. This then becomes baseline information for executives, HR and
legal teams, and the company board to make strategic plans to retain and lower costs as it relates
to HR needs of a company.
Although this is very encouraging information, it is just the tip of the iceberg as it relates to what
is on the horizon for Big Data and people analytics. Personally, I have a love hate relationship
with Big Data. On one hand, it does provide concrete data to either prove or disprove a
proposition as it relates to corporate culture. However, the problem is that some leaders will
miss-use the information and create ineffective solutions to fix systemic problems; of which they
are often part of the cause. For instance, the misuse of information regarding analytics related to
African American individuals not feeling supported as it relates to being hired and treated fairly
in the work environment. Instead of evaluating the environmental factors within the company
that impact the statistics, I have seen some companies look at where they were hiring their
African Americans and decide not to hire from that school any longer. I had the opportunity to
deal with a financial services company that decided that they did not want to work with schools
in the AUC until I personally called the schools and facilitated a face to face meeting to discuss
obstacles with hiring from their school. What we found is that the companies’ Director of
Recruiting stated that the students that she hired from there were not committed, did not readily
adapt to the culture and left the company, and unhappy after less than 3 years. What the
analytics did not show is that this same Director promised all of the recruits that they have a cool
laid back environment in the downtown area of Chicago. This was not a true statement given the
demographics of the area. This financial services company was as buttoned up as the rest until
last year. Further, the company was located in North Chicago, which is a euphemism for South
Wisconsin. The community could not be any more different from Chicago proper. So kids from
Atlanta would come here, get an apartment in Chicago, and never have the time to really
participate in the city life. Once my AUC colleagues explained the student’s perspective, it
really made the company reconsider the statistical information she received.
In summary, that information is only as intuitive as the people collecting and interpreting
it. People will always find a way to discriminate or, better put, revert to comfortable behaviors
when put in uncomfortable positions.
In the end…
On the bright side, people analytics is a very positive use of Big Data. Most of the more
progressive companies only do culture wellness reporting every other year, so there is a gap of
time between when leaders get information and when they can realistically act. HR teams are
becoming more sophisticated as well. The days of old HR departments being paper processors
are over. Most job descriptions today look for people who have an I/O or psychology
background, legal background, HR or business background. Collaboration and solution
generation are the focus of HR services. Another old adage, the more you know the more you
grow seems to be the common theme in the people analytics business. However, if companies
thought that they would be reducing the HR costs they are mistaken. The people analytics

4. business is an expensive proposition. Many companies are trading litigation costs for the cost to
produce and interpret data. The notion of solution generation usually means that more executive
level positions are created to balance the company culture with policies and programs that will
keep them relevant. Legal departments are working overtime as they now have more
information that is discoverable. The more evidence that is created, the more that an employee
can subpoena and make an argument that the evidence was in the hands of the corporation
proving salient gaps in process or people who may have been bad actors against the employee or
against the diversity and inclusion effort. Older HR departments trended towards small agencies.
One of the downsides is that though big data is relevant information, companies struggle with
leadership justifying one more person or an entire department towards this effort. Diversity,
Inclusion and Equity changes are often comprehensive and expensive and this makes the advent
of big data and people analytics much more expensive. Despite its costs, the diversity, Inclusion
and Equity with in the field of Human Resources still has some challenges but it with the
assistance of Big Data it is heading in the right direction.
Kim