C
ustomer Relationship Metrics
Call
Center
Analytics
Revealed
Why Technology is not Your Actionable Business
Intelligence Panacea
Customer Relationship Metrics
and a
pioneer in customer experience
research and transformation.
Her findings and insights have been
part of numerous case studies and
techn
o
logical advances.
She
is
recognized
by
many
as
being
the
most important competitive advantage
in their contact center and customer
experience strategy
.
Other titles:
11
Steps
to
Social
Media
Success
for
Contact
Centers
Eliminating
the
Worst
Call
Center
Practice:
Call
Monitoring
Calibration
Get
it
Now
What’s
in
this
ebook?
1.
Overview
of
a
trend
that
places
analytics
in
a
very
compromising
position.
2.
A
current
gap
in
the
US
that
is
projected
to
continue
to
widen
for
several
years
to
come.
3.
The
difference
between
reporting,
analytics,
and
business
intelligence.
4.
The
power
of
business
acumen.
Book
Chapters:
Prelude ... 5‐6
Chapter 1: A Growing Analytics Skills Gap ... 7‐11
Chapter 2: What is an Analyst? ………...12‐13
Chapter 3: Hey Analyst! Does the CEO really want your Analytics? ………..……....14‐16
Conclusion………..17
Resources ………..…….…..18
About Customer Relationship Metrics………..…….…………19
Prelude
The U.S. education system has come under considerable scruitiny over the past several years,
and not without merit. The fact is that students in the United States are falling further and
further behind other countries in math and science education. As more lower‐skilled jobs
leave our shores and the need in the marketplace for more highly‐skilled workers increases,
U.S. businesses are experiencing a skilled talent crisis in many parts of their business. One
area hit by this talent crisis is the need for more analytic thinkers. There is no supply, and the
education system is not filling this need. Business intelligence (BI) technology and call center
analytics tools will be of no value if there are no highly skilled analytic people to run them.
During the last three times that the Trends in International Mathematics and Science Study
(TIMSS) was conducted (1999, 2003 and 2007), the best ranking that U.S. 8th graders were
able to achieve in either math or science was 6th.
The 2003 Program for International Student Assessment (PISA) study, focusing on the
mathematical problem‐solving skills of 15 year olds, found a widening gap between U.S.
students and students in Europe and Asia. In the 2009 PISA study, U.S. students ranked 23rd
Chapter
1:
A
Growing
Analytic
Skills
Gap
Both industry and academia in the United States are acutely aware of this growing skills gap.
In the past few years more than a dozen analytic‐focused MBA programs have launched at
learning institutions from St. Joseph’s University to Northwestern University, University of
Chicago’s Booth school of business, and Xavier University. IBM recently partnered with
DePaul University to launch the Center for Data Mining and Predictive Analytics, offering the
nation’s first Masters of Science in predictive analytics. And while this trend is encouraging,
the fact is that the experience necessary to succeed and lead in analytic positions takes years
of education and practice using real‐life datasets, not to mention understanding of the key
drivers of business. This is supported by the results of a recent (June 2011) poll taken by
When the poll results were examined by geographic region, North America (U.S. and Canada)
In a separate poll, this same community asked its members about the length of their tenure in
analytic positions. A third had eight or more years of experience.
by 2018 “… demand for deep analytical positions in a big data world could exceed the supply
being produced on current trends by 140,000 to 190,000 positions.” Furthermore, they
project “a need for 1.5 million additional managers and analysts in the United States who can
ask the right questions and consume the results of the analysis of big data effectively.”
1).
As
a
member
,
you’ll
get
access
to
special
briefings
on
the
latest
findings
on
customer
experience
research,
free
training
resources,
and
insiders’
insights
into
the
myths
and
mysteries
in
contact
center
technology,
operations,
and
it’s
role
on
the
entire
customer
experience.
2.)
Frequency
only
3
‐
4
times
per
month
.
(We
won’t
bother
you
with
dirt
that
won’t
grow
anything.
This
will
be
the
good
stuff
that
creates
big
blooms).
3.)
We
guard
your
secrets
better
than
the
real
CIA
.
No
double
agents
or
lost
laptops
here;
your
info
is
never
sold
to
anyone.
Only
an
act
of
Congress
will
open
our
vault.
4.)
You
can
unsubscribe
anytime.
Use
the
link
at
the
bottom
of
your
emails
to
go
back
to
being
lonely
citizen.
Chapter
2:
What
is
an
Analyst?
Webster’s Dictionary defines an analyst as follows:
1. Someone who is skilled at analyzing data.
2. An expert who studies financial data (on credit or securities or sales or financial
patterns etc.) and recommends appropriate business actions.
4. One who analyzes; formerly, one skilled in algebraical geometry; now commonly, one
skilled in chemical analysis.
The key point in the definition above is that an analyst analyzes data. In other words, an
analyst conducts mathematical computations on (raw) data, transforming that data into
actionable knowledge, intelligence that can be used to drive the business forward. Many
organizations fail at the very preliminary steps of making data‐driven decisions by mistaking
reporting and dashboarding with data analysis. These activities are quite different, as are the
skill sets required by the individuals performing these activities!
Years ago, I launched and managed a data analytics department for a third party call
monitoring company. As that department proved to be in‐demand and profitable, I quickly
experience in handling and organizing data prepared me well to streamline and increase the
efficiency of the reporting department. So did my penchant for asking questions. Every
report request was followed by a rather similar barrage of questions: “How are you going to
use this report?” “Are you sure we’re not reporting this same data on another report
already?” “How many reports are we producing each day / week / month / quarter for this
client?” “Wow! That’s a lot, is anyone even looking at our reports?”
While the intention behind every reporting request was the right one (to provide clients with
additional insights into their business), the fact is that mere reporting provides numbers,
figures, quantities, not greater understanding. Reporting summarizes and organizes data into
some tabular or visual format. Reporting may alert an audience to a problem, but provides
no means by which to identify root cause(s). Analysts, conducting statistical analysis and/or
data mining, provide insights into the meaning and drivers behind the numbers so that the
right interventions can be introduced at the right times. That is the role of an analyst!
Chapter
3:
Hey
Analyst!
Does
the
CEO
really
want
your
Analytics?
I remember early on in my analytics career walking into a meeting with the management team and
principal of the company, elated that I had just developed a model that explained 40% of the
variation we were seeing in sales conversion (quite a respectable R‐squared value when you
consider we are modeling human behavior). The independent variables for the regression model
were performance figures of agent behaviors that occurred (or failed to occur) during a call center
interaction with a customer.
I had the model formula, the predictive power of the model, a graph of the residuals. I was
stoked!!! My enthusiasm was met with some blank stares, a few ill‐conceived questions, and
considerable lack of enthusiasm. The model, and my recommendations based on the model, went
nowhere, until I found a better way to present the information to my marketing and business‐
That experience quickly taught me how to monetize nearly any argument. I learned that managers
of businesses generally don’t get excited by cool formulas and residuals, and that the quickest way
to find the door is to speak analytic jargon to a room full of marketing types.
The fact is that many executives are not skilled at analytics either. A survey conducted by executive
search firm Christian & Timbers in May of 2002 revealed that 45% of corporate executives rely
more on instinct than on facts and figures in running their business.
Now, they are wrong in their approach (the figure on the following page, taken from a study
conducted by MIT Sloan and IBM Institute for Business Value, certainly suggests that), but you’re
not going to win them over by telling them this.
A top‐notch analyst must know how to do all of the analysis and data mining, but in order for their
work to be put into practice, they must also possess the business acumen needed to explain the
business dynamics which “humanize” the analytics, and be able to speak in the executive’s
language.
They also need to be skilled at the practices associated with influence and persuasion. Just speaking
their language is not enough, unless it is the right language and put in the right context that aligns
with the executive’s business and personal goals.
Conclusion
Business intelligence and call center analytics solutions are projected to experience year‐over‐year
growth for the next several years. The most successful organizations in the future will be those
that are able to leverage their own data to gain insight into customer desires, behaviors, pain
points and experiences, and act on those insights as a means of differentiating themselves from the
competition. These organizations will not falsely assume the marketing hype that technology can
be dummied down so anybody can use it and generate business insight. They will understand that
skilled talent will be their competitive differentiator.
Since there is no reliance on the U.S. education system to produce the needed supply of analysts,
many organizations will be in an unenviable position having a skilled talent demand with no supply.
The early adopters of these solutions are already suffering from this skills gap issue, as the top
performing analysts are hard to find and retain.
Use the insights in this ebook to propel your future.
Resources:
Big Data: The next frontier for innovation, competition and productivity. McKinsey Global Institute,
May 2011. http://www.mckinsey.com/mgi/publications/big_data/index.asp
Analytics: The new path to value. How the smartest organizations are embedding analytics to
transform insights into action. MIT Sloan Management Review and the IBM Institute for Business
Value. Fall 2010.
www.kdnuggets.com/polls
Learn more about the Trends in International Mathematics and Science Study (TIMSS)
http://nces.ed.gov/timss/index.asp
Learn more about the PISA 2009 results http://www.oecd.org/dataoecd/34/60/46619703.pdf
About Customer Relationship Metrics
We make corporate missions and customer
passions happen. Doing more with less means
outsourcing for skilled talent and solutions that is
too risky to build and that diverts from your core
expertise.
Customer Relationship Metrics (CRM) is a provider of Managed Business Intelligence Services founded
in 1993 at Purdue University.
We collect, analyze, and create actionable insights from unstructured conversations, customer
comments, customer experience data, and operational data.
Our SaaS‐based systems, combined with our academic‐level research methods, enable our clients
to uncover otherwise hidden opportunities to improve service, sales, collections, customer
