Taking your car to the mechanic. Most of us have engaged in this ritual. Some of us recall the process from many years
ago when the local garage sold you gas and fixed your car. Now, it’s all science and technology.
I bring up the modern car as it is analogous to the modern contact
center in many ways. Look at a car made
in the 60’s. They operated with a handful of simple principles. Engines all operated by the same rules. The gauges on the dash told you the basic
info you needed to know when driving the car.
When something broke, most mechanics could quickly diagnose the problem
from a simple description of what happened when you heard the “clunk”.
Call centers used to be operated in a similar manner. There was a basic ACD that held the calls in
various queues and agents took calls on a FIFO basis. When a queue backed up, agents were shuffled
about until a more optimal distribution of manpower was achieved. Reporting was also pretty simple as the ACD
could provide AHT, AWT and other volume and time-related metrics.
Today’s contact center is like today’s automobile;
everything is monitored and computer controlled. Nothing goes unmeasured or untracked. The “dashboard” in today’s contact center
looks more complex than Mission Control in the early NASA years. Everything has “sensors” that continually
monitor the operation in order to maintain peak performance.
Sadly, all of this instrumentation has one big flaw. Today’s automobiles are no different. When something goes wrong in the contact
center, the bells go off, the alarms ring and lots of screens become populated
with red objects. There are lots of
devices that are telling you that something has gone wrong, where it has gone
wrong and how it is effecting other parts of the organization. What they can’t tell you is “Why” and “How do
I fix it.”
Today, you take your ailing auto to the dealer and they plug
in a computer to the car’s interface and lots of data is dumped out for the
mechanic to review. Rarely can the
computer tell you why something broke.
Sadly, in many cases, the computer fails to be able to tell you what
needs fixing. Its sensors are designed
to capture failure not diagnose cause or suggest corrective measures.
Take a look at your ACD reports. Do they tell you why a statistic has taken a
trip South? Do they tell you that
specific actions will correct the problem?
Are your QM systems, speech analytic systems or customer survey systems
any better or more “intelligent?”
What is lacking to close the loop is a system that can bring
together all the data from these statistical gathering systems along with the
statistics from all the existing knowledge enhancing systems and find
correlations between the data points. In
other words, find any and all causal relationships between the various data
sets.
Such relationships, based on historical data, will highlight
what steps to take to bring about a change in behavior in any monitored
statistic. AHT going up. Take a look at
all the data sets where there is a strong correlation between the AHT statistic
and any other statistic. Here you will
find the answer.
Take the AHT situation for example. AHT is going up. That’s considered bad in most shops. Looking through the correlated statistics,
you find that a specific training module on fully acknowledging the customer in
order to end a call politely has a high correlation with AHT. You also see that statistics related to coaching
sessions appear to also have a high correlation.
About this point you realize that the prescriptive answer to
the problem, statistically speaking, is to have the agent(s) take the training
module and then reinforce the training with targeted coaching.
Now many of you are saying to yourselves that you already know
how to fix these types of problems; that’s where experience becomes valuable. I suggest to you that the “shade tree”
approach has long ago outlived its usefulness.
Today, there is no time to experiment with what you think will
work. The luxury of "trial & error” is
no longer available as virtually every market has become highly competitive and
time sensitive. The need for continual
improvement only works fiscally when the actions being taken are immediately producing
the desired results.
What every contact center needs today is a prescriptive
system that provides an intelligent approach to resolving the alarms. No one needs more alarms today. The modern contact center of today is so
highly instrumented that nothing escapes measurement. What it missing is the piece of technology that
takes in all the inputs from all the instrumentation and can produce actions
plans when things go wrong. That missing
piece of software is not missing any more.
It’s just not yet discovered by enough companies.
Optimizer by Silver Lining Solutions provides the analytic
tools that provide the action plan when things go wrong. Optimizer takes in data sets from all
monitoring system that can export data. Learning systems, coaching systems, ACDs, QM
tools and the like all produce tremendous data sets. Optimizer turns these data sets into useful
information whose value goes far beyond making screens red and triggering alarms. Optimizer provides the answers to the
question of “What steps should I take to fix the problem?” Answers that are based on statistics – not personal
opinion.
It is time to close the gap that all the instrumentation has
created. It is time for a system that
takes in all the existing data sets and uses them to produce timely and
accurate responses to the under-performing parts of the contact center. It is time for Optimizer.
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