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.