The Ends of Your Economies
Ric Kosiba
Vice President and Founder of the Bay Bridge Decisions Group at Interactive Intelligence
An Interesting Perspective
We were installing Interaction Decisions™ at a high-tech firm with an analytically focused management team. Their network of contact centers answered somewhere around one to two million calls a week! They directed us to do a bit of extra analysis trying to determine whether to consolidate their centers and their staff groups. They wanted to know how much money they would save.
I was very surprised to find that this organization did not need to route calls amongst many of its centers, even though each center handled the very same types of calls as the next. When asked by my friend, why this was the case, the answer was obvious- “we’re out of our economies.”
“We’re out of our economies” is not something that you hear very often in the contact center industry. Currently, most of the contact center companies are in the process of consolidating centers for the expressed purpose of getting more efficient by gaining economies of scale. Many companies are de-specializing; either through consolidating skills based routing or creating the universal agent. It makes sense, who wouldn’t want to get more efficient?
The question that immediately comes to mind is, of course, what are the ends of your economies of scale and at what point do you lose your economies?
Contact Centers and Economies of Scale
Let’s start out by stating the obvious: there are many other areas that economies of scale, or dis-economies of scale are present, other than just staffing efficiency. We’ll discuss this later but let’s start out by analyzing the staffing efficiencies.
Economies of scale are a natural occurring phenomenon in most production operations. You see it in manufacturing or any other process that has a high fixed startup cost. In an economic definition of economies of scale, the high cost of startup is defrayed on a per unit basis by producing more of the goods.
The same economics work in the contact center world, with an added twist. But there are economies of scale associated with the operation in and of itself. All other things being equal, having more agents on the phone increases the probability of an agent being available when a call randomly comes in. With predictable randomness of contact inter-arrivals as the number of agents increase the number of calls each agent can handle also increases. But this is applicable only to a point. At what point do we keep growing a center?
The graph below shows the very common phenomenon of economies of scale at a contact center. As the call volumes increase, the minimum number of staff required to hit a predetermined service standard also increases, and linearly so. The following graph was created using a discrete-event simulation model of a contact center and a service standard of 80 percent answered within 20 seconds. Your requirements will likely look different from these as the simulation model has assumed customer patience assumptions built in resulting in abandoned calls.
Note: because the Erlang equation assumes no abandons, and every contact center is exactly the same using an Erlang equation will always yield the same (slightly off) curve. The following graph demonstrates the classic economies of scale curve.
What is more interesting, however, is the relationship between call volume and calls handled per agent. This truly represents the added efficiency associated using larger contact volumes and centers.
The following graph represents, for the very same contact center network, the relationship between call volume per week and calls handled per week per minimum staff required. That’s a mouthful. In non-math-math, I divide the agents required to hit my service goals by the number of calls handled. This tells you how productive each agent is over the course of the week.
The curve is interesting because it readily demonstrates the natural point where a contact center group is at maximum capacity. In this example, with an average handle time of around 400 seconds, you run out of natural economies at 50,000 calls per week, or roughly 150 rear-ends-in-seats. I would have expected the number to be higher. And it is, sort of because there are other forces at play which we’ll discuss below.
The next graph demonstrates the very same relationship for contact center networks with a range in handle times between 360 seconds and 600 seconds. What is great to see is that each of these curves follows the classic economies of scale shape.
What is different for each of the graphs is the point at which the economies are played out. Surprisingly the economies play out earlier for centers with higher handle times. I would have expected the opposite result.
In each graph, I have highlighted the approximate point at which the economies of scale vanish noted by the bigger data point in each line. To the right of each point you do not gain much efficiency by growing centers. To the left of each point you still gain by growing or consolidating your contact centers.
Again for each curves, it is surprising how small the centers are before they run out of economies of scale.
Finally, I plot the individual points at where the economies run out for each handle time modeled. Interesting graph!
This graph simply demonstrates the point at which your economies of scale are spent. For example, if your contact center has a 500 second average handle time, you’d be roughly as operationally efficient if you have one center of 540 FTE or if you have two disconnected centers of 270 FTE each. That seems very counterintuitive!
But I am sure it is correct. These graphs represent the ends of our operational efficiency. It is all straightforward math, and the graphs are what the graphs show. No drylabbing necessary but I have one caveat; we have not added financials to the mix or discussed the other areas of economies of scale associated with our businesses. When determining economies of scale from a financial perspective you might see different results.
There are many areas where you get economies of scale associated with consolidating operations: facilities costs, transportation costs, telecom costs, training costs, etc. Often there are dis-economies of scale as well. It may be harder and more costly to be a larger employer in one location compared to a midsized employer in several locations. The cost of risk associated with regional emergencies (i.e. hurricanes) is much greater with a fewer locations compared to decentralized facilities.
All that being said, I am a big, fan of universal agents. Creating skills is often an exercise in busy work- adding complexities that do not have to be present. Many times agents are specialized because it sounds good often to marketing groups which complicates routing and management. The ends of your economies should not be a reason to specialize unnecessarily.
Are you ready for the punch line? Because we had spent the time to put together an accurate discrete-event model for this company using Decisions, this entire economy of scale analysis took less than a half hour to put together.
What are the ends of your economies?
Ric Kosiba, Ph.D. is vice president of Interactive Intelligence’s Decisions Group. He can be reached at Ric.Kosiba@InIn.com, (410) 224-9883 or Twitter: ric@decisionstech