We encourage you to leave us comments and feedback.

Looking forward to seeing you all on our new blog site!

Thank you,

Ric Kosiba

In this graph, we are holding everything constant, and only varying shrinkage (the same sort of graph that we saw with service level versus profit).  In this case we hold all constant but shrink, and track the profitability of the sales center.  Again we find a profit-maximization point!

This is a textbook, marginal profit curve.  What we produce is a change in profitability by agent, meaning, if I hire one more person, how much will they sell, and what will they cost?  If your goal was a 60% service level, you would be leaving revenue on the table.  If your goal was 90%, you would be paying too much in agent costs relative to the revenue being produced.  If you wanted to run the center as if it were a business, you would run a service level between 75% and 85%, in order to maximize profits.

There is a lot that goes into these graphs (and thank goodness I have CenterBridge to produce this one), but the concept is pretty straightforward.  If the marginal value per call changes, these graphs shift substantially.  I’ve got a few stories about the use of these in the real world, and I’ll try and post these soon.

About the last graph (pictured above):  I think CenterBridge is still the only place in the whole workforce management space where abandons are forecasted and determined, as a function of the resource plan.  In other words- we can figure out the marginal abandon rate: “if I hire one more person, how many fewer abandons would we have?”

THAT is very powerful, big picture stuff.

For each contact type this graph will be very different- it depends on the customer patience of each type of caller.

This graph serves as a starting point to some very cool analyses.  By knowing the expected abandon rate, you also can derive the expected revenue!  You can get a very good picture of the number of customers you’ve ticked off (they hung up on you!).  And you can get closer to the mother lode, for revenue centers: the relationship between staffing and profit (we’ll discuss that one soon).

This graph is instructive in drawing out the trade-off for service centers- it helps answer the question “what does one percent increase in service level cost me?”

If you are an outsourcer, this graph will help you price new business opportunities.  If you are a customer service function, this graph helps determine an implied value of each call.

One other note: if you use an Erlang equation to develop this graph, it will be wildly off.

Service Level versus Occupancy is one of the most confused pieces of analyses that we see.  It represents the ironclad relationship between the amount of time an agent will spend working a contact, compared to the time he will spend waiting for a contact to arrive.

Clearly, if you want the phone answered more quickly, then there needs to be more agents potentially available to pounce on the call.  Hence, as service level increases, then the amount of time- on average- that an agent spends waiting for the next call also increases, and occupancy decreases.  Simple, yes?

And so you get a graph that looks like the one above.

Note one thing:  the relationship between service level and occupancy will be different for each contact center- customer patience and economies of scale play into these graphs a lot, and those vary by contact type.

Now the dangerous part.   For the call center described above, an 80% service level results in a 68% occupancy. That is ironclad; it is an unbreakable law of math.  But what it doesn’t mean is that agents who work an 8 hour day have 32% of their time available to do other things!  It means that there may be a 30 or so seconds between calls, before the next one comes in.  It also doesn’t mean you can get rid of 32% of the workforce.

Speaking of Caroline, I took her on a business trip to Utah (where her cousins live), How cool was that!

While she was excited to go on a trip, I think I was more so.  My kid brother lives in a beautiful spot in Park City, Utah, and works for a very cool company, with a very impressive job. I am horribly proud of him.

I stretched the trip (which was an excellent meeting) into the weekend and did a couple snowy things with Carrie and my nieces.  I really should do more of that!

Yesterday, we ran a simple basketball drill.  The girls paired off, faced each other and shuffled side to side while passing a ball to each other.  Sure enough, Carrie missed the pass and got hit in the nose.  That hurts.

But what do you do as dad/coach?  If it was my son, I would growl at him and say “Shake it off”.  But my little girl?

I did just that.

But while I was ignoring Carrie, two other girls on our team got bumped in the nose and started crying.  We ended the drill as too dangerous.

A long time ago, I was presenting an ROI for a project I was working on.  While presenting, we showed an honest to goodness, conservative improvement to the operation of 7 million dollars.  The client told me that since the system (not CenterBridge) took 12 minutes to calculate the optimal answer (which only was a small part of the analyst’s time in the system), they were considering turning the system off.

Dan Mahon says I have business Tourette’s.  My response to this person was “How much is your time worth?”

Would it be perfect that the optimizer returned a response in 5 seconds? Yes. Is it pretty darned good that it saves the company 7 million dollars a year even though the algorithms solved in 12 minutes? Of course it is. Don’t make good the enemy of perfect.