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By on Jun 20, 2014 in Featured | 0 comments

Callback Options Callback technology is a fascinating topic. At one point in time if you wanted to do Callbacks you either programmed your own middleware or purchased a pricey third party product. These days, most contact center solutions include Callback functionality. Often there is little or no extra cost and the functionality can be turned on or off at will.   Callback Examples Back in late 1999 I had the opportunity to study the network level call details of Net Zero’s NBA advertising campaigns during the quarter time and half time intermissions of national play-off games. One of my recommendations at that time was to handle the spikes with call-backs. It worked great. Callbacks can be a useful tool to respond to brief intense advertising spikes.   Mis-Use of Callbacks However, Callbacks are frequently mis-used and relied upon for all the wrong reasons. Try calling the Air Canada call center. Callbacks are always-on and wait times are always over an hour. It’s a great example of using Callbacks instead of good decision making – with persistently terrible results.   Root Causes of Poor Callback Strategies Much of the blame falls on the heavily-marketed, under-performing WFM solutions. These products mislead customers into thinking their forecasts are reliable. They are not reliable, not accurate, not even close. Technically speaking, they are not even forecasts – though that’s what everyone still calls them. The high forecast accuracy reported by WFM solutions is entirely fake. That’s not a criticism of one product. It’s a factual statement about how every vendor manipulates data to present falsified metrics. Most planners don’t realize that this is happening — even though it’s been going on for 30 years.   Ilustrating Callback Strategy Errors So let’s say you have the right number of staff (which most call centers do). But you have the grave mis-fortune of having those staff timed improperly (which many call centers do thanks to WFM). As your day progresses, the queue gets larger and larger. Each interval has to deal not only with the calls that arrive, they also have to deal with the misfortune of every new call lining up behind lots of callers that did not get serviced in the prior intervals....

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By on Apr 12, 2013 in Uncategorized | 0 comments

There are many differences between Wisdom WFO and all other planning systems on the market.  Many of the differences can be summarized quickly in three words: Wait times matter. Planners are often conflicted about the extent that wait times matter.  On the surface, it is obvious that having to wait too long does matter to customers and will have a detrimental impact on business and growth.  However, for decades, WFM vendors and call center planning schools have steadfastly insisted wait times should not matter to planners when formulating a forecast. If you want to understand the benefits of HD forecasting, you need to un-learn some of the wrongs that the industry has imposed on the planning profession. When a call center’s business grows, very often the first signal is increases in wait times.  How can competing vendors respond to those wait times? Well, they all use the classic forecasting method that relies on average talk time and expected call count as the exclusive historical inputs. When limited to these two inputs, the forecast gives no consideration whatsoever to historical wait times. So how to the competitors respond to increasing wait times.  Not at all, because the forecast has no idea what the wait times were.  That means no adaptation to growth and no relief for the customers that may be driven away by increasing wait times. The subject of wait time is really worth understanding in detail. Interval based forecasts and high definition forecasts have a completely different approach to wait times. High definition forecasts intricately respond to the exact wait time experienced by each and every customer.  If you business grows, your HD forecasts responds by shifting resources to precisely support a return to prompt service. Interval based forecasts ignore wait times completely.  Really!  The wait times are completely ignored. And vendors for the most part think its normal and acceptable to do so. This takes us to a widely published mis-interpretation of Erlang’s thoughtful teachings.  The call center schools the vendors of software that use the classic method will routinely explain their positions on wait times by attributing the following statement to Agner Erlang:  “Wait times are not an input to the forecast, they are just an...

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By on Apr 12, 2013 in Uncategorized | 0 comments

So your WFM software uses an ancient forecast method that ignores critical information like wait times.   In fact, it only considers total calls and average call length. That’s not much to go on so you get vague forecasts and big problems. What confuses many people is that these crude forecasts appear 98% accurate.  In reality, every interval of the forecast is usually off by 30% or more. Your software just shuffles the cards to create the illusion of forecast accuracy.  It’s an easy trick when wait times don’t matter. Here’s how it works. You lay down money for WFM software hoping for accurate forecasts. Let’s say the forecast for 9:00 – 9:15 tomorrow is 300 calls offered. As it turns out 400 customers actually call.  That’s 33% over forecast.  It’s a problem for you but not for your WFM software. It scheduled only enough agents to answer 300 calls. So the switch reports close to 300 answered calls. With the typical 2% abandon rate only 6 or fewer callers will abandon before 9:15. The WFM software quietly ignores the real offered call data from the switch.  Instead, it adds-up the answered and abandoned calls and Presto – 98% forecast accuracy.  A third of the callers had to wait until later in the day. But your software says wait times don’t matter. The forecast always looks like it comes true no matter how long your customers wait and no matter how many customers actually call. With the illusion of forecast accuracy, your WFM software wins but everyone else looses including the angry customers, stressed out agents and the entire company (because a third of the wait times were unreasonable high).  Most of the unreasonable wait times don’t even show up in the service levels because the longest wait times don’t matter — at least not when calculating service levels. Wisdom WFO doesn’t play tricks. It uses modern High Definition planning. HD planning evaluates every bit of historical information that is available to a modern call center.  That includes over six characteristics of every call, including wait time. So when you receive 400 calls, over 2400 attributes of those calls are analyzed towards calculating the perfect number of agents to schedule. ...

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By on Apr 12, 2013 in Uncategorized | 0 comments

The balance of the WFM industry seems not to care to much any more about forecasting.  That’s unfortunate because a forecast is the foundation for the schedule and everything else that happens afterward.  With flawed forecast everything that remains in the planning and delivery cycle is doomed to be sub standard. To most of the industry, the a WFM product line and the planning cycles are represented with diagrams like this: Coincidentally, the diagram is a suitable representation of the tread mill that most organizations find themselves in.  The WFM solution creates the forecast.  It’s a thread-bare forecast that only anticipates mediocre activity.  The schedule includes only enough agents to answer the forecasted calls.  Strict adherence ensures that agents log in and out on the 15 minute mark.  This guarantees that the answered call count will mirror the offered call forecast.  Ignore all the callers who continue waiting past the 15 minute mark and you r forecast accuracy will equal “one minus the abandons rate”.  Typically this creates the illusion of 98% forecast accuracy.  The forecast looks accurate thanks to the manufactured call counts.  Those call counts feed the next forecast and nothing ever changes.  The forecast is always right. The forecast never changes or improves. Wait times increase to the point that customers flee to your competitors.  A shrinking customer base validates that the forecast never needed to change. This way of doing business is what we refer to as operating in the GREY ERA. The original inventor of forecasting was Agner Erlang. He operated in a BRONZE ERA. He had to make due with historical data that was limited to call counts form an odometer.  He knew that those call counts were a capacity based metric.  The switch would never count more calls than the switch was capable of handling. The switch never knew how long customers had waited for service.  It was for this reason that he insisted that call counts were only reliable if the planner had good reason to believe that wait times were negligible and well within the expectation of all callers.  Erlang died long before more detailed information became available from switches.  So while he never knew what the wait times were,...

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