Six Sigma in the call centre - CallCenter PROFI

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call centrewhere services with regard to differentcriteria are measured. One of theproblems, Call Centre Managers face,is the task of fixing the quality andperformance of the entire Call Centreon the basis of single measurements(spot tests). This problem typicallyapplies with quality checks from customercalls which do only allow alimited number of spot tests. In othersectors, the amount of spot checks isequal to the number of incidents. Or,statistically spoken, the amount ofspot checks is equal to the size of theso called ‘‘target population.” ModernACD facilities have the pleasant featureof linking together a big amountof data with some basic statistics. Thequestion of a limited amount of spottests does not arise anymore becauseevery single call will be checked accordingto its basic parameters. Witha certain periodicity (for instance halfan hour, one hour, shift, day, week ormonth), average values will be calculatedwhich serve to the performanceand control of the operating units.With view to this, the Call CentreManagement faces the problem thatsome of the true facts might be keptsecret because of the profane measurementof average values. Six Sigmaprovides answers to these difficulties.It is a business concept – or more precisea business culture which reachesthe highest level of customer satisfaction,likewise to the maximizationof profitability. The fundament isbased on the use of statistic knowledgeand a process-oriented way ofthinking.What is Six Sigma‘s contribution toContact Centres? It is innumerable. Inthis essay, we will examine the qualityof statements which refer to differentamounts of spot checks.Big spot test amountsaverage and varianceThe Six Sigma process of improvementor change starts from five basicprocess steps:n Define – this is the phase of definitionwhich categorizes a problem ordescribes a product or a service interms of its performance parameters.In this phase, major importance is ascribedto the customer expectation.n Measure the phase of measuringproduct parameters or services. InDistribution of Abandon RatesFrequencyAverage ValueSigma = 4%the Call Centre, for instance the quantifiedcall capacity, waiting time, callingtime or also the spot test datacontrol is measured.n Analysis – analysis and evaluationof performance data. Facts like average,standard deviation, variance,correlation, data types and theamount of spot checks play a majorrole.n Improve – the changeover to theunemotional evaluation of data to arather creative design and the followupof implementing solutions.n Control – What needs to be done tokeep processes stable, identify thedeviation from given values and interpretthem the right way? Whicharrangements are available for corrections?This step will ensure thechange of existing or the implementationof new processes (which oftenhave been hard to achieve!), comparedto old, rather expensive routines.It is reasonable to call this superiorSix Sigma process the DMAICprocess.Usual ACD facilities normally providea very comfortable range of raw datawith some basic linkages. Normally,average values will be provided forthe single call parameters. Uncommonly,they would also include selectedinformation about the standarddeviation and variance of basicSix Sigma SectorSigma = 12%USL0% 2% 4% 6% 8% 10% 12% 14% 16% 18% 20% 22% 24% 26% 28% 30% 32% 34%The diagram shows two possible ways of distribution for the frequencyof abandon rates, with two different standard deviations (Sigma = 4%, orSigma = 12%) from a middle-point (8%). The smaller the standard deviationis, the more frequent the measured values center around an averagevalue.data. But it is also essential to receivea statement about the variance(standard aviation) of single key values.Usually, for quality features like abandonrates, arrangements are madebetween the customer and the ContactCentre. Low abandon rates areexpensive because a superproportionatenumber of employees has tobalance statistic variations within thecall capacity. If higher abandon ratesare accepted, the call capacity couldbe handled with number of employeeswhich is significantly lower.The customer typically asks for amaximum average abandon ratewhich should not be exceeded. Veryoften, this is the only specificationfixed. Nobody has settled the question,how the average abandon ratehas been composed. Phases with highabandon rates can be compensatedwith phases of low abandon rates.Presuming that such a phase lasts forseveral days, it could be totally inacceptablefor customers – even if themonthly average figures which havebeen arranged for, have been reached.From the entrepreneurial side, it canbe very expensive if the abandon rateist significantly lower. Usually, abandonrates are influentual factorswithin the pricing. They need to bechecked constantly because with val-01/2007www.callcenter-international.eu 25
call centreues which are better than the agreedvalues, a superproportionate numberof employees had to be appointed.Thus, it is recommended not to reducethe specification of a certainservice to an average value, but alsodefine limits together with the customerwhich are not allowed to beexceeded or fall below. This is exactlywhere Six Sigma starts and describesthe USL (Upper Specification Limit)and the LSL (Lower SpecificationLimit) as limits to be fixed around anaverage value, precisely defining theallowed statistic variations. The nameSix Sigma origins from the fact thatthe (nearly) perfect product service orthe (nearly) perfect product on theUpper and Lower Level SpecificationLimit (USL and LSL) is defined withan interval of six standard deviations(= Six Sigma) from the average value.If values are measured beyond specificationlimits, it is called a “defect”.Statisticians know that, with a probability(standard probability) of tenmillion “ events”, defects that are beyondthe Six Sigma limits (USL andLSL), will show a frequency of 34. Inour example, this means that “SixSigma Performance” will be reachedthe moment, ten million abandonedrates are measured without exceedingthe specification for more than 34times. In which way would this approachmake sense in practice? Doyou have to measure ten millionabandon rates in order to be able tomake a statistic statement?AuthorNael El Sayed,Managing Director,asdirekt, Germany.nael.elsayed@asdirekt.deCall Failure Rate12,00%10,00%8,00%6,00%4,00%2,00%0,00%1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30Abandon rates: Importantindicator for the qualityThe previous diagram points up thisdiscussion and can be a starting pointfor the practical discussion:The diagram shows two possibleways of distribution for abandon ratefrequencies, with two different standarddeviations (Sigma = four percentrespectively Sigma = 12 percent) froma midpoint (eight percent). The smallerthe standard aviation is, the morefrequent are the measured avaragevalues which circle ‘‘around a midpoint”.Before measuring abondonrates according to Six Sigma conformity,we will have to check threefacts with the customer:n How will an abandon rate bemeasured as an event? A time intervalcan be chosen, e.g. like measuringthe abandon rate every half hour. Butit is far better to measure the abandonrates in intervals, e.g. every 100oder 200 calls. The result (the averageabandon rate out of 100 or 200calls) is equal to the frequency of one.Throughout constant measurementsyou will receive a population of measuredresults which can be used forfurther data collection.n Which average value does the customerexpect? For the sake of clarity,it is of major importance in whichtime intervals the average values willbe measured. Most typically, averagevalues are measured in a monthlyrhythm.n Which kind of standard deviationaccording to Sigma and which vari-pp_barL_confU_confp= call failure rate from the amount of spot checksp_bar, the current average value of the amount of spot checks,L_conf and U_conf, the lower or upper confidence intervalIt is plain to see that in a long-term period of time, the confidence interval isshrinking and as such helps to get a clear statement about the real call failurerate.ance is acceptable for the customer?Which standard deviation can be calculatedwithin a normal distribution(see chart)?n The definition of an acceptablestandard deviation will automaticallydefine the Six Sigma sector, which isthe sector between the average valueand the USL. The blue distributioncurve in the above shown diagramassumes to have a standard deviationof four percent. Therefore, the SixSigma sector ends with abandonrates beyond 32 percent (averagevalue of the abandon rate of eightpercent plus six times standard aviationof the abandon rate of four percent).In practice, it is recommendableto rather measure standard deviationsconstantly instead of measuringten million abandon rates (thiscould take years), according to theapproach of calculating an acceptablenumber of ‘‘n” measures. Throughthis, you will reach a decent estimationof ‘‘Six Sigma Performance.”The situation is very well-known: Youhave a meeting with a customer andlisten to discussions between CallCentre Agents and customers. Out often calls, one well be totally inacceptablewhich the customer will im-26 wwww.callcenter-international.eu01/2007
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Six Sigma in the call centre - CallCenter PROFI

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