Time Series Analysis英文版).ppt

TimeSeriesAnalysis 2020 4 20 O Network Path Filename ppt 2 BenefitsandUsesofTimeSeries BenefitsoftimeseriesMonitorsalesperformanceovertime removevariationinmonthlysalescausedbycalendardifferencesandseasonalitythatcanconcealpotentialproblemswithsalesAccuratelydeterminethedirectionandrateofgrowth declineinsalesQuicklyidentifychangesinsalestrendsandcorrelatethemtofactorsaffectingsales industry company competitionImprovedecisionmakingregardingsalesandmarketingactionsUsesoftimeseriesAssesscurrentsalesperformanceandevaluatetheeffectivenessofsalesprogramsDetermineunderlyingsalestrendandprojectyearendsalesEstablishappropriatebudgetsfornextyearandestimatemonthlybudgetspreads TimeseriesanalysisistheprimarysalesanalysistechniqueatA B 2020 4 20 O Network Path Filename ppt 3 TimeSeriesAnalysis WhatisTimeSeriesAnalysis HowareTimeSeriesplotsdeveloped WhataretheadvantagesofTimeSeriesAnalysis WhatareTimeSeriesusedfor 2020 4 20 O Network Path Filename ppt 4 WhatisTimeSeriesAnalysis Timeseriesanalysisisastatisticaltechniqueusedtoanalyzeandmonitorsalesvolumeovertime 2020 4 20 O Network Path Filename ppt 5 WhyTimeSeries BeersalesarehighlyseasonalItisverydifficulttoevaluatemonthlysalesovertime 2020 4 20 O Network Path Filename ppt 6 Howdotimeserieswork MonthlyvariationinsalesiscausedbytwomajorfactorsSeasonalitySellingDays calendareffects TimeSeriestechniquestatisticallyremovestheeffectsofthesetwofactorsTimeSeriestechniqueusestheX 11procedureforseasonaladjustmentsTheX 11procedurewasdevelopedbytheU S BureauofCensusinthe1950 s ItwasbroughttoA Bintheearly1960 sandhasbecomethestandardforreportingsales 2020 4 20 O Network Path Filename ppt 7 Howdotimeseriesadjustsales AsellingdayadjustmentfactorforeachmonthiscomputedandappliedtotherawsalesThisfactorallowsyoutocomparemonthsasiftheyhadthesamenumberofsellingdays e g accuratelycomparetheJunethisyearvs JunelastyearAseasonalfactoriscomputedandappliedtothesellingdayadjustedsalesThisfactor whenapplied givesyoumonthlydatadirectlycomparabletoanyothermonth e g accuratelycompareJunethisyearwithMaythisyear 2020 4 20 O Network Path Filename ppt 8 SellingDays Allotherthingsbeingequal salesinAug 03woulddecrease4 8 becauseofonelesssellingday InordertocomparethetwomonthsAug 03saleswillhavetobeadjustedup 4 8 2020 4 20 O Network Path Filename ppt 9 Seasonality Seasonalityisexpressedasanindexforamonthcomparedtoanaveragemonth Amonthwheresaleswere20 higherthanaveragewouldhaveaseasonalfactorof120 Amonthwhichwas10 lowerthanaveragewouldhaveaseasonalfactorof90 StrongSeasonality NoSeasonality 2020 4 20 O Network Path Filename ppt 10 AdjustingSales 2020 4 20 O Network Path Filename ppt 11 Howdotimeserieswork RawSales SellingDayAdjusted SeasonallyAdjusted 2020 4 20 O Network Path Filename ppt 12 DissectingaTimeSeriesPlot AnnualizedSales tellsushowbigthemarketis TrendLine tellsusthedirectionofsalesbasedonpast presentperformance Irregularvariations showsustheimpactofmarketplaceactions STR s OntarioSTC s DataDescription tellsusthetypeofdataplotted 2020 4 20 O Network Path Filename ppt 13 AdvantagesofTimeSeries Advantagesoftimeseries RemovesvariationinmonthlysalescausedbycalendardifferencesandseasonalityHelpustoaccuratelyestimatethedirectionandrateofsalesgrowth declineTheyareanimprovementoverothermethodssuchasyear over yeargrowthormovingaveragesbecausetheyshowuswhatishappeningsooner anearlywarningofchangingsalesconditionsTimeseriessignificantlyimprovedecisionmaking AllowsustotakecorrectiveactionsoonerAllowsustotaketherightcorrectiveactionHelpstoestablishappropriatesalesobjectives 2020 4 20 O Network Path Filename ppt 14 AdvantagesofTimeSeries Ifthetimeseriesshowsarelativesmoothpatternfromoneyeartothenext thetrendandtheyearoveryeargrowthwouldprovideroughlythesamereading But iftherewasasignificantmarketeventorchange theyearoveryeartrendswillbemisleading 50 2020 4 20 O Network Path Filename ppt 15 MisleadingGrowthRates 0 21 2020 4 20 O Network Path Filename ppt 16 MoreMisleadingGrowthRates 21 15 2020 4 20 O Network Path Filename ppt 17 Whataretimeseriesusedfor AtA Bweusetimeseriesto AssesscurrentsalesperformanceDevelopcurrentyearsalesprojections PYE projectedyear end Forecastnextyearsales developbudgetsandmonthlyspreadsOtherquantitativesalesanalysis 2020 4 20 O Network Path Filename ppt 18 AssessingSalesPerformance HowisourYTDperformance 2020 4 20 O Network Path Filename ppt 19 AssessingSalesPerformance 2020 4 20 O Network Path Filename ppt 20 EstimatingPYE Ifthereisnochangeinthebusinessenvironmentsaleswillcontinueoncurrenttrend Pointsoffthetrendlinecanbeusedtoestimatemonthlysales UnderlyingTrend Predicted 2020 4 20 O Network Path Filename ppt 21 UnderlyingTrend Underlyingtrendisatrendlinethatbestdescribesthecurrentsalesgrowthrate Itisthecollectiverepresentationofallunderlyingfactorsthatareinfluencingsales industry competition andcompanyspecific etc Itisdeterminedusingabest fitlinetoasetofpointsonthetimeseries Thepointsareselectedbasedonin depthunderstandingoftheunderlyingfactorsinfluencingsales howtheyhavechangedovertime andhowtheywilllikelychangeinthefuture Pointsofinflectiononthetimeseriesoftensignalchangesintheunderlyingfactorsandhencetheunderlyingtrend 2020 4 20 O Network Path Filename ppt 22 EstimatingPYE Predicted ActualSales Predicted SeasonallyAdj Sales SellingDayFactorXSeasonalFactor MonthlySales 2020 4 20 O Network Path Filename ppt 23 EstablishingBudgetsandSpreads GivenourYTDSep 2003performancewhatwouldbeanappropriatebudgetfornextyearandhowshouldthatvolumebespreadbymonth 2020 4 20 O Network Path Filename ppt 24 EstablishingBudgetsandSpreads 2020 4 20 O Network Path Filename ppt 25 AnotherExampleUsingTimeSeries AnnualizedSTR sinMBBLS 1998 1999 2000 2001 2002 2003 ElasticityCalculationP1 18 99 P2 20 45i e 7 V1 44 5 V2 38 5i e 14 Elasticity 2 0 Estimatingthepriceelasticity Price P1Volume V1 Price P2Volume V2 2020 4 20 O Network Path Filename ppt 26 Conclusions TimeSeriestechniqueisaveryusefulsalesanalysistool itisthestandardforreportingandanalyzingsalesatA BItisapowerfuldecisionmakingtoolforassessingsalesperformance makingaccurateforecasts andestablishingappropriatebudgetsandspreads 2020 4 20 O Network Path Filename ppt 27 TimeSeri