Bewährte Six Sigma Tools in der Praxis

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1 Frankfurt School of Finance & Management 2. ProcessLab-Workshop , 8h Bewährte Six Sigma Tools in der Praxis A. Raab BB Certified GE Commercial Finance

2 Agenda Intro Teaser Vortrag Break Out Sessions Pause Vorstellung der Arbeitsergebnisse Zusammenfassung + / 5 min 20 min 30 min 20 min 20 min 0 min 5 min

3 Six Sigma Tools Process Map Analysis Mood s Median Chi-square Test Design of Experiments Normal probability Plot Control Charts Homogeneity of Variance FMEA Mistake Proofing Pareto Chart Change Management Product Report Run Chart T-Test Fisher Exact Box Plot MSA QFD

4 Q x A = E Change Management Entscheidungsträger Analyse Fahrstuhl Rede Beeinflussungs- Strategie Intrinsische Motivation im Team 00 % INVOLVEMENT Rollen und Verantwortung BBs / MBBs Operating Team Define Measure Analyze Improve Control

5 DMAIC: ein iterativer Prozess Define DEFINE MEASURE Control Measure IMPROVE Improve Analyze ANALYZE

6 Project CTQ Identification Define Team Charter Development High Level Process Map definition VoC Team Charter Prozess in Kontext einbetten C O P I S

7 CTQ Characteristics Selection Measure Performance Standards MSA Operationale Definition MSA Process documentation and Analysis

8 W hy aren t Analyze Process Capability Run Chart Product Report Descriptive Statistics 20 Fishbone Pareto Chart Define Performance Objectives USL = 45 days Identify Variation Sources Descriptive Statistics Defect Rate : > 79% % Confidence Interval for Mu % Confidence Interval for Median Availability to Raising Invoice Anderson-Darling Normality Test A-Squared: P-Value: Mean StDev Variance Skewness Kurtosis N Minimum st Quartile Median 3rd Quartile Maximum 62,469 34,665 57,000 4,470 0,000 7, ,593 62,77 2,2693 6, ,000 49,500 62,000 82, ,000 95% Confidence Interval for Mu 80,699 95% Confidence Interval for Sigma 47,739 95% Confidence Interval for Median 66,544 Pareto Chart Count Percent Team internally T oo little Too m any tributary knowledge about assignments (Statistic ) other arear s A pp le/ IT S 2 Te chno logy C us tom er C om m u nica tion / Residuals not No Transparency of T ran sp are nc y co rres po nd ing (file other Portfolios vs. pm s) Tim e consum ing W e a re so lely E ot Backlog (Tem ps / W ork ) negotiations with rea c tin g: C ustom er doesn t Da ta ba se 4 c u stom e rs 5 react voluntarily C u sto m e r L 0 calls us, not after receiving the Le as in g PMS problems when Backlog +dayly job w e th e offe r co m pre he n sion of b oo kin g on tim e? custom er 4 the custom er T e ch nic al Status 2N Custom er doesn t devices understand leasing C C C o m p u ne t insufficient staffing 5 (E xp la n ation ne ed ) no Asset Plus 2 Report Files are poorly m an ag e d frag m en ted Priority EoT Booking Inc orre ct pro ce ss es 4 in Transaction D ata in P M S M an a ge m en t EoT takes over work of other Departem ents Se arc h in g fo r V alu ation s pro ce ss (Le ga l, R eg is tra tion F ile s incom plete PM S Internal Problem s of Assets Certificates for Cars ) 3 D ata (o the r D ep artm e nts) elab ora te "S tra ig h ten ou t" M iss in g ha nd lin g m istakes of memo s in file Invoices allegedly oth ers 2 Sales people aren t received by C om p un et influence the Policy Structure Operations 2 Process a nd file e xis ting arre ars on accounts m anagement In voic e- a nd Templates in general No Asset Mnt S yst em 3 Various IT System s touch transaction several times Request for offer com es 8 m ths. be fore E ot (too ea rly ) W hy aren t contracts dealt w ith in due tim e of E ot an d promptly booked on the System? A B C D E F G Defect H other Departements Data Situation Processing Process Count Percent Cum % 56 72,7 72,7 6 7,8 80,5 5 6,5 87,0 3 3,9 90,9 2 2,6 93,5,3 94,8,3 96, 3 3,9 00,0

9 Potential Cause Screening Improve Discover Relationship Betw. Variables Establish operating Tolerances Mood s Median Homogeneity of Variance Regression Chi-square X Variable Description Significant? Test P-Value Comments Appendix

10 MSA on X s Control Chart Control Plan FMEA Take Away Individual Value I and MR Chart for Lease Termin by timing Control Process Capability Percent 3,0SL=9, X=-7,883-3,0SL=-24,95 Process Control Implementation Normal Probability Plot for Lease Termin By status -00 Tar get 0 Data Subgroup Moving Range ,0SL=20,97 R=6,48-3,0SL=0,00E+00

11 Break Out Activity Haben Sie ein Lieblings-Tool? 2. Welches Tool haben Sie wo und mit welchem Erfolg eingesetzt? 3. Tools, die Sie noch nie verwendet haben?

12 Agenda Intro Teaser Vortrag Break Out Sessions Pause Vorstellung der Arbeitsergebnisse Zusammenfassung + / 5 min 20 min 30 min 20 min 20 min 0 min 5 min

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