E-Mail Account                                  OptimizationProject Leader:   Michael Madl, Systems EngineerStart Date:   ...
Six Sigma in Action                                                                                                       ...
Upcoming SlideShare
Loading in …5
×

E Mail Optimization Six Sigma Case Study

251 views

Published on

Lean Six Sigma Group Free Project Case Study Overviews http://www.linkedin.com/groups/Lean-Six-Sigma-37987
Sponsored by the International Standard for Lean Six Sigma, e-Zsigma http://www.e-zsigma.com, IQPC, and PEX Network.

Please contact Lean Six Sigma Master Black Belt, Steven Bonacorsi, Owner of the Lean Six Sigma Group to have your project case studies to be added to the Lean Six Sigma Group Library. Steve Bonacorsi sbonacorsi@comcast.net

0 Comments
0 Likes
Statistics
Notes
  • Be the first to comment

  • Be the first to like this

No Downloads
Views
Total views
251
On SlideShare
0
From Embeds
0
Number of Embeds
3
Actions
Shares
0
Downloads
1
Comments
0
Likes
0
Embeds 0
No embeds

No notes for slide

E Mail Optimization Six Sigma Case Study

  1. 1. E-Mail Account OptimizationProject Leader: Michael Madl, Systems EngineerStart Date: March 2002 Master Black Belt: Steven Bonacorsi
  2. 2. Six Sigma in Action E-Mail Account OptimizationCustomer Profile – 1400 seat financial service companyBusiness Problem & Impact P ro ccee s sCC a pa bility Anas is is rfo r ta l taa y sa y s P ro s s a pa bility Ana ly ly s fo To To D l D Process Capability – BeforeE-mail accounts residing on the client’s production servers US L L USwhich their email vendor charges on a per accountS basis.sDDaThe0 U UL L S P roroe e s P c cs a ta ta 55 .00 0 0 .0 0 0 ST LTclient was incurring charges from their e-mail vendor for 1160 **** T aTa rgte t rg e LSL L LSunused accounts, resulting in charges of $3,480 pernmmonth.1.6 334411 Me a a n Me S a m p lele N Sa p N 11 .6 1 82 82 S tDtDv (S T ) S e e v (S T) 00 .3 61 1 8 .3 6 1 1 8Measure & Analyze S tDtDv (L(L ) S e e v T T) 66 .6 62 1 7 .6 6 2 1 7Data Collection: After a one time cleanup of the 1160tia(S(S T)CCaappaabbility** P o te tetia l l T ) Po n n Cp p C ilityaccounts, the data still showed the average time toP Ueliminate .1 2*2* C C PU C PL L CP -6 .1 -6the e-mail account for exiting employees was 11.6 pCkp km C Cpm days Cp -6 .1 2 -6 .1 2 * * -10 -1 0 00 10 1 0 20 20 30 30Root Causes: Variation in the processes used to eliminate P ro c e s s C a p a b ility exptente dlyesP e rfofo ea nTeo taxp eDtea eLcTsPde L Trmearfo e a A c a S is n c r c E l c xp y te rfo P n c rm O veve ra ll (L T) C a p a bility O ra ll (L T ) C a p a b ility O b ssee rve dPP e rfo rm n c ec e O b rve d e rfo rm a a n E xp c e d S T P Trfo rm a rm E E daccounts, a web form which client managers foundP pto be too ** Pp P P M < LL S L PPM < SL Process Capability – After * * P PP P M < L S L M < LS L * * P P M P P S L< L S L < LM * PPU U PP -0 .3 3 -0 .3 3 P P M > U SS L PPM > U L 9 3 9 0 2 4 .3 9 9 9 3 9 0 2 4 .3 P PP P M > L S L1 0 0 1 0 0 0 .0 0 0 .0 0 M > USU 0 00 0 P P M P P M L U S8 4 0 3 2 8 4 0 3 2 > US > L 4 .7 0complex, vendor case processing time and reworkPPloops Dwithin P L P ro c e s s a ta PL * * P P M Too ta l P P M T ta l 9 3 9 0 2 4 .3 9 9 9 3 9 0 2 4 .3 P PP P M ta l ta l 1 0 0 1 0 0 0 .0 0 0 .0 0 M To T o 0 00 0 UP PL P Pta l T o ta l8 4 0 3 2 8 4 0 3 2 S M To M 4 .7 0 P p kp k P -0 .3 3 -0 .3 3HR-owned process steps were contributing to longrgcycle times USL Ta e t 5 .0 0 0 0 0 * LSL *Improve & Control - Streamlined process from 12 to 7 Me a n S a m p le N 3 .4 2 1 0 5 19steps. Created one centralized DB to minimize errors and S tD e v (S T ) S tD e v (L T ) 0 .3 9 4 0 1 1 0 .7 7 9 2 7 6delays in data transfers. Worked with the vendor to create anew web interface resulting in a reduced cycle time nfor vendor P o te tia l (S T ) C a p a b ility Cp * CPU 1 .3 4steps to one day. Improved average time to 3.4 days from 11.6 CPL * Cpk 1 .3 4Results/Benefits - Annualized savings realized by the Cpm * 1 2 3 4 5 6client to date are $42K, and additional savings may ra ll (L T ) C a p a b ility O ve exist O b s e rve d P e rfo rm a n c e E xp e c te d S T P e rfo rm a n c e E xp e c te d L T P e rfo rm a n cbased on the future employee exit rate Pp PPU 0 .6 8 * PPM < LSL PPM > USL * 0 .0 0 PPM < LSL PPM > USL 3 0 .7 0 * PPM < LSL PPM > USL 2 1 3 7 3 .6 PPL * P P M T o ta l 0 .0 0 P P M T o ta l 3 0 .7 0 P P M T o ta l 2 1 3 7 3 .6 Ppk 0 .6 8 Annual savings to the client of US$42K

×