Conclusion - Cummins
Conclusion - Cummins
Conclusion - Cummins
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Vicki Pafumi<br />
Reduce Expense<br />
to Sales Ratio<br />
(Branches – Muswellbrook and Emerald)
2<br />
Reduce Expense to Sales Ratio<br />
Project: Reduce Expense to Sales ratio (Branches – Muswellbrook and<br />
Emerald) from 30.3% to 21.4% while maintaining Gross Margin<br />
Belt: Vicki Pafumi<br />
Sponsor: Col Russell & Shane Jones<br />
RDO/ Distributor / Entity: South Pacific<br />
Net Annual Saving: $1,684,967<br />
Days to Close: 160<br />
Project closure date: 21/7/2008 (as on 6S database)<br />
Project closure status: Green<br />
CFSS: No
3<br />
Project Savings –<br />
Financial Model Project Closure
4<br />
Outstanding Aspects of the Project<br />
� The significant improvement in the “Y” variable which equated to $1.7M US.<br />
� The “Y” variable has continued to improve due to an effective and detailed control plan<br />
increasing the savings to $2M US.<br />
� Excellent experience for the two Branch Managers with respect to the involvement in a<br />
6S project and 6S awareness, all the specific training they received and also substantial<br />
financial support to maximise their PBIT.<br />
� When the Labour rate model was produced this was utilised for all locations<br />
� The effective policies and procedures have impacted all of the business.<br />
� The “How To” manual has continued to improve to a stage where all branches<br />
now have an effective Service Manual. This has been developed and implemented by<br />
Ainslie Perkins. Fantastic work.<br />
� The Tool Box Sessions and audits have ensured compliance.<br />
� The review of the ASSW form has ensured all ASSW jobs are authorized and that follow<br />
up on what training and / or support the technician or apprentice should receive.<br />
� The key to this project was the rigorous training of both the Branch Managers<br />
and Service Administrators especially in Emerald where they had all new staff.
5<br />
Project Y variable, as of Dec’08/Jan’09<br />
Since project closure the Y has improved from 15.2% to 12.45%
6<br />
Project Y variable, as of Dec’08/Jan’09<br />
Highlight that<br />
Baseline Cpk<br />
baseline of<br />
-0.173 to Post<br />
Closure value<br />
Cpk of 0.439<br />
I have changed<br />
the LSL to 10 to<br />
reflect the lower<br />
numbers we are<br />
now seeing
7<br />
C&E Break Points & Taking to FMEA<br />
Reality Check of What’s Appropriate to Take to FMEA<br />
� Taking top 5 Process Inputs from C&E<br />
� These are:<br />
– Hours charged to all service work<br />
– Hours allocated on timesheet<br />
– Standard Cost per hour<br />
– Transfer of hours at the end of the job<br />
– Rework on jobs C&E Break Points<br />
600<br />
500<br />
400<br />
300<br />
200<br />
100<br />
0<br />
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17<br />
Series1
8<br />
FMEA – Summary<br />
� Through the FMEA process the key inputs increased to 13 due to<br />
more than one failure mode per input. However, these can be<br />
combined so in fact 4 main inputs will go through to the next process.<br />
– Hours Charged is Labour Utilisation<br />
– Lost Time<br />
– Standard Cost<br />
– Rework
9<br />
Multi-vari Plan
10<br />
Multi-vari Study – X1<br />
<strong>Conclusion</strong> on X1<br />
� Using One way Anova R2 Adjusted denotes that X1 has 38% impact<br />
on your Y variable<br />
� P value < .05 therefore there is variation between two branches<br />
� If we improve variation between locations and improve Emerald<br />
up to Muswellbrook we will have a big impact on our Y
11<br />
Multi-vari Study – X4<br />
ASSW % of COS<br />
Exp % Sales<br />
0.5<br />
0.4<br />
0.3<br />
0.2<br />
0.1<br />
0.0<br />
Fitted Line Plot<br />
Exp % Sales = 0.2607 + 0.6379 ASSW % of COS<br />
0.1<br />
0.2<br />
ASSW % of COS<br />
<strong>Conclusion</strong>: Slope of �tted line =/ zero therefore there is correlation<br />
0.3<br />
0.4<br />
S 0.0936579<br />
R-Sq 35.0%<br />
R-Sq(adj) 29.1%
12<br />
Multi-vari Study – X4<br />
ASSW % of COS<br />
Regression Analysis: Exp % Sales versus ASSW % of COS<br />
The regression equation is<br />
Exp % Sales = 0.2607 + 0.6379 ASSW % of COS<br />
S = 0.0936579 R-Sq = 35.0% R-Sq(adj) = 29.1%<br />
Analysis of Variance<br />
Source DF SS MS F P<br />
Regression 1 0.052041 0.0520409 5.93 0.033<br />
Error 11 0.096490 0.0087718<br />
Total 12 0.148531<br />
Fitted Line: Exp % Sales versus ASSW % of COS<br />
<strong>Conclusion</strong> : Using regression R2 Adjusted denotes that X4 has 29.1%<br />
impact on your Y variable, P Value < .05 significant correlation
13<br />
Schedule of Improvements<br />
1<br />
2<br />
3<br />
4<br />
5<br />
6<br />
7<br />
8<br />
9<br />
10<br />
No.<br />
Release Policies<br />
Improvement<br />
Update Labour Rate<br />
Policy toolbox sessions & Random<br />
Audits<br />
Add estimated job hours to hard card<br />
Review and release of Short Term<br />
Relocation Policy<br />
Review TM’s project<br />
“How To” for Service Administrator<br />
Implement ASSW Correction Form<br />
Audits on ASSW to review<br />
authorisation<br />
Branch Manager Training<br />
Service Administrator Training<br />
AP<br />
BM’s<br />
All / CR<br />
VP<br />
AP / VP /<br />
RC<br />
BM’s<br />
Resp<br />
BM’s / RC<br />
BM’s / VP /<br />
AP<br />
VP / AP /<br />
BM’s /<br />
SA’s<br />
Due Date<br />
30/6/2008<br />
31/4/2008<br />
31/4/2008<br />
4/7/2008<br />
20/6/2008<br />
20/6/2008<br />
5/6/2008<br />
20/6/2008<br />
3/6/2008<br />
30/6/2008<br />
10/6/2008<br />
4/7/2008<br />
Comp Y / N<br />
Y<br />
Y<br />
Y<br />
Y<br />
Y<br />
Y<br />
Y<br />
Y<br />
Y<br />
Y<br />
Y<br />
Y
14<br />
Control Plan<br />
This control plan has given the Branch Managers the effective tools to manage<br />
crucial parts of their business. Four of these items are automatic uploads of data<br />
so are very easy to manage
15<br />
Project Savings –<br />
Financial Model Project Post Closure<br />
Since project closure<br />
the “Y” has continued<br />
to improve to 12.5%<br />
this equates to USD<br />
$1,995,797 savings