consolidation of analysis and improvement actions for mhe

7/26/2019 Consolidation of Analysis and Improvement Actions for MHE

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I. Executive summary


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II. Comparison of accuracy based on dates

Table 1.Comparison of achieved accuracy rating using processing date1and

verication date2

1 processing date date when the orders were processed by SPi


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Order 1:100 no! of error " weight##

Order 1:100 2 " 2!$##

100 %!&

Order 1:$'!2

Case 1: one error type

(2) Contact Name

Order 1:100 no! of error " weight##

Order 1:100 1 " 2!$##(2"0!)%####

100 2!$(1!*#

Order 1:$%!&

Case 2: error type

(1) Contact Name and

(2) !ales C"annel

+he ob,ective of this simp-e study is to see what wou-d be the achieved

accuracy if the orders wi-- be grouped base on their processing date instead

of when the orders were veried or inspected by ./!

n addition the team wou-d a-so -i3e to see if 4agged errors by ./ is

accurate-y accounted base on the date when the orders were processed! +his

is in the assumption that there might be orders that were veried -ate and

the 4agged errors were a-ready addressed on previous wee3s#! Shown in Table 1 the di5erences of the accuracy rating between the two

dates is not signicant as we on-y recorded an average of 0!0' points! +he

di5erence was caused as ./ veries the order -es 162 days after SPi

processed the orders!

7ased on the given document records whether the team use the processing

date or verication date of ./ a-- 4agged errors are accounted proper-y! 8o

encountered error re-ating to the assumption made on previous-y bu--et!

III. #ccuracya! 9ccuracy computation

Current-y the team is fo--owing the ./ way of accuracy computation!

To get the accuracy rating per order:

To get the overall accuracy rating per order:

2 verication date date when the orders were inspected and veried by ./


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ust average the accuracy of order

Order 1: $'!2Order 2: $%!&Order *: 100Order ': 100

Order %: 100

Overa-- 9ccuracy: $&

t is worth to mention that ./ way of accuracy computation is more -enient

compared to the acceptab-e way of accuracy computation where:

b! ;ee3-y trending

$i%ure 1.;ee3-y: rror and 9ccuracy +rending!

9ccuracy < 100 =no! of error"weight##

Overa-- 9ccuracy < 10061"2!$##(1"2!$##(

Overa-- 9ccuracy:


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+he data are provided by ./! SPi down-oaded the inspected and veried

orders in ./ >ua-ity system on a wee3-y basis to chec3 the achieved overa--

and per agent accuracy for the wee3!

SPi a-so veries the inspection resu-ts on a wee3-y basis and provides the

verication resu-ts to ./! SPi?s focuses in the va-idity of 4agged errors

based on the provided instructions updates and standard operating

procedures! @econci-e the discrepancy on the data and accuracy rating if

4agged errors found inva-id!

Since ./ started the -ive production -ast September SPi a-ready processedan approAimate-y B000 orders!

7ased on the provided data there were %0'% B2# processed orders were

inspected and veried by ./ and out of which *2) )# are found with

errors!

t is worth to note that the team managed to -essen the errors wee36on6wee3

as they ac>uire -earning curve this yie-ds to BB error count reduction!

/owever the error count reduction doesn?t in4uence the overa-- accuracy to

improve as each error has its own c-assied weight according to critica-ity!o ./ provided the -ist of error opportunities in an order!

o t consist of ') error types! ach error type has its own weight based

on critica-ity!o +he weight ranges from D!*2E being the -owest to D*!%%E being the

highest!o f an agent processed an average of 20 orders per day -et?s say this is

e>uiva-ent to 100 orders per wee3! Table 2suggests how many error

counts# are a--owed for the agent not to get an accuracy -ower than

$$!$B!


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Table 2.Simp-e Simu-ation: a--owab-e error count per weight if

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.et or eAceeded the thresho-d @e-eased from ./ G9 inspection

c! 9ccuracy +rending per 9gent

Table &.;ee36on6wee3 9gents 9ccuracy

Hespite that SPi recorded a be-ow par overa-- accuracy rating! n agent -eve-

performance shown in Table & there are % agents that a-ready hitting the

accuracy of $$!$B and 100!

t is a-so worth to mention that these agents a-so re-eased from rigorous ./

>ua-ity inspection! On-y those processed orders tagged with ho-d are the one

wi-- undergo ./ inspection! +his wi-- give them a great chance of achieving

a consistent higher accuracy rating that wou-d a-so re4ect to the overa--

performance of SPi!

t is high-y suggested to continuous-y coach and mentor the two remaining

agents aime and ohn for them to be re-eased in ./ stringent inspections!

d! Overa-- +op contributor

Table '.+op +en rror covering ;FB to present#


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Shown in Table ' is the top 10 error contributors! t is worth to mention that

the error re-ating to ncorrectI8o /o-d 9pp-ied which is consistent-y topped

since wee3 one has been Jero out for two consecutive wee3s a-ready!

On the other side errors re-ating to 9ttachments payment terms and re>uest

date has doub-ed their digits since it was -ast ac>uired! +hese errors was resu-ted due to inattention to detai-s! +he agents missed to

verify and va-idate the needed information in order forms and ./ systems!

K! Comparison of interna- GC vs ./ GCa! 8umber of orders GC?d by SPi and 8umber of orders GC?d by ./b! ;hat are the di5erence

i! Hiscrepancy on chased errorii! /igh-ight the wea3nesses of SPi GC

c! @eso-utions

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