© 2014 Copyright ISC Ltd. Driving out waste by revealing hidden data
Nov 01, 2014
© 2014 Copyright ISC Ltd.
Driving out waste by revealing hidden data
Property Repairs: the problem
© 2014 Copyright ISC Ltd.
C/Sat84
%
RFT 93%
Recalls 7%
Variat-ions 40%
RFT 71%
???
The As Is process
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64 process steps
Process walk-through
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We needed data (in 6 weeks)
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Right First Time (e.g. fault repairs)
Complaints (e.g. formal and informal)
Timeliness (e.g. faults fixed when promised)
Customer Satisfaction (e.g. perception)
Objective customer feedback (e.g. delays, RFT, changed appointments)
Input volumes (e.g. fault calls, failure demand)
Costs (e.g. value of jobs)
Processing times (e.g. call handling)
Delay times (e.g. approval times)
Process Measures:
OutputMeasures:
Satisfaction Measures:
Data collection approach
Existing data CRM system
BUT: few existing reports met our needs
Customer Survey BUT: not very current, or
specific enough Contractor SLA Reports
BUT: questions over definitions
Complaints/Quality Audits BUT: snapshots, few trends
New data CRM system
Case tracking (times) Case categorisation
Customer Interviews Using current cases
Contractor Log Daily record of cases
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CRM data quality challenges Over 5% of the data we
extracted for this review had “issues”.
It doesn’t sound a great deal, but it meant that two of the main reports we produced could not be used without extensive manipulation in Excel every time we ran them.
Examples: Repair types incorrectly flagged Properties incorrectly flagged Fields not filled in – not necessarily
critical to operations, but critical to analysis
Free text in surveys and questionnaires
Text Case – inconsistent case use: Upper / Lower
Use of Excel when CRM could/should have been used
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Once we had cleaned the data…
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The voice of the customer…
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43% felt they
were not kept
informed
58% of orders had up to 3 interactions.25% involved 6 or more interactions.28% of customers called after their order was placed.
4100 calls logged &
categorised over 6 weeks
75% completedat first visit
Some conclusions…It was clear from the data used to manage the Repairs process prior to
this project that the organisation was relatively “immature” in its approach to performance management and continuous improvement. There were too few trend graphs which would enable managers to see whether or
not performance was improving (monthly snapshots seemed to be preferred) There was no data routinely available to track some of the important process
response times; in some instances because fields within CRM were not being used Root cause analysis of some problems was impossible because they were
reported in categories such as “Other” or “No reason given” Data quality issues had not been recognised and their impact on the organisation’s
ability to drive improvement had not been understood
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Some benefits…
Staff loved using the CRM system to improve the way they logged customer contacts because it meant they could give a better service
Managers had better data to hold staff and contractors accountable for performance
Some very simple Quick Wins leading to 30% reduction in “Failure Demand” in 3 months
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Presented by Ian Seath at the Operational Research Society’s 2014 Conference (OR56)
© 2014 Copyright ISC Ltd.
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