Leveraging Voice of the Customer Data to Focus Six Sigma

Date 2/27/17

ASQ Lean & Six Sigma Conference– Session M21 – February 27th 2017

Objectives

1. Understand the importance of the Voice of the Customer to business performance.

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• Leverage the Voice of the Customer into practical applications for operational excellence.

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• Program Management as input to project deck prioritization activities.

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• Project execution. Leverage VOC as a dataset into the project to drive key learnings.

A universe of conversations……….

Some myths…..

-I don’t need to worry about social media, I don’t make consumer products.

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-I don’t need to worry about social media, it’s the fringe customers who post on those platforms.

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-My customers don’t pay attention to Social Media.

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-My product is not really that bad.

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-Those people are just complainers

2008: Brian Solis

Psychology of Complaints

Helpscout.net

Kano Model

Kano Model.com

There’s Data, then there's Analytics

Data is content

Analytics is the discovery and communication of meaningful patterns in data. It relies on the simultaneous application of statistics, programming, and operation knowledge to quantify performance.

Context is the Key

The process of VOC Mining

Data Visualization Technique

Putting it all together

Products returned for a refund are the same products that customers call about

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COMPLAINTS

VOC

Putting VOC to work in the Project

Once you have selected the project, use of the Voice Of the Customer is not over.

Defining �the problem

The ‘Closure’ incident type reported in the call center has been almost doubling year over year. This incident type signifies any issue with opening or closing and represents the total number of calls received for that year.

Correlating VOC data

VoC Analysis

Most frequently mentioned keywords in 1 & 2 star reviews are ‘time’, ‘code’, ‘keypad’, ‘work’, combination’, ‘lock’. Negative reviews support other findings from call data.

Detailed Analysis of Findings (Consumer Experience Survey)

Detailed Analysis of Findings (Cycle Test Continued)

Detailed Analysis of Findings (Cycle Test)

Design Of Experiments Results

Results

Updated Total Call Volume as of 2010 – March 2015

Results

Updated Total Closure Through – March 2015

Improvement Made

Note: The failure rate dropped from 2.3% to 0.18% from January 2014 to in January of 2015.

2015 Estimated Cost Savings

The battery corrective action was implemented in October of 2014. There was a 55% drop in warranty from Q3 to Q4 due to the CI work ($176,000). The estimated 2015 yearly savings will come in at $352,800.

Questions?

James R. Wells– Phone: (865) 410-0727– Email: qualityinpractice@gmail.com