Business Case and Implications for Consistency – Part 7 – Disparate Treatment of Protected Classes

Previously we explored the business case for consistency both within individual channels and across multiple channels.  In this post, we will explore consistency of treatment in a demographic context.

Inconsistent treatment based on certain demographic characteristics is illegal.  The Civil Rights Act of 1964 prohibits discrimination in almost all privately owned service industries based on race, color, religion, gender, or national origin.  Other industries, such as retail banking, have additional regulatory requirements.

Beyond this legal risk, managers must be aware of the significant risk to the reputation of the brand posed by discriminatory practices.

Managers may seek comfort in the knowledge that their company’s policies and procedures are not to refuse service to anyone.  However, this overt discrimination is just a small part of the risk associated with discrimination.  Beyond overt discrimination, which is extremely rare, there are two other categories of discriminatory practices: disparate impact and disparate treatment.

Disparate impact is the result of policies or business practices which have an unequal impact.  A restaurant with a policy to require prepayment for meals from one demographic group and not another is an example of disparate impact.

Disparate treatment is differences in treatment that originate at the customer-employee interface.  Disparate treatment does not necessarily need to be a conscious act.  It can be an unconscious pattern or practice of different treatment that the employee is not even aware of.  The use of name, offering promotional material to a customer of one group as opposed to a customer on another group are all examples of disparate treatment.

Now, observing differences is treatment is not necessarily proof of discrimination.  Human behavior, after all, is variable.  There is a certain amount of normal variation in all service encounters.  The trick is to determine if disparate treatment observed represents a pattern or practice of discrimination.  Fortunately statistics has the answer, we use statistical tests of significance to determine both if observed differences in treatment are the result of actual discriminatory practices and the likelihood that any one member of a protected class will be treated differently than a member of another protected class.  It should be noted, however, that regulatory agencies set the bar much higher.  Many do not necessarily rely on statistical testing.  In their view, any single case of disparate treatment is evidence of discrimination.

In a future post we will discuss the implications for customer experience researchers in testing for disparate treatment.

Tags: , ,

About Eric Larse

Eric Larse is co-founder of Seattle-based Kinesis CEM, LLC, which helps clients plan and execute their customer experience strategies through the intelligent use of customer satisfaction surveys and mystery shopping, linked with training and incentive programs. Visit Kinesis at: www.kinesis-cem.com

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Google+ photo

You are commenting using your Google+ account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s

%d bloggers like this: