The Data Fluent Culture - Data Fluency: Empowering Your Organization with Effective Data Communication - page 149

what can youR metRic measuRe? a shift to pRoactivity
Collecting customer service metrics is a challenge for many organizations.
Consider a call center supporting hospitals across the country for education
and training. With the stated organizational goal of becoming customer-
centric, the call center has a short telephonic survey after every “ticket,”
representing an issue or challenge needing recovery. Collecting data from
in-bound calls after each ticket is resolved seems like a great way to measure
customer service. However, it doesn't tell the whole story. Achieving high
recovery rates might show the skill level of the call center employees (the
client representatives or success managers); however, if the vision is to
create a client-centric company, the data collected might be a sample of
convenience. With better engagement the incoming calls might have never
come in!
Progressive call centers often implement a policy where success managers
call out to clients to see how they are doing without an issue needing
resolution. Another strategy employed by some organizations is the
embedding of high-skilled engineers or other technical skilled persons in
the call center so that more complex in-bound issues can be resolved in real
time rather than being referred to another team for handling at a later time.
Measuring “customer engagement” as the scores realized on recovery tickets
as opposed to engagement of customers regardless of recovery tickets
would result in very different conversations between your organization and
perspective clients.
uNDERSTANDING THE PuRPOSE AND MOTIVATION FOR
DATA PRODuCTS
The endpoint for data sources is, of course, the data products presented to a
target audience. Establishing a shared understanding for data products also
requires building credibility and transparency for the consumer. Essentially,
people want to know why the data is shown and what they are expected to
learn from the data. Cynically, data consumers may wonder whether there is an
ulterior motive to how the data is presented. They want to trust the asserted
results. A more open-minded person might simply want to know what the
organization hopes to achieve through the data product.
For example, we have worked with several services companies who need to
deliver periodic reports to their large corporate clients. In many cases, these
reports are unproductive because the presenter struggles to articulate the