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Why the excitement over self-service? The answer appears simple enough: if
customers can solve their own problems and never call the help desk, the
call volume will decrease. Since the cost of a Web-based service transaction
is significantly lower than engaging a human agent, the reduction in call
volume translates into immediate savings.
The reduction in call volume means lower workload and
burnout, resulting in less stressed agents that provide better service.
Moreover, because agents take fewer calls, they are now free to take more
revenue-generating calls.
But to the surprise of many, these logical expectations
often turn into disappointments and even utter failures. The same
supportindustry.com study indicates that a mere 50% of the call centers that
implemented self-service have experienced reduction in call volume.
Forrester Research reports that only 36% of organizations noticed a
reduction in call volume, and 17% have actually measured an unexpected
increase in call volume.
Call volume is not the only performance metric that
self-help did not improve as promised. Research shows that other key
indicators, including average speed of answer, resolution time and first
contact resolution rate did not appear to improve, and in some instances
have actually worsened.
What Happened?
Let's begin by examining the holy grail of self-help: call volume. Self-help
proponents maintain that instead of calling the help desk, customers can
find the answers to their questions on the Web, thereby "deflecting" calls
away from the call center.
So why did the call volume not decline? There is the
obvious answer: customers couldn't find the answer to their question on the
Web and ended up talking to a live agent after all, often irate and needing
more attention following their frustrating Web experience. But if this were
the only reason, then identifying the missing information and expanding the
content of the self-help facility should be an easy task. However, careful
examination of the detailed operation of a call center reveals additional
challenges in reducing call volume by "deflecting" calls.
Capacity
Most call centers are not staffed to answer 100 percent of customer
requests. Instead, they plan for a certain percentage of abandoned calls –
after waiting on hold for a support agent to respond to the call, some
callers will inevitably hang up. In other words, in a typical call center,
the demand for service always exceeds capacity, so as the self-help facility
eliminates some calls, the available capacity is filled immediately by this
demand.
Call Distribution
A subtle, yet profound reason for the minute effect self-help has on call
volume stems from the impact of self-help on call distribution. In a typical
call center environment, agents handle a mixture of call types: some are
very simple and are answered almost instantaneously because the agent can
convey the information to the caller succinctly and quickly. Other calls are
more complex and take longer to resolve because they require research, may
need more than one conversation with the customer, and sometimes are
escalated to a higher support level. The distribution of call handling times
is not uniform: the number of simple and short calls is typically much
greater than the number of complex, time-consuming calls. In fact, most of
the calls are actually much shorter than the average call length, and there
are few calls that take significantly longer than the average call.
Web-based self-help facilities focus on the frequent
simpler and shorter calls, which customers can easily research and resolve,
but its impact on the very long calls is minimal. Once the majority of these
short calls is eliminated, the overall call volume may decline, but the
relative portion of complex calls increases, and things start to go wrong.
Most call centers are structured in tiers, with Tier One
clearing the larger volume of the easier and shorter calls and escalating
the more complex calls to Tier Two. With the new call distribution, there
are fewer calls that Tier One can solve and the percentage of calls that
require escalation increases. Service level reports will show degradation in
resolution rates, an increase in the percentage of escalated calls, and
lower utilization because of lower call volume handled by Tier One. Overall,
the performance of Tier One following the implementation of self-help will
appear worse, and the additional capacity creating by "deflecting" calls
will be greatly underutilized.
Can Self-Help Help?
This is not to say that self-help can never help. Self-help can provide
valuable help to customers who need information that can be delivered
effectively using self-help technologies, such as providing order
fulfillment status or answering frequently asked questions. One notable
example is Pitney Bowes, where a self-service system to answer questions
concerning postage rates increase reduced the volume of calls to live agents
by 50% relative to the previous rate increase.
Providing technical assistance such as problem
troubleshooting using self-help tools is more challenging. Simple
troubleshooting information of simple devices, such as small printers, and
frequently asked technical questions are reasonable applications, but when
the task requires technical knowledge and accuracy, and the risk of a user
error is too high, self-help may not be the recommended approach.
The Opportunity
Whether a company's objective is to reduce the load in the labor-intensive
call center or to streamline sales interactions with customers, such as
product configurations or order status, the goal of self-service technology
remains the same: to leverage available knowledge resources and improve
quality of service while reducing costs through efficiency.
Almost every discussion about the benefits of
self-service lures the reader to rosy payback predictions based on the high
cost of a call handled by a live agent versus the very low cost of providing
the same service via the Web. However, an ongoing study of call costs by
Diagnostic Strategies demonstrates that this data is highly ambiguous and
cannot be used as a reliable method to estimate savings.
Self-help cannot focus on cost-cutting alone. We must remember that the more
the customer has to do, the less the service organization does, an attitude
that may quickly and unnoticeably lead to poor service. Self-service and
good service can become an oxymoron, especially when the primary focus is on
cost reduction.
Users perceive the value of the self-help facility based
on several, often conflicting aspects, which include ease of access, the
quality and the relevance of the information it provides, and the timeliness
of updates. The following steps will help you devise an approach to
implementing a self-help facility.
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Determine the Need and the Opportunity. There
must be a clear and recognized need that self-help can address. Not all
customer issues are best addresses by self-help, nor are all user
communities good candidates for this approach. The need, the opportunity,
and the willingness and ability of users to solve their own issues should
be defined and quantified and weighed against the risks before any
significant investment in the project is made.
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Define the Value. Oddly enough, many
organizations are strong believers in the "if you build it they will come"
philosophy. Self-service must have a clear value not only to the
implementing organization but also to its intended audience. The value can
have different facets, tangible and intangible, tactical and strategic,
but without establishing the value and maintaining it throughout the life
of the service, the chances of creating a long-term success are greatly
diminished.
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More isn't Better.A view taken by many
organizations is that more information is better, essentially drowning
customers with large amounts of often irrelevant data. Information
provided to users must be easy to navigate and find, and the answers easy
to understand. Customers who call in having spent time sifting through
useless information are much less forgiving than those who quickly realize
that the information they are looking for is not available and are given
an easy way to contact the call center.
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Select Appropriate Technology.Many
organizations fail because they base their self-help strategy on
technology that they have already selected. There are numerous
technologies that can be harnessed to support customers, ranging from Web
portals to well-organized quality documentation to complex decision
support system using artificial intelligence technologies. The choice of
appropriate technology is an involved task, especially when it requires
mapping customer requirements to technical features and involves the
benchmarking and comparison of disparate technologies.
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Make Sure They Come Back.Just when you thought
that the technical challenges are over, you realize that the next hurdle
may be even higher. In most service organizations, technical support
knowledge is never complete and is ever evolving. As the initial
excitement following a successful implementation subsides and the
development team finds new opportunities to pursue, the self-service
knowledge base often remains unattended. As the content is not
continuously updated with new product and support information, its
efficacy deteriorates, leading to value attrition and eventually to user
defection.
About The Author
Joe Barkai is the founder and principal of Diagnostic Strategies, a
management and technology consulting practice specializing in Service
Lifecycle Management (SLM), diagnostic knowledge management, service
process optimization, and advanced diagnostic solutions. Joe brings over
15 years of consulting experience to Fortune and Global 1000 companies in
the US, Canada, France, Germany, Finland, Italy and Israel, that include
John Deere, DaimlerChrysler, General Dynamics, Lucent Technologies, IBM
and the US Army and Navy. His business consulting practice covers service
business strategy, service process reengineering, and implementing support
automation technologies, diagnostic expert systems and advanced diagnostic
and prognostics methods.
About The Company
Diagnostic Strategies is an innovative research, advisory and consulting
firm focusing on service lifecycle (SLM) practices and technologies.
Diagnostic Strategies works with Fortune 1000 companies on service
business process and strategy development and implementing advanced
solutions that include self-service, expert systems, remote diagnostics
and prognostics in their service operations.
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