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DATA DISCONNECT
DATA SYSTEMS ARE NOT SUITED FOR ENGAGEMENT
Executive Summary
Reliance solely on data and systems of record to manage customer interactions is an
approach that has severe limitations. The primary reason for this is that such an
approach only considers historical information contained in the system of record
from completed transactions; it does not consider real-time events, data that has not
yet been entered into the system of record, or other sources of data—all of which
play an important role in customer service. In addition, systems of record are ill-
equipped to manage back-office staff because they can only base decisions on data
contained in their own system, ignoring tasks that are managed elsewhere that are
out of view. For these reasons, companies need to pursue omnichannel engagement
strategies that leverage systems of record with systems of engagement.
TABLE OF CONTENTS
Executive Summary.................. 1
Overview.................................. 2
The Role of Data....................... 2
Impact of Data on Service
Delivery.................................... 4
The Data Disconnect ................ 4
Omnichannel Engagement....... 6
Conclusions .............................. 9
About Genesys ......................... 9
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Overview
Apart from skill and training, the most important thing all great craftsmen do to
achieve outstanding results is simple:
Use the right tool for the job!
That same rule applies to service delivery. When the right process is enabled with the
right tools, great things happen. When the wrong tools are used, things go sideways
resulting in frustrated customers, overworked customer service staff, and declining
profit margins. Why does this happen? Why do companies fail to use the right tools
for the job? More importantly, what does a properly enabled service delivery process
look like, and how can it be achieved?
The Role of Data
Computers made their debut in the mid-twentieth century to consolidate various
tasks and centralize data. Early systems relied on large, expensive mainframe
computers for critical applications and bulk data processing. In the 1990s, companies
found that systems based on microcomputer designs were more flexible and could
be deployed at a fraction of the acquisition price of mainframe systems. Over time,
companies have increased their focus and reliance on data, forcing mainframe and
microcomputer systems to find a way to co-exist. Large-scale, batch processing and
core systems are mostly run on mainframes, while real-time transactions are handled
by microcomputers.
The common thread on both systems is data. Data is collected and analyzed to create
information suitable for making decisions. Broadly speaking, companies rely on three
basic types of data management systems:
• Core: the reference term varies slightly from one industry or company to the
next, but the reference here is meant to focus on those primary systems that
contain and manage anything that represents proof of existence. For
example, financial services companies use CORE (Centralized Online Real-
time Exchange) systems for things like customer data management,
processing payments and calculating interest. These are usually seen as the
system of record that is the authoritative data source for a given data element
or piece of information.
• CRM: Customer Relationship Management is both an approach to managing
customer interactions and the underlying systems that integrate and
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automate sales, marketing, and customer support. There are three main
components to CRM systems: salesforce automation for all stages of the sales
cycle; marketing automation for understanding and influencing customer
behavior; and service automation for customer service needs. These are
usually seen as the source of context for a given customer or interaction.
• BPM: Although Business Process Management initially focused on the
automation of business processes with the use of information technology, it
has since been extended to integrate human-driven processes in which
human interaction takes place in series or parallel with the use of technology.
For example, workflow management systems can assign individual steps
requiring deploying human intuition or judgment to relevant humans and
other tasks in a workflow to a relevant automated system. These are usually
seen as workflow management tools in an operation.
Most companies have some form of all three systems working together to manage
service delivery. A financial services company would store account information in the
Core system, manage offers and promotions with CRM, and process a mortgage
application with BPM.
On its own, data and data management systems have very real limits in the service
delivery process. In fact, it’s useful only if it’s:
• there, in the data system(s)
• accessible, not hidden in an unlinked system or silo, or blocked by other
processes in progress
• correct, current and complete
Some companies have attempted to rely on a single system of record to perform
routing of tasks and customers to agents under the assumption that a single source
of data has everything necessary to
do the job.
But what happens when it’s not?
What happens when key information
has not been captured by the data
systems? When the data system(s)
stop short, the customer becomes
the glue holding everything together.
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Impact of Data on Service Delivery
Within the organization, there are two ways to view the impact of data on service
delivery:
• Front Office: broadly speaking, this refers to the revenue-generating side of
the house, and includes activities that directly interact with customers. Key
measures consider the amount of effort customers need to put forward to
gain access, and effectiveness of systems and staff to respond as reflected in
customer satisfaction evaluations like Net Promoter Score.
• Back Office: broadly speaking, this refers to the cost-generating side of the
house and includes manufacturing and administrative tasks not seen by
customers. Key measures are designed to assess employee productivity and
process efficiency.
Customer sales and service lives across a spectrum, with self-service at one end, and
assisted service at the other. For most situations, customers will gravitate toward self-
service for most of their needs. People like to feel they have control over a situation,
like to see all of the available options, and like to see the results happen right in front
of their very own eyes. This may have started with the rise of ATMs and e-commerce,
but eventually found its way to build it yourself furniture, check-in kiosks at the
airport, and self-check stands at the grocery store. Much of the contribution data has
on service delivery happens in self-service.
But there are times when self-service is not working, not intuitively designed, or the
complexity of the situation exceeds the capabilities of self-service. When that
happens, people need help from a live agent via phone, video, email or chat. Here,
it’s critical to leverage the data used in self-service to find the right resource and
educate them on what needs to happen next. Having systems in place to truly
understand how and why a situation crosses the threshold from self to assisted
service is critical for process improvement.
The Data Disconnect
Information is managed by systems of record. Interactions are managed by systems
of engagement. They are two completely different things, working together to
produce a desirable outcome. The disconnect with data can easily be understood by
considering the difference between information and interactions:
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• Information is data that is (1) accurate and timely, (2) specific and organized
for a purpose, (3) presented within a context that gives it meaning and
relevance, and (4) can lead to an increase in understanding and decrease in
uncertainty.
• Interactions involve reciprocal action, effect, or influence.
A customer service interaction (phone call, web visit, e-mail, chat session) relies on
an exchange of information (data) to resolve a problem. That seems pretty clear.
Where many companies run into a challenge is when they attempt to use systems
of record to perform the work that should be handled by systems of engagement.
This can be observed in two ways:
• Customer access to the front office suffers because the only data used to
identify the customer and the problem is that information that has already
been stored in a core or CRM system. Information that does not exist (wasn’t
completed, hasn’t been batch-processed) cannot be used; information that is
not accessible (in process, in a different location, user lacks permission to
access) also cannot be used; information that is inaccurate (mistakes made
by the customer or employees) will lead things astray. Real-time events
(multiple calls within a short period of time, escalations, events happening on
multiple interaction channels) are not considered at all.
• Productivity in the back office is sub-optimal because data systems are
focused on the process, not on the resource. While they may be good at
determining what, why and how something needs to be done, they are not
good at determining who should do it, and where and when that should
happen. They lack visibility to the broader context of what someone will be
doing throughout the entire workday.
As a result, many studies on the service delivery process find that customers are
frustrated by: the need for multiple attempts to resolve a problem; the amount of
time needed to resolve a problem is longer than it should be; the need to repeat
information. Is there a way to deliver consistent, repeatable, and desirable service
and control the cost?
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Omnichannel Engagement
Companies rely on effective service to maintain and grow the relationships they have
with customers, measured by revenue. Simultaneously, companies rely on efficient
service to optimize resource utilization, measure by cost. Omnichannel engagement
is designed to orchestrate the journey customers take when they go in search of a
solution to produce optimal outcomes for everyone involved in the journey.
Historically, customers searching for solutions took what can be described as a single-
threaded approach. If they had a question about a bill, they called customer service.
It was up to the customer to identify who they were, and explain the problem to the
person on the other end. Even when new channels like email were introduced the
process remained largely the same: identify who you are, outline the problem.
As technology advanced, it became possible to leverage data in a limited way identify
the customer, prompt the customer to categorize their need, access account
information, and pass the collective set of data along to the representative in
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customer service. However, success relied heavily on the customer to reveal their
identity and problem.
Further advances in technology made it possible to deliver multiple interactions from
the same customer to a single agent: the customer could send an email and
subsequently call customer service, and have the email and phone call delivered to
the same agent at the same time. But each of these advances in technology failed to
overcome the ongoing challenge: they all rely on the customer to identify and state
their need.
Omnichannel engagement was designed to overcome this historical conundrum by
leveraging customer data that exists in a system of record along with information
collected in real-time by the system of engagement. This combination makes it
possible to have a multi-threaded interaction, one that considers real-time and
historical information, in order to provide the context needed to dynamically change
the path presented to the customer and resolve the issue in the best possible way.
Here are some omnichannel examples:
• The customer of an insurance company files a claim. The claim is initiated and
adjudicated in the claims management system. The customer profile, wallet
share, and cross-sell opportunities are managed in the CRM system. Both of
these are systems of record. When the customer calls to speak to the claims
rep, claim and interaction history are used to identify the appropriate
representative and route the customer and claim. This is done by the system
of engagement. If the customer sent a fax outlining the estimate for repairs
immediately prior to the call, the system of engagement would be the
platform that would have awareness, collect the fax, and deliver along with
the call and claim to the claims rep as it would not have been in the system
long enough to get processed into the claims management system.
• A prospect visits the company’s website to make a purchase, and places an
item in the shopping cart. On checkout the customer enters shipping and
credit card information. When the information is submitted for processing, it
produces an error. The customer opts to call customer service. Because the
purchase form contained a field for customer phone number that matches
the caller ID, the customer’s identity and failed purchase are matched and
delivered to an agent who greets the caller with, “It looks like you were in the
process of making a purchase online and ran into some difficulty. Would you
like me to help you complete that purchase?” Because the order was not
initially processed, the customer and order do not yet exist in any systems of
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record. However, the system of engagement can leverage cached real-time
information to assist in completing the transaction.
• A patient has just been discharged from the hospital. When they arrive home,
complications from the hospital visit arise. The patient calls the nurse advice
line for assistance. The system of engagement is able to consult with multiple
systems of record to determine that a recent discharge happened even
though it has not yet been processed into the main patient information
database.
In each of these examples, the data did not exist in the system of record. Absent that,
it would be up to the customer to identify the problem to the person helping in the
front office. But the system of engagement has the ability to consult historical data,
real-time data, and interaction history to make informed routing decisions and
present relevant information.
Similar challenges are happening in the back office:
• Insurance claims are assigned to reps based on the total number of claims in
their work bin. No consideration is made for whether the claim is in ‘pending’
status waiting for the claimant or estimator to take action. It is therefore
possible for a claims rep to have many claims assigned, but no real work. The
system of record knows where the claim is in the process, but has no visibility
to other tasks the representative may be assigned that exist outside of the
claims management system such as training, meetings, and breaks. The
system of engagement has visibility to all tasks and status for a given
representative.
• An agent at the processing center could have many orders to fill. But if those
orders are incomplete (e.g., lack shipping information), are not sorted by
product or warehouse location, or prioritized by value, the clerk will waste
time filling the order. The order management system of record knows about
order backlog, but has no visibility to other activities the clerk may be
responsible for that exist outside of the order management system.
• The hospital may process discharges into the system of record on a nightly
basis, but until they are processed they don’t exist. The system of
engagement can access real-time events like recent discharges and use the
information regardless of whether it has been processed into the system of
record.
In each of these examples, the inherent limits of the system of record created
impediments to service delivery, and made it impossible to perform accurate
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resource planning. By leveraging the system of engagement to identify true task
requirements based on the sum of historical and real-time events, routing and
staffing decisions can be optimized.
Conclusions
When the right process is enabled with the right tools, great things happen. Service
delivery requires systems of record to manage data, and systems of engagement to
manage interactions. Systems of record on their own cannot route customers to the
right resource and achieve optimal levels of productivity because they lack real-time
context. That can only happen when paired with systems of engagement. That is why
omnichannel engagement is the only way companies can achieve low-effort customer
service and high levels of employee and system utilization.
About Genesys
Genesys is driven by our cause to save the world from bad customer service. We do
it by applying a relentless focus on the consumer perspective of the customer
experience — and the impact it has on your business. Genesys works with its
customers and partners world-wide to deliver the experience that today’s digital
consumers want. It all adds up to one seamless customer conversation.
Great customer service extends beyond the contact center to the processes and work
streams involved in meeting your commitments. Genesys products give you insight
into and control over these processes, so you can truly track the customer experience
from end to end.
