data disconnect

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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.

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USA

Worldwide Inquiries:

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Fax: +1 650 466 1260

E-mail: [email protected]

www.genesyslab.com

Genesys is a leading provider of contact center and customer service software — with more than 2,200 customers in

80 countries. With over 20 years of contact center innovation and experience, Genesys software directs more than

100 million interactions every day, maximizing the value of customer engagement and differentiating the experience

by driving personalization and multichannel customer service — as well as extending customer service across the

enterprise to optimize processes and the performance of customer-facing employees.

For more information visit: www.genesyslab.com, or call +1 888 GENESYS.

Genesys and the Genesys logo are registered trademarks of Genesys Telecommunications Laboratories, Inc. All other

company names and logos may be trademarks or registered trademarks of their respective holders. © 2013 Genesys

Telecommunications Laboratories, Inc. All rights reserved.

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