There is a high degree of complexity associated
with these efforts and a naturally high cost of integration across an
organization and its end-to-end network. As a result, current views of the potential
values are tempered by a need to bring focus to immediate process improvement
and bottom line returns. Nevertheless, when executed as part of a deployment
of strategies, with enhanced processes and enabling technology applications that
are used to acquire, develop, and retain an organization�s best customers, CRM
becomes a powerful tool for increasing revenue and profit.
In essence, a contemporary CRM operating model will serve to improve the
characteristics and performance of a customer-intimate organization. The inherent
characteristics for customer-intimate organizations will include:
Creation of the best business solutions for the key customers
Introduction of customized products and services to meet these customers�
unique needs
Presentation of a unique range of superior services, so customers can
get the most value from the products delivered
Establishment of the most flexible and responsive system of supply and
delivery possible with current technology
The operating model benchmarks will include:
Management systems geared toward creating superior results for carefully
selected strategic customers
A culture that embraces specific rather than general customer solutions
and thrives on deep and lasting relationships
Deep customer knowledge and breakthrough insights about the customer�s
underlying processes
Decision making delegated to employees close to the customer (Treacy
and Wiersema, 1995)
Reaching these conditions requires a lot of concerted effort and nurturing
a cultural imperative that is often hard for firms accustomed to working within
an internal-only focus. CRM has its roots in the idea that as a firm�s supply
chain moves toward maturity, it becomes more effective at both internal and
external processing; that is, it improves its ability to process within its four
walls, and then extends its learning, with the help of useful business allies, to
constructing a network of delivery that has superior features from the viewpoint
of the most important customers and consumers. Such an accomplishment meansWithin
the intelligent value chain, business allies are working together from
a right-to-left perspective. They begin with what it takes to have a competitively
advantaged value network in the eyes of the most important end customers or
consumers, and then they work backwards toward what the upstream side of
the value chain should be doing across the enterprise processes to achieve the
desired superior conditions. Together, the linked parties are working to find the
best solutions and practices for all of the key process steps. Beginning with
improved forecasting and moving through the necessary linked processes, the
network partners apply their best resources to find greater results with product
development and introduction, the ultimate distribution efficiency, the best
methods for product replenishment, jointly developed marketing strategies, and
the best possible order fulfillment system. Along the way, they work
collaboratively to find the best enterprise processes and become extremely
effective at any point of handoff between supply chain constituents. In short,
they are working in concert to develop business in a manner that greatly satisfies
the key customers and enhances profitability for all of the contributing allies.
Two requirements must be met as this intelligent value chain is constructed
and nurtured. First, each participant or major constituent of what becomes the
network of delivery must have attained a high level of capability in the supply
chain maturity model (level 3 or beyond), an important element of which will
be the ability to use BPM and its enabling business language, BPML, to enter
and access parts of disparate databases so valuable knowledge can be extracted
without compromising the security of the various systems. Second, the enabling
technology applications must be selected collaboratively and be functioning
successfully across the end-to-end network processing. That means the collaborating
business allies are working in concert, with each making valuable contributions
toward finding the enhanced state in which ASCM and CRM converge
to create the desired differentiation in the eyes of the most coveted
customers. They are doing this with the help of enabling BPM technology and
superior systems across the end-to-end processing linking them into an intelligent
value network.
Saturday, July 3, 2010
CREATING THE INTELLIGENT VALUE NETWORK:
To reap the most benefit from level 5 efforts, the linked businesses should apply
their efforts toward specific customers and consumer groups, such that the
perception these groups have of the network is one of superior capabilities and
the one that renders the greatest satisfaction � or, more importantly, the greatest
overall value. Attaining such a condition requires the features of supply
chain maturity to be matched with a �customer intelligence progression.� That
is, the network allies will be using the knowledge being shared, as well as the
process improvements, to distinguish the final results in the eyes of the most
important buyers.
Using the maturity model, which is repeated as Figure 8.1, to describe the
progression of supply chain efforts, we are reminded that the first two levels
are internal only, where focus is brought to functional improvement and operational
excellence to internal operations. The cultural wall standing between
levels 2 and 3 represents all of the collective inhibitions and obstacles to accepting
an external view of the processing and working collaboratively with
willing business allies to build network improvements, which distinguish the
value chain in the eyes of the most important customers. Levels 3 and 4 rep resent the
positions achieved by market leaders, while level 5 is intended to
indicate the presence of total network connectivity with the highest processing
capabilities.Beginning in the mid-1990s, most firms progressed through the first levels
of the supply chain evolution, moving from enterprise integration, where early
savings were made through concentrated sourcing and logistics efforts, to corporate
excellence, where internal obstacles were conquered and planning, order
management, manufacturing skills, and inventory management became serious
parts of the effort. During this time, many companies also progressed into a
form of operational CRM. Sales force automation became a factor, as companies
learned they could use customer data to enhance the ability of sales representatives
to help customers find extra values and build more revenues. Call
centers came into vogue as contact centers were established to match the services
needed with what would truly help the key customers and to guide responses
to customer needs through multichannel customer service hubs. Toward
the end of that period, while in the second phase of the effort, campaign management
became a factor, as firms learned they could ally themselves with key
suppliers and customers to improve the results of special sales efforts.
At the beginning of the new century, those firms that maintained a dedication
to the supply chain effort moved into level 3, and began collaborating in
earnest with their key business partners, to find the hidden values in the supply
chain linkage that eluded those firms bogged down in an internal-only focus.
During this period, these firms typically advanced to a form of collaborative
CRM, applying technology to increase the knowledge available to business
allies having the same purposes. Using the Internet as the major tool of communication,
these companies began to share valuable customer and consumer
information with selected and trusted business allies, so they could further
improve their abilities to create and sustain new revenues. Partner relationship
management became the tool of choice, as these allies learned they could share.
their efforts toward specific customers and consumer groups, such that the
perception these groups have of the network is one of superior capabilities and
the one that renders the greatest satisfaction � or, more importantly, the greatest
overall value. Attaining such a condition requires the features of supply
chain maturity to be matched with a �customer intelligence progression.� That
is, the network allies will be using the knowledge being shared, as well as the
process improvements, to distinguish the final results in the eyes of the most
important buyers.
Using the maturity model, which is repeated as Figure 8.1, to describe the
progression of supply chain efforts, we are reminded that the first two levels
are internal only, where focus is brought to functional improvement and operational
excellence to internal operations. The cultural wall standing between
levels 2 and 3 represents all of the collective inhibitions and obstacles to accepting
an external view of the processing and working collaboratively with
willing business allies to build network improvements, which distinguish the
value chain in the eyes of the most important customers. Levels 3 and 4 rep resent the
positions achieved by market leaders, while level 5 is intended to
indicate the presence of total network connectivity with the highest processing
capabilities.Beginning in the mid-1990s, most firms progressed through the first levels
of the supply chain evolution, moving from enterprise integration, where early
savings were made through concentrated sourcing and logistics efforts, to corporate
excellence, where internal obstacles were conquered and planning, order
management, manufacturing skills, and inventory management became serious
parts of the effort. During this time, many companies also progressed into a
form of operational CRM. Sales force automation became a factor, as companies
learned they could use customer data to enhance the ability of sales representatives
to help customers find extra values and build more revenues. Call
centers came into vogue as contact centers were established to match the services
needed with what would truly help the key customers and to guide responses
to customer needs through multichannel customer service hubs. Toward
the end of that period, while in the second phase of the effort, campaign management
became a factor, as firms learned they could ally themselves with key
suppliers and customers to improve the results of special sales efforts.
At the beginning of the new century, those firms that maintained a dedication
to the supply chain effort moved into level 3, and began collaborating in
earnest with their key business partners, to find the hidden values in the supply
chain linkage that eluded those firms bogged down in an internal-only focus.
During this period, these firms typically advanced to a form of collaborative
CRM, applying technology to increase the knowledge available to business
allies having the same purposes. Using the Internet as the major tool of communication,
these companies began to share valuable customer and consumer
information with selected and trusted business allies, so they could further
improve their abilities to create and sustain new revenues. Partner relationship
management became the tool of choice, as these allies learned they could share.
USING CUSTOMER INTELLIGENCE IS A KEY TO SUCCESS:
Information abounds in most business organizations. The problem is that most
of the important data is not used in an intelligent manner, because it is stored
in nonintegrated databases and rarely shared across internal business units.
What must be done with this valuable information forms the basis of customer
intelligence. That begins with a common definition of customers, a description
of the tools to be applied, and the information integration architecture necessary
to make the system a viable business enhancement process.
Knowledge is the key, and information about customers builds knowledge.
Companies must manage their customer data better to be able to act upon
customer knowledge. Figure 8.7 shows the customer intelligence maturity model,
where we have arrayed the key operational improvement characteristics against
the levels of maturity progression. From basic through foundational, core, and
distinctive levels, the important areas where customer intelligence can bring a
favorable impact are depicted, so a company can gauge how far along the
continuum it wants to or should proceed. Firms need to assess where they are,
what their competitors are doing, and then determine where they need to be in
order to achieve the advantages that we have outlined.
of the important data is not used in an intelligent manner, because it is stored
in nonintegrated databases and rarely shared across internal business units.
What must be done with this valuable information forms the basis of customer
intelligence. That begins with a common definition of customers, a description
of the tools to be applied, and the information integration architecture necessary
to make the system a viable business enhancement process.
Knowledge is the key, and information about customers builds knowledge.
Companies must manage their customer data better to be able to act upon
customer knowledge. Figure 8.7 shows the customer intelligence maturity model,
where we have arrayed the key operational improvement characteristics against
the levels of maturity progression. From basic through foundational, core, and
distinctive levels, the important areas where customer intelligence can bring a
favorable impact are depicted, so a company can gauge how far along the
continuum it wants to or should proceed. Firms need to assess where they are,
what their competitors are doing, and then determine where they need to be in
order to achieve the advantages that we have outlined.
RESPONDING TO THE CUSTOMER EXPERIENCE:
The intelligent value chain that evolves will have many facets, but it will remain
focused on customer satisfaction. The architecture that makes such a value chain
possible is described in Figure 8.6. It progresses from the back-office systems,
necessary to meet the needs of the customers, to the customer touch points so
critical to the provision of value-added services. In between, a customer intelligence
hub is at work, using BPM and providing the profile, rules management,
events and treatments, and the quality data needed to enhance the ASCM/CRM
systems.
New definitions are then brought to the benefits and values being delivered
to the most strategic customers. Differentiated (often customized) answers to
members of a particular segment�s business problems are part of the delivery.
Points of view are specific to each market segment. Solutions are comprised of
a mix of tools, competencies, and offerings matched to actual needs. Specific
solutions are packaged and delivered with a defined and quantifiable business
value � measured across the entire value chain, and for the individual partners,
using the economic value added tools described. The customer intelligence
system at work synthesizes data consolidation and analytics so that a single
view of the customer emerges, as well as individual customer analytics, which
are used in profiling, evaluation, and modeling for success. A single up-to-date,
integrated view of the customer relationship is constantly maintained, along
with robust customer insights to tailor the correct treatment to the right customer
at the right time.
There are three dimensions to customer intelligence, with specific features
and advantages:
1. Customer information integration
Integration and rationalization of disparate customer data, to provide
a persistent cross-channel data store to serve as a focal point for analytic
processing and as a clearinghouse for multiple disparate
touch points
Establishment of relationships in the data to support analysis at the
customer, prospect, household, and segment levels
Development of an operations format for use of customer knowledge
through all customer interaction points
Development of event-based or delta-based sensing mechanisms to
identify changes in front-end CRM systems, such as customer behavior
or profile
Transfer of information on event or delta to the hub-based repository
for integration and consolidation
Utilization of enterprise application integration or low-latency tools
to move data from front-end systems to operational data storage
2. Customer insights: segmentation and modeling
Ability to analyze cleansed and consolidated customer data to develop
descriptive and/or predictive models
Understanding of the economic or lifetime value of each individual
customer
Customer segmentation based on value, demographics, and behavioral
information
Quantification of each customer�s responsiveness to marketing and
other stimuli
Identification of the appropriate treatment or offer for each customer,
and delivery of this insight to front-end application
Mining of vast amounts of data to identify hidden customer insights
Capture and codification of analytical best practices in a business
rules engine, to create intelligent recommendations in a near realtime
environment
3. Customer insights: operationalization
Ability to offer insights at the point of contact
Products and services matched to individual customers
Rules-driven customer interactions
Differentiated service treatments for valuable customers
focused on customer satisfaction. The architecture that makes such a value chain
possible is described in Figure 8.6. It progresses from the back-office systems,
necessary to meet the needs of the customers, to the customer touch points so
critical to the provision of value-added services. In between, a customer intelligence
hub is at work, using BPM and providing the profile, rules management,
events and treatments, and the quality data needed to enhance the ASCM/CRM
systems.
New definitions are then brought to the benefits and values being delivered
to the most strategic customers. Differentiated (often customized) answers to
members of a particular segment�s business problems are part of the delivery.
Points of view are specific to each market segment. Solutions are comprised of
a mix of tools, competencies, and offerings matched to actual needs. Specific
solutions are packaged and delivered with a defined and quantifiable business
value � measured across the entire value chain, and for the individual partners,
using the economic value added tools described. The customer intelligence
system at work synthesizes data consolidation and analytics so that a single
view of the customer emerges, as well as individual customer analytics, which
are used in profiling, evaluation, and modeling for success. A single up-to-date,
integrated view of the customer relationship is constantly maintained, along
with robust customer insights to tailor the correct treatment to the right customer
at the right time.
There are three dimensions to customer intelligence, with specific features
and advantages:
1. Customer information integration
Integration and rationalization of disparate customer data, to provide
a persistent cross-channel data store to serve as a focal point for analytic
processing and as a clearinghouse for multiple disparate
touch points
Establishment of relationships in the data to support analysis at the
customer, prospect, household, and segment levels
Development of an operations format for use of customer knowledge
through all customer interaction points
Development of event-based or delta-based sensing mechanisms to
identify changes in front-end CRM systems, such as customer behavior
or profile
Transfer of information on event or delta to the hub-based repository
for integration and consolidation
Utilization of enterprise application integration or low-latency tools
to move data from front-end systems to operational data storage
2. Customer insights: segmentation and modeling
Ability to analyze cleansed and consolidated customer data to develop
descriptive and/or predictive models
Understanding of the economic or lifetime value of each individual
customer
Customer segmentation based on value, demographics, and behavioral
information
Quantification of each customer�s responsiveness to marketing and
other stimuli
Identification of the appropriate treatment or offer for each customer,
and delivery of this insight to front-end application
Mining of vast amounts of data to identify hidden customer insights
Capture and codification of analytical best practices in a business
rules engine, to create intelligent recommendations in a near realtime
environment
3. Customer insights: operationalization
Ability to offer insights at the point of contact
Products and services matched to individual customers
Rules-driven customer interactions
Differentiated service treatments for valuable customers
THE VALUE OF CUSTOMER INTELLIGENCE:
There is an important purpose behind the effort to establish greater customer
intelligence. Bringing together a single view of the customer with high-value
analytics can serve to optimize customer interactions, reduce operational costs,
and enhance revenue-generating opportunities. To begin, most organizations
have multiple records and accounting for the same customer, with no consistent
information transfer across business units within the same organization. This
condition leads to the absence of a single view of the customer and leads to
inconsistent customer experiences. Much time and effort are wasted collating
reports and gathering information, rather than focusing valuable resources on
analyzing high-value information and knowledge. Much of the marketing effort,
which is intended to build a demand, is focused on mass-market techniques,
rather than the preferred targeted segments that offer the most lucrative returns
on the effort. The inability to target the right customer at the right time, with
no predictive modeling capabilities, exacerbates the problem and leads to expending
corporate energies on low- versus high-level customers and a total lack
of optimized service levels.
Solutions to these complications can add dramatically to the firm�s performance,
including such features as:
Data management personnel savings
Faster call handling of inbound inquiries
Prospect and customer solicitation savings
Reduction in returned communications
Improved data quality in critical operational systems
Improved targeting for cross-sell, up-sell, retention, and acquisition
campaigns
Lower customer attrition or churn rates
More importantly, attaining such conditions puts the internal house in order
and brings the firm to the point of being able to approach customer intelligence
in a more contemporary manner. By today�s standards, CRM has become the
deployment of strategies, processes, and enabling technologies that are used to
acquire, develop, and retain an organization�s best customers. It includes understanding
customer needs, the relative importance of each customer segment,
and the best, most economical means to meet those needs. Within an environment
focused on this view of CRM, strategy, processes, organization, and culture
begin to revolve around a central focus dedicated to satisfying customers in the
most appropriate manner and sustaining those with most strategic value indefinitely.
Businesses adopting such an environment recognize that performing the Process orientation
has never had more meaning in this environment. Organizations
that remain internally fragmented and operate in a stovepipe manner
will never achieve the advantages cited. They will be doomed to local optimizations
within some business units and be prevented from achieving network
process and systems optimization. Such systems as enterprise resource planning,
CRM, and collaborative planning, forecasting, and replenishment simply
will never be achieved in an optimal manner due to the process inefficiencies
that will occur. Process design and enablement with new technologies and
methodologies and tools are what will provide the greatest opportunity to increase
corporate performance in the modern era. The drivers behind this return
to a process focus, moreover, will be an enhanced customer-controlled environment,
where customer satisfaction is the real end objective, with use of the
Internet to create and control the sharing of valuable knowledge.
When ASCM and CRM converge in this advanced level of the evolution,
some important characteristics will be apparent:
Demand management and forecasting will be at improved levels, with
actual need matched with capability to supply.
Sales and operations planning will move to advanced planning and
scheduling, where key suppliers and customers participate in diagnostics
and planning sessions to bring a reality to the planning and supply
processing.
Inventory management will be a network effort, in which the linked
allies work to deliver the right goods to the point of need in the right
quantities at the right time.
Visibility into the end-to-end processing will be on-line, real time, allowing
the constituents to view what is taking place, track important
events, and adapt the supply chain to ever-changing market conditions
faster and more accurately than the competition.
Event management will be at the highest possible level of effectiveness,
as the reactions to any planned sales effort will be instantly relayed back
to the important upstream partners, so they can react appropriately to
actual event conditions and results.
Investment in the extended enterprise will be driven by the good of the
whole network, not just individual partners� local shareholder needs.
intelligence. Bringing together a single view of the customer with high-value
analytics can serve to optimize customer interactions, reduce operational costs,
and enhance revenue-generating opportunities. To begin, most organizations
have multiple records and accounting for the same customer, with no consistent
information transfer across business units within the same organization. This
condition leads to the absence of a single view of the customer and leads to
inconsistent customer experiences. Much time and effort are wasted collating
reports and gathering information, rather than focusing valuable resources on
analyzing high-value information and knowledge. Much of the marketing effort,
which is intended to build a demand, is focused on mass-market techniques,
rather than the preferred targeted segments that offer the most lucrative returns
on the effort. The inability to target the right customer at the right time, with
no predictive modeling capabilities, exacerbates the problem and leads to expending
corporate energies on low- versus high-level customers and a total lack
of optimized service levels.
Solutions to these complications can add dramatically to the firm�s performance,
including such features as:
Data management personnel savings
Faster call handling of inbound inquiries
Prospect and customer solicitation savings
Reduction in returned communications
Improved data quality in critical operational systems
Improved targeting for cross-sell, up-sell, retention, and acquisition
campaigns
Lower customer attrition or churn rates
More importantly, attaining such conditions puts the internal house in order
and brings the firm to the point of being able to approach customer intelligence
in a more contemporary manner. By today�s standards, CRM has become the
deployment of strategies, processes, and enabling technologies that are used to
acquire, develop, and retain an organization�s best customers. It includes understanding
customer needs, the relative importance of each customer segment,
and the best, most economical means to meet those needs. Within an environment
focused on this view of CRM, strategy, processes, organization, and culture
begin to revolve around a central focus dedicated to satisfying customers in the
most appropriate manner and sustaining those with most strategic value indefinitely.
Businesses adopting such an environment recognize that performing the Process orientation
has never had more meaning in this environment. Organizations
that remain internally fragmented and operate in a stovepipe manner
will never achieve the advantages cited. They will be doomed to local optimizations
within some business units and be prevented from achieving network
process and systems optimization. Such systems as enterprise resource planning,
CRM, and collaborative planning, forecasting, and replenishment simply
will never be achieved in an optimal manner due to the process inefficiencies
that will occur. Process design and enablement with new technologies and
methodologies and tools are what will provide the greatest opportunity to increase
corporate performance in the modern era. The drivers behind this return
to a process focus, moreover, will be an enhanced customer-controlled environment,
where customer satisfaction is the real end objective, with use of the
Internet to create and control the sharing of valuable knowledge.
When ASCM and CRM converge in this advanced level of the evolution,
some important characteristics will be apparent:
Demand management and forecasting will be at improved levels, with
actual need matched with capability to supply.
Sales and operations planning will move to advanced planning and
scheduling, where key suppliers and customers participate in diagnostics
and planning sessions to bring a reality to the planning and supply
processing.
Inventory management will be a network effort, in which the linked
allies work to deliver the right goods to the point of need in the right
quantities at the right time.
Visibility into the end-to-end processing will be on-line, real time, allowing
the constituents to view what is taking place, track important
events, and adapt the supply chain to ever-changing market conditions
faster and more accurately than the competition.
Event management will be at the highest possible level of effectiveness,
as the reactions to any planned sales effort will be instantly relayed back
to the important upstream partners, so they can react appropriately to
actual event conditions and results.
Investment in the extended enterprise will be driven by the good of the
whole network, not just individual partners� local shareholder needs.
THE IMPORTANCE OF FOCUS ON PROCESS:
To begin, managing businesses to achieve maximum value requires an understanding
of what is meant by value. There has long been a quantitative approach
to business management based on generally accepted accounting principles. As
the various approaches have matured, they have become much more sophisticated,
especially with the introduction of activity-based costing, balanced
scorecards, and financial dashboards, all of which build on two fundamental
concepts: when you can�t measure it (however that might be), you can�t improve
it, and what you measure generally gets better. We now ask what it is that
delivers goods or services with inherent value from a business or enterprise. It
is a set of focused and coherent processes that bring satisfaction to the consumer.
To improve a business, then, as you change the underlying processes,
each process needs a set of measures which when folded together reflect attainment
of the organization�s goals as well as maximum customer satisfaction �
the essential aims of an advanced supply chain system.
In the quest for such a condition, it has been said that there have been �five
big ideas� in terms of operational management, notably:
Introduction of the moving production line and standardized product by
Henry Ford and Frederick Taylor
Statistical control of quality by W. Edwards Deming
Lean production by Toyota
Theory of Constraints by Eli Goldratt
Process focus by Michael Hammer and James Champy
Of these ideas, process focus is the only one that looks �end to end,� while the
others tend to work on single activities. In the current complicated business
world, you cannot get far by focusing on a single task. Most equipment, for
example, can be relied upon to deal with a single task effectively. On the other
hand, process can be defined as �end-to-end work.� It is an organized group
of related tasks that work together to create value. All supply chain work fits
this description and becomes process work (e.g., �order to cash� or new product
introduction). The redesign of work on an end-to-end basis is central to improvement;
it is the antidote to nonvalue-adding activities. Consequently, process
can have the biggest impact on enterprise operations. Contemporary performance
problems, as a result, are process problems, not task problems. We
must use techniques suited to dealing with the process. This is where simulation
comes in and offers the greatest value.
of what is meant by value. There has long been a quantitative approach
to business management based on generally accepted accounting principles. As
the various approaches have matured, they have become much more sophisticated,
especially with the introduction of activity-based costing, balanced
scorecards, and financial dashboards, all of which build on two fundamental
concepts: when you can�t measure it (however that might be), you can�t improve
it, and what you measure generally gets better. We now ask what it is that
delivers goods or services with inherent value from a business or enterprise. It
is a set of focused and coherent processes that bring satisfaction to the consumer.
To improve a business, then, as you change the underlying processes,
each process needs a set of measures which when folded together reflect attainment
of the organization�s goals as well as maximum customer satisfaction �
the essential aims of an advanced supply chain system.
In the quest for such a condition, it has been said that there have been �five
big ideas� in terms of operational management, notably:
Introduction of the moving production line and standardized product by
Henry Ford and Frederick Taylor
Statistical control of quality by W. Edwards Deming
Lean production by Toyota
Theory of Constraints by Eli Goldratt
Process focus by Michael Hammer and James Champy
Of these ideas, process focus is the only one that looks �end to end,� while the
others tend to work on single activities. In the current complicated business
world, you cannot get far by focusing on a single task. Most equipment, for
example, can be relied upon to deal with a single task effectively. On the other
hand, process can be defined as �end-to-end work.� It is an organized group
of related tasks that work together to create value. All supply chain work fits
this description and becomes process work (e.g., �order to cash� or new product
introduction). The redesign of work on an end-to-end basis is central to improvement;
it is the antidote to nonvalue-adding activities. Consequently, process
can have the biggest impact on enterprise operations. Contemporary performance
problems, as a result, are process problems, not task problems. We
must use techniques suited to dealing with the process. This is where simulation
comes in and offers the greatest value.
USING PROCESS SIMULATION TO MINIMIZE THE RISK:
Now that we have explained how to take a firm to the highest and most appropriate
level of the supply chain maturity model, and how to track the savings
from that model and the SCOR� model to financial statements, we are prepared
to consider how to make sure the potential savings are real before engaging in
what could be a high-risk transformation process. In this chapter, we will introduce
the idea of using computer-based simulations to test business improvement
changes before implementation and will suggest ways in which simulations
can be used to help optimize processes and supply chains before
encountering risk in the possible outcomes. Simulation will be explored and
defined as a logical business implementation tool, with the inherent techniques
explained along with numerous examples of how firms are getting the most
benefit from the tool.
SIMULATION DEFINED
In essence, simulation provides a �virtual test bench� for process improvement,
as it is a technique that focuses on quantitative measures that could result from
various potential actions. It provides a representation of the process actions in
a manner that is transparent to the business user, thereby generating a prediction
of potential business performance � should the process, rules, and parameters
be adopted or altered in practice. It provides a means of testing alternative
solutions and outcomes before actually engaging in the introduction of the
changed processing.
As we explore simulation, we will explain how it is used to gain value, its
role within a business process management suite, and how it can be applied to
business intelligence and management of the enterprise, through analysis of the
resulting metrics. Additionally, we will show how optimization efforts can be
applied with simulation to approach true process optimization in an automated
manner. This level of optimization, implemented within business process management
� enables the extended enterprise to more effectively manage its endto-
end supply chain and supporting business processes.
level of the supply chain maturity model, and how to track the savings
from that model and the SCOR� model to financial statements, we are prepared
to consider how to make sure the potential savings are real before engaging in
what could be a high-risk transformation process. In this chapter, we will introduce
the idea of using computer-based simulations to test business improvement
changes before implementation and will suggest ways in which simulations
can be used to help optimize processes and supply chains before
encountering risk in the possible outcomes. Simulation will be explored and
defined as a logical business implementation tool, with the inherent techniques
explained along with numerous examples of how firms are getting the most
benefit from the tool.
SIMULATION DEFINED
In essence, simulation provides a �virtual test bench� for process improvement,
as it is a technique that focuses on quantitative measures that could result from
various potential actions. It provides a representation of the process actions in
a manner that is transparent to the business user, thereby generating a prediction
of potential business performance � should the process, rules, and parameters
be adopted or altered in practice. It provides a means of testing alternative
solutions and outcomes before actually engaging in the introduction of the
changed processing.
As we explore simulation, we will explain how it is used to gain value, its
role within a business process management suite, and how it can be applied to
business intelligence and management of the enterprise, through analysis of the
resulting metrics. Additionally, we will show how optimization efforts can be
applied with simulation to approach true process optimization in an automated
manner. This level of optimization, implemented within business process management
� enables the extended enterprise to more effectively manage its endto-
end supply chain and supporting business processes.
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