We now return to the Yantra/CellStar case study presented earlier, to emphasize
how these firms found real improvement through advanced supply chain management
network-type efforts. One of the most important factors in the effort
to improve the delivery system for the intended wireless customers was the
ability to handle reverse logistics. CellStar had determined that this factor was
the Achilles� heel in the wireless industry. Traditional reverse solutions, for
example, could not address the need to:
Maximize value of the returned handsets
Track handsets across the enterprise, including the repair process
Evaluate individual handset attributes (software, warranty, etc.)
Reconcile issues with multiple vendors and distributors
Manage multiple repair vendors
Assess product disposition at the unit level
Before developing its Omnigistics solution with Yantra, CellStar had little
chance of providing answers to these problems. Its returns management system
had no process-wide status. Reporting lacked a common format and was not
capable of handling details at a unit level. There was no ability to track unit
status (disposition decisions were made at the pallet level) and no mechanism
to track or manage warranty claims. In short, it was operating with a slow,
costly, and inflexible return-handling system.
With the help of its business ally, CellStar introduced Omnigistics and
brought a new and better dimension to reverse logistics services. In addition to
the software development cost, a multimillion-dollar investment was made in
business process reengineering the existing processes. With the help of Yantra
as the provider of the new and complex supply chain management system and
CSC as the systems integrator, CellStar also established a 230,000-square-feet
dedicated facility with specially trained forward and reverse logistics teams.
This facility became a certified repair center, with a dedicated account management
team.
Facing the issue of reverse logistics, the team adopted level 5 principles and
developed a new strategy and solution based on:
Collaboration � To integrate the customer�s business system, key
business partners, and CellStar�s logistics operations in order to provide
help from a seamless entity
Visibility � To provide electronic access into the processing at both
the enterprise and unit level
Speed � To compress event cycles
The solution delivered a single, seamless management system that streamlined
operations across the end-to-end reverse logistics process. Now the reverse
management system was centralized and could process at the unit level. Reporting
was on demand at the enterprise and unit level. Inventory management
decreased the amount of nonearning assets and maximized the high turnover
stock, while reducing or eliminating the slowest moving items. Asset reclamation
options were included in that part of the system. Multiple repair centers
were linked so they could monitor status at the unit level. Finally, multiple
warranty programs were in place to manage and track claims.
To illustrate the advantages, a major national retailer became an early customer
of the enhanced system. This retailer�s handsets were returned at the store
level and replaced with new units from store inventory. The returned handsets
were sent to the retailer�s centralized return center and then to a carrier for
disposition. The issues were symptomatic of the industry at the time. The
process was marked by escalating costs and loss of profitability. The value of
the returned handsets to the carrier was not known, and returns were difficult
and costly to handle at the store level.
Saturday, July 3, 2010
IMPROVEMENT STARTS IN A COMPLICATED ENVIRONMENT
Any discussion on the possibilities of achieving total enterprise optimization
begins with an understanding of just how complex an extended enterprise supply
chain has become. While the original supply chain efforts were directed toward
achieving optimum operating conditions across a linear set of tightly linked,
internal process steps, from beginning raw materials to final delivery of products
and services,Any analysis that is limited to internal processing
is doomed to operate with suboptimized conditions. There are simply too many
players in a typical business network, most of which are global in extent. The
end-to-end processing that has come under scrutiny for improvement now includes
a multitude of business partners. Concurrently, the necessary flow of
information and knowledge within a business network has become as important
as the physical flow of goods and the transfer of money across what is clearly
an extended enterprise. Supply chain optimization now requires the collaboration
of a host of business partners working in concert for the same end results.
It becomes imperative in such an environment that the firm seeking optimized
conditions make a passage from an internal-only perspective, in terms
of generating process improvement, to one where willing and trusted business
allies are made a part of the process improvement effort, with the end result
focused on customer satisfaction. To accomplish this objective, the leading
firms are merging their advanced supply chain management concepts with their
customer relationship management efforts, yielding a framework and roadmap
for progressing through a series of levels until the highest possible return on
the effort, in terms of value for the customer and benefits for the providing firm
and its allies, is attained. Along the way, a concurrent effort must be made to
balance supply chain progress with the firm�s customer relationship management
capabilities and synchronize the results of the two efforts. In the next
chapter, we will delve into these necessities, as we explain how firms partnering
in level 5 can take advantage of their intelligence sharing and outdistance
competitors in the creation of new revenues.
begins with an understanding of just how complex an extended enterprise supply
chain has become. While the original supply chain efforts were directed toward
achieving optimum operating conditions across a linear set of tightly linked,
internal process steps, from beginning raw materials to final delivery of products
and services,Any analysis that is limited to internal processing
is doomed to operate with suboptimized conditions. There are simply too many
players in a typical business network, most of which are global in extent. The
end-to-end processing that has come under scrutiny for improvement now includes
a multitude of business partners. Concurrently, the necessary flow of
information and knowledge within a business network has become as important
as the physical flow of goods and the transfer of money across what is clearly
an extended enterprise. Supply chain optimization now requires the collaboration
of a host of business partners working in concert for the same end results.
It becomes imperative in such an environment that the firm seeking optimized
conditions make a passage from an internal-only perspective, in terms
of generating process improvement, to one where willing and trusted business
allies are made a part of the process improvement effort, with the end result
focused on customer satisfaction. To accomplish this objective, the leading
firms are merging their advanced supply chain management concepts with their
customer relationship management efforts, yielding a framework and roadmap
for progressing through a series of levels until the highest possible return on
the effort, in terms of value for the customer and benefits for the providing firm
and its allies, is attained. Along the way, a concurrent effort must be made to
balance supply chain progress with the firm�s customer relationship management
capabilities and synchronize the results of the two efforts. In the next
chapter, we will delve into these necessities, as we explain how firms partnering
in level 5 can take advantage of their intelligence sharing and outdistance
competitors in the creation of new revenues.
HIGHER GROUND CAN BE GAINED:
A recent survey by CSC, in conjunction with Supply Chain Management Review
magazine (Quinn, 2004), clearly documented that savings and improvements
are real for serious supply chain efforts, often reaching three to eight points of
new profits. This study, as well as ones conducted by AMR Research and other
major consultancies, also shows that the important savings (particularly those
related to revenue increase) are eluding most firms, which are still bogged down
in the early levels of the maturity and SCOR� models and not inclined to work
with external business partners.
We see an enormous possibility in such a context. The opportunity to use
supply chain as a driving force behind further performance enhancement, and
to move a firm into a position where the distinguishing feature is being solidly
linked in an intelligent value network, has become the means to reap the greatest
return from an end-to-end supply chain improvement effort. Internal obstacles
and cultural conflicts tend to be the greatest inhibitors to achieving such aposition,
the most important of which are good data management and overcoming
process difficulties.
Distancing an individual business from its competitors in areas of importance
in a market has long been the goal of most enterprises. The chance to
extend market leadership, however, and to gain a dominant position through the
application of collaboration and technology focused on customer satisfaction,
the key ingredients of the intelligent value network, is not so well known and
has never been greater � for those businesses willing to overcome normal
cultural barriers and the traditional unwillingness to work cooperatively with
external resources to cope with process problems.
This opportunity is achieved by linking together four topics of importance
to today�s businesses: supply chain management, customer relationship management,
technology application, and customer intelligence. The last topic is our
terminology for the acquisition, management, and integration of customer
knowledge in order to create a differentiating customer value proposition for
the whole extended enterprise. By looking holistically at these usually disparate
topics, companies can develop integrated strategies and solutions for delivering
products and services to key customers better than any competitors. When the
effort is extended through business process management techniques to include
willing and trusted business allies working across an extended enterprise for the
same purposes, the advantages are unmatched.
magazine (Quinn, 2004), clearly documented that savings and improvements
are real for serious supply chain efforts, often reaching three to eight points of
new profits. This study, as well as ones conducted by AMR Research and other
major consultancies, also shows that the important savings (particularly those
related to revenue increase) are eluding most firms, which are still bogged down
in the early levels of the maturity and SCOR� models and not inclined to work
with external business partners.
We see an enormous possibility in such a context. The opportunity to use
supply chain as a driving force behind further performance enhancement, and
to move a firm into a position where the distinguishing feature is being solidly
linked in an intelligent value network, has become the means to reap the greatest
return from an end-to-end supply chain improvement effort. Internal obstacles
and cultural conflicts tend to be the greatest inhibitors to achieving such aposition,
the most important of which are good data management and overcoming
process difficulties.
Distancing an individual business from its competitors in areas of importance
in a market has long been the goal of most enterprises. The chance to
extend market leadership, however, and to gain a dominant position through the
application of collaboration and technology focused on customer satisfaction,
the key ingredients of the intelligent value network, is not so well known and
has never been greater � for those businesses willing to overcome normal
cultural barriers and the traditional unwillingness to work cooperatively with
external resources to cope with process problems.
This opportunity is achieved by linking together four topics of importance
to today�s businesses: supply chain management, customer relationship management,
technology application, and customer intelligence. The last topic is our
terminology for the acquisition, management, and integration of customer
knowledge in order to create a differentiating customer value proposition for
the whole extended enterprise. By looking holistically at these usually disparate
topics, companies can develop integrated strategies and solutions for delivering
products and services to key customers better than any competitors. When the
effort is extended through business process management techniques to include
willing and trusted business allies working across an extended enterprise for the
same purposes, the advantages are unmatched.
CUSTOMER RELATIONSHIP MANAGEMENT: A CONTEMPORARY VIEW
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.
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.
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.
GAINING VALUE FROM DISCRETE EVENT SIMULATION:
Discrete event simulation can be used to model various processes, using entities
or tokens moving through queues over time. Figure 9.3 describes the project
steps in such an effort, beginning with establishment of the objectives and scope
and proceeding to implementation. Typically, there are two types of queues
involved in discrete event simulation. First, we have those where entities just
wait, what we normally consider a queue. Second, we see those where entities
reside while the �value-adding work� is carried out. These queues are often
considered to be activities. The �event� occurs when the model changes state,
normally instantaneously. This is typically the start or end of an activity or some
form of interruption, such as a breakdown, lunch break, etc. At the end of an
activity, the simulation would check to see what other activities can now begin
as a result and schedule the end of that activity after allocating the required
Figure 9.3. Project Steps
About Lanner Applications in Air Travel Status
Establish
Objectives & Scope
Data & Level of Detail
Structure Model
Build Model
Verify Model
Validate Model
Experimentation
Project Management
Documentation
& Communication
Present Results
Implementation
Project Definition
Model Building and Testing
Experimentation
Project Completion
About Simulation
or tokens moving through queues over time. Figure 9.3 describes the project
steps in such an effort, beginning with establishment of the objectives and scope
and proceeding to implementation. Typically, there are two types of queues
involved in discrete event simulation. First, we have those where entities just
wait, what we normally consider a queue. Second, we see those where entities
reside while the �value-adding work� is carried out. These queues are often
considered to be activities. The �event� occurs when the model changes state,
normally instantaneously. This is typically the start or end of an activity or some
form of interruption, such as a breakdown, lunch break, etc. At the end of an
activity, the simulation would check to see what other activities can now begin
as a result and schedule the end of that activity after allocating the required
Figure 9.3. Project Steps
About Lanner Applications in Air Travel Status
Establish
Objectives & Scope
Data & Level of Detail
Structure Model
Build Model
Verify Model
Validate Model
Experimentation
Project Management
Documentation
& Communication
Present Results
Implementation
Project Definition
Model Building and Testing
Experimentation
Project Completion
About Simulation
WHY SHOULD A FIRM SIMULATE POTENTIAL BUSINESS PROCESSES?
Simulation becomes valuable when there is variability of outcomes in the business
processing or when parameters and rules are changed. Under these conditions,
it is not easy to predict the outcomes, particularly when these factors change
over time. For example, the famous �beer distribution game� represents a simple
supply chain consisting of a retailer, wholesaler, and factory. The retailer orders
cases of beer from the wholesaler, which in turn orders beer from the factory.
There is a delay between placing an order and receiving the cases of beer. The
game demonstrates that a small perturbation in the number of cases of beer sold
by the retailer can cause large shifts in the quantity of cases stored and produced
by the wholesaler and factory, respectively. Such a system is subject to dynamic
complexity � like the majority of contemporary supply chains.
Of course, many operating systems are subject to both variability and dynamic
complexity. Indeed, the variability of one component interacts with the
variability of another to create dynamic complexity.The level of customer
service is simple to predict, since there is no variability
in the system and because there is no interaction between components.
The lack of interaction is a result of the service time being exactly the same
for each customer, which means that there is no queuing or blocking. The
Most activities, however, do not take exactly the same time every time.
Assume that the times given above are averages, so customers arrive on average
every five minutes and it takes on average five minutes to serve a customer.
What is the average time a customer spends in the queue waiting to be served?
This is not an easy question to answer, especially when subsequent steps are
also considered, as there is variability in both customer arrivals and service
times. Queues would develop between the steps and create consequential effects
on performance. Most people, when asked for a specific time, tend to underestimate
the likely queuing time. Of course, the actual queuing time depends
on many things even in the one-step system, such as:
Variability in arrivals
Variability in regular service time
Variability in service time that might be affected by type of customer
or time of day
Discrete event simulation provides the technique for evaluating such systems
effectively, modeling the process from the �bottom up,� starting at the
required level of detail. Changing the process inherent in the model provides
the ability to evaluate the effect of such a change. Operations that involve
multiple processes and how they interact can also be modeled, by effectively
linking multiple models together.
The benefits of simulation include:
Risk reduction
Greater understanding of process conditions and interactions1.
processing or when parameters and rules are changed. Under these conditions,
it is not easy to predict the outcomes, particularly when these factors change
over time. For example, the famous �beer distribution game� represents a simple
supply chain consisting of a retailer, wholesaler, and factory. The retailer orders
cases of beer from the wholesaler, which in turn orders beer from the factory.
There is a delay between placing an order and receiving the cases of beer. The
game demonstrates that a small perturbation in the number of cases of beer sold
by the retailer can cause large shifts in the quantity of cases stored and produced
by the wholesaler and factory, respectively. Such a system is subject to dynamic
complexity � like the majority of contemporary supply chains.
Of course, many operating systems are subject to both variability and dynamic
complexity. Indeed, the variability of one component interacts with the
variability of another to create dynamic complexity.The level of customer
service is simple to predict, since there is no variability
in the system and because there is no interaction between components.
The lack of interaction is a result of the service time being exactly the same
for each customer, which means that there is no queuing or blocking. The
Most activities, however, do not take exactly the same time every time.
Assume that the times given above are averages, so customers arrive on average
every five minutes and it takes on average five minutes to serve a customer.
What is the average time a customer spends in the queue waiting to be served?
This is not an easy question to answer, especially when subsequent steps are
also considered, as there is variability in both customer arrivals and service
times. Queues would develop between the steps and create consequential effects
on performance. Most people, when asked for a specific time, tend to underestimate
the likely queuing time. Of course, the actual queuing time depends
on many things even in the one-step system, such as:
Variability in arrivals
Variability in regular service time
Variability in service time that might be affected by type of customer
or time of day
Discrete event simulation provides the technique for evaluating such systems
effectively, modeling the process from the �bottom up,� starting at the
required level of detail. Changing the process inherent in the model provides
the ability to evaluate the effect of such a change. Operations that involve
multiple processes and how they interact can also be modeled, by effectively
linking multiple models together.
The benefits of simulation include:
Risk reduction
Greater understanding of process conditions and interactions1.
SIMULATION AND KEY PERFORMANCE INDICATORS:
Key performance indicators (KPIs) help an organization define and measure
progress toward organizational goals. Once an organization has analyzed its
mission, identified all its stakeholders, and defined its goals, it needs a way to
measure progress toward those goals. KPIs are typically used for that purpose
as measurements that are quantifiable, agreed to beforehand, and reflect the
critical success factors of an organization. They will differ depending on the
organization, but within a vertical industry sector some should be common and
used to benchmark a company�s performance against competitors.
A business needs to set targets for each KPI. A company goal to be the
employer of choice might include a KPI of �people turnover rate.� After the
KPI has been defined as �the number of voluntary resignations and terminations
for poor performance, divided by the total number of employees at the beginning
of the period� and a way to measure it has been set up by collecting the
information in the human resources system, the target has to be established.
�Reduce people turnover by 5% per year� is a clear target that everyone will
understand and be able to take specific action to accomplish. The question then
becomes: What are the specific actions that will deliver the objective?
Business process management is about managing corporate or business performance
through managing those processes which drive the firm to the desired overall objectives.
KPIs therefore need to be designed at various levels in order
to be relevant at an individual process level. While the KPI defined above
concerning turnover rate might be relevant for the board, it is not appropriate
for the supervisor of the human resources department�s contact center. That
center�s performance may well have an effect on turnover rate, but it requires
its own process-level KPIs, perhaps based on responding successfully to employee
questions, in order for it to be managed effectively.
Simulation and optimization supporting the identification and design of
KPIs have been used extensively to help improve processes and consequently
to ultimately improve business performance. Simulation can be used to both
help define and set targets for a KPI. This feature is in addition to the use of
simulation to identify process changes (resources, rules, and structural needs),
which deliver improved performance. Simulation aids the definition of a KPI
(that is, the equation and data of which it is composed), through examining the
reaction of that KPI under different circumstances. This procedure ensures that
the KPI does in fact properly connect to the organization�s goals and will help
drive the appropriate behavior and reaction to different potential events. Most
KPIs are developed directly from the overall goals or critical success factors
of the organization. Process-based KPIs tend to be focused on results or outputs
from a process, such as customers served per hour or claims processed.
Simulation is also valuable in the setting of targets against KPIs (such as
the number of calls to be answered per hour), because the simulation can
accurately assess what is achievable in theory by the process and resources
employed. Many KPIs are now presented as part of a �digital cockpit,� using
gauge or dashboard-style displays. Depending on the KPI and the targets selected,
they often include some use of zones to highlight acceptable levels (e.g.,
green, yellow, and red). It is important when calibrating these gauges to understand
the effect of natural fluctuations due to inherent randomness within processes
or behavior. Simulation can support this calibration to help ensure that
unnecessary reaction to natural short-term fluctuations does not occur.
Processes have a series of steps, and at each step measurement can be taken
to better understand the behavior of the process under different circumstances.
Identification of key points in the process and the relevance of specific measures
(probes) in predicting failure of the process can provide significant opportunity
for improved process management and business value. Effective process monitoring
through probes at specific points in the process involves watching factors
to give prior warning that the target levels are under threat. Simulation is able
to help identify these probes and the threshold values that indicate a deterioration
of the process which will ultimately end in an unacceptable KPI.
progress toward organizational goals. Once an organization has analyzed its
mission, identified all its stakeholders, and defined its goals, it needs a way to
measure progress toward those goals. KPIs are typically used for that purpose
as measurements that are quantifiable, agreed to beforehand, and reflect the
critical success factors of an organization. They will differ depending on the
organization, but within a vertical industry sector some should be common and
used to benchmark a company�s performance against competitors.
A business needs to set targets for each KPI. A company goal to be the
employer of choice might include a KPI of �people turnover rate.� After the
KPI has been defined as �the number of voluntary resignations and terminations
for poor performance, divided by the total number of employees at the beginning
of the period� and a way to measure it has been set up by collecting the
information in the human resources system, the target has to be established.
�Reduce people turnover by 5% per year� is a clear target that everyone will
understand and be able to take specific action to accomplish. The question then
becomes: What are the specific actions that will deliver the objective?
Business process management is about managing corporate or business performance
through managing those processes which drive the firm to the desired overall objectives.
KPIs therefore need to be designed at various levels in order
to be relevant at an individual process level. While the KPI defined above
concerning turnover rate might be relevant for the board, it is not appropriate
for the supervisor of the human resources department�s contact center. That
center�s performance may well have an effect on turnover rate, but it requires
its own process-level KPIs, perhaps based on responding successfully to employee
questions, in order for it to be managed effectively.
Simulation and optimization supporting the identification and design of
KPIs have been used extensively to help improve processes and consequently
to ultimately improve business performance. Simulation can be used to both
help define and set targets for a KPI. This feature is in addition to the use of
simulation to identify process changes (resources, rules, and structural needs),
which deliver improved performance. Simulation aids the definition of a KPI
(that is, the equation and data of which it is composed), through examining the
reaction of that KPI under different circumstances. This procedure ensures that
the KPI does in fact properly connect to the organization�s goals and will help
drive the appropriate behavior and reaction to different potential events. Most
KPIs are developed directly from the overall goals or critical success factors
of the organization. Process-based KPIs tend to be focused on results or outputs
from a process, such as customers served per hour or claims processed.
Simulation is also valuable in the setting of targets against KPIs (such as
the number of calls to be answered per hour), because the simulation can
accurately assess what is achievable in theory by the process and resources
employed. Many KPIs are now presented as part of a �digital cockpit,� using
gauge or dashboard-style displays. Depending on the KPI and the targets selected,
they often include some use of zones to highlight acceptable levels (e.g.,
green, yellow, and red). It is important when calibrating these gauges to understand
the effect of natural fluctuations due to inherent randomness within processes
or behavior. Simulation can support this calibration to help ensure that
unnecessary reaction to natural short-term fluctuations does not occur.
Processes have a series of steps, and at each step measurement can be taken
to better understand the behavior of the process under different circumstances.
Identification of key points in the process and the relevance of specific measures
(probes) in predicting failure of the process can provide significant opportunity
for improved process management and business value. Effective process monitoring
through probes at specific points in the process involves watching factors
to give prior warning that the target levels are under threat. Simulation is able
to help identify these probes and the threshold values that indicate a deterioration
of the process which will ultimately end in an unacceptable KPI.
CONSIDER THE ADVANTAGES OF EXPERIMENTATION:
Consider a health service example, where the number of patients admitted to
the clinic is a set number arriving according to a variable timing profile. To
establish the weekly variability of utilizations of clinical staff, the model can
be run for either a single run of 50 weeks or for 50 runs of a single week. Each
of these runs will enable the variation of utilizations to be observed and confidence
intervals calculated. Multiple runs are important. You would not judge
the fairness of a coin by just one or two tosses!
It is true that the above model is simplistic, as indeed the profile of patients
in such a model would probably vary in ways that would require more extensive
modeling (e.g., the definition of a likely profile over a longer period to take into
account current observed fluctuations from week to week). However, the experimentation
options hold true: either a short period of experimentation can be
repeated many times (with different random number sampling), or a model can
be run for a much longer time and the range of random effects can be observed.
How many repeats and how long to run a model are questions that can be
answered by a combination of input and output data analysis. It is important
when running a model that it experience all the randomness of the input data
and that the output results �settle down� before conclusions are drawn.
At a second level, a user may wish to alter different parameters within a
model to observe the different effects. Again, with this type of experimentation
the range of results might also be important, once they are more accomplished
through elongated or repeated experiments.
At a third level, a user may wish to compare one model with another. For
example, in manufacturing there may be two investment options: production
layout A and production layout B. These may indeed be the only options,
although within each solution there may be parameter choices (e.g., containing
buffer storage level options). In addition, there is again the optional value of
establishing the potential range of results.
With all these levels of experimentation, there are a variety of experimental
designs that can be used � different numbers of replications and different types
of factorial experimental designs, ranging from full factorial to half factorial to
Latin square-type designs where different parameter combinations are chosen.
For different models, the model itself can simply be considered a different type
of parameter.
the clinic is a set number arriving according to a variable timing profile. To
establish the weekly variability of utilizations of clinical staff, the model can
be run for either a single run of 50 weeks or for 50 runs of a single week. Each
of these runs will enable the variation of utilizations to be observed and confidence
intervals calculated. Multiple runs are important. You would not judge
the fairness of a coin by just one or two tosses!
It is true that the above model is simplistic, as indeed the profile of patients
in such a model would probably vary in ways that would require more extensive
modeling (e.g., the definition of a likely profile over a longer period to take into
account current observed fluctuations from week to week). However, the experimentation
options hold true: either a short period of experimentation can be
repeated many times (with different random number sampling), or a model can
be run for a much longer time and the range of random effects can be observed.
How many repeats and how long to run a model are questions that can be
answered by a combination of input and output data analysis. It is important
when running a model that it experience all the randomness of the input data
and that the output results �settle down� before conclusions are drawn.
At a second level, a user may wish to alter different parameters within a
model to observe the different effects. Again, with this type of experimentation
the range of results might also be important, once they are more accomplished
through elongated or repeated experiments.
At a third level, a user may wish to compare one model with another. For
example, in manufacturing there may be two investment options: production
layout A and production layout B. These may indeed be the only options,
although within each solution there may be parameter choices (e.g., containing
buffer storage level options). In addition, there is again the optional value of
establishing the potential range of results.
With all these levels of experimentation, there are a variety of experimental
designs that can be used � different numbers of replications and different types
of factorial experimental designs, ranging from full factorial to half factorial to
Latin square-type designs where different parameter combinations are chosen.
For different models, the model itself can simply be considered a different type
of parameter.
Fitting.Organization,.Environment,.and.ICT:
In the previous section, we argued that businesses can be involved in three types of organizational
integration. As the business needs to be integrated, ICT systems need to be
integrated, too (as is discussed in contingency theory; see, e.g., Borgatti, 2001). Therefore,
as companies are confronted with three basic types of integration at organizational level
(internal, within the Extended Enterprise, and with the marketplace) we should recognize
three levels of IT-integration as well.
The first type of IT-integration companies should realize is the internal integration of the
diverse systems within company walls generally referred to as �enterprise application integration�
(EAI).
The two other types of IT-integration concern B2Bi, the topic of this chapter. First there is the
extended enterprise integration (EEi). In the context of the extended enterprise, companies
that dispose of capabilities that are useful for each other try to cooperate/collaborate. It is
important to note that partnering organizations have decided to do business with each other
for an extended period of time. They know the other company can deliver to a certain extent
what is needed. A partnership is set up to get more out of the other company than what is
already being delivered, and it is recognized that some form of coordination is necessary to
realize additional benefits. Partnering enterprises need to find out how they can be of more
value to each other. The development of customized software is part of this value adding
effort. It is clear that partner-specific IT investments can be made.
Essentially, this is not the case in the other type of B2Bi. This second form of B2Bi we call
market B2Bi. Companies that do business in the marketplace do not cooperate/collaborate.
Basically for each transaction they try to find out who can deliver what is needed. Every
time again, companies have the free choice to choose the services from a company (present
in the marketplace) that fulfills the needs. Therefore, no thorough coordination among the
companies is needed. Of course, service-providing companies try to pick up signals from the
market to deliver the services that are useful, and they try to minimize costs, but there is no
partnering. This scenario shows the IT integration alternatives. Market Web services have
mainly been developed in isolation and may be found through a market mechanism such
as the global UDDI (universal description, discovery, and integration) registries. Furthermore,
organizations may do business with many other organizations through an electronic
marketplace. Figure 3 shows the ideas presented here.
Currently, the boundary between EEi and market B2Bi is vague. These two types of B2Bi
actually cover a whole continuum of B2Bi practices (as is also clear from organization theory).
With the current state of technology, we believe that Market B2Bi primarily concerns the
indirect integration through electronic marketplaces. In the future new Web services standards
and semantic Web standards may be developed that enable organizations to dynamically
integration. As the business needs to be integrated, ICT systems need to be
integrated, too (as is discussed in contingency theory; see, e.g., Borgatti, 2001). Therefore,
as companies are confronted with three basic types of integration at organizational level
(internal, within the Extended Enterprise, and with the marketplace) we should recognize
three levels of IT-integration as well.
The first type of IT-integration companies should realize is the internal integration of the
diverse systems within company walls generally referred to as �enterprise application integration�
(EAI).
The two other types of IT-integration concern B2Bi, the topic of this chapter. First there is the
extended enterprise integration (EEi). In the context of the extended enterprise, companies
that dispose of capabilities that are useful for each other try to cooperate/collaborate. It is
important to note that partnering organizations have decided to do business with each other
for an extended period of time. They know the other company can deliver to a certain extent
what is needed. A partnership is set up to get more out of the other company than what is
already being delivered, and it is recognized that some form of coordination is necessary to
realize additional benefits. Partnering enterprises need to find out how they can be of more
value to each other. The development of customized software is part of this value adding
effort. It is clear that partner-specific IT investments can be made.
Essentially, this is not the case in the other type of B2Bi. This second form of B2Bi we call
market B2Bi. Companies that do business in the marketplace do not cooperate/collaborate.
Basically for each transaction they try to find out who can deliver what is needed. Every
time again, companies have the free choice to choose the services from a company (present
in the marketplace) that fulfills the needs. Therefore, no thorough coordination among the
companies is needed. Of course, service-providing companies try to pick up signals from the
market to deliver the services that are useful, and they try to minimize costs, but there is no
partnering. This scenario shows the IT integration alternatives. Market Web services have
mainly been developed in isolation and may be found through a market mechanism such
as the global UDDI (universal description, discovery, and integration) registries. Furthermore,
organizations may do business with many other organizations through an electronic
marketplace. Figure 3 shows the ideas presented here.
Currently, the boundary between EEi and market B2Bi is vague. These two types of B2Bi
actually cover a whole continuum of B2Bi practices (as is also clear from organization theory).
With the current state of technology, we believe that Market B2Bi primarily concerns the
indirect integration through electronic marketplaces. In the future new Web services standards
and semantic Web standards may be developed that enable organizations to dynamically
The.Extended. Enterprise. vs.. Other.Forms. of.Doing. Business:
For a long time, two basic forms of economic organization have been recognized: markets
on the one hand and hierarchies (firms) on the other. Powell (1990) refers to
Ronald Coase as the person who first discussed the firm as a governance structure
rather than just as a black box that transforms inputs into outputs. Coase (1937)
asserts that firms and markets are alternative means for organizing similar
kinds of transactions. Only in the 1970s did ct upon Coase�s findings. One of these proponents,
Williamson (1975, 1985), argues that some transactions are more likely to take
place within hierarchically organized firms (Williamson equated firms with hierarchies)
than through a market interface. More specifically, he states that transactions that are to
be executed within hierarchically organized firms are likely to involve uncertainty about
their outcome, recur frequently and require substantial �transaction-specific investments�
(of money, time, or energy) that cannot be easily transferred. On the other hand, exchanges
that are straightforward, non-repetitive, and require no transaction-specific investments can
be expected to take place across a market interface. This dichotomous view of markets and
hierarchies�as discussed by Williamson (1975)�sees firms as separate from
markets and assumes the presence of sharp firm boundaries. These
sharp boundaries, however, do not always seem to be present. This is true especially in the
case of partnering organizations (extended enterprises, see Figure 1). Transactions between
partnering companies can be seen as a hybrid form of economic organization. That is, if
transactions are distributed as points along a continuum with discrete market transactions
located at one end and the highly centralized firm at the other end, partnering companies
fall in between these poles. The definition of Podolny and Page is very much aimed at
identifying the differences between the network form of organization on the one hand,
and markets and hierarchies on the other hand:
In pure markets companies do not aim at enduring relations, and in hierarchies there is a
clearly recognized, legitimate authority that can resolve disputes that arise among actors.
Besides these two characteristics, some scholars (e.g., Dore, 1983; Powell, 1990) have argued
that network forms of organization also posses another characteristic, namely a distinct ethic
or value-orientation on the part of exchange partners. Hirschman (1970) argues that partners
are willing to make relationship-specific investments without contractual guarantees protecting
those investments, and for Powell the norm of reciprocity is key (1990, pp. 303-304):
on the one hand and hierarchies (firms) on the other. Powell (1990) refers to
Ronald Coase as the person who first discussed the firm as a governance structure
rather than just as a black box that transforms inputs into outputs. Coase (1937)
asserts that firms and markets are alternative means for organizing similar
kinds of transactions. Only in the 1970s did ct upon Coase�s findings. One of these proponents,
Williamson (1975, 1985), argues that some transactions are more likely to take
place within hierarchically organized firms (Williamson equated firms with hierarchies)
than through a market interface. More specifically, he states that transactions that are to
be executed within hierarchically organized firms are likely to involve uncertainty about
their outcome, recur frequently and require substantial �transaction-specific investments�
(of money, time, or energy) that cannot be easily transferred. On the other hand, exchanges
that are straightforward, non-repetitive, and require no transaction-specific investments can
be expected to take place across a market interface. This dichotomous view of markets and
hierarchies�as discussed by Williamson (1975)�sees firms as separate from
markets and assumes the presence of sharp firm boundaries. These
sharp boundaries, however, do not always seem to be present. This is true especially in the
case of partnering organizations (extended enterprises, see Figure 1). Transactions between
partnering companies can be seen as a hybrid form of economic organization. That is, if
transactions are distributed as points along a continuum with discrete market transactions
located at one end and the highly centralized firm at the other end, partnering companies
fall in between these poles. The definition of Podolny and Page is very much aimed at
identifying the differences between the network form of organization on the one hand,
and markets and hierarchies on the other hand:
In pure markets companies do not aim at enduring relations, and in hierarchies there is a
clearly recognized, legitimate authority that can resolve disputes that arise among actors.
Besides these two characteristics, some scholars (e.g., Dore, 1983; Powell, 1990) have argued
that network forms of organization also posses another characteristic, namely a distinct ethic
or value-orientation on the part of exchange partners. Hirschman (1970) argues that partners
are willing to make relationship-specific investments without contractual guarantees protecting
those investments, and for Powell the norm of reciprocity is key (1990, pp. 303-304):
Approaches. to. Business.Modeling:
Business modeling is a vast area of research and practice, which is gaining increasing importance
in the rapid development of e-business and globalisation (Holsapple, 2001). The
following are some approaches used in business modeling:
1. Textual description (e.g., abstract use cases)
2. Categories and visualization
3. Simulation approaches
4. Data/workflow-description programs
5. Process notation languages (e.g., Unified Modeling Language (UML))
The common categorization of B2B models seen in the literature is divisions based on target
audience or type of products/services involved in the business processes.
In order to understand this categorization, we have first to observe the two dimensions
through which companies obtain the products and services they need (Kaplan & Sawhney,
2000). The first dimension is related to the kind of products and services purchased, and the
second relates to the frequency with which companies make their purchases. The products
and services can be classified into manufacturing inputs and operating inputs. Manufacturing
inputs are raw materials applied in the manufacturing process. Operating inputs are
normally low-value products and services, usually commodities (e.g., advertising, utilities,
electricity, office supplies), also known as maintenance, repair, and operations (MRO)
inputs. In relation to the frequency inputs are acquired, there are both systematic sourcing
and spot-market sourcing.
Another more general and easier-to-remember categorization can be attained by focusing on
the processes that these e-business models are designed to facilitate. E-businesses can support
the relationship between a company and its customers and suppliers (usually commercial
transactions) and with related partners like collaborators and contractors. Thus e-business
models can be classified according to its focus (IBM, 2003a; Weill & Vitale, 2001):
� Focus on the process of selling goods and services to other companies (e-commerce
sell-side)
� Focus on the process of e-procurement and other processes related to the supply chain
management. Various sub-models in this category are as follows:
o Buyer model (few buyers, many sellers)
o Marketplace model (many buyers and many sellers)
o Longer-term relationship model (few buyers and few sellers)
o Seller model (few sellers, many buyers)
� Focus on collaboration between businesses, partners, and contractors (i.e., e-collaboration,
in the rapid development of e-business and globalisation (Holsapple, 2001). The
following are some approaches used in business modeling:
1. Textual description (e.g., abstract use cases)
2. Categories and visualization
3. Simulation approaches
4. Data/workflow-description programs
5. Process notation languages (e.g., Unified Modeling Language (UML))
The common categorization of B2B models seen in the literature is divisions based on target
audience or type of products/services involved in the business processes.
In order to understand this categorization, we have first to observe the two dimensions
through which companies obtain the products and services they need (Kaplan & Sawhney,
2000). The first dimension is related to the kind of products and services purchased, and the
second relates to the frequency with which companies make their purchases. The products
and services can be classified into manufacturing inputs and operating inputs. Manufacturing
inputs are raw materials applied in the manufacturing process. Operating inputs are
normally low-value products and services, usually commodities (e.g., advertising, utilities,
electricity, office supplies), also known as maintenance, repair, and operations (MRO)
inputs. In relation to the frequency inputs are acquired, there are both systematic sourcing
and spot-market sourcing.
Another more general and easier-to-remember categorization can be attained by focusing on
the processes that these e-business models are designed to facilitate. E-businesses can support
the relationship between a company and its customers and suppliers (usually commercial
transactions) and with related partners like collaborators and contractors. Thus e-business
models can be classified according to its focus (IBM, 2003a; Weill & Vitale, 2001):
� Focus on the process of selling goods and services to other companies (e-commerce
sell-side)
� Focus on the process of e-procurement and other processes related to the supply chain
management. Various sub-models in this category are as follows:
o Buyer model (few buyers, many sellers)
o Marketplace model (many buyers and many sellers)
o Longer-term relationship model (few buyers and few sellers)
o Seller model (few sellers, many buyers)
� Focus on collaboration between businesses, partners, and contractors (i.e., e-collaboration,
A.Process-Based.Categorization. and.Analysis.of. Business-to-Business.Models:
The economic impact of the Internet is like the oil shock in reverse. The jump in oil prices
during the 1970s increased inflation and pushed the world into recession. However, the
Internet reduces the cost of information. This has positive economic effects, since it makes
it easier for buyers and suppliers to compare prices and eliminate the middlemen between
firms and customers, lowers transaction costs, and reduces entry barriers. Economists have
an interesting argument: the main reason why firms exist is to minimize transaction costs.
These reduced transaction and communication costs can lead to both bigger and smaller
optimal firm sizes. Smaller firms can buy services cheaply from outside, and this reduces
the barriers to entry.
The Internet can link up supply chains, make it easy to place and track orders, and display
specifications at the click of a mouse. Hence few companies are willing to miss out on
the benefits e-commerce offers. So, it is certain that the Internet reduces costs, increases
competition, and improves functioning of the pricing mechanism. The Internet moves the
economy closer to the theory of perfect competition, which assumes abundant information,
zero transaction costs and no entry barriers. Analysts feel markets should become more
efficient as the Internet increases the flow of information between buyers and sellers. This,
in turn, should ensure efficient allocation of scarce resources.
E-commerce increases competitive intensity by allowing business customers to consider
every available alternative to every offering. Suppliers no longer compete with two or three
familiar competitors but with every company in the world that has a web site and a comparable
product or service. E-commerce also undermines traditional sources of advantage based on
asymmetries of information. In the past, sellers derived some advantage by knowing more
than their buyers. Such an advantage came from knowing more about the product, the cost
availability of raw materials and components, and the efficiency of their own manufacturing
processes. Each step in the supply chain had a lock on its own information, which made
each link more defensible but the chain as a whole less efficient.
The Internet does away with much of this privileged access to information, shifting the
competitive emphasis away from secrecy and toward transparency and the absolute comparative
value of the offering. Distribution and sales channels have always conveyed a certain
amount of information back to suppliers. However, bandwidth, precision, ease, speed, and
manageability of the information flowing in both directions are orders of magnitude greater
on the Internet. The interactive exchange of information, design requirements, component
specifications, cost tracking, logistics oversight, service requests and troubleshooting advice
permits an unprecedented level of customization. Competition on this level will necessarily
become the rule.
As B2B e-commerce becomes one of the most profitable applications for the Internet, we
need to understand the implications of the many technological and market changes that will
usher in an entirely new way of doing business. The B2B e-commerce revolution includes
e-procurement, B2B exchanges, and business infrastructure relationships.
E-procurement involves firms selling supplies, equipment, materials, and services with
a streamlined online purchasing function that often eliminates traditional intermediaries,
thereby reducing costs and cycle times while offering greater flexibility and responsiveness
to changes in demand. Web-based supply chain management networks improve coordination
during the 1970s increased inflation and pushed the world into recession. However, the
Internet reduces the cost of information. This has positive economic effects, since it makes
it easier for buyers and suppliers to compare prices and eliminate the middlemen between
firms and customers, lowers transaction costs, and reduces entry barriers. Economists have
an interesting argument: the main reason why firms exist is to minimize transaction costs.
These reduced transaction and communication costs can lead to both bigger and smaller
optimal firm sizes. Smaller firms can buy services cheaply from outside, and this reduces
the barriers to entry.
The Internet can link up supply chains, make it easy to place and track orders, and display
specifications at the click of a mouse. Hence few companies are willing to miss out on
the benefits e-commerce offers. So, it is certain that the Internet reduces costs, increases
competition, and improves functioning of the pricing mechanism. The Internet moves the
economy closer to the theory of perfect competition, which assumes abundant information,
zero transaction costs and no entry barriers. Analysts feel markets should become more
efficient as the Internet increases the flow of information between buyers and sellers. This,
in turn, should ensure efficient allocation of scarce resources.
E-commerce increases competitive intensity by allowing business customers to consider
every available alternative to every offering. Suppliers no longer compete with two or three
familiar competitors but with every company in the world that has a web site and a comparable
product or service. E-commerce also undermines traditional sources of advantage based on
asymmetries of information. In the past, sellers derived some advantage by knowing more
than their buyers. Such an advantage came from knowing more about the product, the cost
availability of raw materials and components, and the efficiency of their own manufacturing
processes. Each step in the supply chain had a lock on its own information, which made
each link more defensible but the chain as a whole less efficient.
The Internet does away with much of this privileged access to information, shifting the
competitive emphasis away from secrecy and toward transparency and the absolute comparative
value of the offering. Distribution and sales channels have always conveyed a certain
amount of information back to suppliers. However, bandwidth, precision, ease, speed, and
manageability of the information flowing in both directions are orders of magnitude greater
on the Internet. The interactive exchange of information, design requirements, component
specifications, cost tracking, logistics oversight, service requests and troubleshooting advice
permits an unprecedented level of customization. Competition on this level will necessarily
become the rule.
As B2B e-commerce becomes one of the most profitable applications for the Internet, we
need to understand the implications of the many technological and market changes that will
usher in an entirely new way of doing business. The B2B e-commerce revolution includes
e-procurement, B2B exchanges, and business infrastructure relationships.
E-procurement involves firms selling supplies, equipment, materials, and services with
a streamlined online purchasing function that often eliminates traditional intermediaries,
thereby reducing costs and cycle times while offering greater flexibility and responsiveness
to changes in demand. Web-based supply chain management networks improve coordination
Achieving.the.Necessary.Coordination.in.Web.Services..Development:
The question concerning distributed vs. decentralized computing directly shows in a discussion
on standards. After all, standards play a big role in integrating systems; they resolve the need
for coordination (at the level at which the standard works). The concept of Web services is
currently receiving very much attention as a paradigm that allows B2Bi. The biggest strength
of this concept is just that it includes a set of ICT standards. Simple object access protocol
(SOAP), for example, is a standard way to communicate with Web services.
In building a business-to-business process, companies need to agree on a number of issues.
Agreement is not only needed at ICT level but also at business level. Above that, it is important
to know how to translate the business agreement into an ICT agreement, and�the
other way around�how to use ICT agreements to enable the business.
It is important to recognize the role of standards, their powers, and their threats. It can be
very useful to standardize issues�be it business issues or ICT issues�on which it does not
make any sense to compete. But of course, by standardizing some issues, competition shifts
to other issues. Companies want to make a difference somewhere. Standards such as SOAP
are very useful and lift the competition to the level of using the standard creatively.
There are different levels of compromise possible among parties (Besen & Farrell, 1994).
The levels of agreement on ICT issues are shown in Figure 5. Parties need at least bilateral
agreements. An active coordination among the parties is, however, not always necessary.
Some issues have already been standardized sufficiently at a higher level (for example at
the level of the software vendor). Clearly, companies do not have to discuss on the contents
covered by a standard anymore if they both agree to use the same existing standard.
Of course, not everything is being standardized. When it comes to technology, it is only where
interoperability is important that standards become required. Features that cause customer
dissatisfaction or hinder industry growth4 evolve into standards, while �customer-useful
differentiating features� do not tend to evolve into standards. Furthermore, the demand for
standards usually comes from the users and customers of the technology who experience
the confusion caused by the lack of standards (Cook, 1996). Employees (be it business or
ICT employees) may for example notice that there is no standard terminology for important
concepts in their company and that this creates communication problems. Companies then
consider creating a �data dictionary� with a standardized vocabulary. At the level of business-
to-business relations, companies may suffer from a non-standardized vocabulary too.
If one company uses the field �customerno� in its database, and another company uses the
field �customernumber,� both companies know the same concept but have a different name
assigned to the concept. In order to have IT systems of such companies talking to each other,
a translation will be necessary (from the standardized vocabulary of one company to the
standardized vocabulary of another company).
In choosing which level of agreement (and which standard) to use, it is important to evaluate
the opportunities that are being offered by the different levels (and standards at those levels).
As such, the presence/absence of network effects should be taken into account when deciding
when to use standards. Network effects are based on the concept of positive feedback,
that is, the situation in which success generates more success. The value of connecting to
a network depends on the number of other people already connected to it (i.e., you can
connect to). Network effects do not play in the extended
enterprise (�change partners� is a contradiction in terms), but they do play in market B2Bi
on standards. After all, standards play a big role in integrating systems; they resolve the need
for coordination (at the level at which the standard works). The concept of Web services is
currently receiving very much attention as a paradigm that allows B2Bi. The biggest strength
of this concept is just that it includes a set of ICT standards. Simple object access protocol
(SOAP), for example, is a standard way to communicate with Web services.
In building a business-to-business process, companies need to agree on a number of issues.
Agreement is not only needed at ICT level but also at business level. Above that, it is important
to know how to translate the business agreement into an ICT agreement, and�the
other way around�how to use ICT agreements to enable the business.
It is important to recognize the role of standards, their powers, and their threats. It can be
very useful to standardize issues�be it business issues or ICT issues�on which it does not
make any sense to compete. But of course, by standardizing some issues, competition shifts
to other issues. Companies want to make a difference somewhere. Standards such as SOAP
are very useful and lift the competition to the level of using the standard creatively.
There are different levels of compromise possible among parties (Besen & Farrell, 1994).
The levels of agreement on ICT issues are shown in Figure 5. Parties need at least bilateral
agreements. An active coordination among the parties is, however, not always necessary.
Some issues have already been standardized sufficiently at a higher level (for example at
the level of the software vendor). Clearly, companies do not have to discuss on the contents
covered by a standard anymore if they both agree to use the same existing standard.
Of course, not everything is being standardized. When it comes to technology, it is only where
interoperability is important that standards become required. Features that cause customer
dissatisfaction or hinder industry growth4 evolve into standards, while �customer-useful
differentiating features� do not tend to evolve into standards. Furthermore, the demand for
standards usually comes from the users and customers of the technology who experience
the confusion caused by the lack of standards (Cook, 1996). Employees (be it business or
ICT employees) may for example notice that there is no standard terminology for important
concepts in their company and that this creates communication problems. Companies then
consider creating a �data dictionary� with a standardized vocabulary. At the level of business-
to-business relations, companies may suffer from a non-standardized vocabulary too.
If one company uses the field �customerno� in its database, and another company uses the
field �customernumber,� both companies know the same concept but have a different name
assigned to the concept. In order to have IT systems of such companies talking to each other,
a translation will be necessary (from the standardized vocabulary of one company to the
standardized vocabulary of another company).
In choosing which level of agreement (and which standard) to use, it is important to evaluate
the opportunities that are being offered by the different levels (and standards at those levels).
As such, the presence/absence of network effects should be taken into account when deciding
when to use standards. Network effects are based on the concept of positive feedback,
that is, the situation in which success generates more success. The value of connecting to
a network depends on the number of other people already connected to it (i.e., you can
connect to). Network effects do not play in the extended
enterprise (�change partners� is a contradiction in terms), but they do play in market B2Bi
Scope.of.the.EDI.and.Web-EDI.Models.in.B2B:
EDI is the electronic transfer of business documents such as purchase orders or invoices
between computer systems of different enterprises based on an established norm/format
such as UN/EDIFACT or ANSI X.12 (Galileo Computing, 2003). EDI has now been used
for over 30 years for the exchange of business data (e.g., delivery notes and invoices as
mentioned above) between two application systems in a standardized and automated form
(Emmelhainz, 1993; Dressler, 2003). The benefits associated with traditional EDI include
cost reductions induced by rationalization and automation and shorter order processing
time (Deutsch, 1994).
Traditional EDI includes converters on both sides of the communication line. Data are normally
transferred between enterprises as illustrated in Figure 6. Therefore, on both sides, a
translation into formats understandable by different ERP systems such as SAP R/3 or JDEdwards
is to be guaranteed. Because of the early introduction and the market acceptance
of EDI systems in the 1980s, different standards exist for the description of EDI data (EDI
Comp., 2003).
Beck, Weitzel, and K�nig (2000) state that besides the alleged benefits, EDI is not as widespread
as many had expected. Presently only 5% of all companies that could benefit from
EDI actually use it (Segev et al., 1997) due to the considerably high costs for implementing
EDI systems (Swatman et al., 1997). New developments of innovative EDI solutions such
as Web-EDI or XML/EDI avoid the problems of traditional EDI technologies.
between computer systems of different enterprises based on an established norm/format
such as UN/EDIFACT or ANSI X.12 (Galileo Computing, 2003). EDI has now been used
for over 30 years for the exchange of business data (e.g., delivery notes and invoices as
mentioned above) between two application systems in a standardized and automated form
(Emmelhainz, 1993; Dressler, 2003). The benefits associated with traditional EDI include
cost reductions induced by rationalization and automation and shorter order processing
time (Deutsch, 1994).
Traditional EDI includes converters on both sides of the communication line. Data are normally
transferred between enterprises as illustrated in Figure 6. Therefore, on both sides, a
translation into formats understandable by different ERP systems such as SAP R/3 or JDEdwards
is to be guaranteed. Because of the early introduction and the market acceptance
of EDI systems in the 1980s, different standards exist for the description of EDI data (EDI
Comp., 2003).
Beck, Weitzel, and K�nig (2000) state that besides the alleged benefits, EDI is not as widespread
as many had expected. Presently only 5% of all companies that could benefit from
EDI actually use it (Segev et al., 1997) due to the considerably high costs for implementing
EDI systems (Swatman et al., 1997). New developments of innovative EDI solutions such
as Web-EDI or XML/EDI avoid the problems of traditional EDI technologies.
B2B.E-Procurement:
B2B e-procurement is used not only by participation in a procurement marketplace but also
as an enhancement of the existing conventional model. The goals of various e-procurement
business models are cost saving through exchanges/marketplaces, direct connection
of supply chain via electronic data interchange (EDI), Web-EDI, desktop purchasing, and
elimination/reduction of procurement department (Lee, 2001).
The above e-procurement models are normally implemented by e-procurement systems
and supplier portals. The major goals in most cases are process and marketing advantages,
such as:
� Availability: 24/7 availability is provided for a set of services 365 days a year
� Speed: Transactions are fulfilled faster, compared to non-electronic transactions
� Logistics efficiency considerations: Support for �Just in time delivery� and �Just in
sequence delivery�
� Integration.of.processes: Synergy effects of integrated processes can be achieved,
and parallelism of processes is supported. As a result, the time between the output of
one process to be recognized as an input to another process is significantly reduced.
Due to the integration of processes and systems, the complexity of the e-procurement
models increases as businesses further digitally enhance their business with e-procurement
facilities.
as an enhancement of the existing conventional model. The goals of various e-procurement
business models are cost saving through exchanges/marketplaces, direct connection
of supply chain via electronic data interchange (EDI), Web-EDI, desktop purchasing, and
elimination/reduction of procurement department (Lee, 2001).
The above e-procurement models are normally implemented by e-procurement systems
and supplier portals. The major goals in most cases are process and marketing advantages,
such as:
� Availability: 24/7 availability is provided for a set of services 365 days a year
� Speed: Transactions are fulfilled faster, compared to non-electronic transactions
� Logistics efficiency considerations: Support for �Just in time delivery� and �Just in
sequence delivery�
� Integration.of.processes: Synergy effects of integrated processes can be achieved,
and parallelism of processes is supported. As a result, the time between the output of
one process to be recognized as an input to another process is significantly reduced.
Due to the integration of processes and systems, the complexity of the e-procurement
models increases as businesses further digitally enhance their business with e-procurement
facilities.
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