Week 5 Project
Instructions
Case Study: Manufacturing Plant Network Setup
You will be presented with a situation showing the details of how a company is currently working, a manufacturing plant with various stand-alone computers and printers, and you will research and determine the best configuration to help the manufacturing plant network their computers and include connections to the Internet for all computers. You will need to explain and support the decisions and be able to explain how the changes will benefit the manufacturing plant, including describing how the changes will be managed and implemented.
urgenton time
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Managing Knowledge in Digital Firms—Part 2
Genetic algorithms: Solve speci�c problems using genetically based processes such as mutation, crossover, and �tness. Genetic algorithms are applicable to
problems involving product design, the monitoring of industrial systems, and optimization where many variables or alternatives are evaluated to generate an
optimal solution.
Expert systems: Extract tacit knowledge from a limited domain of human expertise and transform that knowledge into rules. An inference engine, which is a
methodology to search through the knowledge base, will use either forward or backward chaining. The forward chaining procedure uses the information that a user
enters as search criteria and then searches the rule base in the expert system to arrive at a conclusion. The backward chaining problem-solver approach starts with
a hypothesis and then seeks out more information until the hypothesis is either proved or disproved. Expert systems are most useful for solving problems of
diagnosis or classi�cation.
Case-Based Reasoning (CBR): Stores organizational knowledge in a database of cases that can be dynamically re�ned and expanded. When the CBR system faces a
new case, it searches its database for similar cases with solutions and workarounds, �nds the closest �t, and then applies the proven solutions to the new case. Once
proven the new case is added to the database of successful solutions. A temporary workaround is suggested until a new version of product is released with
permanent solutions. The CBR can notify clients or users when a new release or solution is available for installation.
Neural networks: Consist of a con�guration of hardware and software that attempts to mimic the human brain. Neural networks have the ability to recognize
patterns that humans can’t easily detect and learn without programming. Neural networks are utilized in medicine, science, and business primarily to differentiate
patterns buried within massive amounts of data.
Let us now explore how using DSS enhances management decision-making in organizations.
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Examples of DSS Applications—Part 1
Some of the many examples of DSS applications are:
Asset utilization: Parkway Corporation, Philadelphia, manages 100 garages and 30,000 parking spaces in East Coast cities from Jacksonville, Florida to
Toronto, Canada. Their new DSS system enables Parkway to analyze revenue by type of garage, rate structure, duration of stay, utilization rates, and overtime
costs. This enables managers to make better decisions on garage space allocation and pricing. Parkway can also identify its most pro�table customers and
determine the best mix of daily, weekly, and monthly parking in a speci�c city. The DSS system has helped Parkway increase the percentage of �lled spaces per
lot. In addition, Parkway increased revenue by nearly 10% and reduced overtime costs by 65%.
Customer Relationship Management (CRM): The U.S. division of The Body Shop International plc, the skin and hair product vendor from the U.K., wanted to
boost the ef�ciency of its mail order business. The Body Shop acquired predictive analysis software tools from Sightward to improve the analysis of its
database of web, store, and catalog customers. Predictive analysis used historical data, data mining techniques, and assumptions about future conditions to
predict outcome. The Sightward tools helped the company identify customers who were more likely to make catalog purchases. Therefore it could build a
more targeted and precise mailing list for the 120,000 copies of its fall 2001 catalog. Revenue per catalog increased from 10 to 20%.
Pricing decisions: ShopKo Stores Inc. in Greenbay, Wisconsin, has 162 ShopKo discount stores in midsize and large cities and 165 Pamida discount stores in
small rural communities. Pricing decisions made at each store have a large impact on pro�ts. ShopKo uses Spotlight Markdown Optimizer software to
determine the optimal price and time for marking down items. The software estimates a seasonal demand curve for each item. It also predicts the number of
units that will sell each week at various prices by analyzing sales data of several years for similar items. ShopKo often marked down items 3 or 4 times before
using this software. It now makes 1 or 2 markdowns to sell all items.
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Examples of DSS Applications—Part 2
Supply Chain Management (SCM): SCM systems use data about costs, inventory, logistics, production schedules, and supplier performance. This helps
managers search combinations of alternatives that are cost effective and ef�cient for moving goods through the supply chain. Sonoco Products Co., a global
manufacturer of consumer and industrial packaging, maintains hundreds of manufacturing operations around the globe and has a complex supply chain.
Sonoco started using Optiant Inc.’s PowerChain 4.0 design and analysis software to explore alternative scenarios with various costs, lead times, and raw
material inventory. They then set optimal inventory targets. The DSS software helped Sonoco store the right amount of inventory at the right location at the
right time. Therefore the new DSS system made it possible for Sonoco to �ll orders on time with inventory on hand 95% of the time.
Geographic Information Systems (GIS) and data visualization: GIS is a software that can analyze and display data using digitized maps. Therefore GIS
enhances decision making and planning. Data visualization is a technology used to help users see relationships and patterns in large amounts of data by
presenting data graphically. GIS can support decisions that require knowledge of the geographic distribution of people or other resources in development,
planning, resource management, and scienti�c research. General Electric Network Solutions collaborated with LinksPoint, which is a technology company
based in Norwalk, Connecticut, to develop GIS software that several municipal governments use to help prevent West Nile virus outbreaks. The software
analyzes information on the location and number of dead birds that host the West Nile virus to predict the magnitude and location of future epidemics. After
implementing this GIS system, Chicago and New York City were able to predict outbreaks with 80% accuracy two weeks before they occurred.
After understanding the importance of several DSS applications, let us now explore another DSS application, group decision support systems (GDSS). Organizations
use this application for group decision making.
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Managing Knowledge in Digital Firms—Part 1
Let us discuss how to manage knowledge in digital �rms.
Organizations can use a knowledge management IS to leverage organizational knowledge by making it easily available to users. Knowledge management is a set of
business processes designed to create, store, transfer, and utilize knowledge in the organization. Communicating and collaborating with experts and practitioners,
creating new knowledge, organizing and storing information, and using corporate knowledge to improve business processes have become vital for corporate
survival. Organizations require knowledge management systems because knowledge has become a source of competitive advantage and a strategic and central
productive asset in today’s knowledge-driven economy.
Some aspects of organizational knowledge are unstructured, tacit, and not easily codi�ed or captured. Tacit knowledge is the undocumented knowledge residing in
the minds of employees. On the other hand, documented knowledge is called explicit knowledge. Knowledge management captures and promotes organizational
learning by increasing the ability of an organization to incorporate knowledge into its business processes and learn from its environment.
The three principal approaches to knowledge management systems are:
Intelligent techniques
Knowledge work systems
Enterprise-wide knowledge management systems
Let us discuss some of these approaches.
Arti�cial Intelligence (AI): Captures, codi�es, and extends corporate knowledge even though it lacks the generality, breadth, and �exibility of human intelligence.
Firms use AI to help �lter and search information, discover knowledge, capture and preserve tacit knowledge, and generate solutions to problems that are too
complex and massive for human beings to analyze.
Fuzzy logic: Expresses knowledge in the form of rules that use subjective or approximate values. Fuzzy logic is a software technology used for limited decision-
making applications. But it has been traditionally used to control physical devices.
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Steps Required to Build a New IS
System development is structured problem solving with distinct activities that convert an IS solution to a business opportunity. The system development process
consists of:
Systems analysis: Analyzes and studies the problems of existing systems and identi�es requirements for their solutions. A systems analyst conducts a
feasibility study, which is a way to determine whether the solution is achievable with the �rm’s constraints and resources. The systems analyst de�nes the
speci�c information requirements that the selected system solution should meet. Information requirements include a detailed statement of the information
needs that the new system should satisfy, identi�es who requires what information, how, when, and where.
Systems design: Provides the speci�cations for an information system solution, showing how its organizational and technical components �t together.
Programming: Translates the system speci�cations prepared during the design stage into program code.
Testing: Determines whether the system produces the desired results under known conditions. The three types of tests are:
Unit testing separately tests each program in the system.
System testing tests the functioning of the entire IS to determine if discrete modules will function together, as planned.
Acceptance testing provides the �nal certi�cation that the system is ready for use in a production environment.
The development team prepares a test plan after user approval. The plan includes all the preparations for the series of tests to be performed on the system to certify
the system for production.
Conversion: Changes from the old system to the new system utilizing one of the four principal conversion strategies. They are:
Direct Cutover strategy: The new system completely replaces the old one on a selected day.
Parallel strategy: Both the old system and its potential replacement are run together for a time until everyone is assured that the new one functions
correctly.
Phased Approach strategy: The new system is deployed by organizational units, functions, or geography.
Pilot Study strategy: The new system is introduced to a limited area of the enterprise until it proves to be fully functional. Conversion takes place across
the entire enterprise only after this.
Maintenance and production: Production is the stage after the new system is installed and conversion is complete. In this time, technical specialists and
users carefully review the system to determine how well it has met its original goals. Sometimes a formal post-implementation audit document is
prepared. After the system is �ne-tuned, it will need maintenance. This occurs over time and changes in software, procedures, documentation, or
hardware meet new requirements, improve processing ef�ciency, or correct errors.
In the next lecture page, we will discuss some alternative methods for building IS.
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Alternative Methods for Building IS
The selection of a systems-building approach can have a big impact on the cost, time, and result of systems development. Let us discuss some alternative methods
for building IS:
Systems Lifecycle: Develops IS in formal, sequential stages that have a de�ned output. The system lifecycle is useful for large projects that require tight
management control and formal speci�cations over each stage of system building. The weakness of this approach is that it’s costly, rigid, and not suited for
decision-oriented, unstructured applications where requirements can’t be immediately visualized.
Application Software-Based IS: Eliminates the requirement for writing software programs when developing IS. You don’t spend as much time designing,
installing, testing, and maintaining the new system. Application software packages are helpful if an organization doesn’t have the �nancial resources or
internal IS staff to customize a system. The weakness of this alternative is that when packages need extensive modi�cations to meet a �rm’s unique
requirements, development costs may increase.
Prototyping: Builds an experimental system inexpensively and quickly for evaluation and demonstration to users for determining information requirements.
Continuous re�nement of the prototype occurs until all the requirements of the users are satis�ed. This then acts as a template to create the �nal system. The
weakness of this approach is that the rapid creation of prototypes can result in systems that have not been completely documented or tested or are technically
inadequate for a production setting.
End-User development: Refers to the development of IS by end users with minimal assistance from IS specialists. These systems are created using fourth-
generation software tools. The primary bene�ts are an improved requirements determination with increased end-user participation. The system development
process is controlled while the total application backlog is reduced. The weakness of end-user development is that distributed computing introduces new
organizational risks due to low quality data resources and IS.
Outsourcing: Subcontracts computer center operations, applications development, or telecommunications networks to external vendors. Outsourcing can
save application development costs or allow �rms to develop applications without internal information systems staff. The weakness here is that organizations
might lose control over their information.
After discussing some alternative methods for building IS, let us focus on web-based ESS and EAI software which integrate software applications and enhance
decision making.
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New Systems and Organizational Changes
Constructing a new IS involves a planned organizational change that should coordinate many people in the enterprise. Four structural organizational changes that IT
enables are:
Automation: Refers to the use of the computer to speed up the performance of existing tasks.
Rationalization of procedures: Refers to the streamlining of standard operating procedures (SOPs) and eliminating obvious bottlenecks so that automation
makes procedures ef�cient.
Business process re-engineering: Refers to the radical redesign of business processes, eliminating paper-intensive, repetitive tasks to improve service, quality,
and cost. The aim is to combine steps to reduce wastage and maximize the bene�ts of IT.
Paradigm Shift: Refers to the reconceptualization of the nature of the organization and that of the business, with far-reaching changes carrying the greatest
rewards and risks.
In many instances businesses seeking paradigm shifts and pursuing re-engineering strategies achieve stunning, order-of-magnitude increases in ROI or productivity.
Other Roles of IS
IS can also support business process management (BPM), Six Sigma, TQM, and other initiatives for incremental process improvement. Let us discuss each one in
detail:
BPM: Consists of business process modeling, change management, quality management, and work�ow management. Organizations that practice BPM use
process-mapping tools to de�ne and document existing processes and create models of improved processes that can then be coded into software systems. The
output of BPM includes analytics and process monitoring. Firms are able to measure the impact of process changes on key performance indicators and verify
that process performance has improved.
Six Sigma: Measures quality to represent 3.4 defects per million opportunities and designates a set of techniques and methodologies for reducing costs and
improving quality. It uses statistical analysis tools to detect �aws in the execution of an existing process and make minor adjustments. General Electric,
Johnson & Johnson, and Toyota have implemented Six Sigma methodologies with great success.
TQM: Makes quality control the responsibility of all the people in an enterprise. Quality management concepts that are developed by American quality
experts, Joseph Juran and W. Edwards Deming, and popularized by the Japanese, are together known as TQM. TQM focuses on making a series of continuous
improvements rather than dramatic bursts of change.
Benchmarking: Sets strict standards for activities, products, or services and measures organizational performance against the standards. Firms use standards
set by other �rms, external industry standards, or internally developed high standards for benchmarking.
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Understanding the Business Value of IS
Let us discuss the various ways in which IS can provide business value to a �rm. The categories of methods are traditional capital budgeting models, models based on
strategic considerations, and models that measure productivity and pro�tability.
Traditional Capital Budgeting Models
Capital budgeting models determine if an investment in IT provides suf�cient returns to justify its costs. The main capital budgeting models are:
Accounting Rate of Return on Investment (ROI): Calculates the rate of return on an investment by adjusting the cash in�ow produced by the investment for
depreciation. This gives the approximate accounting income that the project earned.
Cost-bene�t ratio: Calculates the return on capital expenditure by dividing total bene�ts by total costs.
Internal Rate of Return (IRR): Calculates the rate of pro�t or return that an investment is expected to earn.
Net Present Value (NPV): Calculates the amount of money an investment is worth, taking into account its cost, earnings, and the time value of money.
Payback method: Calculates the time required to repay the initial investment of a project.
Pro�tability index: Compares the pro�tability of investments by dividing the present value of the total cash in�ow from an investment by the initial cost of the
investment.
After discussing the traditional capital budgeting models, let us focus on models based on strategic considerations.
Models Based on Strategic Considerations
Some models for evaluating IS investments use strategic and non�nancial considerations. They include:
Portfolio Analysis: Analyzes the portfolio of potential applications within an organization. The analysis helps determine bene�ts and risks and select among
alternatives for IS. The management can determine the optimal mix of investment, reward, and risk for their �rm by balancing safer, lower-reward projects
with riskier, high-reward ones.
Scoring Models: Decide among alternative systems based on a system of ratings for selected objectives. It evaluates two different ERP systems by measuring
how well they will be able to meet the information requirements of the �rm.
Real Options Pricing Models (ROPM): Evaluate IT investments with uncertain returns by using techniques for valuing �nancial options. ROPM allows
managers to systematically consider the volatility in the value of IT projects over time, the changing cost of implementation as interest rates or prices fall or
rise over time, and the optimal timing of the investment.
Knowledge Value-Added Approach: Uses knowledge input in IT to change business processes. Knowledge input is measurable in terms of the learning time
required to master a new process and then estimate a return on knowledge.
Pro�tability and Productivity: Uses multifactor productivity, which is a measure of the ef�ciency of the company, to convert input to output. It refers to the
amount of labor and capital required to produce a unit of output.
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Information Systems Security and Control
IS in different locations can be interconnected using a communication network. Potential for abuse, fraud, or unauthorized access is not limited to one location but
can occur at any access point on the network. Computerized IS are vulnerable to destruction, errors, fraud, misuse, and software and hardware failure. In addition
many procedures are invisible due to automation and data concentrated into electronic form. Let us categorize these security issues.
Intruders can easily penetrate wireless networks using sniffer programs to obtain an address to access the resources of the network. The Wi-Fi network range
can extend up to one-quarter of a mile using an external antenna.
The Internet poses a set of problems because it allows easy access by people on different computer systems.
The primary concern is that of hackers who use their skills and the latest technology to break into secure computers and disable them. A hacker is a person
who gains unauthorized access to a computer network for criminal mischief, personal pleasure, or pro�t. In denial of service attacks, hackers �ood a Web or
network server with thousands of requests for service or false communications to crash the network. Hackers propagating computer viruses and other
malicious code have caused serious system disruptions. Computer viruses are rogue software programs that attach themselves to other data �les or software
programs and replicate themselves repeatedly disrupting memory and processing systems or destroying data. Several thousands of viruses are known to
exist today, and more than 5,000 new worms and viruses are being added each year. Worms are independent software programs that propagate themselves to
destroy other programs and data or disrupt the operation of computer networks. Viruses and worms are often spread through the Internet from downloaded
software �les attached to the e-mail messages or from within compromised e-mail. They can also come from infected diskettes or from other computer
networks. Viruses are also spreading to wireless computing devices. Individuals and organizations can use screening procedures and antivirus software to
reduce the chances of infection.
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Summary
This week you explored how knowledge management helps businesses capture, create, distribute, and apply information and knowledge to enhance decision
making and business processes across digital enterprises. Today’s organizations require knowledge management systems because knowledge has become a
potential source of competitive advantage and a strategic and central productive asset in today’s information economy.
You also learned how DSS enhances business performance by helping managers make better decisions. You discussed several DSS applications and learned how
GDSS facilitates decision makers to work together as a group rather than individually.
In addition, you explored how organizations can use IS to redesign their business processes and organizations.
You investigated Web-based ESS and EAI software and learned how EAI integrates applications on a common platform and how to tie the interfaced information
into an ESS.
You learned about change management to ensure success when implementing IS. The lectures focused on a few techniques to avoid system failure.
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Concerns for Users and System Builders
The vulnerability of automated data has contributed to the following concerns of users and system builders:
Cyber-warfare and Cyber-terrorism: Foreign intelligence services, terrorists, or other groups could exploit the vulnerabilities of the Internet or other
networks to create widespread harm and disruption. Cyber attacks might target software that executes air-traf�c control systems, electric power grids, or
networks of major �nancial institutions or banks. The U.S. government created National Infrastructure Protection Center in February 1998 to act as a liaison
between corporations and the U.S. government and provide an early warning system for cyber attacks. The Pentagon has formed a Joint Task Force, named
Computer Network Operations, to coordinate offensive and defensive information warfare programs.
Disaster: Many corporations contract with disaster recovery �rms such as SunGard Recovery Services located in Wayne, Pennsylvania, and Comdisco
Disaster Services in Rosemont, Illinois. These disaster recovery companies provide hot sites housing spare computers at locations around the country where
subscribing �rms can run their critical applications in an emergency. Disaster recovery services offer backup for traditional mainframe applications as well as
client/server systems.
Computer errors: Computers can serve as instruments of error by severely disrupting or destroying an organization’s operations and record keeping. Poor
software caused the crash of Mars Polar Lander operated by U.S. National Aeronautics and Space Administration (NASA) in December 1999. Errors in
automated systems can occur at many points in the processing cycle through:
Computer operations
Data entry
Hardware
Program code
Security: Security refers to the procedures, policies, and technical measures used to prevent unauthorized access, theft, alteration, or physical damage to IS.
Let us learn about some quality problems associated with the software and data used in organizations.
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DSS to Manage Decision Making
Let us now discuss how DSS works in conjunction with business intelligence to manage decision making in an organization. Business intelligence is the intersection
of the needs of the business and the available information necessary to make the best business decisions. Business intelligence IS include the Internet, extranets,
intranets, online transaction processing (OLTP), operational data stores (ODS), data warehouses (DWs), data marts (DMs), analytical applications (AAs), data mining
applications, statistical analysis applications, predictive modeling applications, reporting systems, and data islands.
Let us explore the concepts of DSS.
Decision Support Systems
A DSS provides new sets of capabilities for user control and nonroutine decisions. With DSS, effort required to link users to structured information �ow is reduced
and greater emphasis is placed on models, ad-hoc queries, display graphics, and assumptions. The two basic types of DSS are:
Data-Driven DSS: Is a system that supports decision making by allowing users to analyze and extract useful information previously buried in large databases.
Often data from transaction processing systems (TPS) is collected in data warehouses for this purpose. Online analytical processing (OLAP) and data mining is
then used to analyze the data.
Model-Driven DSS: Is primarily a stand-alone system that uses a model to perform what-if and other types of analyses. These systems were often developed
by end-user divisions or groups not under the control of central IS. Their analysis capabilities were based on a model or strong theory combined with a user
interface. This made the model easy to use.
The types of information that data mining can yield include:
Associations and occurrences linked to an event. For example, a person who purchases corn chips from a supermarket also purchases cola 65% of the time.
Classi�cation recognizes patterns that describe the group to which an item belongs by examining existing, classi�ed items and by inferring a set of rules.
Work is clustered in a manner similar to classi�cation when no groups have been de�ned.
Forecasts sales �gures with the help of existing values.
Sequences occur when events are linked over time. For example, if somebody purchases a house then the person will also purchase a new refrigerator within
two weeks 65% of the time.
Components of DSS
A DSS database is a collection of historical and current data from several groups or applications. The source can be a massive data warehouse or a small,
computerized database. A DSS software system is a collection of software tools used for data analysis such as data mining and OLAP tools or a collection of
analytical and mathematical models. A model is an abstract representation that illustrates the relationships or components of a phenomenon. A model can be
mathematical, physical, or verbal. Statistical modeling software helps establish relationships such as relating product sales to differences in income, age, or other
factors among communities. Optimization models use linear programming to determine optimal resource allocation to either maximize pro�ts or revenue or
minimize time or costs. A classic use of optimization models is to determine the proper mix of products within a market to maximize pro�ts. Model sensitivity
analysis models ask what-if questions to determine the impact of changes in multiple factors on outcome.
After learning the concepts of DSS, let us focus on its applications and uses.
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Global Systems Implementation Challenges
The implementation challenges are:
IS for each country in the international community re�ects local political, social, and cultural conditions, which may not be compatible with global information
�ow and business processes. European countries have strict laws governing privacy and trans-border data �ow, which is the movement of information in any
form across international boundaries. English has become a standard business language. Software may have to be built with local language interfaces before
new IS can be successfully implemented.
The lack of reliable communications infrastructure and the high costs of installation is a great challenge in implementing IS in under-developed countries.
Existing standards for Electronic Data Interchange (EDI) and networking are country-speci�c and industry-speci�c. The Open Systems Interconnect (OSI)
reference model for linking networks is more popular in Europe than it is in the U.S. Various industry groups have also standardized other networking
architectures.
Businesses with enterprise systems, supply chain management, and other cross-functional systems are not always compatible with business processes,
cultural heritages, and languages in other countries.
It is dif�cult to convince local managers anywhere in the world to change their business processes to coordinate the development of projects around the world
in the absence of a powerful telecommunications network. It is also dif�cult to encourage local users to take on ownership of the developed systems.
After understanding the challenges faced during the IS implementation process, let us now explore the security and control measures that IS adopts to ensure
organizational data safety.
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Web-Based ESS and EAI Software—Part 1
When EAI middleware integrates and ties key applications together on a common platform, it is a good idea to tie the interfaced information into an ESS to help
senior managers speed up decision-making. ESS helps senior executives with unstructured problems, combining data from external and internal sources to create a
generalized communications and computing environment. This data is used to apply and focus on a changing array of problems. ESS helps forecast trends, identify
problems, monitor organizational performance, spot problems, and track the activities of competitors while increasing the upper management’s span of control. ESS
gives executives the ability to drill down, moving from a piece of summary data to lower levels of detail. OLAP tools for analyzing large databases provide this
functionality.
Implementations of ESS can take on the following different forms:
Activity-Based costing: Identi�es all the corporate activities that incur costs while producing a speci�c service or product. This helps managers see which
services or products are at a loss or a pro�t so that they can make changes to maximize pro�tability. SAP offers a web-enabled mySAP Strategic Enterprise
Management module that features corporate performance metrics, planning, and simulation tools. Executives can use the Management Cockpit tool to
monitor strategic performance indicators using external and internal benchmarks. The system can focus on customer accounts and contribution margins with
the ability to calculate the lifetime and current value of each account instead of reporting in terms of income and product. Detroit Edison which is the seventh-
largest electric utility company in the U.S. needed an in-depth understanding of the true nature of its costs to cope with new sources of competition and
deregulation. It implemented PeopleSoft’s Activity-Based Management (ABM) analytics software, which provides executives with operational views of the
processes and activity costs for which they are personally responsible. ABM extracts information from existing ERP systems to provide industry-speci�c, high-
level, role-based pro�tability and performance measurements, reporting, and analysis. The software helped the company analyze their production processes
and costs to identify cost reduction opportunities and process improvements to save millions of dollars.
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Software and Data Quality Problems
Software presents some quality problems because it may be impossible to eliminate software bugs due to the high costs of correcting software errors. Data quality
can also affect system performance and quality. Three principal areas that contribute to system quality problems are:
Defects and Bugs: Bugs are program code errors or defects. About 60% of errors discovered during testing are due to speci�cations that are ambiguous, in
con�ict, in error, or missing in design documentation. Zero defects can’t be achieved in large programs. Even with rigorous testing you will never know for sure
that a piece of software is dependable until the product proves itself as such after rigorous operational use. We can’t eliminate all bugs and we can’t accurately
know the seriousness of existing bugs.
Data quality problems: Poor quality data is the most common source of IS failure. Data that is inaccurate, inconsistent, or untimely with other sources of
information can create serious �nancial and operational problems for businesses. Poor data quality might stem from errors during faulty database and IS
design or data input.
Maintenance nightmare: Maintenance is the most expensive phase of the systems development process. Nearly half of the time of IS staff is spent on
maintaining existing systems in most businesses. The enterprise might experience large internal changes in leadership or structure or change may come from
the surrounding environment. The organizational changes affect information requirements. Software complexity and faulty analysis of information
requirements, systems analysis, and system design also contribute to long-term software maintenance problems.
Control Environment
Controls consist of all the methods, organizational procedures, and policies that ensure the safety of an organization’s assets, adherence to management standards,
and reliability of accounting records. The two primary categories of controls are:
Application controls: Are unique to speci�c, computerized applications. They focus on the accuracy and completeness of input, maintenance, updating, and
validity of the information contained in the system. Application controls include input controls, processing controls, and output controls.
General controls: Handle the overall design, security, and use of computers, �les, and programs for the organization’s IT infrastructure. General controls
consist of administrative disciplines, computer operations controls, controls over the system implementation process, data �le security controls, physical
hardware controls, and system software controls.
Risk assessment: Speci�es that users and designers of systems must identify all the control weaknesses and control points to perform risk assessment. They should
also perform a cost-bene�t analysis of controls and design controls that can effectively safeguard systems without making them too cumbersome to use.
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IS Plans
An IS plan is a road map indicating the direction of systems development. This includes:
Strategic systems plans
Current systems
New developments
Management strategy
Implementation plans
Budget requirements
Let us understand how an IS plan works in an organization. The organization should ful�ll some requirements for an IS plan to work. Let us discuss these
requirements.
New Systems Should Support Business Plans
Enterprise analysis and critical success factors (CSFs) can elicit enterprise-wide requirements that the plans must address. Let us explore these two terms.
Enterprise analysis: Is an analysis of enterprise-wide information requirements that examines the entire organization in terms of organizational units,
functions, processes, and data elements. The analysis pulls out the key attributes and entities buried in the �rm’s data. This analysis interviews a large sample
of managers on their objectives and data needs, how they use information to make decisions, what is the source of their information, what are their
environments, and who are the people affected. Data elements are organized into logical application groups that support related sets of organizational
processes. The output of an enterprise analysis shows what information is required to support a particular process, which processes create the data, and
which use them.
CSFs: Are a small number of easily identi�able operational goals that the industry, the organization, the manager, and the environment share. CSFs determine
the information needs of the �rm and assure its success. The CSF methodology asks managers to examine their environment and consider how their analysis
shapes their information requirements.
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Web-Based ESS and EAI Software—Part 2
Balanced Scorecard model: Analyzes organizational performance that supplements traditional �nancial measures with measurements from additional
business perspectives, including customers, growth, learning, and internal business processes. Pharmacia Corporation, which is a global pharmaceutical
company based in Peapack, New Jersey, uses Oracle’s Balanced Scorecard software and a data warehouse to ensure that the �rm is operating in a coordinated
manner. Pharmacia develops and delivers innovative medicines and has 43,000 employees and more than $16 billion in annual revenue. The product
development cycle for a new drug typically takes seven years. Pharmacia can use the scorecard system to see how funds allocated for research are being
spent, to monitor the number of patents in clinical trials, and to track the attrition rate of new compounds under study. The CEO of General Electric (GE)
Jeffrey Immelt, and his senior managers can obtain a solid overview of each division and of the entire corporation in a matter of minutes by using the digital
dashboard from GE’s intranet. The dashboard displays key performance indicators that give top executives quick, clear pictures of the �nancial health of the
company. GE’s dashboard presents information in nine categories, including headcount, orders, pricing, and sales, with divisional dashboards displaying critical
information speci�c to their own units.
Competitive Intelligence: Gathers intelligence with the special capabilities of the Internet combined with new models. Four Star Distribution is a designer and
distributor of innovative skateboarding and snowboarding equipment that is based in San Clemente, California. Four Star needs to stay abreast of the latest
global buying trends in a volatile industry catering to young adults and teenagers. It relies on a hosted Oracle E-business suite with Oracle 9i/AS Discoverer
ad-hoc query, analysis, and reporting software to provide accurate, up-to-date information on the performance of its global buying trends and business. One
report tracks footwear and shows which shoes are the most popular and where in the world they are selling the best. This information is immediately shared
with its manufacturers, sales representatives, and distributors to get the latest products to the customer before the new selling season begins.
/
Implementation and Challenges
The risk level of each project determines the appropriate mix of formal planning, control tools, external integration tools, and internal integration tools. Let us
discuss the important aspects of implementing IS.
Formal planning and control tools: Formal planning sequences and structures tasks. Planning also handles the budgeting of technical resources, time, and
money required to complete the tasks. Formal control helps monitor progress toward ful�llment of goals and completion of tasks. Microsoft Project is a
standard tool that can be used to:
Link tasks sequentially.
Assign responsibilities to each task.
Estimate the duration of each task.
Display all tasks across a timeline of days, weeks, and months.
Create Gantt Charts, resource allocation reports, and budget reports.
Overcoming user resistance by increasing user involvement: Projects with many unde�ned requirements and relatively less structure should involve users at
all stages. External Integration tools link the work of the implementation team to users at all organizational levels. Special organizational architects bridge
communication gaps between technology specialists and business users. If the use of the system is mandatory, resistance may take the form of increased
disruption, error rates, turnover, and sabotage. If the use of the system is voluntary, users may choose to avoid it.
Managing technical complexity: Internal Integration tools help projects with complex and challenging technology by ensuring that the implementation team
operates as a cohesive unit. Project leaders need to anticipate problems and develop smooth working relationships among a predominantly technical team.
Challenges during implementation process
The entire implementation process and IS design should be managed as planned organizational change. Let us discuss some of the considerations when
implementing IS in an organization. They are:
Organizational impact analysis: Studies the way a proposed system will affect attitudes, decision-making, operations, and organizational structure.
Quality of IS: Is evaluated in terms of user criteria rather than the criteria of the IS staff. System objectives should include standards for user performance in
addition to targets of access rates, calculation times, and memory size.
Participatory design: Emphasizes the participation of the individuals most affected by a new system. Areas of user interface with the system should be
carefully designed with sensitivity to ergonomic issues.
Sociotechnical design: Is the optimal blend of social and technical design solutions. Social design plans explore the allocation of tasks, design of individual jobs, and
different workgroup structures. As a result, the �nal sociotechnical design produces an IS that blends sensitivity to human and organizational needs with technical
ef�ciency, leading to high job satisfaction.
/
Software and Data Quality Assurance
Various development methodologies and tools are employed by organizations to help system builders analyze, design, document, and implement IS. A development
methodology is a collection of methods, one or more for each activity within each phase of a development project. Using a standard development methodology,
software metrics, thorough testing procedures, and allocating resources to place emphasis on the analysis and design stages of systems development can improve
the reliability and quality of software. Let us focus on some methodologies and tools:
Structured methodologies: Have been used to increase software quality from the 1970s. Structured refers to the fact that techniques are carefully drawn up,
systematic, with each step building on the previous one. Structured analysis highlights the �ow of data and the processes through which data is transformed.
Its main tool is data �ow diagram (DFD).
DFD: Graphically illustrates a system’s component processes and the �ow of data between them. Process speci�cations describe the logic of the process
occurring within the lowest levels of the DFD.
Structured design: Is the software design discipline encompassing a set of design techniques and rules for designing systems in the top-down hierarchical
fashion.
Structured chart: Is the system documentation that shows each level of design, the relationship among the levels, and the overall place of each level in the
design structure. It can document a program, a system, or part of a program.
Uni�ed Modeling Language (UML): Provides a standard methodology for modeling an object-oriented system that promotes consistency during analysis,
design, and implementation.
Computer-Aided Software Engineering (CASE): Automates methodologies for systems development. CASE improves consistency and coordination and
promotes standards during systems development. CASE tools help system builders construct a better model of a system and facilitate revision of design
speci�cations in sync with the correction of errors. System Architect by Popkin Software is an excellent example of a CASE tool based on the Zackman
Framework. The system architect’s support for enterprise applications includes:
Business Modeling
Data Modeling
Structured Modeling
Object-Oriented Modeling
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Application of Management Information Systems
© 2013 South University
Page2 of 2
Application of Management Information Systems
© 2013 South University
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Enhancing Management Decision Making for Digital Firms (3 of 3)
(http://www.teamspace.com/)
Group Decision Support Systems
GDSS is an interactive computer-based system. It assists decision makers to solve unstructured problems and work together as a group rather than individually.
GDSS consists of hardware, people, and software elements. These are:
Hardware: Includes conference facilities such as chairs and tables. It should include some electronic hardware such as audiovisual equipment, computers,
electronic display boards, and networking equipment.
People: Includes trained facilitators and participants with hardware and software support staff on call.
Speci�c GDSS Software Tools: Include tools that support group meetings such as:
Electronic brainstorming tools
Electronic questionnaires
Group dictionaries
Idea organizers
Policy forming tools
Questionnaire tools
Stakeholder identi�cation and analysis tools
Tools for setting priorities or voting
Together these elements have led to the creation of different types of GDSS from elaborate collaboration laboratories to simple electronic boardrooms. Their input
is integrated on a �le server and can be viewed on a common, large screen. In most systems, integrated input is also viewable on the participant’s screen.
A GDSS helps decision makers arrive at decisions more ef�ciently. It increases the productivity of a meeting attended by more than four or �ve people. The
documentation of a meeting by a group at one site is also usable as input for another meeting on the same project at another site which contributes to organizational
memory. GDSS can lead to democratic and participative decision-making when used by project teams for frequent meetings.
Let’s now discuss the role of IS in redesigning an organization.
/
Change Management
IT has increased productivity in the process of manufacturing IT products as well as in retail. Wal-Mart has experienced an increase in pro�tability and productivity
over the past 10 years through powerful supply chain management systems and managerial innovations. The banking industry didn’t experience any gains in
productivity throughout the 1990s even though they were one of the most intensive users of IT. Corporate cost-reduction and downsizing measures have increased
employee ef�ciency but have not yet led to sustained enhancements that signify genuine productivity gains. Up-to-date IT infrastructures make e-commerce
investments in business performance improvements more effective.
Change Management
The process of planned organizational change should be carefully managed when building an information system. The systems analyst is a change agent in the
implementation process who ensures successful organizational adaptation to new innovation or a new system.
A large percentage of IS fail to solve the problems of organizational change. The main causes of system failure are:
Lack of management support: An IS project is more likely to be perceived positively by technical information services staff and users if it has the commitment
and backing of management. Managerial backing ensures that an IS project will receive suf�cient resources and funding to be successful.
Level of complexity and risk: Project structure, project size, and the level of technical expertise of the project team, and the information staff in�uence the
level of project risk.
Poor management of the implementation process: There are several reasons for poorly managed projects. Slippage in projects, doubts, and failure is often not
reported to the senior management. Optimism and ignorance also count a lot towards a poorly managed project. The traditional unit of measurement used by
system designers to project costs of different heads is man-month. Adding personnel to projects doesn’t necessarily reduce the time required to complete a
systems project. It often slows down delivery. Users need to get and stay involved in the design process of a new information system. Communication
problems between designers and end users are a primary reason why all user requirements are not properly incorporated into IS and why many users are
driven out of the implementation process.
Let us now discuss the important aspects of implementation of IS in the change management environment.
/
Criteria
No Submission
0 points
Emerging (F
through D Range)
(21-24)
24 points
Satisfactory (C
Range) (25-28)
28 points
Proficient (B Range)
(29-31)
31 points
Exemplary (A
Range) (32-35)
35 points
Criterion
Score
Provided an
executive
summary of
the
project
including all
parts of the
report.
/ 35Component is not
addressed
Component does
not meet
assignment
expectations
Component is
addressed but with
noticeable errors
Component meets
expectations with
minor errors
Component fully
meets or exceeds
expectations
Criteria
No Submission
0 points
Emerging (F
through D Range)
(21-24)
24 points
Satisfactory (C
Range) (25-28)
28 points
Proficient (B Range)
(29-31)
31 points
Exemplary (A
Range) (32-35)
35 points
Criterion
Score
Explained the
potential
success of the
project
including
advantages in
the areas of
saving money,
saving time,
and potential
future IT
projects.
/ 35Component is not
addressed
Component does
not meet
assignment
expectations
Component is
addressed but with
noticeable errors
Component meets
expectations with
minor errors
Component fully
meets or exceeds
expectations
Criteria
No Submission
0 points
Emerging (F
through D Range)
(21-24)
24 points
Satisfactory (C
Range) (25-28)
28 points
Proficient (B Range)
(29-31)
31 points
Exemplary (A
Range) (32-35)
35 points
Criterion
Score
Included
details about
the
types of
individual
computers
that will be
installed
(brand, RAM,
CPU, etc.).
/ 35Component is not
addressed
Component does
not meet
assignment
expectations
Component is
addressed but with
noticeable errors
Component meets
expectations with
minor errors
Component fully
meets or exceeds
expectations
Criteria
No Submission
0 points
Emerging (F
through D Range)
(21-24)
24 points
Satisfactory (C
Range) (25-28)
28 points
Proficient (B Range)
(29-31)
31 points
Exemplary (A
Range) (32-35)
35 points
Criterion
Score
Included
information
and details
about other
types of
/ 35Component is not
addressed
Component does
not meet
assignment
expectations
Component is
addressed but with
noticeable errors
Component meets
expectations with
minor errors
Component fully
meets or exceeds
expectations
/
hardware
that will be
required
for the
installation
(routers,
printers,
Criteria
No Submission
0 points
Emerging (F
through D Range)
(21-24)
24 points
Satisfactory (C
Range) (25-28)
28 points
Proficient (B Range)
(29-31)
31 points
Exemplary (A
Range) (32-35)
35 points
Criterion
Score
Included
information
about the
server to be
used and how
it
will connect
internally to
the network.
/ 35Component is not
addressed
Component does
not meet
assignment
expectations
Component is
addressed but with
noticeable errors
Component meets
expectations with
minor errors
Component fully
meets or exceeds
expectations
Criteria
No Submission
0 points
Emerging (F
through D Range)
(21-24)
24 points
Satisfactory (C
Range) (25-28)
28 points
Proficient (B Range)
(29-31)
31 points
Exemplary (A
Range) (32-35)
35 points
Criterion
Score
Added
information
about how
the network
will connect
to the
Internet
(firewall,
monitoring
service,
connection
type, etc.).
/ 35Component is not
addressed
Component does
not meet
assignment
expectations
Component is
addressed but with
noticeable errors
Component meets
expectations with
minor errors
Component fully
meets or exceeds
expectations
Criteria
No Submission
0 points
Emerging (F
through D Range)
(18-21)
21 points
Satisfactory (C
Range) (22-24)
24 points
Proficient (B Range)
(25-27)
27 points
Exemplary (A
Range) (28-30)
30 points
Criterion
Score
Provided the
timeline for
the project to
be successful
that
integrates all
portions of
the work
breakdown
structure.
/ 30Component is not
addressed
Component does
not meet
assignment
expectations
Component is
addressed but with
noticeable errors
Component meets
expectations with
minor errors
Component fully
meets or exceeds
expectations
Criteria No Submission
0 points
Emerging (F
through D Range)
7 points
Satisfactory (C
Range)
8 points
Proficient (B Range)
9 points
Exemplary (A
Range)
10 points
Criterion
Score
/
Total / 250
Overall Score
Close
Used
correct
APA
formatting,
correct
spelling,
grammar, and
professional
vocabulary.
/ 10Student did not
submit assignment
No attempt at
Academic/APA
formatting
Academic/APA
format is attempted
but
errors are
distracting
Using
Academic/APA
format, accurately;
errors are
noticeable but
minor
Using
Academic/APA
format proficiently;
text is basically
error free
No Submission
0 points minimum
Emerging (F through D Range)
172 points minimum
Satisfactory (C Range)
200 points minimum
Proficient (B Range)
222 points minimum
Exemplary (A Range)
250 points minimum