turban, aronson, liang sauter 1 management support systems: an overview

Turban, Aronson, LiangSauter

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Management Support Systems:An Overview


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Learning Objectives

• Understand how management uses computer technologies.

• Learn basic concepts of decision-making. • Understand decision support systems.• Recognize different types of decision

support systems used in the workplace.• Determine which type of decision support

system is applicable in specific situations.• Learn what role the Web has played in the

development of these systems.


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Opening Vignette: Casino Harrah’s

The Problem• Gaming is highly competitive and profitable.• Early 90’s: gambling on riverboats• 1990-97: # casinos tripled.• In the past: star treatment for high rollers,

free drink for slot m/c players.• End of 80’s: Slot m/c’s surpassed table

games, 25 million players • Loyal slot players are the key to profitability!


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• Player-tracking system– 30% of customers who spend b/w $100-$500

account for 80% of total revenue, almost 100% of profits.

• Total rewards program– Magnetic cards to capture info on How long

they play, how much they spend, games preferred, winning ratios...

– Incentives based on money inserted, not won!, free meals, rooms, shows

– Electronically linked clubs

Opening Vignette: The Solution


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• Magnetic card readers: read customer ID., send a personalized greeting

• Electronic gaming m/c’s: capture transaction data and send to mainframe

• Onsite transaction system: store all casino, hotel and dining transaction data

• National data warehouse: links computer system and customer data to a server that tallies customer history and rewards.

• Predictive analysis software: predict customer profile

• Web site: keeps customers informed, connected entertained

Opening Vignette: The Solution


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Harrah’s Decision Support System

• Transaction Processing System (TPS)• Data Warehouse• Data Mining or Business Intelligence

– Regression analysis, neural networks, cluster analysis, optimization techniques

• Customer Relationship Management (CRM)• Decision Support System


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Resulting decisions: Some examples

• Defn of the perfect player:

“62 year old woman who lives in 30 min. Kansas city, Missouri and playes dollar video pocker!”

• Customers who live far away receive discounts in meal, hotel, transportation

• Close living customers get food, entertainment, cash incentives

• Tight expiration days • Design new campaigns according to estimated

response rates, return on investment


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1.2 Managers and Decision Making

• Airlines,• Retail organizations• Banks• Service Companies all use these methods...

“To run effective business in a competitive environment,

a real time, targeted and computerized DSS is essential”


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Factors Affecting Decision-Making

• Complexity of the systems is increasing, so there are more alternative courses of action to choose from.

• With new technologies and faster communication, the amount of available data is huge.

• Time limitations are getting very strict; thus the cost of an erronous decision is high.

• Due to several factors like political destabilization or globalization, environmental uncertainty is increasing.

Thus decision making gets harder!...


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1.3 Managerial Decision Making and IS

• Productivity: The ratio of outputs to inputs that measures the degree of success of an organization and its individual parts

• Management Support Systems increase the productivity of managerial decision making in a complex and uncertain environment by– evaluating numerous alternatives– in a very short time.

• Thus, better decisions are made with lower costs of error.


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Decision Support Systems

• Computer-based systems that – collect information from various sources,– assist in the organization and analysis of the

data,– facilitate the evaluation of the alternatives by

the use of specific models,– provide a good user interface through which

users can easily navigate and interact.


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What do Decision Support Systems Offer?

• Quick computations at a lower cost

• Group collaboration and communication

• Increased productivity

• Access to multiple databases and warehouses

• Ability to analyze multiple alternatives and apply risk management

• Enterprise resource management and empowerment

• Tools to obtain and maintain competitive advantage which is based on price, timeliness, quality, customization and support.

• Overcome cognitive limits in processing and storage


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Cognitive Limits

• The human mind has limited processing and storage capabilities. Any single person is therefore limited in his/her decision making abilities.

• Collaboration with others allows for a wider range of possible answers, but will often be faced with communications problems.

• Computers improve the coordination of these activities.

• This knowledge sharing is enhanced through the use of GSS, KMS, and EIS.

What is the role of web here?


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Management Support Systems Technologies

(Tools)• DSS• MS/OR Techniques• Business Analytics• Data Mining• Data Warehouse• Business Intelligence• OLAP• CASE tools• GSS

• EIS/EIP• ERM/ERP• CRM• SCM• KMS/KMP• ES• ANN• Intelligent Agents• E-commerce DSS


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Management Support Systems

• Repetitive, structured problems

• Linear logic• Regular reports• Low support of decision

• Not Repetitive, unstructured problems

• Specialized heuristics• No regular reports• System makes

decisions

TPS ESEISGSSKMS

DSS

Structured processes include routine and repetitive problems with standard solution methodsUnstructured processes are fuzzy, complex problems without cut-and-dried solution methods.

MIS

The Features of Management Support Systems• Decision making process has three phases:

– Intellegence: Searching for conditions that call for decisions

– Design: Inventing, developing and analyzing possible courses of action.

– Choice: Selecting a course of action from those available

• In an unstructured problem none of these phases are structured!In a semistructured problem, some of these phases are structured.

• In a structured problem procedures for obtaining the best solution are known, like management science, data processing or clerical methods.Ex: Best investment plan, best production and inventory control plan.

• In an unstructured problem human intuition is often the basis for decision making. Ex: Planning new services, hiring an executive, chosing a set of R&D projects for the next year.Only part of an unstructured problem can be supported by advanced decision support tools such as GDSS, ES, KMS.


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Components of a DSS

• Database Management System (DBMS)– Collect data from various resources– Organize data– Provide user interface to access data

• Model base Management System– Keep track of models– Provides run control for the models– Provides data in the format required as a model input– Provides format of the model output– Provides sensitivity analysis after the model is run– Provides the decision maker, the ability to question the assumptions of

the model

• User Interface– Provides input screens by which users request data and models– Provides output screens where the results are shown

• Message Management System– Provide the features of web environment for data collection, modeling– Provide group support for decision making– Provides integration with other MSS’s.


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Management Science/Operations Research

Adopts systematic approach– Define problem– Classify into standard category– Construct mathematical model– Evaluate alternative solutions– Select solution

Management science process is based on mathematical modeling.

Computerized methodologies are used for solution.

For less structured problems methodologies are customized. Ex: In a bookstore, human judgement is necessary to predict the demand and decide on how much to order.


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MSS as an umbrella term

• Used to describe any computerized system that supports decision making.Ex: In an organization MSS encompasses:

– KMS for personnel, – DSS for marketing and accounting, – SCM System– Several expert systems for diagnostics


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Group Support Systems

• Getting people at one place is expensive and time consuming

• Time limitation to give the decision• Traditional meetings last long

Systems that provide interaction and communication between people with the aid of IT are called

collaborative computing systems, groupware systems, electronic systems, or simply

GSS

• Videoconferencing, audioconferencing, electronic brainstorming, voting, document sharing, etc..


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Enterprise Information Systems

• Evolved from Executive Information Systems combined with Web technologies

• EIPs view information across entire organizations

• Provide rapid access to detailed information through drill-down.

• Provide user-friendly interfaces through portals.

• Identifies opportunities and threats


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Enterprise Information Systems

• Specialized systems include ERM/ERP, CRM, and SCM

• Provides timely and effective corporate level tracking and control.

• Filter, compress, and track critical data and information.

What is the relation b/w ERP, CRM, SCM?


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Knowledge Management Systems

Do not reinvent the wheel each time!

• Knowledge that is organized and stored in a repository for use by an organization

• Can be used to solve similar or identical problems in the future

• ROIs as high as a factor of 25 within one to two years

• Web technologies feature prominantly• Provides access to knowledge repository, a

textual database


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Issues in Knowledge Management Systems

• Where to find knowledge• How to classify it• How to ensure its quality• How to store it• How to maintain it• How to use it• Motivate people to contribute their knowledge• People who leave the organization take their

knowledge with them

KMS Application: Xerox Experience

• Problem: With decreasing demand for copying, Xerox strugled to survive the digital revolution.

• Solution Method: Developed an intranet based knowledge repository in 1996 to support sales people to quickly answer customers’ queries.

• Result: Days of investigations have decreased to a few minutes.

• Implications:– Questions and solutions are indexed to easily retrieve information in the

latter requests. So the system improves itself.– Accumulated knowledge is analyzed to learn the products strenghts,

weaknesses, customer trends, etc.

• Challenges in organizational culture change:– Persuade people to share knowledge.– Learn to use intranet and KMS.


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Expert Systems

Decison makers ask for expert opinions!• ES Attempts to mimic human experts’ problem

solving• Uses technologies that apply reasoning

methodologies in a specific domain• Examples include:

– Artificial Intelligence Systems– Artificial Neural Networks (neural computing)– Genetic Algorithms– Fuzzy Logic– Intelligent Agents

• Most ES software is implemented on the web tools (java applets), installed on web servers and use web browsers for interfaces. Ex: Corvid Exsys


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Expert Systems

• Expertise is transferred from expert to computer

• The knowledge is stored in the computer• Users run the computer whenever advice is

needed• The ES asks for facts, make inferences,

arrive at a conclusion like a human consultant

• May explain the logic behind the advice


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Methodologies of ES: Artificial Neural Networks

• Application of decision methodologies requires explicit data, information or knowledge stored in a computer ad manipulated when needed.

• In complex real world where the environment changes rapidly, people make decisions based on partial, incomplete or inexact information, by using their “experiences”.

• In the absence of explicit data, ANN recall similar experiences, learn from them in a computerized system.

• Uses pattern recognition approach, i.e., learns patterns in data presented during training and can apply it to new cases, predict the future behaviors of systems, people, markets, etc.

Ex: Detecting unusual credit card expenditures and bank loan approvals


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Methodologies of ES:

• Genetic algorithms: mimic the process of evolution and search for an extremely good solution by survival of the fittest ruleEx: Max. Advertising profit at tv stations

• Fuzzy logic: assist decision makers in solving problems with imprecise statements of parameters, approaches the problems the way people do.Ex: “The weather is really hot”. How hot is hot?

• Intelligent agents learn what you want to do, take over some tasks like travel agents, real estate agents.


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Hybrid Support Systems

• Integration of different computer system tools to resolve problems

• Tools perform different tasks, but support each other• Work together to produce smarter answers

Ex: United Sugars Corporation revises its marketing and distribution plans to gain access to new markets and serve the existing customers more efficiently.

–Model is developed (millions of decn. var’s and 250,000 constraints) to find the minimum cost solution for packaging, inventory and distribution.

–SAP and and DB system provides data

–Web based GIS graphically displays reports for optimal solution.

–Results are uploaded to SAP and subsequent optimization models are run for inventory control.


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Emerging Technologies

• Grid computing– Cluster computing power in an organization and utilize unused cycles

for problem solving and other data processing needs.

• Improved GUIs– Due to improvements in web, expectations have risen.

• Model-driven architectures with code reuse– Software reuse and machine generated software by the computer aided

software engineering tools has become prevalent.

• M-based and L-based wireless computing– As cellular phones and wireless pc cards are getting less expesive, m-

commerce is evolving. Ex: FedEx uses mobile computer to track shipping packages and analyze patterns

• Intelligent agents: – help users and assist in e-commerce negotiations.

• Genetic algorithms, heuristics and new problem-solving techniques– Distributed as part of Java middleware and other platforms.

turban, aronson, liang sauter 1 management support systems: an overview

Documents

liang sauter

customer data

solution slide

investment slide

overview slide

essential slide

management support systems

capture transaction