Chapter 9 : Enabling the Organization – Decision Making

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DECISION MAKING
Reasons for growth of decision-making information systems
  1. People need to analyze large amounts of information—Improvements in technology itself, innovations in communication, and globalization have resulted in a dramatic increase in the alternatives and dimensions people need to consider when making a decision or appraising an opportunity.
  2. People must make decisions quickly—Time is of the essence and people simply do not have time to sift through all the information manually.
  3. People must apply sophisticated analysis techniques, such as modeling and forecasting, to make good decisions—Information systems substantially reduce the time required to perform these sophisticated analysis techniques.
  4. People must protect the corporate asset of organizational information— Information systems offer the security required to ensure organizational information remains safe.
Model – a simplified representation or abstraction of reality. Models can calculate risks, understand uncertainty, change variables, and manipulate time

IT systems in an enterprise

  • Decision support system (DSS) – models information to support managers and business professionals during the decision-making process
  • Executive information system (EIS) – a specialized DSS that supports senior level executives within the organization
  • Artificial intelligence (AI) – simulates human intelligence such as the ability to reason and learn
  • Data mining – typically includes many forms of AI such as neural networks and expert systems.  Data mining tools apply algorithms to information sets to uncover inherent trends and patterns in the information.


TRANSACTION PROCESSING SYSTEMS
  • Moving up through the organizational pyramid users move from requiring transactional information to analytical information
  • The structure of a typical organization is similar to a pyramid
  • Organizational activities occur at different levels of the pyramid
  • People in the organization have unique information needs and thus require various sets of IT tools (see Figure)
  • At the lower levels of the pyramid, people perform daily tasks such as processing transactions
  • Moving up through the organizational pyramid, people (typically managers) deal less with the details (“finer” information) and more with meaningful aggre­gations of information (“coarser” information) that help them make broader decisions for the organization
  • Granularity refers to the extent of detail in the information (means fine and detailed or “coarse” and abstract information)
  • Transaction processing system - the basic business system that serves the operational level (analysts) in an organization
  • Online transaction processing (OLTP) – the capturing of transaction and event information using technology to (1) process the information according to defined business rules, (2) store the information, (3) update existing information to reflect the new information
  • Online analytical processing (OLAP) – the manipulation of information to create business intelligence in support of strategic decision making
  • Analysts typically use TPS to perform their daily tasks
  • What types of TPS are used at your college?
    • Payroll system (Tracking hourly employees)
    • Accounts Payable system
    • Accounts Receivable system
    • Course registration system
    • Human resources systems (tracking vacation, sick days)


DECISION SUPPORT SYSTEMS
•          Decision support system (DSS) – models information to support managers and business professionals during the decision-making process
•          In a DSS, data is first queried and collected from the knowledge database
•          Results from the query are then checked and analyzed against decision models
•          Once checked against the decision models, the results are then generated for review to find a “best” solution for the situation
•          One national insurance company uses DSSs to analyze the amount of risk the company is undertaking when it insures drivers who have a history of driving under the influence of alcohol. The DSS discovered that only 3 percent of married male homeowners in their forties received more than one DUI. The company decided to lower rates for customers falling into this category, which increased its revenue while mitigating its risk.
•          Three quantitative models used by DSSs include:
Sensitivity analysis – the study of the impact that changes in one (or more) parts of the model have on other parts of the model. Sensitivity analysis – studies the impact on a single change in a current model.  For example – if we continually change the amount of inventory we carry, how low can our inventories go before issues start occurring in other parts of the supply chain?  This would require changing the inventory level and watching the model to see “how sensitive” it is to inventory levels.
What-if analysis – checks the impact of a change in an assumption on the proposed solution. What-if analysis – determines the impact of change on an assumption or an input.  For example – if the economic condition improves, how will it affect our sales?
Goal-seeking analysis – finds the inputs necessary to achieve a goal such as a desired level of output. Goal-seeking analysis – solves for a desired goal.  For example – we want to improve revenues by 30 percent, how much does sales have to increase and costs have to decrease to meet this goal?

EXECUTIVE INFORMATION SYSTEMS
•          Executive information system (EIS) – a specialized DSS that supports senior level executives within the organization
•          Most EISs offering the following capabilities:
Consolidation – involves the aggregation of information and features simple roll-ups to complex groupings of interrelated information
Drill-down – enables users to get details, and details of details, of information
Slice-and-dice – looks at information from different perspectives

Interaction between a TPS and an EIS


Why would you need interaction between a TPS and EIS?
§  The EIS needs information from the TPS to help executives make decisions
§  Without knowing order information, inventory information, and shipping information from the TPSs, it would be very difficult for the CEO to make strategic decisions for the organization

•          Digital dashboard – integrates information from multiple components and presents it in a unified display. As digital dashboards become easier to use, more executives can perform their own analysis without inundating IT personnel with queries and request for reports

ARTIFICIAL INTELLIGENCE (AI)
•          Intelligent system – various commercial applications of artificial intelligence
•          Artificial intelligence (AI) – simulates human intelligence such as the ability to reason and learn
•          RivalWatch offers a strategic business information service using AI that enables organizations to track the product offerings, pricing policies, and promotions of online competitors
•          Clients can determine the competitors they want to watch and the specific information they wish to gather, ranging from products added, removed, or out of stock to price changes, coupons offered, and special shipping terms
•          RivalWatch allows its clients to check each competitor, category, and product either daily, weekly, monthly, or quarterly
•          The ultimate goal of AI is the ability to build a system that can mimic human intelligence
•          Four most common categories of AI include:
1.       Expert system  
§  A computerized advisory programs that imitate the reasoning processes of experts in solving difficult problems. Example robot.
§  Human expertise is transferred to the expert system, and users can access the expert system for specific advice
§  Most expert systems contain information from many human experts and can therefore perform a better analysis than any single human

2.       Neural Network
§  attempts to emulate the way the human brain works. Example  California  police.
§  Fuzzy logic – a mathematical method of handling imprecise or subjective information
§  Neural networks are most useful for decisions that involve patterns or image recognition
§  Typically used in the finance industry to discover credit card fraud by analyzing individual spending behavior

3.       Genetic algorithm

§  an artificial intelligent system that mimics the evolutionary, survival-of-the-fittest process to
generate increasingly better solutions to a problem.
§  Example to determine fiber optic by telecommunication
§  Essentially an optimizing system, it finds the combination of inputs that give the best outputs

4.       Intelligent agent  

§  special-purposed knowledge-based information system that accomplishes specific tasks on behalf of its users.
§  Example Ford Motor Co. Balance with cost and demands.
§  Used for environmental scanning and competitive intelligence
§  An intelligent agent can learn the types of competitor information users want to track, continuously scan the Web for it, and alert users when a significant event occurs
§  RivalWatch uses intelligent agents

DATA MINING
Common forms of data-mining analysis capabilities include:
1.      Cluster analysis
•          a technique used to divide an information set into mutually exclusive groups such that the members of each group are as close together as possible to one another and the different groups are as far apart as possible
•          CRM systems depend on cluster analysis to segment customer information and identify behavioral traits
•          Some examples of cluster analysis include:
§  Consumer goods by content, brand loyalty or similarity
§  Product market typology for tailoring sales strategies
§  Retail store layouts and sales performances
§  Corporate decision strategies using social preferences

2.      Association detection
•          reveals the degree to which variables are related and the nature and frequency of these relationships in the information
•          Market basket analysis – analyzes such items as Web sites and checkout scanner information to detect customers’ buying behavior and predict future behavior by identifying affinities among customers’ choices of products and services


3.      Statistical analysis –
•          performs such functions as information correlations, distributions, calculations, and variance analysis
•          Forecast – predictions made on the basis of time-series information
•          Time-series information – time-stamped information collected at a particular frequency
The End of Chapter Chapter 9 : Enabling the Organization – Decision Making by syahirahzfri. 

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