Transcript C12- Enhancing Decision Makingx

C12 Enhancing
Decision Making
How demand responds to changes in price?
Adjust pricing based on location?
Price-sensitive customers?
How much of a difference does this knowledge make?
Agora across Bangladesh
P&G’s Supply Chain- Complex?
One of the world’s largest
consumer good companies
Annual revenue $51 billion
80 000 employees in 140
countries
300 brands
100000+ suppliers
P&G Global Beauty
Care division
• Hundreds of
combinations of
suppliers,
manufacturing facilities
and markets.
• Even small changes
ripple through the
supply chain and affect
• inventory levels
• service levels
• costs
Challenges
Changes Are Constant!
10-15 new product launches per year
Each product has multiple sizes and package designs
Pressure to
reduce costs
competitors
large customers
like Wal-Mart
How many
plants?
A new product?
Where/Location?
Deliver products
faster
Distribution
centres?
New product- Dove!
 Where to locate the
plant(s)?
 What are the sources of
raw materials?



Marketing Managers wants it
in their respective countries
Corporate experts prefer one
megaplant
And there are millions of
other solutions in between
 IT Global Analytics group
used:





Data from Oracle data warehouse (36
months of supplier, manufacturing,
customer and consumer history by region)
Excel enhanced by LINDO
(add-on) for optimization
Palisade’s @Risk for Monte
Carlo simulation (add-on)
X-press-MP from Dash
Optimiztion Inc.
(optimization models)
Cplex from Ilog Inc.
(optimization models)
Extend from Imagine That
Inc. (simulation models)
P&G’s Supply Chain …
 Optimization models to allocate supply chain resources
 Simulation models to mathematically try various options
to see the impact of changes in important variables
 Decision trees to combine the possibilities of various
outcomes with their financial results
 Success of a supply chain is not necessarily the most
optimal solution but rather a robust solution that
would stand up in real world conditions
Result:
consolidation of plants by 20%
Supply chain costs reduced by
$200 million each year
P&G’s Supply Chain …
 Problem
 Cost pressures, complex supply chain.
 Solutions
 Deploy modeling and optimization software to
maximize return on investment and predict the most
successful supply chain.
Modeling software fueled with data from Oracle data warehouse improved efficiency
and reduced costs.
Illustrates digital technology improving decision making through information systems.
Demonstrates IT’s role in restructuring a supply chain.
The Business Value
Estimat
ed value
to firm
of a
single
improve
d
decision
Example decision
Decision maker
No. of
decisions
per year
Allocate support to most valuable
customers
Accounts manager
12
100,000
1200000
Predict call center daily demand
Call center management
4
150,000
600000
Decide parts inventory levels daily
Inventory manager
365
5,000
1825000
1
2,000,00
0
2000000
Annual
value
Identify competitive bids from
major suppliers
Senior management
Schedule production to fill orders
Manufacturing manager
150
10,000
1500000
Allocate labor to complete a job
Production floor manager
100
4,000
400000
monetary value of improved decision
quality of decision making
12.1 Decision making and information systems
IS for Key Decision-Making Groups
MIS- Based
Decision support
systems (DSS)
Executive
support systems
(ESS)
Group decision
support systems
(GDSS)
Senior managers, middle managers, operational managers, and employees
have different types of decisions and information requirements.
12.1 Decision making and information systems
Types of Decisions
• Unstructured decisions
• decision maker must provide judgment, evaluation, and
insight to solve the problem.
• Structured decisions
• repetitive and routine
• they involve a definite procedure for handling them.
• Many decisions have elements of both
• Middle manager gets report from ES system about sales
decline at Rajshahi, gets secondary (related) report
from the ES. Now needs to do interview.
Consider senior managers, middle managers, operational managers, and employees
12.1 Decision making and information systems
Decision-support systems
 Model-driven DSS
 Earliest DSS were heavily model-driven
 E.g. voyage-estimating DSS (Chapter 2)
 Data-driven DSS
 Some contemporary DSS are data-driven
 Use OLAP (On-Line Analytical Processing) and data
mining to analyze large pools of data
Systems for Decision Support
The Decision-Making Process
12.1 Decision making and information systems
Managers and Decision Making
in the Real World
 What managers do? Five classical functions
 planning, organizing, coordinating, deciding, and
controlling
 How do the do it?
 Behavioral models state that the actual behavior of
managers appears to be less systematic, more informal,
less reflective, more reactive, and less well organized
than the classical model would have us believe.
12.1 Decision making and information systems
Managers and Decision Making
in the Real World
 engage in more than 600 different activities each day
 managerial activities are fragmented- most less than nine
minutes, 10% exceed one hour
 prefer current, specific, and ad hoc information
 refer oral forms of communication- greater flexibility, ess
effort, aster response
 give high priority to maintaining a diverse and complex
web of contacts- acts as an informal information system,
helps them execute their personal agendas and short- and
long-term goals
Mintzberg’s Managerial Roles …
12.1 Decision making and information systems
12.1 Decision making and information systems
Managers and Decision Making
in the Real World
 investments in information technology do not always
produce positive results. There are three main reasons:
Quality
Description
 information quality
Dimension
Accuracy
Do the data represent reality?
 management filters

selective attention, biases
 organizational culture
 resist major change
 decisions represent various
interest groups rather than
the best solution to the
problem.
Integrity
Are the structure of data and relationships among
the entities and attributes consistent?
Consistency
Are data elements consistently defined?
Completeness
Are all the necessary data present?
Validity
Do data values fall within defined ranges?
Timeliness
Area data available when needed?
Accessibility
Are the data accessible,comprehensible,and
usable?
12.1 Decision making and information systems
High-Velocity Automated Decision Making
 Google’s search engine
 High frequency traders at NYSE execute their
trades in under 30 milliseconds
 humans (including managers) are eliminated
from the decision chain because they are too slow
 Flash Crash- 2010
12.1 Decision making and information systems
Infrastructure for DSS
 At the foundation of all of these DSSs are
infrastructure
business intelligence (BI) and
 business analytics (BA)

 that supplies the
 data and
 analytic tools
 for supporting decision making.
12.2 Business Intelligence In The Enterprise
Business Intelligence?
 Humans are intelligent beings
 ability to take in data from their environment,
 understand the meaning and significance of the information, and
 then act appropriately.
Just like human beings, some
business firms do this well, and
others poorly .)
 “Business intelligence” the infrastructure for warehousing, integrating, reporting, and
analyzing data that comes from the business environment
 An infrastructure collects, stores, cleans, and makes relevant
information available to managers
 databases, data warehouses, and data marts
12.2 Business Intelligence In The Enterprise
BI and BA Capabilities
 “Business analytics” focuses more on tools and
techniques for analyzing/understanding data

OLAP, statistics, models, and data mining
 BI and BA are about integrating all the
information streams produced by a firm into a
single, coherent enterprise-wide set of data, and
then, using modeling, statistical analysis tools
(like normal distributions, correlation and
regression analysis, forecasting,), and data
mining tools (pattern discovery and machine
learning), to make sense out of all these data
12.2 Business Intelligence In The Enterprise
BI and BA Vendors
Vendor
Market
Share
Business Intelligence Software
SAP
25%
SAP BusinessObjects EPM Solutions
SAS Institute
15%
SAS Activity Based Management;
financial, human capital,
profitability and strategy
management
Oracle
14%
Enterprise Performance
Management System
IBM
11%
IBM Cognos
Microsoft
7%
SQL Server with PowerPivot
12.2 Business Intelligence In The Enterprise
BI and BA Vendors
Business intelligence and analytics requires a strong database foundation, a set of
analytic tools, and an involved management team that can ask intelligent
questions and analyze data.
12.2 Business Intelligence In The Enterprise
5 analytic functionalities of BI systems
Casual users are consumers of BI output, while intense power users are the
producers of reports, new analyses, models, and forecasts.
12.2 Business Intelligence In The Enterprise
Business Intelligence Applications
 Predictive Analytics
 Credit card risk
 Data Visualization and Geographic Information
Systems (GIS)
12.2 Business Intelligence In The Enterprise
Management Strategies for Developing
BI and BA Capabilities
 One-stop integrated solutions versus multiple
best-of-breed vendor solutions
 Advantage/Not!
 switching is very costly
 When you adopt these systems, you are in essence
taking in a new partner
12.2 Business Intelligence In The Enterprise
Decision Support for Operational and Middle
Management
Company MIS Application
California Inventory Express application “remembers” each
Pizza
restaurant’s ordering patterns and compares the amount
Kitchen
of ingredients used per menu item to predefined
portion measurements established by management. The
system identifies restaurants with out-of-line portions
and notifies their managers so that corrective actions will be
taken.
PharMark Extranet MIS identifies patients with drug-use patterns
that place them at risk for adverse outcomes.
Black &
Intranet MIS tracks construction costs for various
Veatch
projects across the United States.
Taco Bell Total Automation of Company Operations (TACO) system
provides information on food, labor, and period-todate costs for each restaurant.
12.3 Business Intelligence Constituencies
Decision Support for Operational and Middle
Management
 Some managers are “super users”/ business analysts who
 want to create their own reports
 use more sophisticated analytics and models
 find patterns in data
 model alternative business scenarios
 to test specific hypotheses.
 Decision support systems (DSS) are the BI delivery
platform

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

rely more heavily on modeling than MIS
what-if or other kinds of analysis
Sensitivity analysis - predict a range of outcomes
OLAP- pivot table
12.3 Business Intelligence Constituencies
Sensitivity Analysis
This table displays the results of a sensitivity analysis of the effect of changing the
sales price of a necktie and the cost per unit on the product’s break-even point. It
answers the question, “What happens to the break-even point if the sales price and
the cost to make each unit increase or decrease?”
12.3 Business Intelligence Constituencies
The Excel PivotTable Wizard
The PivotTable Wizard in Excel makes it easy to analyze lists and databases by simply
dragging and dropping elements from the Field List
12.3 Business Intelligence Constituencies
Using spreadsheet pivot tables to support decision
making
 Online Management Training Inc. (OMT Inc.),
sells online management training books and
streaming online videos to corporations and
individuals
 Records of online transactions can be analyzed
using Excel to help business decisions, e.g.:
Where do most customers come from?
 Where are average purchases higher?
 What time of day do people buy?
 What kinds of ads work best?

Systems for Decision Support
Example: ALICO Insurance
 Using widely available insurance industry data, ALICO defines small
groups of customers, or “cells,” such as motorcycle riders aged 30 or
above with college educations, credit scores over a certain level, and
no accidents.
 For each “cell,” Progressive performs a regression analysis to
identify factors most closely correlated with the insurance losses that
are typical for this group.
 It then sets prices for each cell, and uses simulation software to test
whether this pricing arrangement will enable the company to make a
profit.
 These analytic techniques, make it possible for ALICO to profitably
insure customers in traditionally high-risk categories that other
insurers would have rejected.
Consider GP Package
12.3 Business Intelligence Constituencies
Example: Business value of DSS …
 Burlington Coat Factory: DSS for pricing
 DSS manages pricing and inventory nationwide, considering
complex interdependencies between initial prices, promotions,
markdowns, cross-item pricing effects and item seasonality
 Syngenta: DSS for profitability analysis
 DSS determines if freight charges, employee sales commissions,
currency shifts, and other costs in proposed sale make that sale or
product unprofitable
 Compass Bank: DSS for customer relationship
management

DSS analyzes relationship between checking and savings account
activity and default risk to help it minimize default risk in credit
card business
Systems for Decision Support
DSS for CRM …
Systems for Decision Support
Senior Management: The Balanced Scorecard and
Enterprise Performance Management Methods
• Executive Support Systems (ESS)
• a methodology for understanding exactly what is “the
really important performance information”
• develop systems capable of delivering this information
The balanced scorecard
•
•
•
a framework for operationalizing a firm’s strategic plan
by focusing on measurable outcomes on four
dimensions of firm performance: financial, business
process, customer, and learning and growth
Performance on each dimension is measured using key
performance indicators (KPIs), which are the measures
proposed by senior management
12.3 Business Intelligence Constituencies
The balanced scorecard
•
If your firm is a bank, one KPI of business process performance is
the length of time required to perform a basic function like creating
a new customer account.
CATEGORY
Purpose
Aim
Learning & Growth
for Employees
To achieve our vision
How will we sustain our
ability to change &
improve?
Internal Business
Processes
To satisfy our
stakeholders &
customers
Where must we excel in
our business processes?
Customer
Satisfaction
To achieve our vision
How should we appear
to our customers?
Financial
Performance
To succeed financially
How should we appear
to our stakeholders?
12.3 Business Intelligence Constituencies
The balanced scorecard
12.3 Business Intelligence Constituencies
Executive support systems (ESS)
Integrate data from different functional systems for
firmwide view
 Incorporate external data, e.g. stock market news,
competitor information, industry trends, legislative
action
 Include tools for modeling and analysis


Primarily for status, comparison information about
performance
Facilities for environmental scanning - detecting
signals of problems, threats, or strategic opportunities
 Able to drill down from summary information to lower
levels of detail

Executive Support Systems (ESS)
Business value of ESS
 Enables executive to review more data in less
time with greater clarity than paper-based
systems

Result: Needed actions identified and carried out
earlier
 Increases upper management’s span of control
 Can enable decision making to be decentralized and
take place at lower operating levels
 Increases executives’ ability to monitor activities
of lower units reporting to them
Executive Support Systems (ESS)
Case of National Life
National Life: Markets life insurance, health insurance,
and retirement/investment products executive
information system
 Executive information system:

Allows senior managers to access corporate databases through
Web interface
 Shows premium dollars by salesperson
 Authorized users can drill down into these data to see product,
agent, and client for each sale
 Data can be examined by region, by product, and by broker,
and accessed for monthly, quarterly, and annual time periods

ESS for business intelligence
Executive Support Systems (ESS)
Group Decision-Support Systems (GDSS)
• Much work is accomplished in groups within firms that a
special category of systems called group decision-support
systems (GDSS) has been developed to support group
and organizational decision making.
• An interactive computer-based system for facilitating the
solution of unstructured problems by a set of decision
makers working together as a group in the same location
or in different locations
•
•
•
Collaboration systems type tools and technologies
Geared explicitly toward group decision making
promotes a collaboration by guaranteeing anonymity
12.3 Business Intelligence Constituencies
California’s South Coast Air
Quality Management District
(AQMD) is responsible for
monitoring and controlling
emissions in all of Orange
County and the urban portions
of Los Angeles, Riverside, and
San Bernardino counties.
Displayed is a map produced
with ESRI GIS software tracking
particulate matter emissions
from building construction
activity in a two-by-two kilometer
area.
Systems for Decision Support
Overview of a GDSS meeting
Each attendee has workstation, networked to
facilitator’s workstation and meeting’s file server
 Whiteboards on either side of projection screen
 Seating arrangements typically semicircular, tiered
 Facilitator controls use of tools during meeting
 All input saved to server, kept confidential
 After meeting, full record (raw material and final
output) assembled and distributed

Make meetings more productive by providing tools to facilitate:
• Planning, generating, organizing, and evaluating ideas
• Establishing priorities
• Documenting meeting proceedings for others in firm
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MIS- Based
 Help managers monitor and control business by
providing information on firm’s performance and address
structured problems
 Typically produce fixed, regularly scheduled reports
based on data from TPS

E.g. exception reports: Highlighting exceptional conditions, such
as sales quotas below anticipated level
 E.g. Pizzahut Kitchen MIS
 For each restaurant, compares amount of ingredients used per
ordered menu item to predefined portion measurements and
identifies restaurants with out-of-line portions
Systems for Decision Support
Components of DSS
 Database used for query and
analysis


Current or historical data from number
of applications or groups
May be small database or large data
warehouse
 User interface
 Often has Web interface
 Software system with models, data
mining, and other analytical tools
Overview of a Decision-Support System
Systems for Decision Support
Model
 Abstract representation that illustrates components or
relationships of phenomenon; may be physical,
mathematical, or verbal model
Statistical models
Optimization models
Forecasting models
Sensitivity analysis models
Systems for Decision Support
DSS for Supply Chain Management
 Comprehensive examination of inventory,
supplier performance, logistics data
 To help managers search alternatives and decide
on the most efficient and cost-effective
combination
 Reduces overall costs
 Increases speed and accuracy of filling customer
orders
Systems for Decision Support
 Data visualization tools:
 Help users see patterns and relationships in large amounts of data
that would be difficult to discern if data were presented as
traditional lists of text
 Geographic information systems (GIS):
 Category of DSS that use data visualization technology to analyze
and display data in form of digitized maps
 Used for decisions that require knowledge about geographic
distribution of people or other resources, e.g.:


Helping local governments calculate emergency response times to
natural disasters
Help retail chains identify profitable new store locations
Systems for Decision Support
Web-based customer decision-support systems
(CDSS)
 Support decision-making process of existing or
potential customer
 Automobile companies that use CDSS to allow
Web site visitors to configure desired car
 Financial services companies with Web-based
asset-management tools for customers; Fidelity
Investments: customer portfolio allocations,
retirement savings plans...
 Home.com: mortgage, rent or buy...
Systems for Decision Support
Bonita Bay Properties
Digital dashboard: Displays on single screen key
performance indicators as graphs and charts for
executives
 Bonita Bay Properties Inc.: Develops planned
communities centered around golf courses and fitness
centers
 Executive dashboard displays:

Summaries from point-of-sale systems and general ledger
accounts
 Staffing levels
 Executives can drill down to performance of fitness centers,
activity on golf courses

Monitoring corporate performance with digital dashboards
Executive Support Systems (ESS)
Case of Pharmacia Corporation
Balanced scorecard model: Supplements traditional
financial metrics with measurements from additional
perspectives (customers, internal business processes,
etc.)
 Pharmacia Corporation: global pharmaceutical firm
 Balanced scorecard shows:

Performance of U.S. or European clinical operations in relation
to corporate objectives
 Attrition rate of new compounds under study
 Number of patents in clinical trials
 How funds allocated for research are being spent

Monitoring corporate performance with balanced scorecard systems
Executive Support Systems (ESS)
Caesar’s Entertainment
Has integrated reporting structure to help management
determine how well it is performing against forecasts
on a daily basis
 Integrates data from internal TPS with other internal
and external sources

Financial data from general ledger system, personnel data,
weather pattern and real estate data
 Delivers daily cost, effect, impact analysis, and profit-and-loss
reports
 Reports predict combined effect of these factors on company’s
business performance


System lets executives adjust plans as required online
Enterprise-wide performance analysis
Executive Support Systems (ESS)
Components of GDSS

Hardware
Facility: Appropriate facility, furniture, layout
 Electronic hardware: Audiovisual, computer, networking
equipment


Software
Electronic questionnaires, electronic brainstorming tools, idea
organizers
 Tools for voting or setting priorities, stakeholder identification
and analysis tools, policy formation tools
 Tools ensure anonymity
 Group dictionaries


People

Participants and trained facilitator, support staff
Group Decision-Support Systems (GDSS)
Group System Tools
The sequence of activities and
collaborative support tools used in
an electronic meeting system
facilitate communication among
attendees and generate a full
record of the meeting.
Source: From Nunamaker et al.,
“Electronic Meeting Systems to
Support Group Work,”
Communications of the ACM, July
1991. Reprinted by permission.
Group Decision-Support Systems (GDSS)
Business value of GDSS

Supports greater numbers of attendees


Without GDSS, decision-making meeting process breaks down
with more than 5 attendees
More collaborative atmosphere

Guarantees anonymity
Can increase number of ideas generated and quality of
decisions made
 Most useful for idea generation, complex problems,
large groups
 Successful use of GDSS depends on many factors


Facilitator’s effectiveness, culture and environment, planning,
composition of group, appropriateness of tools selected, etc.
Group Decision-Support Systems (GDSS)
Learning Objectives
 Assess how information systems support the activities of
managers and management decision making.
 Demonstrate how decision-support systems (DSS) differ
from MIS and how they provide value to the business.
 Demonstrate how executive support systems (ESS) help
senior managers make better decisions.
 Evaluate the role of information systems in helping
people working in a group make decisions more
efficiently.
Questions
 1. What are the different types of decisions and how does




the decision-making process work?
2. How do information systems support the activities of
managers and management decision making?
3. How do business intelligence and business analytics
support decision making?
4. How do different decision-making constituencies in an
organization use business intelligence?
5. What is the role of information systems in helping
people working in a group make decisions more
efficiently?
TOC
12.1 Decision Making And Information Systems
• Business Value of Improved Decision Making
• Types of Decisions
• The Decision-Making Process
• Managers and Decision Making in the Real World
• High-Velocity Automated Decision Making
12.2 Business Intelligence In The Enterprise
• What Is Business Intelligence?
• The Business Intelligence Environment
• Business Intelligence and Analytics Capabilities
• Management Strategies for Developing BI and BA Capabilities
12.3 Business Intelligence Constituencies
• Decision Support for Operational and Middle Management
• Decision Support for Senior Management: The Balanced Scorecard
and Enterprise Performance Management Methods
• Group Decision-Support Systems (GDSS)
Interpersonal
Role
Description
Identifiable Activity
Figurehead Manager serves as an official
representative of the organization
or unit
Greeting visitors;
signing legal documents
Leader
Manager guides and motivates staff
and acts as a positive influence in
the workplace
Staffing, training
Liaison
Manager interacts with peers and
with people outside the
organization to gain information
Acknowledging
mail/email; serving on
boards; performing
activities that involve
outsiders
Mintzberg’s Managerial Roles
12.1 Decision making and information systems
Informational
Role
Monitor
Description
Identifiable Activity
Manager receives and collects
information
Reading magazines
and reports;
maintaining personal
contacts
Communicati Manager distributes
on
information within the
(Disseminato organization
r)
Holding meetings;
making phone calls to
relay information;
email/memos
Spokesperso
n
Holding board
meetings; giving
information to the
media
Manager distributes
information outside the
organization
Mintzberg’s Managerial Roles
12.1 Decision making and information systems
Role
Entreprene
ur
Decisional
Description
Identifiable Activity
Manager initiates change
Organizing sessions to
develop new
programs; supervises
design of projects
Disturbance Manager decides how conflicts
Handler
between subordinates should
be resolved
Steps in when an
employee suddenly
leaves or an important
customer is lost
Resource
Allocator
Manager decides how the
organization will use its
resources
Scheduling; requesting
authorization;
budgeting
Negotiator
Manager decides to negotiate
major contracts with other
organizations or individuals
Participating in union
contract negotiations
or in those with
suppliers
Mintzberg’s Managerial Roles
12.1 Decision making and information systems