ACS 1803
Lecture Outline 7
“OTHER” SYSTEMS 1
Legacy Systems *MC
Stand Alone (Legacy) Systems
A single system or group of systems, designed to each
support one or a few business functions (e.g. accounting
system or a manufacturing system, etc.)
Stand Alone (Legacy) Systems
• Little or no integration with other organizational
systems. If integration exists, it is usually in batch (i.e.
the accounting system gets updates from manufacturing
system once a day or week)
• Organizational fit may be better than integrated
packages due to the focus on one function and that
they have been highly modified over time
• Customization and the age of these systems make
them difficult to support due to the complexity, use of
older or obscure languages, etc.
Enterprise Resource Planning Systems (ERP) *L
- for very large organizations (originally)
- attempt to use one extensive system (composed of
different subsystems) to satisfy the information needs of
the entire organization (to a point)
- not only plan, but run the different functions
- use ONE relational database, which may be
composed of several thousand tables
- P. 264
-major benefits: what is entered in one subsystem is
available immediately to other subsystems (e.g. an order
is entered and it the affects the production schedule and
the purchase of raw materials)
- it is a BIG effort to install such a system (Manitoba
Govt, MTS)
- sometimes, business processes have to be reengineered
- but, it may not be possible to fit the organizational
workings into how the software is structured (this is a
drawback)
- examples: SAP, Oracle, (PeopleSoft, JD Edwards)
- study carefully the Electro-Tech illustration *L
More on SAP *MC
• - SAP implementation at Microsoft
• - SAP moving into small-medium business
in Canada
SAP – ERP System in Winnipeg
*X
• Provincial Government (extensive)
• Selected modules:
– MTS
– Manitoba Hydro
– Great-West Life
Interorganizational Enterprise
Systems *L
• Supply Chain Management systems
• Upstream
• ERP systems
• Inside the organization
• Customer Relationship Management
systems
• Downstream
Customer Relationship
Management (CRM) *L
• p. 272 see key features** (make notes)
• Firstly, it is a marketing philosophy
• Want to maintain an ongoing relationship with
existing customers
challenge: to address the right customer with the
right offer at the right time
- CRM systems help collect data about individual
customers and analyze the data into useful
information
CRM (cont’d)
• Can provide information to a customer on
the status of an order (e.g., on a truck)
• Can store information on sales order
history to assist in addressing the
customer uniquely in the future
– e.g., Marriott hotel;
CRM (cont’d)
• Can store data on customer interactions
no matter where they came from (retail
store, website, e-mail, call centre etc.)
downstream integration
• Allow the org. to provide customized,
individual attention to existing customers
(e.g., follow-up) increases competitive
advantage
e.g. last minute e-mails to fill cruise ships
CRM Software *MC
• Come in the form of packaged software
that is purchased from software vendors
• E.g, Oracle’s Siebel system, SAP’s CRM
• Systems tend to come in modules
– Some have pre-sales features that we
covered under marketing systems
– Also, most valuable are post-sales features
Electronic Data Interchange (EDI) *L
-We have talked about interorganizational systems
-How can such systems communicate?
- we can have the computer systems of one company
“talk” directly to the computer systems of another
company through EDI
- for example, the Purchasing system of Company A
connects electronically with the Order Entry system of
Company B
- further example:
- supplier’s proposal is sent electronically to the
purchasing organization
- an electronic copy is approved over the network;
both orgs maintain a digital copy
- supplier manufactures and packages the goods,
attaching to each box shipping data recorded on a bar
code
- quantities shipped and their prices are entered
into the system and flow automatically to an invoicing
system; shipping data documents and invoices are
transmitted to the purchasing organization, so the
receiving workers know what items they are to receive
- manufacturer ships the order
- when the packages are received at the
purchasing organization, the bar codes are scanned and
the data are compared with both the data transmitted
with the invoices and the actual items received
- if there are no discrepancies, an approval for
payment is transferred electronically by the purchaser to
its accounts payable department, which instructs the
bank to pay the supplier
- using electronic funds transfer, the bank reduces
the purchasing organization’s balance by the proper
amount, and electronically transfers the sum to the
supplier’s account at its bank
- there were no paper documents involved
- e.g., Toys R Us , the world’s largest toy retailer,
processes over half a million invoices per year
electronically
Benefits of EDI *L
- savings in paper costs, employee paper handling
time, mailing costs
- speed in transmission (JIT support)
- rekeying of information minimized
- can ‘cement’ business relationships
Two forms of EDI:
- VAN (Value Added Network) EDI
- Internet EDI
VAN EDI
VAN has its own communication lines and mailboxes
and provide network management
VAN mediates all EDI communication between the
companies with special software that translates business
documents into EDI documents (software conforms to
EDI standards - may need translation software to enable
the two companies’ systems to ‘talk’)
- this is the older type of EDI
Web EDI
-practically all new EDI implementations use Web
EDI
-Internet is a natural vehicle for EDI because of its
ease of access and inexpensive implementation
- many companies may use extranets where they
had used VAN EDI before
- HTML: hypertext markup language is used to
make standard web pages
- most common interface used with extranet EDI is
a common web browser
Extranet EDI has advantages over VAN EDI
- lower cost
- more familiar software
- worldwide connectivity
- fast communication
Executive Information Systems
(EIS) *L
• systems to help very high executives in
their daily work
• - provide info. in such a way that the other
systems do not
• Often internal and external information
• Often graphical
• May use touch screens
System Type: Executive
Information System (EIS)
EISs, also called Executive Support Systems (ESS), are
special purpose information systems to support executive
decision-making
System Details *L
These systems use graphical user interfaces to display
consolidated information and can deliver both:
• Soft Data - textual news stories or non-analytical data
• Hard Data – facts, numbers, calculations, etc.
Supported Activities *X
The activities supported by these kinds of systems include:
• Executive Decision Making
• Long-range Strategic Planning
• Monitoring of Internal and External Events
• Crisis Management
• Staffing and Labour Relations
COMMON EIS FEATURES *L
1. Drill-down reporting: can drill down summarized info
to lower levels for more insight; e.g., exec. sees a low
profit; he can drill down through simple menu choices to
see data -by region, -by market within region, - by
salesperson; can often trace the root of a problem
through this feature
2. Exception reporting: emphasizes business items that
may be out of line (in another color)
3. Graphic presentation: more impact on a busy exec.
4. Trend analysis: explores data, e.g., sales over time
to highlight trends and patterns
5. Electronic mail: for efficient communications; may also
include features such as electronic appointment book
6. On-demand ratios that provide meaningful insight,
often on financial issues
7. Access to external data pools
EIS must be very easy to use, often not requiring the
keyboard
Decision Support Systems *L
- designed to help management make semistructured (or unstructured) decisions
- they focus more on what might happen rather
than what has happened
Decision Support Systems *L
Special-purpose information systems designed to support
managerial-level employees in organizational decision
making
System Details
These systems use computational software to construct
models for analysis to solve semi-structured problems (e.g.
sales or resource forecasts)
Supported Activities:
“What-if” analysis – changing one or more variables in the
model to observe the effect (e.g. What is the payment if the
interest rate increases by 1% ?)
- typically include: *L
a) a data base, perhaps a "data warehouse", extracted
from a "live“ database,
b) a model base*** that uses the data base [a model is a
structured representation of some aspect of reality; it is
because of the model that we can examine effects of
decisions; but, a model always has assumptions e.g.,
inflation rate, net earnings level over 5 years; cost
increases]
c) a user-friendly interface (dialog), often involving
graphics
-a DSS may be developed by people outside of the
Information Systems Department
- a DSS also can have capability for ad hoc reporting
from the data base (warehouse)
examples of decision support: *L
- should we buy out a company? should we expand into
another product line? [why semi-structured?I]
- classic illustration: Houston Oil and Mineral Co
DSS Examples *L
• A more primitive example of a DSS is a
spreadsheet used for “what-if” analysis
• There are Excel templates built for certain
types of decisions [terms: template, model;
explain these]
• Can be data driven or model driven
• See comparison of DSS with MIS p. 292
More DSS Examples *MC
• Canadian gov’t: PRAIRIE CROP
PROTECTION PLANNER
• Farmer describes: spraying equipment,
size of field, current chemical prices
• Model calculates: application rates, costs
per acre, amount of chemical needed
• US: helps farmers decide in which regions
of Nebraska to plant grapevines to avoid
freezing
More DSS Examples
• Airline industry: DSS helps to find proper
pricing to maximize overall revenue from
selling seats for each flight
– Mgr enters depart. pt, arr. pt, no of stops,
times of dep and arr, # days in advance for
res, # persons, size of plane, utilized capacity
on similar previous flights etc.
– System suggests variable ticket prices
DSS development and use
• Many DSS are not developed by computer
professionals (at least not alone)
– E.g., power sales support system at Manitoba
Hydro (engineer with MBA degree uses IFPS
system in the Finance department)
• DSS are used largely by middle and
higher managers
Model Driven DSS vs. Data
Driven DSS
• A Model Driven DSS uses various models
such as statistical model, simulation
model or financial model for decision
makings. So, decisions are based on
models.
• A Data Driven DSS emphasizes access to
and manipulation of a time-series of
internal company data and sometimes
external data to aid decision makings. So,
decisions are based on analyzed data. 32
A Comparison of DSS and MIS
• DSS differs from an MIS in numerous
ways, including:
– The type of problems solved
– The support given to users
– The decision emphasis and approach
– The type, speed, output, and development of
the system used
– See comparison of DSS with MIS p. 320
33
Expert Systems *MC
• p. 362-366
• such systems are different than traditional
reporting or DSS systems
• they apply artificial intelligence to situations
where many facts and complex decision rules
are involved, such that only a few people can
solve such problems well
• an expert system mimics the thinking of an
expert
Expert Systems
• Expert system manipulate knowledge and
not just information
• e.g what drug and in what dose to give for
particular types of cancer
– Many factors involved
– Many questions must be asked
– Many IF … THEN rules
• A rule is a way of encoding knowledge
- an ES should be able to explain its
reasoning to the user
Expert Systems
• ***why develop them? *L
- to retain expert's knowledge if he retires or dies
- to pool expertise from several experts
- to clone the expert's knowledge and have it
available in many places at once (e.g., cancer
treatment in remote Manitoba areas)
• they can be developed through detailed
programming or through an "expert system
shell" such as VP Expert
Expert System structure *L
• Knowledge base
– Facts and rules
• Inference engine
– Software that takes user input and “sifts
through” the knowledge base mimicking the
mind of an expert
• This is artificial intelligence
Expert System Development *MC
• A knowledge engineer has special
expertise in eliciting information and
expertise from experts
• He / she translates the expert’s knowledge
into a set of (if .. then) rules
Expert Systems Examples *MC
• ES at California State U to advise students
on class selection
• Complex machine repair
• Cancer treatment in remote areas
• Computer user help desk
Knowledge Management
• An expert system works on a knowledge
base
– It is part of a larger area called ‘knowledge
management’
Knowledge Management
Knowledge Management
Definitions *MC
The process an organization uses to gain the greatest value
from its knowledge assets
Knowledge Assets
All underlying skills routines, practices, principles, formulae,
methods, heuristics, and intuitions whether explicit or tacit
Explicit Knowledge
Anything that can be documented, archived, or codified
often with the help of information systems
Tacit Knowledge
The processes and procedures on how to effectively
perform a particular task stored in a person’s mind
Knowledge Management System (KMS) *MC
Best Practices
Procedures and processes that are widely accepted as
being among the most effective and/or efficient
Primary Objective
How to recognize, generate, store, share, manage this tacit
knowledge (Best Practices) for deployment and use
Technology
Generally not a single technology but rather a collection
of tools that include communication technologies (e.g.
e-mail, groupware, instant messaging), and information
storage and retrieval systems (e.g. database
management system) to meet the Primary Objective