Re: question about component integration or assembly
- From: "WALLYWORLD" <random@xxxxxxxxxx>
- Date: Thu, 17 Jan 2008 14:59:45 -0600
welcome to Wallyworld. Today I am goint to have teeth cleaned... Sani daai
File Design and File Indexing
It could be useful to go through the rudiments of file indexing to evaluate
the requirements for this project. First the question would be design of
the file structure and some basic system analyst work for the software
design.
Microcomputer Applications by Graurer and Sugrue p. 370, "Implicit in the
process of data management are the creation of the file itself and the
important determination of what data is needed. Thus you must first decide
exactly what information the system is to provide, the determine the data
necessary for the system to accomplish its objectives. You then design a
file structure that establishes the fields in each record, their order,
their length, and the type of data to be stored in each.
These decisions are subjective in nature, and consequently, there can be
multiple solutions for any given system.
Numeric fields store data for calculation variables (no commas, dollar$
etc.)
Character fields text, or any character at all even special characters # ^
etc.
Data fields formatted dates can be entered (not pertinent to a simple file
creation with notepad.exe
Logical fields assigned to fields that can assume only one of two values,
true or false (preferred over one-position character fields for efficiency
p. 371)
After you have defined the file structure, data is entered into the system
on a record-to-record basis. Should you make a mistake during data entry,
you can edit (correct or modify) the data in any record at any time. A data
management system also provides the ability to delete records as well as add
them, but it distinguishes between physical and logical deletion. A
logically deleted record is still in the file, except that it is hidden from
view and it can be recalled at a later time. A physically deleted record
however, has been permanently removed without possibility of recall.
Consider an example record structure with the fields, Soc Sec Num, Name,
Salary, Hire Date, Title, Location
Soc Sec Num Name Salary Hire Date Title Location
100000000 Davis 34000 01/02/86 Account Rep
200000000 Friedel 48000 02/17/84 Manager
300000000 Kendrick 26500 02/16/86 Account Rep
333333333 McGrath 17000 04/25/86 Account Rep
400000000 Cordell 27200 04/02/87 Account Rep
444444444 Facella 24700 01/15/87 Account Rep
500000000 Pattishall 38500 11/11/84 Account Rep
555555555 Ferraro 26400 02/02/85 Account Rep
600000000
700000000
800000000
900000000 Tillberg 35500 10/29/82 Manager
999999999 Grauer 37500 03/16/85 Account Rep
The records shown above are our complete record set from Grauer and Sugrue
p. 367. The indexing of records is discussed p. 373 Grauer and Sugrue, as
well as Stair p. 93 data management. Sugrue p. 373 "The records above are
stored in the physical sequence in which they were entered. The reports,
(those three (3) reports shown p. 369) Grauer and Sugrue and some summary
reports given here:
Below the reports display the records in different logical sequences, for
example, ny name, salary, and date of hire (further below). The ability to
store records in one sequence and list them in another (or several others)
is made possible through indexing. Indexing involves a departure from the
physical order in which the records are stored, instead they will be
retrieved and listed in a different logical sequence (by last name, or
department).
Location: Boston
Number of Employees 4
Total salaries: $123,700
Average Salary $40,400
Location: Chicago
Number of Employees 3
Total salaries: $122,900
Average Salary $40,967
Location: Los Angeles
Number of Employees 3
Total salaries: $101,750
Average Salary $33,917
Location: Miami
Number of Employees 6
Total salaries: $205,400
Average Salary $34,233
Company:
Number of Employees 16
Total salaries: $553,750
Average Salary $34,609
===================================
Salaries by location
Title: Account Rep
Number of Employees: 12
Total Salaries: $369,250
Average Salary: $30,771
Title: Manager
Number of Employees: 4
Total Salaries: $184,500
Average Salary: $46,125
Title: Account Rep
Number of Employees: 16
Total Salaries: $553,750
Average Salary: $34.609
===================================
Salaries by title
The issue of SQL is that SQL allows programmers learn only one query
language and it is useful for systems ranging from PCs to mainframe
computers. Programmers and database users also find SQL to be valuable
because SQL statements can be embedded into many programming languages, such
as widely used COBOL. Because SQL uses standardized and simplified
procedures for retrieving, storing, and manipulating data in a database
system, the popular database query language can be easy to understand and
use. The manuals and books are also widely available Stair p. 106.
The output-control features of a database allow you to select the records
and fields to appear in reports. You can also complete calculations for the
report by manipulating database fields. Formatting controls and
organization options (i.e., headings) help to customize reports and to
create flexible, convenient, and powerful information handling tools.
These database management systems are an important personal productivity
tool along with word processing, spread***, and graphics software.
Some data management systems such as Superbase 95 provide "wizards" that
walk you through how to build customized databases, modify ready-to-run
applications, use existing record templates, and quickly locate the data you
want. Some include Web-publishing capabilities, as well as complete help
and support features. Lotus Approach, Microsoft Access, and Aprise's dBASE
are very popular. In the higher ranges of the database market are Sybase,
Oracle, IBM, and Informix.
General Uses - Reports
A database program can produce a variety of documents, reports, and other
outputs that can help organizations to achieve their goals. The most common
reports select and organize data to present summary information about some
aspect of company operations. For example, accounting reports often
summarize financial data such as current and past-due accounts. Many
companies base their routine operating decisions on regular status reports
that show progress of specific orders towards completion and delivery.
Copmanies consider these improvements to their capability to provide
customer service.
Decision Support - Reports
Exception, scheduled, and demand reports highlight events that require
urgent management attention. Exception reports are produced only upon the
occurrence of some predefined exception condition -i.e., a sales change by
+/- 10%. Scheduled reports are produced according to predetermined time
schedule -e.g., the fourth work night of the month. Demand reports are
produced only upon the explicit request of the user.
Database Programs - Internal Reporting Capabilities
Some of the documents and reports produced with databases:
Form letters with address labels
Payroll checks and reports
Invoices
Orders for materials and supplies
A variety of financial performance reports
Data Dictionary
An important step in creating a database is to establish a data dictionary,
a detailed description of all data used in the database. The data
dictionary contains the name of the data item, aliases or other names that
may be used to describe the item, the range of values that can be used, the
type of data i.e., alphanumeric or numeric, the length of the data item in
bytes, a notation responsible for updating the various users permissions,
and a list of reports that use the data item.
The typical uses of a data dictionary:
Provide a standard definition of terms and data elements
Assist programmers in designing and writing programs
Simplify database modification
A database approach has certain advantages which are aided by implementation
of a data dictionary:
Reduced data redundancy
Increased data reliability
Faster program development
Easier modification of data and information
A Database Application
An application, by statements in the North book discussion P. 11, may
consist of a general-purpose main window and pop-up windows for purposes of
displaying modal, and modeless dialog boxes (or dialogs). Modal dialogs are
a tool for decision points in your application because they call for a
specific user action before the application continues. Modeless dialog
boxes permit you to display information in situations that don't require the
user to enter something before continuing.
Although the Windows screen may consist of a number of windows, only one
window is active for the purpose of receiving input. This is known as
having the focus. Windows is a multitasking environment that is capable of
running several concurrent tasks, or processes so your access to a database
may be in a non-serial fashion (parallel multi-tasking modes). Windows
provides more than one method for sharing information between applications.
The book Visual Objects: A Developer's describes Modal vs Modeless with
mention of ideas on DOS vs Windows. DOS applications are generally Modal
whereas Windows applications are "Modeless". The difference between modal
(non-event driven and procedural) and modeless (event-driven) systems can be
summarized in the question of who is in control of the flow, the user or the
programmer. A modal system is tightly structured and easier to code,
because the developer maintains control at all times. The user begins at
the main menu, and then selects from submenus, but not able to interact with
the system as in the case of an event-driven system such as the Windows
operating system. The typical Windows software applications are designed to
be event-driven , and often involve multiple windows which are to respond to
the browsing whims of the user. A user can move between a database, a
calendar, etc.
Windows Software Development: Concepts and Issues
By 1993 the Windows API programming interface, and the inventory of existing
Windows applications was so great that even companies producing for other
operating systems were making the effort to integrate their software with
the Windows machines. This explains the rising of the multidatabase DBMS.
Macintosh, SUN, and OS/2 computers have features which connect their
applications with Windows compatibility design. The date which Superbase 95
provides on the splash screen at startup is the date December 1994.
Resources are defined as "elements of an application such as string tables,
fonts, dialog boxes, cursors, icons, and keyboard accelerators that are
compiled independently of the source code and bound to the executable image
at link time." In other words he says that he wants to describe resources
as independently linked software components.
A Windows database i.e., Superbase 95 can be used to access and present
information to the user. The information would be of a format such as text,
graphics, sound, and video. Windows has a rich features set and the
capabilities are extended with custom extensions that have been written for
Windows.
North will outline some of the tools and developer products for Windows in a
latter chapter. GUI objects such as push buttons, check boxes, list boxes,
and so on are small child windows called controls. Windows includes a
standard set of controls, but you can extrend an applications capabilities
by creating and installing custom controls.
The form-processing facilities are controls in the API which allow basic
input through the browser.
Multi-document features
Dynamic Data Exchange (DDE) permits two applications to establish a dialog
to exchange data. The Windows Clipboard is an area of shared memory that
supports cut-and-paste operations. Windows ODBC provides a single API for
database access. Object Linking and Embedding (OLE) includes a set of
functions that provide object sharing across applications. The Messaging
API (MAPI) provides functions that permit developers to support messaging
and to produce email-enabled applications. Note that a technology known as
CORBA may be an advanced cross-platform implementation which is
programmable. The books are highly technical.
The use of the Windows extended area memory is suitable for larger objects
and for large buffers that can be set aside for SQL queries. This would
point in the direction of database applications with high end data
extraction performance requirements. Data warehousing deserves a good
introduction later in this paper. QBE data extraction procedures may fit
into this discussion.
You can use QBE's Insert, Update, and Delete commands to insert, update, and
delete groups of records in database files. You enter the Insert, Update,
or Delete command on a row of the table that represents the file where you
want to insert, update, or delete records. When you need to make the same
change to many records in a database file, you can use the file menu
Data/Update command. You write a filter to select the group of records you
want to update. You can link files if you want to update two files at once.
You create an update definition to tell Superbase which fields you want to
update, and how you want to update them. An update definition contains:
A filter which specifies which records you want to update
An update formula to specify which fields you want to update, and the data
you want to update them with.
You can save an update definition and use it again later
Windows Data Objects
QBE Insert command - use Insert to add new records to a database file. (See
QBE Basics of Database Management)
QBE Update command - use Update to update the records in a database file
with new values. You can also update a group of records, rather than all
records, in a file.
Enter the Update command in only one row of the table however. Make sure
the format properties of the new data matches the format of the field you
are updating. Do not enter commands such as Include, Group, or Sort, with
an Update row.
When you need to make the same change to many records in a database file,
you can use the file menu Data/Update command. You write a filter to
select the group of records you want to update. You can link files if you
want to update two files at once.
Database Management
The chapter 11 Microcomputer Applications by Graue and Sugrue presents a
Corporate Profile (a feature of each chapter) on Ashton-Tate Corporation,
the developer of the dBase series, the dominant data management software for
the PC. After reading chapter 11 you will be able to:
Define the terms field, record, and file; describe what is meant by the term
file structure
Distinguish between data and information; describe the techniques used to
convert data to information
Describe what is meant by file maintenance; list its three basic operations
Differentiate between character, numeric, date, and logical fields
Distinguish between an ascending and a descending sequence, and between a
primary and a secondary key
Define GIGO; state its relevance to data management (garbage in - garbage
out)
Describe indexing; explain how the availability of indexes makes it possible
to list a given file in multiple sequences
Describe what is meant by a relational database and the advantages of this
type of file organization
A record is similar to the manual system's uses for manila folders stored in
file cabinets. All of the information about a particular individual would
be held within a single manila folder. The complete set of these manila
folders would be called a file.
The order of the fields within a record of a computerized data management
system is the same for every record in the file, and is caled a file (or
record) structure.
The key is used to keep records of the file in a sequence, by a particular
field.
Rearranging Fields by Using Query-By-Example
Basics of Data Management Using QBE - you can use QBE's Insert, Update, and
Delete commands to insert, update, and delete groups of records in database
files. You enter the Insert, Update, or Delete command on a row of the
table that represents the file where you want to insert, update, or delete
records.
QBE Insert command - use Insert to add new records to a database file. (See
QBE Basics of Database Management)
QBE Update command - use Update to update the records in a database file
with new values. You can also update a group of records, rather than all
records, in a file. Enter the Update command in only one row of the table
however. Make sure the format properties of the new data matches the format
of the field you are updating. Do not enter commands such as Include,
Group, or Sort, with an Update row.
Using a combination of selection, and calculation and then presentation of
the results in a meaningful sequence is fundamental to converting data to
information. For example, in assessing the effects of a contemplated
across-the-board salary increase, management needs to know the total payroll
rather than individual salary amounts. In similar fashion, decisions about
next year's hiring will be influenced, at least in part, by knowing how many
individuals are currently employed in each job category. Information needed
will be rearranged into the form perceived as useful, i.e., a list of
employees earning more than $35,000 or a total of all employee salaries.
Consider an example record structure with the fields, Soc Sec Num, Name,
Salary, Hire Date, Title, Location
Soc Sec Num Name Salary Hire Date Title Location
100000000 Davis 34000 01/02/86 Account Rep
200000000 Friedel 48000 02/17/84 Manager
300000000 Kendrick 26500 02/16/86 Account Rep
333333333 McGrath 17000 04/25/86 Account Rep
400000000 Cordell 27200 04/02/87 Account Rep
444444444 Facella 24700 01/15/87 Account Rep
500000000 Pattishall 38500 11/11/84 Account Rep
555555555 Ferraro 26400 02/02/85 Account Rep
600000000
700000000
800000000
900000000 Tillberg 35500 10/29/82 Manager
999999999 Grauer 37500 03/16/85 Account Rep
Selection
Selection implies that only some of the records in a file, that is, those
records meeting a specified criterion, should be included in the resulting
report. A few examples are provided just below and referred to a few useful
reports. One report lists the employers that are managers. Another report
lists the employees who earn more than $35,000. And the other lists those
who are employed in Miami.
Each of the reports mentioned has a different presentation sequence,
consistent with the overall nature of the report. One report lists the
employees alphabetically. Another displays the employees in decreasing
order of salary . The third displays the employees in a chronological order
in order of the hire date.
Sequencing
A sequence by which the records in a report are displayed is done
independently from selection and further enhances the utility of a
particular report.
Sequencing can also be useful without selection or calculation, to produce
information. For example a grouping of employees , listing employees
alphabetically by last name by their location. The process of sequencing
produces a report that is inherently more useful than the original data of
the original file (natural order of entry).
Your sequence will be based on two keys for the example described above.
The two keys would be employee location and employee name. Location is the
more important, or primary key. Name is less important, secondary key.
Another type of terminology refers to location as the major key, and the
employee name as the minor key.
Calculation
Calculation takes advantage of what the computer does best, number
crunching. Calculation is often used to produce summary reports. Summary
reports omit the detail lines and show summary totals instead. Such summary
reports are used by management to present an aggregate view of an
organization.
Note the sequences in which the results are presented: alphabetically by
location, and alphabetically by title. It would be a good idea to enter the
given employee records into Superbase 95 and practice producing the reports
which are shown see p. 369 Microcomputer Applications Grauer and Sugrue.
Reporting Software Constraints
The utility of reports produced with selection and sequencing, or with
sequencing alone will be only as useful as the data from which they are
produced will allow. And even the most sophisticated data-management system
cannot compensate for inaccurate or incomplete data.
File Design
The process of data management involves the creation of the file itself and
the all-important determination of what data is needed for problem-solving.
You must first decide exactly what information the system needs to provide,
then determine the data necessary for the system to accomplish its
objectives. You then design a file structure that establishes the fields in
each record, their order, their length, and the type of data to be stored
in each field. The decisions about the fields are subjective in nature, and
consequently, there can be multiple solutions for any given system.
Once your conceptual decision about the type of information needing to be
stored is made, the data type choices are not as subjective, because once
you have decided to include a piece of information in a particular field,
its data type follows automatically from the purpose of the field. Four
distinct data types are commonly used, as follows:
Numerica fields
Character fields
Data fields
Logical fields
Once the file definition is decided and the file structure is created using
Superbase 95, the data is entered into the system on a record by record
basis.
Data Management
This information is from Microcomputer Applications by Graue and Sugrue
publ. McGraw Hill 1987. Chapter 11 introduces the subject of data
management, and begins with a comparison of principles under which a manual
record-keeping system is similar to computerized data management. Basic
data management uses terms such as field, record, file, and database and
leads to procedures known as file-maintenance where new records are added,
and existing records are modified or deleted. The objective if any data
management system is the analysis of data. The term data management system
is the very term used in the Superbase manuals Designing Databases, and
Using Superbase. The emphasis of chapter 11 Introduction to Data Management
is the distinction between data and information, and an explanation of how
data is converted to information.
Programmers use file and record managers to provide data management, but
these products generally lack features found in a true DBMS. These are
products which North compares to hierarchical and other "true" DBMS products
P. 3 North.
The test as to whether a DBMS meets the test as a relational database would
be whether that software product is in conformance with the 12 Rules of E.
F. Codd, the author of the relational model.
..
The book by North discusses Visual Basic objects, Access objects, OLE
objects, C++ objects and others.
Additions, Deletions and Modifications
Normal business operations will require updates to the records in the manila
folders in the filing cabinet. The filing cabinet contents should always
reflect the current state of the business. Whenever an employee is hired,
you will have to add another manila folder for his record. In a similar
fashion, when an employee resigns from the company you will delete the
folder. You will need to modify the folder of an employee who receives a
raise, changes location, and so on. Changes of this nature (additions,
deletions, and modifications) are known as file maintenance operations, and
are necessary in both a manual or computerized system.
An organized system of data MIS requires file maintenance operations because
they take place within the overall quality of any information which can be
produced by using the data (to use is to effect change). The data in the
system has to accurately reflect the current state of the business. Putting
data into the computer is relatively easy, but to retrieve it in a
meaningful form is quite another matter.
In computer science as well as in statistics data refers to a fact or facts
about a person, place or thing. John K. Lyon gave an interesting definition
of data in his book. Data refers to something, he said (check that paper)..
Each field in a row of data is a data item. Data is used as the raw
material from which information can be produced.
Converting Data into Information
Data is converted into information through a process of selection and
calculation, and then presentation of the results in a meaningful sequence.
Some useful reports produced from the same data were:
Employees earning more than $35,000
Name Salary Hire Date Title Location
Fitzgerald $53000 04/19/83 Manager Chicago
Friedel $48000 02/17/84 Manager Miami
Martineau $48000 02/28/83 Manager Los Angeles
Pattishall $38500 11/11/84 Account Rep Miami
Grauer $37500 03/16/85 Account Rep Miami
McGrath $37000 04/25/86 Account Rep Chicago
Tillberg $35000 10/29/82 Manager Boston
===============================================
Miami office's employees by seniority
Name Salary Hire Date Title
Friedel $48000 02/17/84 Manager
Hirschberg $28500 06/19/84 Account Rep
Pattishall $38500 11/11/84 Account Rep
Ferraro $26400 02/02/85 Account Rep
Grauer $37500 03/16/85 Account Rep
Kendrick $26500 02/16/86 Account Rep
===============================================
Employees who are managers
Name Salary Hire Date Location
Fitzgerald $53000 04/19/83 Chicago
Friedel $48000 02/17/84 Miami
Martineau $48000 02/28/83 Los Angeles
Tillberg $35000 10/29/82 Boston
===============================================
Information Utilities
Public databases are also known as information utilities, which are
available to users that have the means of accessing them. Generally, public
utilities are private companies that sell universally necessary services and
information. In this age of computers, there are a number of public
information utilities that sell computer services and information. These
more general information utilities are not yet universally necessary
services, but their importance is growing rapidly also.
Many of the public information utility companies are highly specialized.
For example the Dow Jones News/Retrieval Service provides investors and
stockholders with financial news and up-to-the-minute stock prices and bond
prices. LEXIS serves lawyers by offering them a rapid overview of cases
that may serve as precedents in any given area of legal interest.
University-based information utilities supply the latest scientific research
data and run bibliographic searches for scholars.
A public information utility has a large computer and a variety of
constantly updated databases; its product (information) can be accessed by
customers over telephone lines or other networks; and billing is based on
the access time. Some information utilities gather together specialized
databases from many disciplines. Subscribers to Lockheed's DIALOG system,
for example, may choose from the offerings of over 150 database developers
in such fields as business, government, the social sciences, engineering,
and medicine - the computer user will usually begin a session by searching
the utilities reference database for possibly useful references. The user
then accesses the most useful references in the utility's source database
which is made up of books, technical journals, magazines, and newspapers.
The user writes his choice of research to a disk and disconnects from the
DIALOG database. Then he prints his reference material for himself.
Note that it may be argued that personal computer users are voting with
their dollars for public information utilities as necessary to their lives.
General information databases as well as recreational and business
information datebases command prices from their markets, nightly rates are
discounted usually.
Other general-purpose information utilities serve the microcomputer
audience. General-purpose information utilities offer both general-interest
and specialized databases -for example national news, financial data,
recipes, or information about computers -as well as such communication
services such as electronic mail, electronic BB's, and multiplayer
electronic games. The growing system of networks and information utilities,
linking microcomputers to large computers as well as to other
microcomputers, may expand the reach of computer power and the effect that
it has on our lives.
Personal Databases
At the most common end of information utility services would be those which
can be created on our personal computer, for our own personal research or
informational needs. The articles we have written from our own personal
library of books that we use for references can be outlined and linked for
quick reference. The formats of data which we use can be saved within file
templates that can be reproduced when we need to write new programs which
further exploit data of the format from these file types. Technical help
files that describe some of the code in our own programs can similarly, be
saved as links in a local information space. Information sharing between
reference document databases and reference books can offer an effective
information services resource.
Data Processing Applications (Problem-solving Approach)
Application software programs can be considered, or can be taken to be
compositions of a hierarchical (horizontal or vertical) series of task
modules which are performed within a hierarchy from the lower levels of the
designs of the application program system, or from beginning to end; to
serve an organizational purpose or a broad schema.
Logically an applicaton can be divided into measurable tasks with a lower
level task module representing a processing task which can be invoked
(called) to serve upper level task modules. Otherwise, it can be seen as a
task series which is sequentially repetitious also. Yet in the world of
business transactions the connections are not clean and regimental as those
of the most simple designs for applications, such as the Corporation.
Logically a task module is one problem related task that the software
program performs i.e., Add NewRecord, or Create Bill. However, physically a
module is implemented as a sequence of programming instructions bounded by
an entry point and an exit point. Modules are usually also interrelated by
a control structure. Control is defined as program block-to-block action,
and the statements which are used are: IF ( ), WHILE ( ), DO-WHILE ( ), FOR
( ), SWITCH ( ), BREAK, ERROR, FLAG, CONTINUE, and GOTO to affect the
control of logical operatons.
An appreciation of the current state of the environment which we are
interested in influencing is the place we have to begin. An essential
technique used for planning for participating in the changes occurring
within the environment would need to understand and assess the likely
changes to occur even without intervention -indirect participation can be
related to the observation of changes, and can also be related to the
observer's position -oneself in relationship to other systems of the world.
Another indirect participation can amount to understanding the environment
and preparation of a plan for intervention in the environment and this is in
fact a strategy used in game theory. Will the systems influencing the
environment be totally in agreement or partly resistant to another/new
effort to implement changes in the environment? How much of the effort at
intervening within the environment depends upon a clandestine shock attack?
How functional is the network which supports the environment? The
assumptions about the performance of the network would amount to another
assessment of an indirect influence with regard to a plan, and a
consideration of issues needed for a direct involvement in the environment.
Applications (systems) which are built upon their client-server network
architecture foundation apply the instructions of Third Generation
programming languages, and Fourth Generation programming languages which are
meant to perform tasks within an environmment controlled through a useful
distributed client server network architecture and an integrated mix of
functional resources (function applications i.e., accounting, inventory,
etc.). Utility applications are also used for general file management,
system monitoring, etc
Private Data Banks
Private or restricted data banks may contain confidential information about
individuals; others hold highly sensitive information relevant to national
security, which must be maintained with integrity.
OLTP Systems
OLTP systems are used by production workers in corporations. The data that
they work with is current data. Reports using the data cannot be
reconstructed with the expectation of obtaining the same results each time,
due to the nature of this live data. Data access of the production workers
to the data is continuous. The data format of the data is raw data, as
opposed to an compiled information report. The data is at a detailed and
unsummarized transaction data level.
Database performance is fast performance, using highly automated repetitive
tasks. The data formats are defined at the time that the applications for
the OLTP are designed. And access to the database will usually be limited to
a few records at a time. There are no provisions to display timed snapshots
of the data, or multiple versions. The data access pattern is that of a a
multiple user access production database p. 207 Client Server Survivor
Guide.
The description of the OLTP transaction system above tends to be associated
with what private data banks would be expected to utilize with respect to
the lower levels of a working data bank model. OLTP systems collect data
from a single application. The source of the data will always be connected
back to the application. A data warehouse supports an OLTP system by
providing a place for the OLTP database to offload data as it accumulates,
and by providing services that would complicate and degrade OLTP operations
if they were performed in the OLTP database.
Without a data warehouse to hold historical information, data is archived to
static media such as magnetic tape, or allowed to accumulate in the OLTP
database.
If data is simply archived for preservation, it is not available or
organized for use by analysts and decision makers. If data is allowed to
accumulate in the OLTP so it can be used for analysis, the OLTP database
continues to grow in size and requires more indexes to service analytical
and report queries. These queries access and process large portions of the
continually growing historical data and add a substantial load to the
database. The large indexes needed to support these queries also tax the
OLTP transactions with additional index maintenance. These queries can also
be complicated to develop due to the typically complex OLTP database schema.
A data warehouse offloads the historical data from the OLTP, allowing the
OLTP to operate at peak transaction efficiency. High volume analytical and
reporting queries are handled by the data warehouse and do not load the
OLTP, which does not need additional indexes for their support. As data is
moved to the data warehouse, it is also reorganized and consolidated so that
analytical queries are simpler and more efficient.
Online analytical processing (OLAP) is a technology designed to provide
superior performance for ad hoc business intelligence queries. OLAP is
designed to operate efficiently with data organized in accordance with the
common dimensional model used in data warehouses.
A data warehouse provides a multidimensional view of data in an intuitive
model designed to match the types of queries posed by analysts and decision
makers. OLAP organizes data warehouse data into multidimensional cubes based
on this dimensional model, and then preprocesses these cubes to provide
maximum performance for queries that summarize data in various ways. For
example, a query that requests the total sales income and quantity sold for
a range of products in a specific geographical region for a specific time pe
riod can typically be answered in a few seconds or less regardless of how
many hundreds of millions of rows of data are stored in the data warehouse
database.
OLAP is not designed to store large volumes of text or binary data, nor is
it designed to support high volume update transactions. The inherent
stability and consistency of historical data in a data warehouse enables
OLAP to provide its remarkable performance in rapidly summarizing
information for analytical queries.
In SQL Server 2000, Analysis Services provides tools for developing OLAP
applications and a server specifically designed to service OLAP queries.
Data mining is a technology that applies sophisticated and complex
algorithms to analyze data and expose interesting information for analysis
by decision makers. Whereas OLAP organizes data in a model suited for
exploration by analysts, data mining performs analysis on data and provides
the results to decision makers. Thus, OLAP supports model-driven analysis
and data mining supports data-driven analysis.
Data mining has traditionally operated only on raw data in the data
warehouse database or, more commonly, text files of data extracted from the
data warehouse database. In SQL Server 2000, Analysis Services provides data
mining technology that can analyze data in OLAP cubes, as well as data in
the relational data warehouse database. In addition, data mining results
can be incorporated into OLAP cubes to further enhance model-driven analysis
by providing an additional dimensional viewpoint into the OLAP model. For
example, data mining can be used to analyze sales data against customer
attributes and create a new cube dimension to assist the analyst in the
discovery of the information embedded in the cube data.
Data Mining is a Data Warehouse Tool
Before embarking on the design of a data warehouse, it is imperative that
the architectural goals of the data warehouse be clear and well understood.
Because the purpose of a data warehouse is to serve users, it is also
critical to understand the various types of users, their needs, and the
characteristics of their interactions with the data warehouse. A data
warehouse exists to serve its users-analysts and decision makers. A data
warehouse must be designed to satisfy the following requirements:
Deliver a great user experience-user acceptance is the measure of success
Function without interfering with OLTP systems
Provide a central repository of consistent data
Answer complex queries quickly
Provide a variety of powerful analytical tools, such as OLAP and data mining
Most successful data warehouses that meet these requirements (above) have
these common characteristics:
Are based on a dimensional model
Contain historical data
Include both detailed and summarized data
Consolidate disparate data from multiple sources while retaining consistency
Focus on a single subject, such as sales, inventory, or finance
Data warehouses are often quite large. However, size is not an architectural
goal-it is a characteristic driven by the amount of data needed to serve the
users.
Data Warehouses
The data warehouse is based upon the emphasis between decision support
processing systems, and operational informational support processing OLTP
production. By 1994 hundreds of data warehouse products started to
ship -including various decision support tools. Sybase 10's replicated
server, Oracle 7's replication facility, Teradata, Ingres' Replica Manager,
MDI Database Gateway, Red Brick, Prism Solutions' Warehouse Manager,
Evolutionary Technologies Extract Toolsuite, Trinzic Corp's InfoPump, and
Digital's Data Distributor. Data warehouse products will grow into a $8
billion market by 1997, up $2 billion from 1995.
A relational database is designed for a specific purpose. Because the
purpose of a data warehouse differs from that of an OLTP, the design
characteristics of a relational database that supports a data warehouse
differ from the design characteristics of an OLTP database which is used to
collect and to clean up data and provide that fresh data to the data
warehouse.
Data warehouse users can be divided into four categories: Statisticians,
Knowledge Workers, Information Consumers, and Executives. Each type makes up
a portion of the user population as illustrated in this diagram:
-------------
(1) Statisticians: There are typically only a handful of sophisticated
analysts (2% of users)-Statisticians and operations research types-in any
organization. Though few in number, they are some of the best users of the
data warehouse; those whose work can contribute to closed loop systems that
deeply influence the operations and profitability of the company. It is
vital that these users come to love the data warehouse. Usually that is not
difficult; these people are often very self-sufficient and need only to be
pointed to the database and given some simple instructions about how to get
to the data and what times of the day are best for performing large queries
to retrieve data to analyze using their own sophisticated tools. They can
take it from there.
(2) Knowledge Workers: A relatively small number of analysts (15% of users)
perform the bulk of new queries and analyses against the data warehouse.
These are the users who get the "Designer" or "Analyst" versions of user
access tools. They will figure out how to quantify a subject area. After a
few iterations, their queries and reports typically get published for the
benefit of the Information Consumers. Knowledge Workers are often deeply
engaged with the data warehouse design and place the greatest demands on the
ongoing data warehouse operations team for training and support
(3) Information Consumers: Most users (82% of users) of the data warehouse
(includes Corporate Executives) are Information Consumers; they will
probably never compose a true ad hoc query. They use static or simple
interactive reports that others have developed. It is easy to forget about
these users, because they usually interact with the data warehouse only
through the work product of others. Do not neglect these users! This group
includes a large number of people, and published reports are highly visible.
Set up a great communication infrastructure for distributing information
widely, and gather feedback from these users to improve the information
sites over time.
(4) Executives: Executives are a special case of the Information Consumers
group. Few executives actually issue their own queries, but an executive's
slightest musing can generate a flurry of activity among the other types of
users. A wise data warehouse designer/implementer/owner will develop a very
cool digital dashboard for executives, assuming it is easy and economical to
do so. Usually this should follow other data warehouse work, but it never
hurts to impress the bosses.
The Elements of Data Warehousing
Almost all data warehousing systems provide the following four elements
(see. fig 12-1 Client Server Survivor Guide)
The Data Replication Manager
The data replication manager manages the copyiing and distribution of data
across databases as defined by the information user. The information user
defines the data that needs to be copied, the source and destination
platforms, the frequency of updates, and the data transforms. Refresh
involves copying over the entire data source; update only propagates the
changes. Everything can be automated or done manually. Data can be obtained
from relational or non-relational sources.
Note that almost all external data is transformed and cleansed before it's
brought into the warehouse. Will be covering data replication in detail in
the next sections p. 210 Client Server Survivor Guide.
On page 214 Client Server Survivor Guide the chapter is named Replication
vs. Direct Access he explains that it is impractical to create a centralized
repository of data because of performance, security, availability, and local
control etc. Replicated data management will increasingly be used to remove
the capacity, performance, and organizational roadblocks of centralized data
access. In the explanation replication is reference to data files which are
duplicated and updated on schedule to control the availability of updated
data records without using a centralized repository.
The Informational Database
The Informational Database is a relational database that organizes and
stores copies of data from multiple data sources in a format that meets the
needs of the information users. We can think of the informational database
as a decision support server that transforms, aggregates, and adds value to
data from various production sources. It also stored metadata (data about
data) that describes the content of the informational database.
The informational database can be a personal database on a PC, a medium
sized database on a local server, or a massively parallel database on an
enterprise server.
System level metadata describes the tables, indexes, and source extracts to
a database administrator (DBA); semantic level metadata describes the
contents of the data to an information user (what does this describe
exactly..?)
Most of the major SQL database engines can be used as information databases.
We will have more to say on database engines in the next two chapters
Chapter 13-14 Client Server Survivor Guide.
How Users Query the Data Warehouse
Information for users can be extracted from the data warehouse relational
database or from the output of analytical services such as OLAP or data
mining. Direct queries to the data warehouse relational database should be
limited to those that cannot be accomplished through existing tools, which
are often more efficient than direct queries and impose less load on the
relational database.
Reporting tools and custom applications often access the database directly.
Statisticians frequently extract data for use by special analytical tools.
Analysts may write complex queries to extract and compile specific
information not readily accessible through existing tools. Information
consumers do not interact directly with the relational database but may
receive e-mail reports or access web pages that expose data from the
relational database. Executives use standard reports or ask others to create
specialized reports for them.
When using the Analysis Services tools in SQL Server 2000, Statisticians
will often perform data mining, Analysts will write MDX queries against OLAP
cubes and use data mining, and Information Consumers will use interactive
reports designed by others.
Developing a Data Warehouse - Details
The phases of a data warehouse project listed below are similar to those of
most database projects, starting with identifying requirements and ending
with deploying the system:
Identify and gather requirements
Design the dimensional model
Develop the architecture, including the Operational Data Store (ODS)
Design the relational database and OLAP cubes
Develop the data maintenance applications
Develop analysis applications
Test and deploy the system
Identify sponsors. A successful data warehouse project needs a sponsor in
the business organization and usually a second sponsor in the Information
Technology group. Sponsors must understand and support the business value of
the project.
Understand the business before entering into discussions with users. Then
interview and work with the users, not the data-learn the needs of the users
and turn these needs into project requirements. Find out what information
they need to be more successful at their jobs, not what data they think
should be in the data warehouse; it is the data warehouse designer's job to
determine what data is necessary to provide the information. Topics for
discussion are the users' objectives and challenges and how they go about
making business decisions. Business users should be closely tied to the
design team during the logical design process; they are the people who
understand the meaning of existing data. Many successful projects include
several business users on the design team to act as data experts and
"sounding boards" for design concepts. Whatever the structure of the team,
it is important that business users feel ownership for the resulting system.
Interview data experts after interviewing several users. Find out from the
experts what data exists and where it resides, but only after you understand
the basic business needs of the end users. Information about available data
is needed early in the process, before you complete the analysis of the
business needs, but the physical design of existing data should not be
allowed to have much influence on discussions about business needs.
Communicate with users often and thoroughly-continue discussions as
requirements continue to solidify so that everyone participates in the
progress of the requirements definition.
Design the Dimensional Model
User requirements and data realities drive the design of the dimensional
model, which must address business needs, grain of detail, and what
dimensions and facts to include.
The dimensional model must suit the requirements of the users and support
ease of use for direct access. The model must also be designed so that it is
easy to maintain and can adapt to future changes. The model design must
result in a relational database that supports OLAP cubes to provide
"instantaneous" query results for analysts.
An OLTP system requires a normalized structure to minimize redundancy,
provide validation of input data, and support a high volume of fast
transactions. A transaction usually involves a single business event, such
as placing an order or posting an invoice payment. An OLTP model often looks
like a spider web of hundreds or even thousands of related tables.
In contrast, a typical dimensional model uses a star or snowflake design
that is easy to understand and relate to business needs, supports simplified
business queries, and provides superior query performance by minimizing
table joins.
For example, contrast the very simplified OLTP data model in the first
diagram below with the data warehouse dimensional model in the second
diagram. Which one better supports the ease of developing reports and
simple, efficient summarization queries
Dimensional Model Schemes
The principal characteristic of a dimensional model is a set of detailed
business facts surrounded by multiple dimensions that describe those facts.
When realized in a database, the schema for a dimensional model contains a
central fact table and multiple dimension tables. A dimensional model may
produce a star schema or a snowflake schema.
A schema is called a star schema if all dimension tables can be joined
directly to the fact table. The following diagram shows a classic star
schema
see microsoft.com site on data design for SQL Server.
A schema is called a snowflake schema if one or more dimension tables do not
join directly to the fact table but must join through other dimension
tables. For example, a dimension that describes products may be separated
into three tables (snowflaked) as illustrated in the following diagram.
Dimension Tables
Dimension tables encapsulate the attributes associated with facts and
separate these attributes into logically distinct groupings, such as time,
geography, products, customers, and so forth.
A dimension table may be used in multiple places if the data warehouse
contains multiple fact tables or contributes data to data marts. For
example, a product dimension may be used with a sales fact table and an
inventory fact table in the data warehouse, and also in one or more
departmental data marts. A dimension such as customer, time, or product that
is used in multiple schemas is called a conforming dimension if all copies
of the dimension are the same. Summarization data and reports will not
correspond if different schemas use different versions of a dimension table.
Using conforming dimensions is critical to successful data warehouse design.
User input and evaluation of existing business reports help define the
dimensions to include in the data warehouse. A user who wants to see data
"by sales region" and "by product" has just identified two dimensions
(geography and product). Business reports that group sales by salesperson or
sales by customer identify two more dimensions (salesforce and customer).
Almost every data warehouse includes a time dimension.
In contrast to a fact table, dimension tables are usually small and change
relatively slowly. Dimension tables are seldom keyed to date.
The records in a dimension table establish one-to-many relationships with
the fact table. For example, there may be a number of sales to a single
customer, or a number of sales of a single product. The dimension table
contains attributes associated with the dimension entry; these attributes
are rich and user-oriented textual details, such as product name or customer
name and address. Attributes serve as report labels and query constraints.
Attributes that are coded in an OLTP database should be decoded into
descriptions. For example, product category may exist as a simple integer in
the OLTP database, but the dimension table should contain the actual text
for the category. The code may also be carried in the dimension table if
needed for maintenance. This denormalization simplifies and improves the
efficiency of queries and simplifies user query tools. However, if a
dimension attribute changes frequently, maintenance may be easier if the
attribute is assigned to its own table to create a snowflake dimension.
It is often useful to have a pre-established "no such member" or "unknown
member" record in each dimension to which orphan fact records can be tied
during the update process. Business needs and the reliability of consistent
source data will drive the decision as to whether such place holder
dimension records are required.
Hierarchies
The data in a dimension is usually hierarchical in nature. Hierarchies are
determined by the business need to group and summarize data into usable
information. For example, a time dimension often contains the hierarchy
elements: (all time), Year, Quarter, Month, Day, or (all time), Year
Quarter, Week, Day. A dimension may contain multiple hierarchies-a time
dimension often contains both calendar and fiscal year hierarchies.
Geography is seldom a dimension of its own; it is usually a hierarchy that
imposes a structure on sales points, customers, or other geographically
distributed dimensions. An example geography hierarchy for sales points is:
(all), Country or Region, Sales-region, State or Province, City, Store.
Note that each hierarchy example has an "(all)" entry such as (all time),
(all stores), (all customers), and so forth. This top-level entry is an
artificial category used for grouping the first-level categories of a
dimension and permits summarization of fact data to a single number for a
dimension. For example, if the first level of a product hierarchy includes
product line categories for hardware, software, peripherals, and services,
the question "What was the total amount for sales of all products last
year?" is equivalent to "What was the total amount for the combined sales of
hardware, software, peripherals, and services last year?" The concept of an
"(all)" node at the top of each hierarchy helps reflect the way users want
to phrase their questions. OLAP tools depend on hierarchies to categorize
data-Analysis Services will create by default an "(all)" entry for a
hierarchy used in a cube if none is specified.
A hierarchy may be balanced, unbalanced, ragged, or composed of parent-child
relationships such as an organizational structure. For more information
about hierarchies in OLAP cubes, see SQL Server Books Online
Videotex
What is videotex? In 1984, three giant companies CBS, IBM, and
Sears -announced a joint venture in the videotex business. Videotex differs
from other information utilities where the others have transmissions made
solely of text, but videotex also transmits pictures.
The user of a home terminal interacts with the videotex system by - for
example, calling up a page of a an electronic catalog, studying the text and
pictures describing an item, and then transmitting the message "send me
that..". The videotex will transmit an image from the videotex database to
the home computer user's terminal.
AT & T has a true videotex system known as NAPLPS (North Amer. Presentation
Level Protocol Syntax) which was an improvement over some pseudo video
competition i.e.,Canada's Telidon system which achieves enhanced graphics by
means of alphageometric transmission, and uses television lines for
transmission.
At the present time, the videotex technology is maintained by the
general-purpose information utilities. If specialized databases of the
professional users function like libraries, then the general-purpose
information utilities for home-users resemble houseparties with animated
conversations are going on during the day and night. The general-purpose
information utilities are indeed vast, and highly interactive databases to
provide online customers with a range of information, graphics, and the
opportunity to exchange views with other subscribers.
The videotex meduim has a large potential for effect upon our lives i.e.,
at-home shopping, at-home banking, and other two-way consumer services are
convenient and when popularly priced they are likely to be successful.
Videotex is used for educational programming for the young as well as for
adults. Yet television was also considered to have potential as an
educational medium. The television did not reach the educational goals.
Another popular use is for engagement with politics and issues of the day.
Systems Development and Operations Management Strategy
A business education is incomplete without an understanding of modern
approaches to managing operations. Operations management (OM) provides a
systematic way of examining organizational processes. OM presents
interesting career opportunities and the concepts and tools of OM are widely
used in managing other functions of a business. The time frame of
management decisions is discussed along with the different types of
transformation processes. Services are compared to goods production with
emphasis on the primary inputs, resources, the primary transformation
functions, and the typical desired outputs in a variety of service and
operations examples. Value-added services are also discussed along with
their benefit to external customers.
Operations management is identified within the organizational chart and its
role in the organization is defined.
Chapter one presents a concept map and outlines the textbook chapters. The
chapters are grouped by the key themes of strategic planning, project
management, decision analysis, quality, supply chain management, and
e-commerce from Chap. II summary on web page Operations Management for
Competitive Advantage.
Historical Operations Managememnt
The historical roots of the development of OM are traced from scientific
management through the moving assembly line, the Hawthorne studies, and on
to today's current manufacturing topics including supply chain management
and e-commerce. This chapter concludes with current issues facing OM
executives including effectively consolidating the operations resulting from
mergers, developing flexible supply chains to enable mass customization of
products and services, managing global suppliers, production, and
distribution networks, increased commoditization of suppliers, achieving the
service factory, and achieving excellent service from service firms. -
Developing a flexible organizational model which distinguishes between
profitable and unprofitable customers.
Systems Development
Systems development is the activity of creating and modifying existing
business systems. It begins with an initiation of a systems investigation
to gain a clear understanding of the problem to be solved or opportunity to
be addressed. A business education is incomplete without an understanding
of modern approaches to managing operations. Several typical organizational
practices require close monitoring through operations management techniques.
I refer to organizational practices such as a learning curve in production,
delivery of customer services, and others.
Operations management (OM) provides Operations Management for Competitive
Advantage, by Chase, Jacobs, Aquilano et al. from Key Points chap. 1 from
mcgraw-hill.com/sites/ (shortcut on Francisco) a systematic way of
examining organizational processes. OM presents interesting career
opportunities and the concepts and tools of OM are widely used in managing
other functions of a business.
The time frame of management decisions is discussed in chapter 1 along with
the different types of transformation processes. Services are compared to
goods production with emphasis on the primary inputs, resources, the primary
transformation functions, and the typical desired outputs in a variety of
service and operations examples. Value-added services are also discussed
along with their benefit to external customers.
Operations management is identified within the organizational chart and its
role in the organization is defined.
Chapter one presents a concept map and outlines the textbook chapters. The
chapters are grouped by the key themes of strategic planning, project
management, decision analysis, quality, supply chain management, and
e-commerce.
Chapter 1. Key Outline
I. Operations Management - A Critical Responsibility for Every Manager
II. What is Operations Management?
III Transformation Processes
IV OM in the Organizatinal Chart
V Operations as Service
VI Why is Operations Not Perceived as Important?
VII Historical Development of OM
VIII Current Issues in Operations Management
Chapter 2. Key Outline
I Operations Strategy
II Operations Competitive Dimensions
III The Corporate Strategy Design Process
IV Strategic Fit - Fitting Operational Activities to Strategy
V Attacking Through Operations - (Competitive Advantage)
VI Productivity Measurement
VII Conclusion
Chapter 2. Technical Note
Optimizing the Use of Resources with Linear Programming
1. Introduction - Linear Programming - Define
2. The Linear Programming Model
3. Graphical Linear Programming
4. Linear Programming Using Microsoft Excel
5. Genetic Solver Option
Chapter 2 In Brief - Linear programming, or LP, is one of the most powerful
tools of management science. It is a mathematical technique used to allocate
limited resources among competing demands in an optimal way. LP is a
mathematical optimization technique.
Linear programming problems must have limited resources, workers, equipment,
finances or material. They must also have an explicit objective such as to
maximize profit or minimize cost. There must be linearity and homogeneity.
Another constraint is divisibility. Normal linear programming assumes that
products and resources can be subdivided into fractions (parts of a whole).
If this subdivision is not possible, a modification of linear programming
called integer programming is used.
The steps in the graphical linear programming optimizing process are to (1)
formulate the problem in mathematical terms, (2) plot the constraint
equations, (3) determine the area of feasibility, (4) plot the objective
function, and finally (5) find the optimal point.
Spreadsheets can be used to solve linear programming problems and most
spreadsheets have built-in optimization routines that are very easy to use
and understand. For example, Microsoft Excel has an optimization tool called
Solver. The CD that accompanies your textbook has a new product from
Frontline Systems, called Premium Solver, that will work with Microsoft's
Solver and provide additional features including those for doing genetic
searches for non-linear problems.
Chapter 3. Project Management
A project is a series of related jobs or tasks directed toward a major
output. They require a long period of time to perform. Managing projects
require planning, directing and controlling resources. Before a project can
begin, senior management must decide which of three organizational
structures will be used to tie the project to the parent firm: pure project,
functional project, or matrix project. All three structures have advantages
and disadvantages.
Projects begin with a statement of work, which can be a written description
of the objectives. Breaking the work into smaller and smaller pieces that
defines the system in detail is at the center of project management.
Milestones or critical steps in the project might be (1) completion of the
design or (2) production of a prototype. Maintaining control over projects
requires the use of charts to show the scope of the entire project as well
as the steps completed at a particular time. Other reports for detailed
presentations of projects are used.
Critical path scheduling is a graphical technique used to plan and control
projects. Techniques like PERT and CPM display a project's completion in
graphical form. Both techniques focus on finding the longest time-consuming
path through a network of tasks as a basis for planning and controlling a
project. This longest sequence of activities is also the shortest processing
time for a project. Slack time for an activity is the amount of time an
activity can be delayed without affecting the overall completion time of the
project. Non-critical path activities have some slack time. Managers also
use PERT and CPM to compute the early start schedule and late start
schedules for activities so as not to delay the entire project and change
its original completion date.
Managers must consider the time to complete a project versus the cost to
complete the project. Time-cost trade-off models have been developed to help
managers with this task. (1) Clearly identified project responsibilities,
(2) a simple and timely progress reporting system, (3) teamwork, and (4)
good people-management practices are required in effective project
management. Teams must have the commitment of top management as well as a
talented project manager. CPM and PERT are simply tools to assist the
manager in meeting these objectives.
Chapter 4. Produt Design
Designing new products and getting them quickly to the market is the
challenge facing manufacturers in most industries. This chapter reviews how
manufactured products are designed. Many firms outsource major functions
rather than performing them in-house. Contract manufacturers specialize in
manufacturing products for other companies.
When deciding when to outsource manufacturing, a company must decide its
core competency or what it does better than competitors and outsource areas
other than the core competence. At one extreme is a fully vertically
integrated firm where all activities from design to part fabrication is
handled in-house to the other extreme of a company that only sells products
and outsources all design and manufacturing companies.
The product development process includes the conception and design of the
product as well as the actual steps to bring a product to the market. The
six phases are: (1) planning, (2) concept development, (3) system-level
design, (4) detail design, (5) testing and refinement, and (6) production
ramp-up. Products may range from generic or market-pull products to more
complex systems made up of several subsystems and many components. In
complex systems, like large-scale automobiles or airplanes, the design of
the components may be performed in a parallel process where many development
teams work on part of the product's design at the same time in a concurrent
engineering process.
Economic analysis also accompanies the product design. Teams may analyze the
net present value of cash flows. In addition sensitivity analysis is often
used to answer the "what if" questions. This analysis calculates changes in
the net present value to changes in one or more of the factors included in
the costing model.
The successful manufacturer must be able to generate new product ideas and
convert these into customer-friendly designs. These designs must be easy to
manufacture using an appropriate production process. In addition the voice
of the customer is part of the design specification of a new product. The
quality function deployment process begins with studying and listening to
the customer to determine characteristics of a superior product. Tools
including the house of quality assist in developing customer requirements.
Value analysis and value engineering is important to ensure any unnecessary
costs are identified and eliminated in products already in production and
even prior to production. Product designers must consider the function of
the product as well as the industrial uses of the product. Most products
have more technological features than necessary. In translating the
functional product design into a manufacturable product, designers must
consider materials to use as well as parts.
Generating a steady stream of new products to the market is important to an
organization's competitiveness. Firms must respond to changing customer
needs and the moves of their competitors. The ability to identify
opportunities, mounts the development effort, and brings the new products
and processes to market quickly are all key actions. Measures of product
development success relate to the time to the market, productivity, and
quality of the products introduced. Product development is a major challenge
directly impacting the long-range success of a firm.
Chapter 5. Process Analysis
An operations manager uses job design techniques to structure work to meet
the physical and behavioral needs of the employee. Work measurement methods
are used to determine the most efficient means of performing a given task,
as well as to set reasonable standards for performing it. Work performance
standards are important to the workplace so accomplished can be measured and
evaluated. Standards permit better planning and costing and provide a basis
for compensating the work force and even providing incentives.
Trends in job design include quality as part of the worker's job. Today many
workers are cross-trained to perform multiskilled jobs and total quality
programs are important for all employees. Team approaches, informating, use
of temporary workers, automation, and organizational commitment are other
key issues in job design decisions.
Behavioral considerations in job design include how specialized a job will
be. Specialization has unique advantages and disadvantages. At the other
extreme from specialization are the concepts of job enlargement and job
enrichment. Sociotechnical systems of the interaction between technology and
the work group influence job design as do ergonomic or physical
consideration.
Work methods determine how the work should be accomplished in organizations,
while work measurement determines how performance may be evaluated. Work
methods can be established for an overall productive system, a worker alone,
a worker interacting with equipment, and a worker interacting with other
individuals.
Work measurement and standards exist to set time standards for a job. A
technique used in work measurement is the time study. Examples of time
studies are included for a four-element job and for a nursing environment.
Finally, work sampling is compared to time study.
Another issue in job design is the financial incentive plan. These plans
determine how workers should be compensated. In preparing a financial
incentive plan, management must consider individual, group, and organization
wide rewards.
Chapter 6. Manufacturing Process Selection and Design
Process selection refers to the strategic decisions of selecting the kind of
production process to have in a manufacturing plant. The process flow in an
organization refers to how a factory organizes material flow using one or
more of the process technologies including the job shop, batch shop,
assembly line, and continuous flows. The process chosen depends on the
customization of the product as well as the volume required in the market.
The relationship between the process structures and volume requirements is
depicted on a product-process matrix. As volume increases the product line
narrows and specialized equipment and standardized material flows are come
economically feasible. The evolution in the process structure is often
related to the product's life cycle stage. Thus the matrix is useful in
linking marketing and manufacturing strategies.
Break even analysis allows manufacturing managers to visually present
alternative profits (and losses) based on the number of units produced or
sold. Specific equipment selection follows the selection of the general type
of process structure in an organization. The tools of break-even analysis
help managers make equipment selection decisions.
Process flow designs focus on the specific processes that raw materials,
parts, and subassemblies follow as they move through the plant. Charts and
drawings aid in process flow design.
Chapter 7. Service Process Selection and Design
Services are different from manufacturing, with the key service difference
being the interaction of the customer in the delivery process. Service
design is no longer considered to be an art form as logical approaches to
better design and management of service systems are emerging.
In a facilities-based service, the customer must go to the service facility.
In contrast, in a field-based service, the production and consumption of the
service takes place in the customer's environment. Internal services refer
to services required to support the activities of the larger organization.
There is a blurring of manufacturing and service firms since the
manufacturer product always has a certain percentage of service content.
Services are also seen as the next source of competitive advantage for
firms.
In services we also consider the amount of customer contact or the physical
presence of the customer in the system. Service systems range from those
with a high degree of customer contact to those with a low degree of
customer contact.
Service encounters can be configured in a number of different ways. The
service-system design matrix includes six common alternatives. Flowcharting,
like in manufacturing process design, is the standard tool for service
process design. The flowchart, or service blueprint, emphasizes the
importance of design. Poka-yoke systems applied to services prevent mistakes
from becoming service defects.
Approaches to services include the production line approach, the
self-service approach, and the personal attention approach. Service
guarantees are not only a marketing tool for services but, from an
operations perspective, these guarantees can be used as an improvement
incentive and can focus the firm's delivery system on things it must do well
to satisfy the customer. Finally the case on Pizza USA provides an example
of design of services.
Chapter 9. Operations Consulting and Reengineering
Operations' consulting assists clients in developing operations strategies
and improving production processes. In strategy development, the focus is on
analyzing the capabilities of operations in light of the firm's competitive
strategy. In process improvement, the focus is on employing analytical tools
and methods to help operating managers enhance the performance of their
departments. Regardless of where one focuses, an effective job of operations
consulting results in an alignment between strategy and process dimensions
in a way that enhances the business performance of the client firm.
The management consulting industry can be categorized in three ways: by
size, by specialization, and by in-house and external consultants. Most
consulting firms are small, generating less than $500,000 in annual
billings. Consulting firms are also frequently characterized according to
whether their primary skill is in strategic planning or in tactical analysis
and implementation.
Some of the major strategic and tactical areas where companies typically
seek operations consulting can be classified in five key areas. In the plant
area, assistance is provided for adding and locating new plants, expanding,
contracting or refocusing existing facilities. In the people area, the
consultants focus on quality including quality improvement, setting or
revising work standards, and learning curve analysis. Make or buy decisions
and vendor selection decisions are key parts decisions. Process decisions
for consultants include technology evaluation, process improvement, and
reengineering. Finally, planning and control systems analyzed by consultants
include supply chain management, MRP, shop floor control, and warehousing
and distribution.
Consultants are needed when companies are faced with major investment
decisions or when they believe they are not realizing maximum effectiveness
from their productive capacity. Operations consulting tools can be
categorized as tools for problem definition, data gathering, data analysis
and solution development, cost impact and payoff analysis, and
implementation.
Business process reengineering (BPR) is a way of rethinking and redesigning
business processes for improvements of performance, including cost, quality,
service, and speed. BPR uses many of the same tools used in consulting.
Principles of reengineering include: organize around outcomes, not tasks,
have those who use the output of the process perform the process, merge
information-processing work into the real work that produces the
information, treat geographically dispersed resources as though they were
centralized, link parallel activities instead of integrating their results,
put the decision point where the work is performed and build control into
the process, and capture information once - at the source.
Chapter 10. Supply Chain Strategy
The idea of supply-chain management is to apply a total systems approach to
managing the entire flow of information, materials, and services from
raw-materials suppliers through factories and warehouses to the end
customer. The focus is on those core activities that a business must operate
each day to meet demand. The topic is popular because many companies are
achieving competitive advantage by the way they configure and manage their
supply chain operations. Dell Computer is a good example of effective supply
chain management.
Because inventory at each stage of an operation ties up money, it is
important that the operations at each stage are synchronized to minimize the
size of buffer inventories. The efficiency of the supply chain can be
measured based on the size of the inventory investment in the supply chain.
Key measures to evaluate supply chain efficiency are inventory turnover and
weeks-of-supply. Other measures include the cost of goods sold and the
average aggregate inventory value.
Variability within the supply chain magnifies as we move from the customer
to the producer in the supply chain. This bullwhip effect indicates a lack
of synchronization among supply chain members. Programs like continuous
replenishment smooth the flow of materials through the supply chain.
Other supply chain issues occur because of the length of the product life
cycle, demand predictability, product variety, and market standards for lead
times and service. Products may be either functional staples or primarily
innovative and require different management methods.
Outsourcing is moving some of a firm's internal activities and decision
responsibility to outside providers. Companies have a variety of reasons for
outsourcing but primarily the reasons are to reduce costs and create a
competitive advantage. One popular area to outsource is logistics. In
determining the shipping mode for an item a key variable is the value
density or value per unit of weight.
Chapter 11. Strategic Capacity Management
Capacity is the ability to hold, receive, store, or accommodate. In a
business sense, it is viewed as the amount of output that a system is
capable of achieving over a specific period of time.
Strategic capacity planning has as its objective, to determine the overall
capacity level of capital-intensive resources - facilities, equipment, and
overall labor force size - that best supports the company's long-range
competitive strategy.
Economies of scale are important to capacity decisions. This concept
signifies that as production volumes increase, the average cost per unit
decreases. The experience curve also plays a role in capacity planning. As
plants produce more units, they gain experience in their production methods,
which in turn, results in reducing the per unit costs of production in a
predictable manner.
Capacity flexibility means having the ability to rapidly increase or
decrease production levels or to shift production capacity quickly from one
product or service to another. Such flexibility is achieved through flexible
plants, processes, and workers, as well as through strategies that use the
capacity of other operations.
Issues to be considered in adding capacity include maintaining system
balance, frequency of capacity additions, and the use of external capacity.
Capacity strategies can be proactive, neutral, and reactive. Reactive and
neutral strategies are not responsive to anticipating future growth or
building a facility for future demand. Capacity planning decisions are based
on forecasts for product demand, labor requirements, and equipment
requirements. Decisions include whether to add capacity, determining
capacity requirements, and planning service capacity throughout the product
life-cycle stages.
Chapter 11. Key Point - Facility Location
The problem of facility location is faced by both new and existing
businesses. Criteria that influence facility location include proximity to
customers, business climate, total costs, availability and quality of
infrastructure, quality of labor, suppliers, other available facilities,
free trade zones, political risk, government barriers, trading blocs,
environmental regulations, the host community and finally competitive
advantage.
Factor-rating systems are the most widely used location techniques as they
combine diverse factors in an easy-to-understand format. The transportation
method is a special linear programming method while the center of gravity
methods is another popular location solution method that focuses on
minimizing shipping costs and distances.
While it is usually less expensive to establish a service facility than a
manufacturing facility, service facilities have unique issues to consider.
When choosing a location for a service facility it is important to maintain
close contact with the customer. Frequently, regression models are used to
assist with site selection.
The criteria for selecting appropriate locations have evolved beyond the
singular focus on minimizing cost or distance. Today a number of
quantitative and qualitative issues impact location decisions. A company's
long-term success depends on its managers' ability to make a comprehensive
synthesis of the various dimensions of the multifaceted location problem.
Chapter 12. Lean Production
Lean production is based on the logic that nothing will be produced until it
is needed. Need is created by an actual demand for the product. When an item
is sold, in theory, the market pulls a replacement from the last position in
the system or final assembly. This triggers an order to the production line
which generates orders at upstream work stations. Lean demands high levels o
quality at each stage of the process, strong vendor relations, and a fairly
predictable demand for the end product.
In the 1990's many companies adopted the term lean in place of JIT (or
just-in time management) to emphasize the goal of systematically eliminating
all waste throughout their operations. Today JIT has come to refer mainly to
the production scheduling aspects including pull systems, which underlie the
lean philosophy.
In Japan, lean production principles have been used to isolate the elements
of waste in an organization. The Japanese practice a great respect for
people and depend on the personnel to identify and eliminate sources of
waste, excess, and inefficiency. The basic elements of lean are a focused
factory with networks following the strategy of reducing waste, the use of
group technology or teams for problem-solving, quality at the source so no
time and energy and materials are wasted on less than perfect quality
products, JIT production, uniform plant loading, Kanban production control
systems, and minimized setup times.
Value stream mapping is a network of steps from beginning to end that
provides the result for the customer. It is widely used as a means of
eliminating waste in a process. The key is to concentrate on moving all
waste in the process which includes all non-value added activities. Waste
should be identified in the factory as well as in other areas including the
office and all physical, procedural, and technical operations.
Group technology where similar parts are grouped into families for
production within a work cell eliminates movement and wait times between
operations and supports lean practices by reducing inventory and the number
of employees required.
Other principles of lean include quality at the source or stopping the
process or line immediately when something goes wrong. Workers become their
own inspectors and are responsible for quality. JIT production is producing
only what is needed when it is needed and no more. To eliminate large
variations in production schedules, uniform plant loadings are important.
Setting a firm monthly production plan and freezing the output rate will
provide a stable production environment. Kanban control systems can be used
as signaling devices to regulate JIT flows. Respect for people is also part
of lean implementations as is on-going preventive maintenance to ensure
machines and equipment are kept in top working order.
Just as customers and employees are key components of the Lean system,
vendors are also important to the process. Lean is also applicable to
service industries. Successful service applications include organizing
problem-solving groups, upgrading housekeeping and quality, clarifying
process flows, eliminating unnecessary activities, and developing supplier
networks.
Chapter 13. Forecasting
Forecasts are vital to every business organization and for every significant
management decision. While a forecast is never perfect due to the dynamic
nature of the external business environment, it is beneficial for all levels
of functional planning, strategic planning, and budgetary planning.
Decision-makers use forecasts to make many important decisions regarding the
future direction of the organization.
Forecasting techniques and models can be both qualitative and quantitative,
and their level of sophistication depends on the type of information and the
impact of the decision. The forecasting model a firm should adopt depends on
several factors including: forecasting time horizon, data availability,
accuracy required, size of the forecasting budget, and availability of
qualified personnel.
Demand management exists to coordinate and control all sources of demand so
the productive system can be used efficiently and the product delivered on
time. Demand can be either dependent on the demand for other products or
services or independent because it cannot be derived directly from that of
other products.
Forecasting can be classified into four basic types: qualitative, time
series analysis, causal relationships, and simulation. Qualitative
techniques in forecasting can include grass roots forecasting, market
research, panel consensus, historical analogy, and the Delphi method. Time
series forecasting models try to predict the future based on past data. A
simple moving average forecast is used when the demand for a product or
service is constant without any seasonal variations. A weighted moving
average forecast varies the weights, given a particular factor and is thus
able to vary the effects between current and past data.
Exponential smoothing improves on the simple and the weighted moving average
forecasts since exponential smoothing considers the more recent data points
to be more important. To correct for any upward or downward trend in data
collected over time periods to smoothing constants are used. Alpha is the
smoothing constant, while delta reduces the impact of the error that occurs
between the actual and the forecast.
Forecast errors are the difference between the forecast value and what
actually occurred. All forecasts contain some degree of error; however, it
is important to distinguish between sources of error and measurement of
error. Sources of error are random errors and bias. Various measurements
exist to describe the degree of error in a forecast. Bias errors occur when
a mistake is made, i.e., not including the correct variable or shifting the
seasonal demand. While random errors cannot be detected, they occur
normally.
A tracking signal indicates whether the forecast average is keeping pace
with any movement changes in demand. The MAD or the mean absolute deviation
also is a simple and useful tool in obtaining tracking signals. A more
sophisticated forecasting tool to define the functional relationship between
two or more correlated variables is linear regression. This can be used to
predict one variable given the value for another. It is useful for shorter
time periods as it assumes a linear relationship between variables.
Causal relationship forecasting attempts to determine the occurrence of one
event based on the occurrence of another event. Focus forecasting tries
several rules that seem logical and easy to understand to project past data
into the future. Today many computer forecasting programs are available to
easily forecast variables. When making long-term decisions based on future
forecasts, great care should be taken to develop the forecast. Likewise,
multiple approaches to forecasting should be used.
Chapter 14. Aggregated Sales and Operations Planning
Aggregate operations planning involves translating annual and quarterly
business plans into broad labor and output plans for the intermediate term
of 6 to 18 months. Its objective is to minimize the cost of resources
required to meet demand over that period. The aggregate operations plan is
necessary to translate long-term strategy plans down to the operational
level. It takes a broad view of the organization and attempts to match the
demand for the firm's products with its ability to supply these products at
a minimum cost.
Long-range planning is done once a year, focusing on a multi-year horizon
while medium-range planning covers 6 to 18 months into the future.
Short-range plans cover one day to six months in weekly increments. The
master production schedule generates the amounts and dates for the
production of end products and is fixed in the short run. Rough-cut capacity
planning verifies that the scheduled production is possible given capacity
constraints of facilities, equipment, and labor. Materials requirements
planning take the end product requirements from the MPS and break them down
into their component parts and subassemblies to create a material plan.
The final assembly schedule provides the operations required to put the
product in its final form. Production activity control focuses on scheduling
and shop floor control activities. Aggregate production planning varies from
company to company. Strategies of production planning include maintaining a
stable work force working at a constant rate, using a stable work force with
variable work hours, or using a chase strategy where workers are hired or
laid off as the demand varies. In addition, managers may choose to
subcontract some portion of production.
Costs relevant to aggregate production planning include basic production
costs to costs associated with changes in the production rate, inventory
holding costs, and backordering costs. To receive funding, operations
managers are generally required to submit annual and sometimes quarterly
budget requests.
Aggregate operations planning link the corporate strategic plan and the
capacity plans into broad categories of work-force size, inventory quantity,
and production levels. It does not do detailed planning. Once decision rules
for production planning have been selected, it is important for management
to maintain them. Historical data and simulations should be used prior to
implementation of aggregate planning to select an optimal decision rule.
Yield management allocates the right type of capacity to the right type of
customer at the right price and time to maximize revenue or yield and it can
make demand more predictable which is important to aggregate planning.
Chapter 15. Inventory Control
Inventory is the stock of any item or resource used in an organization.
Inventory can exist as raw materials, finished products, components parts,
supplies, and work-in process. Organizations keep inventory for a number of
reasons including to maintain independence of operations, to meet variation
in product demand, to allow flexibility in production scheduling, to provide
a safeguard for variation in raw material delivery time, and to take
advantage of economic purchase order size. Costs associated with inventory
include holding or carrying costs, setup or ordering costs, and shortage or
stockout costs.
Independent demand items are unrelated to each other and thus needed
quantities for these independent items must be determined separately. For
dependent demand items, the demand for one item is a direct result of the
need for other items. Component parts demand, for example, is dependent on
the demand for the final product.
Inventory systems can be modeled as fixed-order quantity or fixed-time
period. In the fixed-order quantity model, the same amount of inventory is
replenished in each order period. Necessary assumptions include: demand is
known, constant, and uniform throughout a period. Lead time is constant and
the price per unit and ordering costs are constant.
In a fixed-time period system, inventory is counted at fixed time intervals
and orders are placed on a periodic basis. This model is desirable in
situations when vendors make routine visits to customers and take orders for
their complete line of products or when buyers want to combine orders to
save on transportation costs.
Organizations must make decisions about the amount of safety stock to
maintain for protection against stockouts. The safety stock ensures a firm's
desired service level will be met. The quantity-discount inventory model
applies when the cost of an item varies with the order size. This model, as
in all inventory models, computes an economic order quantity (EOQ) to
minimize order costs and holding costs.
ABC analysis is a control technique. The highest dollar volume items, or "A"
items, are given the most rigorous cycle counting and attention for
inventory control.
Because many firms, including services, may have large inventory
investments, inventory reductions will also lead to improved quality and
performance in addition to reduced costs. Two examples of inventory control
in services are included and profile a department store and an automobile
service agency.
Chapter 16. Materials Requirements Planning
When demand is dependent on multiple materials, managers use a concept known
as materials requirements planning, or MRP, to determine demand for lower
level items. MRP is a logical approach to determine the number of parts,
components, and material needed to produce each end item. It also provides
the time schedule specifying when each of these materials, parts, and
components should be ordered or produced.
MRP has grown from planning materials to also planning for other
organizational resources needed. BOM can be used in a number of
manufacturing environments but does not work well in companies that produce
a low number of units annually. From an organization's aggregate plan, the
master production plan is developed. The MPS is the time-phased plan
specifying how many and when the firm plans to build each specific end item.
Further down the MPS process is the MRP, which calculates and schedules all
of the raw materials, parts, and supplies needed for production.
Management must specify a time fence, or period of time in which the
customer can make changes in their order. Once this time has passed, the
order becomes fixed. The MRP uses this fixed plan to create schedules to
identify the parts and materials required to produce end items, the exact
numbers needed, and the dates when orders for these materials should be
released and be received or completed within the production cycle.
Today, computerized inventory systems for MRP control inventory levels,
assign operating priorities for items, and plan capacity to load the
production system. The goal of MRP is to get the correct materials to the
right place at the right time.
The objectives of inventory management under an MRP system are to improve
customer service, minimize inventory investment, and maximize production
operating efficiency. The MRP interacts with the master production schedule,
the bills of material file, and the inventory records file. Product demand
data for MRP systems comes from two sources -- from customers who have
placed firm orders and from forecasted or anticipated demand.
The bill of materials (BOM) file contains the complete product description
listing the materials, parts, and components as well as the sequences in
which the product is created. MRP outputs can take a variety of forms and
can be classified as primary and secondary output reports. Capacity
constraints can be determined using capacity requirements planning. An MRP
program with a capacity requirement planning module allows rescheduling to
level capacity through either backward or forward scheduling. The master
schedule will level the load so requirements for work centers remain within
the available capacity.
MRP II has expanded the role of MRP to include planning for staffing,
facilities, and tools. Called manufacturing resource planning, it can plan
and monitor all the resources of a manufacturing firm including
manufacturing, marketing, finance, and engineering within a closed-loop
system.
MRP and JIT each have many benefits. Although JIT is best suited to
repetitive manufacturing, MRP is used in everything from custom job shops to
assembly line production. The term flow manufacturing is now being used by
many software vendors to describe new software modules that combine MRP and
JIT logic. Over time, experts predict that e-business will force
manufacturers to abandon the MRP or work order business model, a model that
depends on accurate forecasts. While MRP applications have many uses, few
service organizations have developed or implemented MRP believing it is just
a manufacturing tool.
Chapter 17. Operations Scheduling
Work centers are areas in a business in which productive resources are
organized and work is completed. It may be a single machine, a group of
machines, or an area where a particular type of work is done. The work
centers can be organized in a variety of ways including by function in a
job-shop configuration; or by product in a flow, assembly line, or
group-technology-cell configuration.
A characteristic that distinguishes one scheduling system from another is
how capacity is considered in determining the schedule. The scheduling
systems can use infinite loading or finite loading. Infinite loading occurs
when work is assigned to a work center simply based on what is needed over
time, while finite loading actually schedules in detail each resource using
the setup and run time required for each order.
Another characteristic that distinguished scheduling systems is whether the
schedule is generated forward or backward in time. Processes can be machine
limited or labor limited. Determining the sequence of orders and
establishing job priorities are critical as is dispatching orders. Shop
floor control is necessary to review job status and expediting late and/or
critical orders when necessary. The schedule must be revised as necessary to
reflect changes in order status.
Various priority rules work to satisfy job arrival patterns, the number and
variety of machines in the manufacturing facility, the ratio of workers to
machines in the shop, the flow pattern of jobs through the shop, the
priority rules for allocating jobs to machines, and schedule evaluation
criteria. Priority rules for allocating jobs to machines can use a variety
of methods.
The objectives of work-center scheduling are to meet customer due dates,
minimize lead-time, minimize set-up time, minimize work in process
inventory, and maximize machine or labor utilization.
Scheduling and controlling functions of an operation are critical. The
functions must be performed beginning with allocating orders, equipment, and
personnel to work centers or the specified locations for short-run capacity
planning. Next is the determination of the sequence of order performance or
establishing job priorities. Initiating the scheduled work or dispatching of
orders is followed by shop-floor control. Shop floor control or production
activity control involves reviewing the status and controlling the progress
of orders as they are being worked on and expediting late and critical
orders.
In manufacturing job shops, scheduling relies heavily on simulation to
estimate the flow of work through the system to determine bottlenecks and
adjust job priorities. Software packages are available to do this. In
services, the focus is typically on employee scheduling using mathematical
tools that can be used to set work schedules in light of expected customer
demand.
Optimizing the Use of Resources with Linear Programming - A business
education is incomplete without an understanding of modern approaches to
managing operations. Operations management (OM) provides a systematic way of
examining organizational processes. OM presents interesting career
opportunities and the concepts and tools of OM are widely used in managing
other functions of a business.
The time frame of management decisions is discussed along with the different
types of transformation processes. Services are compared to goods production
with emphasis on the primary inputs, resources, the primary transformation
functions, and the typical desired outputs in a variety of service and
operations examples. Value-added services are also discussed along with
their benefit to external customers.
Operations management is identified within the organizational chart and its
role in the organization is defined. Chapter one presents a concept map and
outlines the textbook chapters. The chapters are grouped by the key themes
of strategic planning, project management, decision analysis, quality,
supply chain management, and e-commerce.
The historical roots of the development of OM are traced from scientific
management through the moving assembly line, the Hawthorne studies, and on
to today's current manufacturing topics including supply chain management
and e-commerce. This chapter concludes with current issues facing OM
executives including effectively consolidating the operations resulting from
mergers, developing flexible supply chains to enable mass customization of
products and services, managing global suppliers, production, and
distribution networks, increased commoditization of suppliers, achieving the
service factory, and achieving excellent service from service firms.
The historical roots of the development of OM are traced from scientific
management through the moving assembly line, the Hawthorne studies, and on
to today's current manufacturing topics including supply chain management
and e-commerce. This chapter concludes with current issues facing OM
executives including effectively consolidating the operations resulting from
mergers, developing flexible supply chains to enable mass customization of
products and services, managing global suppliers, production, and
distribution networks, increased commoditization of suppliers, achieving the
service factory, and achieving excellent service from service firms.
Developing information systems to meet business needs is highly complex and
difficult; it is common for information systems projects to over-run budgets
and to exceed scheduled completion dates. Business managers would like the
development process to be more manageable, with predictable costs and
timiing. System development includes investigation, analysis, design,
implementation, and maintenance and review.
An information system (IS) is a set of interrelated components that
collect, manipulate, and disseminate data and information and provide a
feedback mechanism to meet an objective. We all interact daily with
information systems, both personally and professionally. WE use automatic
teller machines at banks, checkout clerks scan our purchases for bar codes,
and we access informaiton over the Internet. Major Fortune 500 companies
are spending more than $1 billion per year on information technology. In
the future, we will depend upon information systems even more. Knowingthe
potential of information systems and being able to put this knowledge to
work can result in a successful personal carreer, organizations that reach
their goals, and a society with a higher quality of life.
Computers and information systems are constantly changing the way
organizations conduct business. Today we live in an information economy.
Information itself has value, and commerce often involves the exchange of
information, rather than the exchange of tangibles. Systems based upon
computers are increasingly being used to create, store, and transfer
information. Investors are using information systems to make multi-million
dollar decisions. And financial institutions are employing information
systems totransfer billions of dollars around the world electronically, and
manufacturers are using them to order supplies and to distribute goods
faster than ever before.
An organization is a formal collection of people and other resources
established to accomplish a set of goals. The primary goal of a for-profit
organization is to maximize the shareholder value, often measured by the
price of the company's stock. Nonprofit organizations include social
groups, religious groups, universities, and other organizations that do not
have profit as the primary goal. An organization is a system. money,
people, materials, machines, and equipment, data, information, and decisions
are constantly in use in any organization.
Environment
---------------
Employee Decision-making
---------------
|
|
--------------- --------------- ---------------
Input ---- Product transformation ---- Output
--------------- --------------- ---------------
---> --->Value Flow ---> --->---> --->---> --->---> --->---> --->
The process of transforming data into information begins with input. In
some cases data is organized or processed mentally or manually. In other
cases a computer is used. A sales manager can manually calculate the sum
ofthe sales of each sales representative, or a computer could be used to
calculate this sum. What is important is not so muuch where the data comes
from or how it is processed, but whether the results are useful and
valuable. The transformation process is where applying knowledge by
selecting, organizing, and manipulating data is done.. The result should be
useful information. Developing information systems to meet business needs
is highly complex and difficult; it is common for information systems
projects to over-run budgets and to exceed scheduled completion dates.
As depicted above, resources such as materials, people, and money are input
into the organizational system from the environment, go through a
transformation mechanism, and are output to the environment. The outputs
from the transformation mechanism are usually goods or services. The goods
or services produced by the organization are of higher relative value than
the inputs alone. through adding value (worth) organizations attempt to
achieve their goals. Data flows between the several processing modules in
the simple representation depicted.
Turning data into informatio is a process, or a set of logically related
tasks performed to achieve a defined outcome. The process of defining
relationships among data to create useful information requires knowledge.
Knowledge is an awareness and understanding of a set of information and how
that information can be made useful to support a specific task or to reach a
decision. The process of converting data into information also requires
knowledge to select or to reject facts based upon their relevancy to
particular tasks. So information can be considered data made useful through
the application of knowledge Stair p. 5 Fundamentals of Information Systems.
Information systems support and work within all parts of an organizational
process. Input to the process module (subsystem) can come by internal
and/or external sources. Once data enter the input subsystem it becomes
internal. And likewise goods and services can be output to either internal
or external systems. A module is a logical problem related task (problem
solving) that the program performs analysis and reporting on. Control is
passed to a module on the lower levels using a control statement of a
programming language. An IF( ) statement, or a FOR( ) statement, ERROR,
FLAG, RETURN, and CONTINUE, are thought of as control statements. There are
others we can list at a later point.
The inputs which are gathered by lower utiltities can be treated by lower
level tasks as values (attribute/value pair) which have a global scope,
because the lower level task modules in the data processing task hierarchy
are aware of only the entry and exit which is a return to the calling module
as other technicians can argue in these cases.The data which is to be
processed within any of these task modules will reflect a certain way of
considering the function and status of the applicaton program system.
Control always passes back to the calling module from the lower level task
modules. And there is only one entry point at the top module or the top
level. There is only one exit from any of the modules, it returns control to
the calling module. It is however possible for more than one module to
transfer control to a task module on a lower level. Module A invokes module
C, and module B also invokes module C. And there is at most one control
relationship between any two modules, i.e., if A invokes B then B can not
invoke A. Module C is known as a common module, and module C may have a
(lower level) task processing modules below itself. But no module can call
itself (recursion) these modules of the lower level are not aware of the
upper level modules (until they have been invoked and activated). I have
develoed the idea that the database which accumulates the data is a common
module, while the lower level tasks are as described in terms of
attribute/value pairs.
The most meaningful records for the systems analyst are those data flow
diagrams (process control charts) depicting how the various systems are
interconnected, since outputs from one system become the inputs of another.
An appreciation of the current state of the environment which we are
interested in influencing is the place we have to begin.
How functional is the network which supports the environment? The
assumptions about the performance of the network would amount to another
assessment of an indirect influence with regard to a plan, and a
consideration of issues needed for a direct involvement in the environment.
Applications (systems) which are built upon their client-server network
architecture foundation apply the instructions of Third Generation
programming languages, and Fourth Generation programming languages which are
meant to perform tasks within an environmment controlled through a useful
distributed client server network architecture and an integrated mix of
functional resources (function applications i.e., accounting, inventory,
etc.). Utility applications are also used for general file management,
system monitoring, etc.
An essential technique used for planning for participating in the changes
occurring within the environment would need to understand and assess the
likely changes to occur even without intervention -indirect participation
can be related to the observation of changes, and can also be related to the
observer's position -oneself in relationship to other systems of the world.
Another indirect participation can amount to understanding the environment
and preparation of a plan for intervention in the environment and this is in
fact a strategy used in game theory. \how far will the systems influencing
the environment be totally in agreement or partly resistant to another/new
effort to implement changes in the environment? How much of the effort at
intervening within the environment depends upon a clandestine shock attack?
Whereas businesspeople are inundated with information, ideas, and theories
on new technologies as well as new organizational forms and changing
business conditions and strategies, there has been little success in
developing a coherent view that synthesizes these factors. The Digital
Economy explains the new econoomy, the new enterprise, and the new
technology, and how they link to one another. The role of the new
technology in creating the new enterprise for a new economy is a
relationship which an organization must understand to master.
Systems development allows an organization to effectively use computer
technology to increase revenues and reduce costs. Well-designed,
well-implemented information systems can help organizations to achieve their
goals. We discuss the use of the information systms in the organizational
context.. The correctness of the adherence to a theory of the design of the
system and applications would be the desired end result for these
applications. The nature of such grand systems -derived from the adherence
to the tenets of the scientific revolution is not, in fact to produce a
computer as the servant of man; and the bold applications of man are a
secondary effect. Enslavement of man, put into second place by technologies
and an attempt at trivial tasking management is a failure to learn the
design of the splendors of a system and the programs and the system. (I
dont know how this seems to you I wrote it in frustration). Stair p. 16
Information Systems in perspective.
A best selling book The Digital Economy by Don Tapscott states, "Today we
are witnessing the early, turbulent days of a revolution as significant as
any other in human history. A new medium of huuman communications is
emerging, one that may prove to surpass all previous revolutions -the
printing press, the telephone, the television -in its impact on our economic
and social life. The computer is expanding from a tool for information mana
gement to a tool for communications. Interactive multimedia and the
information highway, and its exemplar the Internet, are enabling a new
economy based on the networking of human intelligence. In this digital
econopmy, individuals and enterprises create wealth by applying knowledge,
networked human intelligence, and effort to manufacturing, agriculture, and
services. In the digital frontier of this economy, the players, dynamics,
rules, and requirements for survival and success are changing.
Such a shift in economic and societal relationships has occurred only a
handful of times before on the planet. It is causeing every company to
think far beyond the lines of "reengineering", to transform itself. A new
enterprise is emerging -the internetworked business -which is as different
from the corporation of the twentieth century as the latter was from the
feudal craft shop."
The term internetworked business (Tapscott note) is based on the term
internetworked enterprise -a concept first explained by the alliance for
Converging Technologies.
"The Digital Ecoomy (Tapscott's book) attempts to answer the question: What
does it all mean for my business> Whereas business people are inundated
with information, ideas, and theories on new technologies and new
organizational forms as well as changing business conditions and strategies,
there has been little success in developing a coherent view that synthesizes
these factors. The Digital Economy explains the New Economy, the New
Enterprise, and the New Technology and how they link to one another-how they
enable one another.
---------
The age of Networked Intelligence is an age of promise, involving the
networking of technology along with the networking of humans through
technology. It is an age of hmans who can combine their intelligence,
knowledge, and creativity for breakthroughs in the creation of wealth and
social development.. It is not just an age of linking computers but of
internetworking human ingenuity.
And rather than a single expensive supercomputer used in suimulations,
supporting a single group of scientists, a global network of computers can
be internetworked to support distributed teams of scientists. the network
iteslf is more powerful than any single computer would be. And networked
human intelligence is applied to research, thus creating a higher order of
thinking, knowledge -and maybe even a internetworked consciousness -among
people. the same networking can be applied to business and almost every
other aspect of human endeavor -learning, health care, work, entertainment.
Networking can change the intelligence of a business by bringing collective
know-how to bear on problem solving and innovation. By dramatically opening
the channels of human communication, consciousness can be extended
fromindividuals to organizations. Unconscious organizations, just like
unconsciousness people can not learn. Learnig is a precondition for
survival. Networked intelligence is the missing link in organizational
learning, and the consious organization may be the foundation for the
elusive learning organization. And broader networked intelligence beyond
organizations can be extended to create a broader awakening -social
consciousness -in communities, nations, and beyond.
System Investigation
The goal of systems investigation is to gain a clear understanding of the
problem to be solved or opportunity to be addressed. Once this is
understood, the next question is, "Is this problem worth solving?". Since
organizations have limited resources -people and money -this question
deserves careful consideration. If the decision is to continue with the
solution, then the next step is systems analysis.
System analysis is the step where the problems are defined, as well as the
opportunities of the existing system.
System design is the following step when it is determined how the new system
will work to meet all of the business needs defined during systems analysis.
Systems implementation involves creating or acquiring the various system
components (hardware, software, databases, and so on) defined during the
design step; assembling them and putting the new system into operation.
Systems maintenance and review is a process which is implemented to maintain
and modify the system to meet any changing needs of the business.
A few practical guidelines to use to proceed:
1). Organizations use information systems Stair p. 31 to support
organizational goals. Before deciding on an information system for an
organization, managers should identify the firm's critical success factors,
which must be supported by the system. Because information systems
typically are designed to improve productivity, methods for measuring the
system's impact upon productivity should be devised. This would imply a
statistical evaluation of efforts to use the system as proposed.
2). Feedback is output that is used to make changes to input or to
processing activities, and it should also be gathered into the MIS for
distribution, and storage purposes. The technology acceptance model (TAM)
investigates factors, such as perceived usefulness of the technology, ease
of use, quality of the information system, and the degree to which the
organization supports the use of the information system, to predict
information system use and organization performance (feedback).
3). An expert system (ES) acts as an expert consultant to a user seek