Project management chapter 14

Project Management for Construction
Fundamental Concepts for Owners, Engineers, Architects and Builders

Chapter 14. Organization and Use of
Project Information
14.1 Types of Project Information
Construction projects inevitably generate enormous and complex
sets of information. Effectively managing this bulk of information to
insure its availability and accuracy is an important managerial task.
Poor or missing information can readily lead to project delays,
uneconomical decisions, or even the complete failure of the desired
facility. Pity the owner and project manager who suddenly discover
on the expected delivery date that important facility components
have not yet been fabricated and cannot be delivered for six
months!

With better information, the problem could have been identified
earlier, so that alternative suppliers might have been located or
schedules arranged. Both project design and control are crucially
dependent upon accurate and timely information, as well as the
ability to use this information effectively. At the same time, too
much unorganized information presented to managers can result in
confusion and paralysis of decision making.

As a project proceeds, the types and extent of the information used
by the various organizations involved will change. A listing of the
most important information sets would include:
• cash flow and procurement accounts for each organization,
• intermediate analysis results during planning and design,
• design documents, including drawings and specifications,
• construction schedules and cost estimates,
• quality control and assurance records,
• chronological files of project correspondence and memorandum,
• construction field activity and inspection logs,
• legal contracts and regulatory documents.

Some of these sets of information evolve as the project proceeds.
The financial accounts of payments over the entire course of the
project is an example of overall growth. The passage of time results
in steady additions in these accounts, whereas the addition of a
new actor such as a contractor leads to a sudden jump in the
number of accounts. Some information sets are important at one
stage of the process but may then be ignored. Common examples
include planning or structural analysis databases which are not
ordinarily used during construction or operation. However, it may
be necessary at later stages in the project to re-do analyses to
consider desired changes. In this case, archival information storage
and retrieval become important. Even after the completion of
construction, an historical record may be important for use during
operation, to assess responsibilities in case of facility failures or for
planning similar projects elsewhere.

The control and flow of information is also important for
collaborative work environments, where many professionals are
working on different aspects of a project and sharing information.
Collaborative work environments provide facilities for sharing
datafiles, tracing decisions, and communication via electronic mail
or video conferencing. The datastores in these collaborative work
environments may become very large.

Based on several construction projects, Maged Abdelsayed of
Tardif, Murray & Assoc (Quebec, Canada) estimated the following
average figures for a typical project of US$10 million:
• Number of participants (companies): 420 (including all suppliers
and sub-sub-contractors)
• Number of participants (individuals): 850
• Number of different types of documents generated: 50
• Number of pages of documents: 56,000

• Number of bankers boxes to hold project documents: 25
• Number of 4 drawers filing cabinets: 6
• Number of 20inch diameter, 20 year old, 50 feet high, trees used
to generate this volume of paper: 6
• Equivalent number of Mega Bytes of electronic data to hold this
volume of paper (scanned): 3,000 MB
• Equivalent number of compact discs (CDs): 6

While there may be substantial costs due to inaccurate or missing
information, there are also significant costs associated with the
generation, storage, transfer, retrieval and other manipulation of
information. In addition to the costs of clerical work and providing
aids such as computers, the organization and review of information
command an inordinate amount of the attention of project
managers, which may be the scarcest resource on any construction
project. It is useful, therefore, to understand the scope and
alternatives for organizing project information.

14.2 Accuracy and Use of Information
Numerous sources of error are expected for project information.
While numerical values are often reported to the nearest cent or
values of equivalent precision, it is rare that the actual values are
so accurately known. Living with some uncertainty is an
inescapable situation, and a prudent manager should have an
understanding of the uncertainty in different types of information
and the possibility of drawing misleading conclusions.

We have already discussed the uncertainty inherent in making
forecasts of project costs and durations sometime in the future.
Forecast uncertainty also exists in the short term. For example,
consider estimates of work completed. Every project manager is
familiar with situations in which the final few bits of work for a task
take an inordinate amount of time. Unforeseen problems,
inadequate quality on already completed work, lack of attention,
accidents, or postponing the most difficult work problems to the end
can all contribute to making the final portion of an activity actually
require far more time and effort than expected. The net result is
that estimates of the actual proportion of work completed are often
inaccurate.

Some inaccuracy in reports and estimates can arise from
conscious choices made by workers, foremen or managers. If the
value of insuring accuracy is thought to be low or nonexistent, then
a rational worker will not expend effort or time to gather or to report
information accurately. Many project scheduling systems flounder
on exactly this type of non-reporting or mis-reporting. The original
schedule can quickly become extremely misleading without
accurate updating! Only if all parties concerned have specific
mandates or incentives to report accurately will the data be reliable.

Another source of inaccuracy comes from transcription errors of
various sorts. Typographical errors, incorrect measurements from
reading equipment, or other recording and calculation errors may
creep into the sets of information which are used in project
management. Despite intensive efforts to check and eliminate such
errors, their complete eradication is virtually impossible.

One method of indicating the relative accuracy of numerical data is
to report ranges or expected deviations of an estimate or
measurement. For example, a measurement might be reported as
198 ft. + 2 ft. There are two common interpretations of these
deviations. First, a range (such as + 2) might be chosen so that the
actual value is certain to be within the indicated range. In the case
above, the actual length would be somewhere between 196 and
200 feet with this convention. Alternatively, this deviation might
indicate the typical range of the estimate or measurement. In this
case, the example above might imply that there is, say, a two-thirds
chance that the actual length is between 196 and 200.

When the absolute range of a quantity is very large or unknown,
the use of a statistical standard deviation as a measure of
uncertainty may be useful. If a quantity is measured n times
resulting is a set of values xi (i = 1,2,...,n), then the average or
mean value then the average or mean value is given by:
The standard deviation can be estimated as the square root s of
the sample variance s2, i.e. , where:

The standard deviation is a direct indicator of the spread or
variability in a measurement, in the same units as the
measurement itself. Higher values of the standard deviation
indicate greater and greater uncertainty about the exact value of
the measurement. For the commonly encountered normal
distribution of a random variable, the average value plus or minus
one standard deviation, + , will include about two-thirds ofx the
actual occurrences. A related measure of random variability is the
coefficient of variation, defined as the ratio of the standard
deviation to the mean:

Thus, a coefficient of variation indicates the variability as a
proportion of the expected value. A coefficient of variation equal to
one (c = 1) represents substantial uncertainty, whereas a value
such as c = 0.1 or ten percent indicates much smaller variability.

More generally, even information which is gathered and reported
correctly may be interpreted incorrectly. While the actual
information might be correct within the terms of the data gathering
and recording system, it may be quite misleading for managerial
purposes. A few examples can illustrate the problems which may
arise in naively interpreting recorded information without involving
any conceptual understanding of how the information is actually
gathered, stored and recorded or how work on the project actually
proceeds.

Example 14-1: Sources of Delay and Cost Accounts
It is common in construction activity information to make detailed
records of costs incurred and work progress. It is less common to
keep detailed records of delays and their causes, even though
these delays may be the actual cause of increased costs and lower
productivity. [1] Paying exclusive attention to cost accounts in such
situations may be misleading. For example, suppose that the
accounts for equipment and material inventories show cost savings
relative to original estimates, whereas the costs associated with
particular construction activities show higher than estimated
expenditures.

In this situation, it is not necessarily the case that the inventory
function is performing well, whereas the field workers are the cause
of cost overrun problems. It may be that construction activities are
delayed by lack of equipment or materials, thus causing cost
increases. Keeping a larger inventory of materials and equipment
might increase the inventory account totals, but lead to lower
overall costs on the project. Better yet, more closely matching
demands and supplies might reduce delay costs without concurrent
inventory cost increases. Thus, simply examining cost account
information may not lead to a correct diagnosis of a problem or to
the correct managerial responses.

Example 14-2: Interest Charges
Financial or interest charges are usually accumulated in a separate
account for projects, while the accounts associated with particular
activities represent actual expenditures. For example, planning
activities might cost $10,000 for a small project during the first year
of a two year project. Since dollar expenditures have a time value,
this $10,000 cost in year 1 is not equivalent in value to a $10,000
cost in year 2. In particular, financing the early $10,000 involves
payment of interest or, similarly, the loss of investment
opportunities.

If the borrowing rate was 10%, then financing the first year $10,000
expenditure would require $10,000 x 0.10 = $1,000 and the value
of the expenditure by the end of the second year of the project
would be $11,000. Thus, some portion of the overall interest
charges represents a cost associated with planning activities.
Recognizing the true value of expenditures made at different
periods of time is an important element in devising rational planning
and management strategies.

14.3 Computerized Organization and
Use of Information
Numerous formal methods and possible organizations exist for the
information required for project management. Before discussing the
details of computations and information representation, it will be
useful to describe a record keeping implementation, including some
of the practical concerns in design and implementation. In this
section, we shall describe a computer based system to provide
construction yard and warehouse management information from
the point of view of the system users. [2] In the process, the
usefulness of computerized databases can be illustrated.

Use of Information
A yard or warehouse is used by most construction firms to store
equipment and to provide an inventory of materials and parts
needed for projects. Large firms may have several warehouses at
different locations so as to reduce transit time between project sites
and materials supplies. In addition, local "yards" or "equipment
sheds" are commonly provided on the job site. Examples of
equipment in a yard would be drills, saws, office trailers, graders,
back hoes, concrete pumps and cranes. Material items might
include nails, plywood, wire mesh, forming lumber, etc.

Use of Information
In typical construction warehouses, written records are kept by
warehouse clerks to record transfer or return of equipment to job
sites, dispatch of material to jobs, and maintenance histories of
particular pieces of equipment. In turn, these records are used as
the basis for billing projects for the use of equipment and materials.
For example, a daily charge would be made to a project for using a
concrete pump. During the course of a month, the concrete pump
might spend several days at different job sites, so each project
would be charged for its use. The record keeping system is also
used to monitor materials and equipment movements between
sites so that equipment can be located.

Use of Information
One common mechanism to organize record keeping is to fill out
cards recording the transfer of items to or from a job site. Table 14-
1 illustrates one possible transfer record. In this case, seven items
were requested for the Carnegie-Mellon job site (project number
83-1557). These seven items would be loaded on a delivery truck,
along with a copy of the transfer record. Shown in Table 14-1 is a
code number identifying each item (0609.02, 0609.03, etc.), the
quantity of each item requested, an item description and a unit
price. For equipment items, an equipment number identifying the
individual piece of equipment used is also recorded, such as
grinder No. 4517 in Table 14-1; a unit price is not specified for
equipment but a daily rental charge might be imposed.

Use of Information

Use of Information
Transfer sheets are numbered (such as No. 100311 in Table 14-1),
dated and the preparer identified to facilitate control of the record
keeping process. During the course of a month, numerous transfer
records of this type are accumulated. At the end of a month, each
of the transfer records is examined to compile the various items or
equipment used at a project and the appropriate charges.
Constructing these bills would be a tedious manual task.
Equipment movements would have to be tracked individually, days
at each site counted, and the daily charge accumulated for each
project. For example, Table 14-1 records the transfer of grinder No.
4517 to a job site. This project would be charged a daily rental rate
until the grinder was returned. Hundreds or thousands of individual
item transfers would have to be examined, and the process of
preparing bills could easily require a week or two of effort.

Use of Information
In addition to generating billing information, a variety of reports
would be useful in the process of managing a company's
equipment and individual projects. Records of the history of use of
particular pieces of equipment are useful for planning maintenance
and deciding on the sale or scrapping of equipment. Reports on the
cumulative amount of materials and equipment delivered to a job
site would be of obvious benefit to project managers. Composite
reports on the amount, location, and use of pieces of equipment of
particular types are also useful in making decisions about the
purchase of new equipment, inventory control, or for project
planning.

Use of Information
Unfortunately, producing each of these reports requires manually
sifting through a large number of transfer cards. Alternatively,
record keeping for these specific projects could have to proceed by
keeping multiple records of the same information. For example,
equipment transfers might be recorded on (1) a file for a particular
piece of equipment and (2) a file for a particular project, in addition
to the basic transfer form illustrated in Table 14-1. Even with these
redundant records, producing the various desired reports would be
time consuming.

Use of Information
Organizing this inventory information in a computer program is a
practical and desirable innovation. In addition to speeding up billing
(and thereby reducing borrowing costs), application programs can
readily provide various reports or views of the basic inventory
information described above. Information can be entered directly to
the computer program as needed. For example, the transfer record
shown in Table 14-1 is based upon an input screen to a computer
program which, in turn, had been designed to duplicate the manual
form used prior to computerization. Use of the computer also allows
some interactive aids in preparing the transfer form. This type of aid
follows a simple rule: "Don't make the user provide information that
the system already knows." [3]

Use of Information
In using the form shown in Table 14-1, a clerk need only enter the
code and quantity for an item; the verbal description and unit cost
of the item then appear automatically. A copy of the transfer form
can be printed locally, while the data is stored in the computer for
subsequent processing. As a result, preparing transfer forms and
record keeping are rapidly and effectively performed.

Use of Information
More dramatically, the computerized information allows warehouse
personnel both to ask questions about equipment management and
to readily generate the requisite data for answering such questions.
The records of transfers can be readily processed by computer
programs to develop bills and other reports. For example,
proposals to purchase new pieces of equipment can be rapidly and
critically reviewed after summarizing the actual usage of existing
equipment. Ultimately, good organization of information will
typically lead to the desire to store new types of data and to provide
new views of this information as standard managerial tools.

Use of Information
Of course, implementing an information system such as the
warehouse inventory database requires considerable care to insure
that the resulting program is capable of accomplishing the desired
task. In the warehouse inventory system, a variety of details are
required to make the computerized system an acceptable
alternative to a long standing manual record keeping procedure.
Coping with these details makes a big difference in the system's
usefulness.

Use of Information
For example, changes to the status of equipment are generally
made by recording transfers as illustrated in Table 14-1. However,
a few status changes are not accomplished by physical movement.
One example is a charge for air conditioning in field trailers: even
though the air conditioners may be left in the field, the construction
project should not be charged for the air conditioner after it has
been turned off during the cold weather months. A special status
change report may be required for such details. Other details of
record keeping require similar special controls.

Use of Information
Even with a capable program, simplicity of design for users is a
critical factor affecting the successful implementation of a system.
In the warehouse inventory system described above, input forms
and initial reports were designed to duplicate the existing manual,
paper-based records. As a result, warehouse clerks could readily
understand what information was required and its ultimate use. A
good rule to follow is the Principle of Least Astonishment: make
communications with users as consistent and predictable as
possible in designing programs.

Use of Information
Finally, flexibility of systems for changes is an important design and
implementation concern. New reports or views of the data is a
common requirement as the system is used. For example, the
introduction of a new accounting system would require changes in
the communications procedure from the warehouse inventory
system to record changes and other cost items.

Use of Information
In sum, computerizing the warehouse inventory system could save
considerable labor, speed up billing, and facilitate better
management control. Against these advantages must be placed the
cost of introducing computer hardware and software in the
warehouse.

14.4 Organizing Information in
Databases
Given the bulk of information associated with construction projects,
formal organization of the information is essential so as to avoid
chaos. Virtually all major firms in the arena of project management
have computer based organization of cost accounts and other data.
With the advent of micro-computer database managers, it is
possible to develop formal, computerized databases for even small
organizations and projects. In this section, we will discuss the
characteristics of such formal databases.

Databases
Equivalent organization of information for manual manipulation is
possible but tedious. Computer based information systems also
have the significant advantage of rapid retrieval for immediate use
and, in most instances, lower overall costs. For example,
computerized specifications writing systems have resulted in well
documented savings. These systems have records of common
specification phrases or paragraphs which can be tailored to
specific project applications.

Databases
Formally, a database is a collection of stored operational
information used by the management and application systems of
some particular enterprise. [5] This stored information has explicit
associations or relationships depending upon the content and
definition of the stored data, and these associations may
themselves be considered to be part of the database. Figure 14-1
illustrates some of the typical elements of a database. The internal
model is the actual location and representation of the stored data.
At some level of detail, it consists of the strings of "bits" which are
stored in a computer's memory, on the tracks of a recording disk,
on a tape, or on some other storage device.

Databases

Databases
A manager need not be concerned with the details of data storage
since this internal representation and manipulation is regulated by
the Database Manager Program (DBM). The DBM is the software
program that directs the storage, maintenance, manipulation and
retrieval of data. Users retrieve or store data by issuing specific
requests to the DBM. The objective of introducing a DBM is to free
the user from the detail of exactly how data are stored and
manipulated. At the same time, many different users with a wide
variety of needs can use the same database by calling on the DBM.

Databases
Usually the DBM will be available to a user by means of a special
query language. For example, a manager might ask a DBM to
report on all project tasks which are scheduled to be underway on a
particular date. The desirable properties of a DBM include the
ability to provide the user with ready access to the stored data and
to maintain the integrity and security of the data. Numerous
commercial DBM exist which provide these capabilities and can be
readily adopted to project management applications.

Databases
While the actual storage of the information in a database will
depend upon the particular machine and storage media employed,
a Conceptual Data Model exists which provides the user with an
idea or abstract representation of the data organization. (More
formally, the overall configuration of the information in the database
is called the conceptual schema.) For example, a piece of data
might be viewed as a particular value within a record of a datafile.

Databases
In this conceptual model, a datafile for an application system
consists of a series of records with pre-defined variables within
each record. A record is simply a sequence of variable values,
which may be text characters or numerals. This datafile model is
one of the earliest and most important data organization structures.
But other views of data organization exist and can be exceedingly
useful. The next section describes one such general model, called
the relational model.

Databases
Continuing with the elements in Figure 14-1, the data dictionary
contains the definitions of the information in the database. In some
systems, data dictionaries are limited to descriptions of the items in
the database. More general systems employ the data dictionary as
the information source for anything dealing with the database
systems. It documents the design of the database: what data are
stored, how the data is related, what are the allowable values for
data items, etc. The data dictionary may also contain user
authorizations specifying who may have access to particular pieces
of information. Another important element of the data dictionary is a
specification of allowable ranges for pieces of data; by prohibiting
the input of erroneous data, the accuracy of the database
improves.

Databases
External models are the means by which the users view the
database. Of all the information in the database, one particular
user's view may be just a subset of the total. A particular view may
also require specific translation or manipulation of the information
in the database. For example, the external model for a paycheck
writing program might consist solely of a list of employee names
and salary totals, even if the underlying database would include
employee hours and hourly pay rates. As far as that program is
concerned, no other data exists in the database.

Databases
The DBM provides a means of translating particular external
models or views into the overall data model. Different users can
view the data in quite distinct fashions, yet the data itself can be
centrally stored and need not be copied separately for each user.
External models provide the format by which any specific
information needed is retrieved. Database "users" can be human
operators or other application programs such as the paycheck
writing program mentioned above.

Databases
Finally, the Database Administrator is an individual or group
charged with the maintenance and design of the database,
including approving access to the stored information. The
assignment of the database administrator should not be taken
lightly. Especially in large organizations with many users, the
database administrator is vital to the success of the database
system. For small projects, the database administrator might be an
assistant project manager or even the project manager.

14.5 Relational Model of Databases
As an example of how data can be organized conceptually, we
shall describe the relational data model. In this conceptual model,
the data in the database is viewed as being organized into a series
of relations or tables of data which are associated in ways defined
in the data dictionary. A relation consists of rows of data with
columns containing particular attributes. The term "relational"
derives from the mathematical theory of relations which provides a
theoretical framework for this type of data model.

Here, the terms "relation" and data "table" will be used
interchangeably. Table 14-2 defines one possible relation to record
unit cost data associated with particular activities. Included in the
database would be one row (or tuple) for each of the various items
involved in construction or other project activities. The unit cost
information associated with each item is then stored in the form of
the relation defined in Table 14-2.

Using Table 14-2, a typical unit cost entry for an activity in
construction might be:
ITEM_CODE: 04.2-66-025
DESCRIPTION: common brick masonry, 12" thick wall, 19.0 bricks
per S.F.
WORK_UNIT: 1000 bricks
CREW_CODE: 04.2-3
OUTPUT: 1.9
TIME_UNIT: Shift
MATL_UNIT_COST: 124
DATEMCOS: June-09-79
INSTCOST: 257
DATEICOS: August-23-79

This entry summarizes the unit costs associated with construction
of 12" thick brick masonry walls, as indicated by the item
DESCRIPTION. The ITEM_CODE is a numerical code identifying a
particular activity. This code might identify general categories as
well; in this case, 04.2 refers to general masonry work.
ITEM_CODE might be based on the MASTERFORMAT or other
coding scheme. The CREW_CODE entry identifies the standard
crew which would be involved in the activity. The actual
composition of the standard crew would be found in a CREW
RELATION under the entry 04.2-3, which is the third standard crew
involved in masonry work (04.2). This ability to point to other
relations reduces the redundancy or duplication of information in
the database. In this case, standard crew number 04.2-3 might be
used for numerous masonry construction tasks, but the definition of
this crew need only appear once.

WORK_UNIT, OUTPUT and TIME_UNIT summarize the expected
output for this task with a standard crew and define the standard
unit of measurement for the item. In this case, costs are given per
thousand bricks per shift. Finally, material (MATL_UNIT_COST)
and installation (INSTCOSTS) costs are recorded along with the
date (DATEMCOS and DATEICOS) at which the prices were
available and entered in the database. The date of entry is useful to
insure that any inflation in costs can be considered during use of
the data.

The data recorded in each row could be obtained by survey during
bid preparations, from past project experience or from commercial
services. For example, the data recorded in the Table 14-2 relation
could be obtained as nationwide averages from commercial
sources.

An advantage of the relational database model is that the number
of attributes and rows in each relation can be expanded as desired.
For example, a manager might wish to divide material costs
(MATL_UNIT_COST) into attributes for specific materials such as
cement, aggregate and other ingredients of concrete in the unit
cost relation defined in Table 14-2. As additional items are defined
or needed, their associated data can be entered in the database as
another row (or tuple) in the unit cost relation. Also, new relations
can be defined as the need arises. Hence, the relational model of
database organization can be quite flexible in application. In
practice, this is a crucial advantage. Application systems can be
expected to change radically over time, and a flexible system is
highly desirable.

With a relational database, it is straightforward to issue queries for
particular data items or to combine data from different relations. For
example, a manager might wish to produce a report of the crew
composition needed on a site to accomplish a given list of tasks.
Assembling this report would require accessing the unit price
information to find the standard crew and then combining
information about the construction activity or item (eg. quantity
desired) with crew information. However, to effectively accomplish
this type of manipulation requires the definition of a "key" in each
relation.

In Table 14-2, the ITEMCODE provides a unique identifier or key
for each row. No other row should have the same ITEMCODE in
any one relation. Having a unique key reduces the redundancy of
data, since only one row is included in the database for each
activity. It also avoids error. For example, suppose one queried the
database to find the material cost entered on a particular date. This
response might be misleading since more than one material cost
could have been entered on the same date. Similarly, if there are
multiple rows with the same ITEMCODE value, then a query might
give erroneous responses if one of the rows was out of date.
Finally, each row has only a single entry for each attribute. [6]

The ability to combine or separate relations into new arrangements
permits the definition of alternative views or external models of the
information. Since there are usually a number of different users of
databases, this can be very useful. For example, the payroll
division of an organization would normally desire a quite different
organization of information about employees than would a project
manager. By explicitly defining the type and organization of
information a particular user group or application requires, a
specific view or subset of the entire database can be constructed.
This organization is illustrated in Fig. 14-1 with the DATA
DICTIONARY serving as a translator between the external data
models and the database management system.

Behind the operations associated with querying and manipulating
relations is an explicit algebraic theory. This algebra defines the
various operations that can be performed on relations, such as
union (consisting of all rows belonging to one or the other of two
relations), intersection (consisting of all rows belonging to both of
two relations), minus (consisting of all rows belonging to one
relation and not another), or projection (consisting of a subset of
the attributes from a relation). The algebraic underpinnings of
relational databases permits rigorous definitions and confidence
that operations will be accomplished in the desired fashion. [7]

Example 14-3: A Subcontractor Relation
As an illustration of the preceding discussion, consider the problem
of developing a database of possible subcontractors for
construction projects. This database might be desired by the cost
estimation department of a general contractor to identify
subcontractors to ask to bid on parts of a project. Appropriate
subcontractors appearing in the database could be contacted to
prepare bids for specific projects. Table 14-3 lists the various
attributes which might be required for such a list and an example
entry, including the subcontractor's name, contact person, address,
size (large, medium or small), and capabilities.

To use this relation, a cost estimator might be interested in
identifying large, electrical subcontractors in the database. A query
typed into the DBM such as:
SELECT from SUBCONTRACTORS
where SIZE = Large and ELECTRICAL = Yes
would result in the selection of all large subcontractors performing
electrical work in the subcontractor's relation. More specifically, the
estimator might want to find subcontractors in a particular state:
SELECT from SUBCONTRACTORS
where SIZE = Large and ELECTRICAL = Yes and STATE = VI.

In addition to providing a list of the desired subcontractors' names
and addresses, a utility application program could also be written
which would print mailing labels for the selected firms.
Other portions of the general contracting firm might also wish to
use this list. For example, the accounting department might use this
relation to record the addresses of subcontractors for payment of
invoices, thereby avoiding the necessity to maintain duplicate files.
In this case, the accounting code number associated with each
subcontractor might be entered as an additional attribute in the
relation, and the accounting department could find addresses
directly.

Example 14-4: Historical Bridge Work Relation
As another simple example of a data table, consider the relation
shown in Table 14-0 which might record historical experience with
different types of bridges accumulated by a particular agency. The
actual instances or rows of data in Table 14-4 are hypothetical. The
attributes of this relation are:
• PROJECT NUMBER - a 6-digit code identifying the particular
project.
• TYPE OF BRIDGE - a text field describing the bridge type. (For
retrieval purposes, a numerical code might also be used to
describe bridge type to avoid any differences in terminology to
describe similar bridges).
• LOCATION - The location of the project.
• CROSSING - What the bridge crosses over, eg. a river.

• SITE CONDITIONS - A brief description of the site peculiarities.
• ERECTION TIME - Time required to erect a bridge, in months.
• SPAN - Span of the bridge in feet.
• DATE - Year of bridge completion.
• ACTUAL-ESTIMATED COSTS - Difference of actual from
estimated costs.
These attributes could be used to answer a variety of questions
concerning construction experience useful during preliminary
planning.

As an example, suppose that a bridge is to be built with a span of
250 feet, located in Pittsburgh PA, and crossing a river with
limestone sub-strata. In initial or preliminary planning, a designer
might query the database four separate times as follows:
• SELECT from BRIDGEWORK where SPAN > 200 and SPAN <
300 and where CROSSING = "river"
• SELECT from BRIDGEWORK where SPAN > 200 and SPAN <
300 and where SITE CONDITIONS = "Limestone"
• SELECT from BRIDGEWORK where TYPE OF BRIDGE =
"Steel Plate Girder" and LOCATION = "PA"
• SELECT from BRIDGEWORK where SPAN < 300 and SPAN >
200 and ESTIMATED LESS ACTUAL COST < 100,000.

Each SELECT operation would yield the bridge examples in the
database which corresponds to the desired selection criteria. In
practice, an input/output interpreter program should be available to
translate these inquiries to and from the DBM and an appropriate
problem oriented language.
The four queries may represent subsequent thoughts of a designer
faced with these problem conditions. He or she may first ask,
"What experience have we had with bridges of this span over
rivers?" "What experience have we had with bridges of this span
with these site conditions? What is our experience with steel girder
bridges in Pennsylvania? For bridges of this span, how many and
which were erected without a sizable cost overrun? We could pose
many more questions of this general type using only the small data
table shown in Table 14-4.

14.6 Other Conceptual Models of
Databases
While the relational model offers a considerable amount of flexibility
and preserves considerable efficiency, there are several alternative
models for organizing databases, including network and
hierarchical models. The hierarchical model is a tree structure in
which information is organized as branches and nodes from a
particular base. [8] As an example, Figure 14-2 illustrates a
hierarchical structure for rented equipment costs. In this case, each
piece of equipment belongs to a particular supplier and has a cost
which might vary by the duration of use. To find the cost of a
particular piece of equipment from a particular supplier, a query
would first find the supplier, then the piece of equipment and then
the relevant price.

Databases
The hierarchical model has the characteristic that each item has a
single predecessor and a variable number of subordinate data
items. This structure is natural for many applications, such as the
equipment cost information described above. However, it might be
necessary to construct similar hierarchies for each project to record
the equipment used or for each piece of equipment to record
possible suppliers. Otherwise, generating these lists of
assignments from the database illustrated in Figure 14-2 would be
difficult. For example, finding the least expensive supplier of a
crane might involve searching every supplier and every equipment
node in the database to find all crane prices.

Databases

Databases
The network model or database organization retains the
organization of information on branches and nodes, but does not
require a tree of structure such as the one in Figure 14-2. [9] This
gives greater flexibility but does not necessarily provide ease of
access to all data items. For example, Figure 14-3 shows a portion
of a network model database for a building. The structural member
shown in the figure is related to four adjoining members, data on
the joints designed for each end, an assembly related to a room,
and an aggregation for similar members to record member
specifications.

Databases
While the early, large databases were based on the hierarchical or
network organizations, the relational model is now preferred in
many applications due to its flexibility and conceptual simplicity.
Relational databases form the kernel for large systems such as
ORACLE or SAP. However, databases distributed among
numerous servers may have a network structure (as in Figure 14-3),
with full relational databases contained at one or more nodes.
Similarly, "data warehouse" organizations may contain several
different types of databases and information files. For these data
warehouses, more complicated search approaches are essential,
such as automatic indexing of multi-media files such as
photographs.

Databases
More recently, some new forms of organized databases have
appeared, spurred in part by work in artificial intelligence. For
example, Figure 14-4 illustrates a frame data structure used to
represent a building design element. This frame describes the
location, type, cost, material, scheduled work time, etc. for a
particular concrete footing. A frame is a general purpose data
representation scheme in which information is arranged in slots
within a named frame. Slots may contain lists, values, text,
procedural statements (such as calculation rules), pointers or other
entities. Frames can be inter-connected so that information may be
inherited between slots. .

Databases
Figure 14-5 illustrates a set of inter-connected frames used to
describe a building design and construction plan. [10] Object
oriented data representation is similar in that very flexible local
arrangements of data are permitted. While these types of data
storage organizations are active areas of research, commercial
database systems based on these organizations are not yet
available

14.7 Centralized Database
Management Systems
Whichever conceptual model or database management system is
adopted, the use of a central database management system has a
number of advantages and some costs compared to the commonly
employed special purpose datafiles. A datafile consists of a set of
records arranged and defined for a single application system.
Relational information between items in a record or between
records is not explicitly described or available to other application
systems. For example, a file of project activity durations and
scheduled times might be assembled and manipulated by a project
scheduling system. This datafile would not necessarily be available
to the accounting system or to corporate planners.

Management Systems
A centralized DBM has several advantages over such stand-alone
systems: [11]
• Reduced redundancy good planning can allow duplicate or
similar data stored in different files for different applications to
be combined and stored only once.
• Improved availability information may be made available to any
application program through the use of the DBM
• Reduced inconsistency if the same data is stored in more than
one place, then updating in one place and not everywhere can
lead to inconsistencies in the database.
• Enforced data security authorization to use information can be
centralized.

Management Systems
For the purpose of project management, the issue of improved
availability is particularly important. Most application programs
create and own particular datafiles in the sense that information is
difficult to obtain directly for other applications. Common problems
in attempting to transfer data between such special purpose files
are missing data items, unusable formats, and unknown formats.

Management Systems
As an example, suppose that the Purchasing Department keeps
records of equipment rental costs on each project underway. This
data is arranged so that payment of invoices can be handled
expeditiously and project accounts are properly debited. The
records are arranged by individual suppliers for this purpose.
These records might not be particularly useful for the purpose of
preparing cost estimates since:
• Some suppliers might not exist in the historical record.
• Finding the lowest cost supplier for particular pieces of
equipment would be exceedingly tedious since every record
would have to be read to find the desired piece of equipment
and the cost.
• No direct way of abstracting the equipment codes and prices
might exist.

Management Systems
An alternative arrangement might be to separately record
equipment rental costs in (1) the Purchasing Department Records,
(2) the Cost Estimating Division, and (3) the Company warehouse.
While these multiple databases might each be designed for the
individual use, they represent considerable redundancy and could
easily result in inconsistencies as prices change over time. With a
central DBM, desired views for each of these three users could be
developed from a single database of equipment costs.

Management Systems
A manager need not conclude from this discussion that initiating a
formal database will be a panacea. Life is never so simple.
Installing and maintaining databases is a costly and time
consuming endeavor. A single database is particularly vulnerable
to equipment failure. Moreover, a central database system may be
so expensive and cumbersome that it becomes ineffective; we will
discuss some possibilities for transferring information between
databases in a later section. But lack of good information and
manual information management can also be expensive.

Management Systems
One might also contrast the operation of a formal, computerized
database with that of a manual filing system. For the equipment
supplier example cited above, an experienced purchasing clerk
might be able to immediately find the lowest cost supplier of a
particular piece of equipment. Making this identification might well
occur in spite of the formal organization of the records by supplier
organization. The experienced clerk will have his (or her) own
subjective, conceptual model of the available information. This
subjective model can be remarkably powerful. Unfortunately, the
mass of information required, the continuing introduction of new
employees, and the need for consistency on large projects make
such manual systems less effective and reliable.

14.8 Databases and Applications
Programs
The usefulness of a database organization is particularly evident in
integrated design or management environments. In these systems,
numerous applications programs share a common store of
information. Data is drawn from the central database as needed by
individual programs. Information requests are typically performed
by including pre-defined function calls to the database
management system within an application program. Results from
one program are stored in the database and can be used by
subsequent programs without specialized translation routines.
Additionally, a user interface usually exists by which a project
manager can directly make queries to the database. Figure 14-6
illustrates the role of an integrated database in this regard as the
central data store.

Programs

Programs
An architectural system for design can provide an example of an
integrated system. [12] First, a database can serve the role of
storing a library of information on standard architectural features
and component properties. These standard components can be
called from the database library and introduced into a new design.
The database can also store the description of a new design, such
as the number, type and location of individual building components.
The design itself can be composed using an interactive graphics
program.

Programs
This program would have the capability to store a new or modified
design in the database. A graphics program typically has the
capability to compose numerous, two or three dimensional views of
a design, to introduce shading (to represent shadows and provide
greater realism to a perspective), and to allow editing (including
moving, replicating, or sizing individual components). Once a
design is completed and its description stored in a database,
numerous analysis programs can be applied, such as:
• structural analysis,
• daylight contour programs to produce plots of available daylight
in each room,
• a heat loss computation program
• area, volume and materials quantities calculations.

Programs
Production information can also be obtained from the integrated
system, such as:
• dimensioned plans, sections and elevations,
• component specifications,
• construction detail specifications,
• electrical layout,
• system isometric drawings,
• bills of quantities and materials.

Programs
The advantage of an integrated system of this sort is that each
program need only be designed to communicate with a single
database. Accomplishing appropriate transformations of data
between each pair of programs would be much more difficult.
Moreover, as new applications are required, they can be added into
an integrated system without extensive modifications to existing
programs. For example, a library of specifications language or a
program for joint design might be included in the design system
described above. Similarly, a construction planning and cost
estimating system might also be added.

Programs
The use of integrated systems with open access to a database is
not common for construction activities at the current time. Typically,
commercial systems have a closed architecture with simple
datafiles or a "captive," inaccessible database management system.
However, the benefits of an open architecture with an accessible
database are considerable as new programs and requirements
become available over time.

14.9 Information Transfer and Flow
The previous sections outlined the characteristics of a
computerized database. In an overabundance of optimism or
enthusiasm, it might be tempting to conclude that all information
pertaining to a project might be stored in a single database. This
has never been achieved and is both unlikely to occur and
undesirable in itself. Among the difficulties of such excessive
centralization are:
• Existence of multiple firms or agencies involved in any project.
Each organization must retain its own records of activities,
whether or not other information is centralized. Geographic
dispersion of work even within the same firm can also be
advantageous. With design offices around the globe, fast track
projects can have work underway by different offices 24 hours a
day.

• Advantages of distributed processing. Current computer
technology suggests that using a number of computers at the
various points that work is performed is more cost effective than
using a single, centralized mainframe computer. Personal
computers not only have cost and access advantages, they also
provide a degree of desired redundancy and increased reliability.
• Dynamic changes in information needs. As a project evolves,
the level of detail and the types of information required will vary
greatly.

• Database diseconomies of scale. As any database gets larger, it
becomes less and less efficient to find desired information.
• Incompatible user perspectives. Defining a single data
organization involves trade-offs between different groups of
users and application systems. A good organization for one
group may be poor for another.
In addition to these problems, there will always be a set of untidy
information which cannot be easily defined or formalized to the
extent necessary for storage in a database.

While a single database may be undesirable, it is also apparent
that it is desirable to structure independent application systems or
databases so that measurement information need only be manually
recorded once and communication between the database might
exist. Consider the following examples illustrating the desirability of
communication between independent application systems or
databases. While some progress has occurred, the level of
integration and existing mechanisms for information flow in project
management is fairly primitive. By and large, information flow relies
primarily on talking, written texts of reports and specifications and
drawings.

Example 14-6: Time Cards
Time card information of labor is used to determine the amount
which employees are to be paid and to provide records of work
performed by activity. In many firms, the system of payroll accounts
and the database of project management accounts (i.e.,
expenditure by activity) are maintained independently. As a result,
the information available from time cards is often recorded twice in
mutually incompatible formats. This repetition increases costs and
the possibility of transcription errors. The use of a preprocessor
system to check for errors and inconsistencies and to format the
information from each card for the various systems involved is likely
to be a significant improvement (Figure 14-8). Alternatively, a
communications facility between two databases of payroll and
project management accounts might be developed.

Example 14-7: Final Cost Estimation, Scheduling and Monitoring
Many firms maintain essentially independent systems for final cost
estimation and project activity scheduling and monitoring. As a
result, the detailed breakdown of the project into specific job related
activities must be completely re-done for scheduling and monitoring.
By providing a means of rolling-over or transferring the final cost
estimate, some of this expensive and time-consuming planning
effort could be avoided.

Example 14-8: Design Representation
In many areas of engineering design, the use of computer analysis
tools applied to facility models has become prevalent and
remarkably effective. However, these computer-based facility
models are often separately developed or encoded by each firm
involved in the design process. Thus, the architect, structural
engineer, mechanical engineer, steel fabricator, construction
manager and others might all have separate computer-based
representations of a facility. Communication by means of
reproduced facility plans and prose specifications is traditional
among these groups. While transfer of this information in a form
suitable for direct computer processing is difficult, it offers obvious
advantages in avoiding repetition of work, delays and transcription
errors.

A de facto standard for transfer of geometric information emerged
with the dominance of the AUTOCAD design system in the A/E/C
industry. Information transfer was accomplished by copying
AUTOCAD files from user to user, including uses on construction
sites to visualize the design. More flexible and extensive standards
for design information transfer also exist, such as the Industry
Foundation Classes (IFC) standard developed by the International
Alliance for Interoperability (See http://www.iai-
international.org/iai_international/) and the "Fully Integrated and
Automated Project Processes" developed by FIATECH (see
http://www.fiatech.org/)

14.10 References
1.Au, T., C. Hendrickson and A. Pasquale, "Introduction of a
Relational Database Within a Cost Estimating System,"
Transportation Research Record 1050, pp. 57-62, 1986.
2.Bosserman, B.E. and M.E. Ford, "Development of Computerized
Specifications," ASCE Journal of Construction Engineering and
Management, Vol. 110, No. CO3, 1984, pp. 375-384.
3.Date, C.J., An Introduction to Database Systems, 3rd Ed.,
Addison-Wesley, 1981.
4.Kim, W., "Relational Database Systems," ACM Computing
Surveys, Vol. 11, No. 3, 1979, pp. 185-211.

14.10 References
5. Mitchell, William J., Computer Aided Architectural Design, Van
Nostrand Reinhold Co., New York, 1977.
6. Vieceli, A.M., "Communication and Coding of Computerized
Construction Project Information," Unpublished MS Thesis,
Department of Civil Engineering, Carnegie Mellon University,
Pittsburgh, PA, 1984.
7. Wilkinson, R.W., "Computerized Specifications on a Small
Project," ASCE Journal of Construction Engineering and
Management, Vol. 110, No. CO3, 1984, PP. 337-345.
8. Latimer, Dewitt and Chris Hendrickson, “Digital Archival of
Construction Project Information,” Proceedings of the International
Symposium on Automation and Robotics for Construction, 2002."

14.11 Problems
1.Suppose we wish to develop a database consisting of contractor
names, addresses and particular specialties as in Table 14-3.
• Suggest two hierarchical organizations of this data.
• Suggest an alternative relational organization for this data.
• Which organization would you recommend for implementation of
a database?
2. Suggest four reports which could be obtained from the
warehouse inventory system described in Section 14.3 and
describe what each report might be used for and by whom.

14.11 Problems
3. Suppose that a general contractor wished to keep a historical
database of the results of bid competitions. Suggest (a) the
information that might be stored, and (b) a possible organization of
this information.
4. For your suggested database from Problem 3, implement a
prototype system on a spreadsheet software program.
5. Describe a relational database that would be useful in storing the
beginning, ending and all intermediate stages for blockworld robot
movements as described in Problem 6 in Chapter 9.
6. Describe a relational database that would be appropriate for
maintaining activity scheduling information during project
monitoring. Be explicit about what relations would be defined, the
attributes in each relation, and allowable ranges of values.

14.12 Footnotes
1. See D.F. Rogge, "Delay Reporting Within Cost Accounting
System," ASCE Journal of Construction Engineering and
Management, Vol. 110, No. 2, 1984, pp. 289-292.
2. The system is based loosely upon a successful construction yard
management system originally for Mellon-Stuart Company,
Pittsburgh, PA. in 1983. The authors are indebted to A. Pasquale
for providing the information and operating experience of the
system.
3. Attributed to R. Lemons in J. Bentley "Programming Pearls,"
Communications of the ACM, Vol. 28, No. 9, 1985, pp. 896-899.
4. See Wilkinson, R.W. "Computerized Specifications on a Small
Project," ASCE Journal of Construction Engineering and
Management, Vol. 110, No. CO3, 1984, pp. 337-345.

14.12 Footnotes
5. See C.J. Date, An Introduction to Database Systems, 3rd ed.,
Addison-Wesley Publishing Company, Reading, MA, 1981.
6. This is one example of a normalization in relational databases.
For more formal discussions of the normalizations of relational
databases and the explicit algebra which can be used on such
relations, see Date op cit.
7. For a discussion of relational algebra, see E.F. Codd, "Relational
Completeness of Data Base Sublanguages," Courant Computer
Science Symposia Series, Vol. 6, Prentice-Hall, l972.
8. See D.C. Trichritzis and F.H. Lochovsky, "Hierarchical Data-
Base Management," ACM Computing Surveys Vol. 8, No. 1, 1976,
pp. 105-123.

14.12 Footnotes
9. For a more extensive comparison, see A.S. Michaels, B. Mittman,
and C.R. Carlson, "A Comparison of Relational and CODASYL
Approaches to Data-Base Management," ACM Computing Surveys,
Vol. 8, No. 1, 1976, pp. 125-157.
10. This organization is used for the central data store in an
integrated building design environment. See Fenves, S., U.
Flemming, C. Hendrickson, M. Maher, and G. Schmitt, "An
Integrated Software Environment for Building Design and
Construction," Proc. of the Fifth ASCE Conference on Computing in
Civil Engineering, 1987

14.12 Footnotes
11. For a discussion, see D.R. Rehak and L.A. Lopez, Computer
Aided Engineering Problems and Prospects, Civil Engr. Systems
Lab., Univ. of Illinois, Urbana, IL, 1981.
12. See W.J. Mitchell, Computer-Aided Architectural Design, Van
Nostrand Reinhold Co., New York, 1977.
13. This figure was adapted from Y. Ohsaki and M. Mikumo,
"Computer-aided Engineering in the Construction Industry,"
Engineering with Computers, vol. 1, no. 2, 1985, pp. 87-102.

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