title higher education planning and management systems: a
TRANSCRIPT
DOCUMENT RESUME
ED 091 962 HE 005 504
AUTHOR Huff, Robert A.; Manning, Charles W.TITLE Higher Education Planning and Management Systems: A
Brief EIplanation.INSTITUTION Western Interstate Commission for Higher Education,
Boulder, Colo. National Center for Higher EducationManagement Systems.
PUB DATE May 72NOTE 37p.
EDRS PRICE MF-$0.75 HC-$1.85 PLUS POSTAGEDESCRIPTORS Colleges; *Decision Making; *Educational Planning;
*Higher Education; Institutional Administration;*Management; Program Planning; *Resource Allocations;Universities
ABSTRACTThe theme of this document is that programmatic
decision making can be carried out effectively only if appropriatekinds of information are made available. If an institution knows itsobjectives, it can define a course of action for the years ahead.Through use of a cost simulation model, it can forecast the resourceimplications of that plan. Student flow information will indicatewhich programs exhibit holding power and are most relevant to theneeds and interests of the student population. Output measures canprovide information related to the benefits or the value added tostudents and can be useful in identifying needed midcoursecorrections. Planning and management systems can improve themanagement of resources allocated to higher education.(Author/M3M)
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By
Robert A. Huff
Charles W. Manning
May, 1972
The National Center for Higher Education
Management Systems (NCHEMS) has been in
existence for some time.
Therefore, it
seems appropriate to ask such questions as,
How is NCHEMS doing, or more importantly,
Is the planning and management process in
higher education changing?
We think the
answer to the latter question is yes, ed-
ucational planning and management innova-
tions are beginning to appear.
We hope the
NCHEMS effort is partly responsible for
this change.
The changing concepts of educational
management are being adopted because of
a number of pressures related to the need to
meet many demands for educational services in
an environment of constrained resources.
The
work of the National Center is timely in that
it coincides with the perceived need for im-
proved management methodologies.
Management
by objective and program budgeting concepts
are no longer nebulous theories to the rank
and file of administrators.
Yesterday's
speculations about innovations in educational
administration are about to become tomorrow's
realities.
Mr. Average College President of the 1950's and
early 60's had diffe-ent types of problems than
his present day counterpart.
Money was flowing
into higher education from a variety of sources.
Few people were asking hard questions about how
funds were being used and what specific out-
puts were being produced.
Higher education
was assumed to be a fundamentally sound invest-
ment, and few expenditures of public and private
funds were thought to reap as high a return
for the general society as the educational
investment.
Operating in such an environment,
educational managers concentrated their planning
and budgeting efforts on defining the amounts
of resources needed as inputs to the various
organizational units that comprise colleges and
universities.
Little effort was given to
answering the question, Needed for what?
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Planning and budgeting based on inputs has
been the traditional approach.
The tradi-
tional line-item budget defines the amount
of resources required by each of the organi-
zational units (i.e., departments) of an insti-
tution.
A traditional line-item budget does
not relate dollar inputs to outputs.
Now,
many projects are competing for public and
private dollars.
A question commonly posed
is, Are the products of higher education
worth the cost?
The public is wondering
whether it is better to build low-cost
housing or reduce pollution than to produce
more degrees.
Educational administrators
must address these questions.
They are
being asked to justify the cost of educational
outputs, and this demand
Is
fostering an
emerging approach to planning and budgeting.
In this new approach management must establish
its output goals, formulate programs intended
to produce those outputs, and finally conduct
analyses to define the quantity and mix of
resources that must be input to each organiza-
tional unit to ensure each program's success.
Thus, academic planners are increasingly aware
of the fact that resources flow into instruc-
tional departments only because departments
contribute to various degree programs.
Cur-
rently, many funding agencies are requesting
budget formats that link resource requests
directly to programs that produce outputs.
When we observe Mr. Average College President of
the 1970's, we see that he is under more pres-
sures, or at least different pressures, than
his counterpart of the 1960's.
He is being
encouraged on many sides to implement planning
and management systems in order to gain an
improved understanding of how his institu-
tion actually operates and produces out-
puts.
He is told that the new kinds of
information derived from such a system can
help him more effectively use his limited
resources as well as satisfy the increasing
demands for program cost accounting and bud-
geting information.
He is inclined to believe
that planning and management systems will help,
but he wonders how he should proceed and how
he can determine his institution's PMS capa-
bility to implement new planning and manage-
ment systems.
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Those who are considering planning and manage-
ment system (PMS) implementation must first
decide if such systems are really needed.
If an institution has unlimited resources
and there are sufficient funds available for
all desirable activities, planning and manage-
ment systems are not required.
Today, few
educators enjoy such luxury, and most are
fa(ing difficult decisions concerning which
programs among a large number of worthy acti-
vities will be funded.
Having decided that planning and management
systems are desirable, an institution cannot
proceed with PMS implementation unless
specific prerequisite elements are present.
The institution must have operational data
systems from which the required data base can
be derived.
Personnel are required who have
the analytic capability to learn about and
maintain planning and management systems.
The
institution's organizational health must be
such that it can smoothly incorporate the
necessary changes for implementation.
This
will require a great deal of cooperation from
many areas of the campus.
Computer availability
is necessary to manipulate data rapidly.
Good
PMS tools and techniques must be readily avail-
able.
These tools must be complex erough to
accommodate the institution's needs and still
be relatively easy to install and use.
Finally,
successful implementation will never occur
without fortutide and willingness to work.
PMS implementation requires a good deal of
effort as well as commitment of resources to
the implementation tasks.
OR
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A great deal of attention should be given to
the manner of organizing for implementation of
planning and management systems.
Gaining
explicit commitment from top executive manage-
ment is of primary importance.
All those who
are to play a part in PMS implementation must
be aware of that commitment.
Specific
individuals must be designated as having
centralized responsibility for the implement-
ation task, and it is important that they
also be given sufficient authority to enable
them to fulfill their responsibility.
Many
individuals and offices throughout the
institution will be required tc cooperate in
data collection.
All of these individuals can
be expected to cooperate more freely if they
understand the reason for the PMS undertaking
and perceive that there will be some relative
advantage under the new systems for the insti-
tution as a whole, as well as for themselves.
Such understanding will require an in-service
training program within the institution in
order that all those involved know not only
what they are required to do but also why they
are being asked to do it.
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PMS tools fall into two general categories:
(1) those that are used to gather historical
data, and (2) those that use the historical
data as a point of departure to project future
costs and assist in planning for future oper-
ation.
The diagram above displays some
PMS tools concerned with historical data
collection.
Institutions that wish to gather their histori-
cal data for comparative purposes will find
the NCHEMS Program Classification Structure
(PCS) a valuable asset.
The PCS provides
cost centers for the primary and support
activities of an institution.
It may be
viewed as a common filing structure to which
various kinds of data may be attached.
The
PCS cost centers in the instructional area
consist of a list of disciplines that corres-
pond to the reporting categories required by
the Higher Education General Information
Survey (HEGIS).
Institutional data may be
translated into the NCHEMS PCS in prepara-
tion for reporting to the USOE through HEGIS.
If an institution determines the cost of
instruction in each discipline, degree program
-7-
costs may be obtained by allowing the dollars
to flow from the discipline cost centers to the
various degree program cost centers in propor-
tion to the flow of credit hours from disciplines
to degree programs.
For example, the history
discipline costs would flow proportionally to
each degree program as students from the various
degree programs take credits in the history
discipline.
If support costs were previously
allocated to the disciplines, then these costs
would also flow to the degree program cost
centers along with the direct instructional
costs and would be calculated as part of the
total cost of each degree program.
Two additional areas of concern are program out-
put indicators and information exchange pro-
cedures.
If cost benefit analysis is to
be applied to an institution, good program
output indicators are necessary.
Likewise,
costing and output studies must be performed
under precisely the same set of procedures if
information exchange is to have any validity.
Both of these areas are receiving a great
deal of attention and will continue to be
researched over the next few years.
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Once an institution knows its current program
costs and outputs, it has a base on which to
plan for future operations.
Various alternative
plans can be developed that will lead the insti-
tution toward its objectives.
Student flow
models and cost simulation models can be
very helpful at this point in evaluating
various plans and in predicting the long-
range resource requirements that are being
committed by current decisions.
Student flow models may be used to project
student enrollments by major and by student
level within the institution.
This is
valuable information that serves as a
princpal input to a cost simulation model.
NCHEMS cost simulation models use student
enrollments and planning parameters related
to faculty, classes, support staff, supplies
and equipment, etc., to forecast in a program
budget format the resources required when the
institution is operated in accordance with a
variety of alternative plans.
Usina a program budget, decision makers can
compare the costs of various alternatives and
weigh these costs against the anticipated
benefits of the various alternatives.
In
addition, PMS tools may be used to aenerate a
traditional budget that will show the flow of
resources to various departments as required to
implement a desired set of programs.
Thus, PMS
tools are able to generate program budgets for
program decision making and traditional line-
item budgets for program execution.
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A student flow model may take different forms.
The NCHEMS model uses transitional probabilities
to forecast the flow of students between
majors from one year to the next.
In the
example above, 100 type A majors enter
the institution in Year One.
During Year
One, ten percent leave the institution.
Of
those students that remain, sixty percent con-
tinue as type A majors in Year Two; ten ,per-
cent switch to type B majors; and thirty per-
cent switch to type C.
This same cycle repeats
itself through Year Four, producing, in this
example, 34 type A graduates; 13 type B
graduates; 16 type C graduates; and 8 type
D graduates.
Obviously, good predictions from this model
are dependent on valid and reliable transition
probabilities.
Tests have been completed that
demonstrate the advantage of this approach to
forecasting student flow.
NCHEMS, in
cooperation with pilot institutions, is re-
searching various methods of developing and
using student flow models.
A great advantage of the type of student
flow model shown above is its flexibility.
The flow of various student categories (male,
female, minority groups) may be examined
individually.
The attrition rates of different
majors may be compared.
The effect of changing
admission Policies related to certain types of
students can be examined and analyzed.
Through
the use of a student flow model, the educator
can understand better what is happening to
different groups of students as they pass through
his institution.
This improved understanding
can lead to efforts to shape the institution
to offer the best possible service to various
categories of students.
IND
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1 4
AV
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1615
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One of the foundation blocks of a cost simu-
lation model is an Induced Course Load Matrix
(ICLM).
This matrix displays the load induced
in each discipline or department by an average
major of each type.
The Induced Course Load
Matrix displayed above shows the number of
credit hours in each discipline or department
taken by the average student enrolled in each
of the degree programs of the institution.
For example, the average type A major can be
expected to take 6.1 credit hours in Discipline
One, 4.3 credit hours in Discipline Two, 2.6
credit hours in Discipline Three, and 3.0
credit hours in Discipline Four.
If one
hundred type A majors are admitted to the
institution, it can be readily ascertained that
the load induced on Discipline One will be
610 credit hours; the resulting load in Discipline
Two will be 430 credit hours, and so forth.
Thus, any given set of enrollment projections
may be multiplied down through the Induced
Course Load Matrix to determine the total
estimated credit hour load that will be de-
manded of each of the disciplines or depart-
ments in the institution.
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When the projected enrollments have been mul-
tiplied through the Induced Course Load
Matrix, the predicted credit hour demand in
each discipline or department induced by each
type of major is known.
Summing across the
matrix containing the credit hour loads
induced by each type of major gives the
total credit hours that a department must
produce.
Various planning parameters may then
be input to describe how each department's
instructional function will be operated.
Parameters such as average section size,
faculty work load, salary schedules, support
staff ratios, and expense formulas have
substantial resource implications.
Once
the department planning parameters are established
and the student enrollments are known, the
projected department costs are calculated.
The
cost per credit hour may then bt derived by
dividing the total instructional cost of each
department by the total credit hours to be
produced.
Cost comparisons between departments
are very difficult at best because of different
departmental roles and missions.
However, if
cost comparisons are desired, they are most
appropriately made using cost per credit
hour (or contact hour), since this eliminates
the effect of size difference between departments.
1 2 3 4
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Having determined the instructional cost for
each department, a cost simulation model will
proceed to distribute those department costs
to the various degree programs in direct pro-
portion to the number of credit hours drawn
from each department by each degree program.
The workload induced in a given department
by majors in a specific type of program repre-
sents a percentage of the total workload of
that department.
If the percentages for
each department are added horizontally, they
will equal 100 percent.
Each percentage
will represent a degree program's contribu-
tion to the total workload of a particular
department.
The instructional costs of each
department may be distributed across the
various programs in accordance with the
derived percentages and placed in another
matrix.
The cost of each degree program is
calculated by summing all the dollars in a
column of this final matrix.
Thus, the cost
of degree program A is obtained by summing
all the dollars in column A.
The annual
cost per major is a useful unit for comparing
degree program costs and is obtained by
dividing the total cost of a degree program by
the number of majors.
This entire view of cost simulation models
can be expanded from two dimensions to four
dimensions.
The expanded model handles
student levels within degree programs (lower
division, upper division, and graduate)
and different instruction levels (lower divi-
sion, upper division, and graduEte).
Such
an expanded model provides costs for each
discipline at different levels of instruc-
tion and for each degree program at different
levels of student major.
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A program budget can be constructed in a variety
of formats; however, there are certain kinds of
information that will almost always be in-
cluded.
The sample format above displays
the direct instructional costs for the history
degree program at lower division, upper division,
and graduate levels.
The total direct instruc-
tional cost is a result of the annual cost
per major and the anticipated number of majors.
If these numbers are accurate, the total
direct cost is an inevitable consequence.
Thus,
any negotiation or justification pertaining to
a program budget must center on the number of
students to be admitted and the annual cost
per major.
The number of students may be set
by policy, or if not limited, predicted by a
student flow model.
The annual cost per
major is a consequence of p,nnning parameter
decisions (displayed as back-up information
in a program budget).
Once it is determined
what the average section size, faculty
work load, salary schedule, expense formulas,
etc., will be, and the number of students is
known, the annual cost per major and total
cost of each degree program are calculated by
means of a cost simulation model.
When the
costs used to prepare a program budget are
deemed reasonable and valid, yet not enough
funds are available for all desirable programs,
institutions' priorities must be established.
The anticipated outputs or benefits of the
various programs must be compared and weighed
against costs in order to establish which programs
will be diminished or nourished.
A program budget is not a panacea.
It cannot
be expected to make decision making easier.
Rather, it displays resource requirements
in relation to output-generating programs and
provides greater insight into what we are
buying with our educational expenditures.
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Output accounting is an essential complement
to program accounting and program budgeting.
The Research Group at NCHEMS is currently
exploring the area of output accounting.
An attempt is being made to establish a list
of variables (related to instruction, research,
community service and the institutional
environment) which, if measured, would provide
a comprehensive profile of the institution and its
outcomes.
Only through trying a wide variety of
approaches in pilot institutions will we be able
to increase our understanding of what is possible,
feasible, and desirable insofar as institutional
output accounting is concerned.
In this area,
it is certainly true that progress will come
slowly and in small increments.
With the increase in cost information related
to educational programs on varicus campuses,
it becomes imperative that improved means of
assessing the relative merits and varying
purposes of programs be developed.
Without
improved output accounting, there is grave
danger that funders may fail to recognize
basic differences among groups of degree
programs with similar names and may be
tempted to hastily proclaim that cheap is
best.
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There are three overlapping functions within
the NCHEMS organization, Research, Development
and Applications, and Training and Implementation
Assistance.
The Research Group is responsible
for generating the conceptualized products.
Those conceptualizations are then passed on to
the Development and Applications Group where
documents and software are written and pilot
tests are conducted.
The Training and Imple-
mentation Group is responsible for displaying
and explaining the various NCHEMS products and
for assisting those institutions which decide
to adopt specific PMS tools in preparing for
the implementation tasks.
NCHEMS projects may be divided into two
categories, those that deal with the accounta-
bility function and
procedures for communica-
tion among institutions and those that are
related to institutional planning, analysis
and projection.
Some of the currently- funded
projects are listed above.
Several additional
projects are currently being developed at
NCHEMS, and it is expected that the list
presented here will be extended in the future.
The National Center exists to serve the needs
of higher education.
As additional needs are
identified, NCHEMS can be expected to take
whatever action is possible within the limits
of its resources.
Of special concern in the
future will be the development of statewide
planning and management systems, investigation
of special applications of PMS products at
small colleges, and the development of planning
tools and techniques for academic administrators
at the department and division levels.
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An important consideration of NCHEMS is the
wide variety of institutions that it is at-
tempting to serve.
Each institution has
unique needs and problems.
The ?MS tools
developed at NCHEMS must have the flexibility
to serve various types and sizes of higher
education organizations.
NCHEMS is guided
and controlled by the institutions and
agencies of the higher education community.
It is a collective, cooperative undertaking
in which institutions and NCHEMS staff are
learning together.
Some false starts, some
errors in direction will inevitably be made.
However, with a great deal of honest effort
and a spirit of cooperation, NCHEMS hopes to
succeed ii4 adding an element of management
science to the art of educational administration.
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The theme of this document and the entire
NCHEMS endeavor is that programmatic decision
making can be carried out effectively only if
appropriate kinds of information are made
available.
If an institution knows it's
objectives, it can define a course of action
for the years ahead.
Through use of a cost
simulation model, it can forecast the
resource implications of that plan.
Student
flow information will indicate which programs
exhibit holding power and are most relevant
to the needs and interests of the student
population.
Output measures can provide
information related to the benefits or the
value added to students and can be useful
in identifying needed mid-course corrections
-17-
in program design.
Planning and management systems can improve
the management of resources allocated to
higher education.
PMS will not make decision
making easy or eliminate political considera-
tions.
Political considerations and pressures
will never cease to exist, but they may be
tempered in the future by the creation of
more objective information.
Higher education
institutions will be difficult to manage even
with the availability of the best planning
and management systems information.
Without
such information, good management at a com-
plex institution may be virtually impossible.
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