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.

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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.

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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-

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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.

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department by the total credit hours to be

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Cost comparisons between departments

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the effect of size difference between departments.

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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.

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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).

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discipline at different levels of instruc-

tion and for each degree program at different

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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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