A theory of computer based management control

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A theory of computer based management control
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Computer based management control
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ix, 172 leaves. : illus. ; 28 cm.
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Corporations -- Finance   ( lcsh )
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Thesis:
Thesis--University of Florida, 1971.
Bibliography:
Bibliography: leaves 164-171.
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Manuscript copy.
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Vita.

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Full Text














A THEORY OF COMPUTER BASED

MANAGEMENT CONTROL







By

HEINZ DINTER


A Dissertation Presented to the Graduate Council of

The University of Florida


in Partial


Fulfillment of the Requirements for the


Degree of Doctor of


philosophy


University of Florida
























Copyright


Heinz


Dinter
















ACKNOWLEDGEMENTS


The writer expre


sses


sincere appreciation to Dr


William V.


Wilmot, Jr., Chairman of the Supervisory Committee,


for his


innumerable


suggestions


, constant advice,


guidance and great patience throughout the


course of this work.


The writer acknowledges hi


i ndebtednes


to Dr.


Ralph H. Blodgett,


Warren W


Menke and Dr.


Mil ford


. Tysse


land for serving a


members of


the Supervisory Committee


Dr


ysse


land has been especially helpful


improving the proposed model.


The encouragement and faithful


support of the wri ter


family


have been essential


elements


in the completion of this dissertation.















TABLE OF CONTENTS


Chapter


Page


ACKNOWLEDGEMENTS .

LIST OF TABLES .

LIST OF FIGURES


ABSTRACT


v111


INTRODUCTION


The Nature of the Problem
Postulates and Hypothesis
Scope and Methodology .
Expected Results .


a a a S a a
S S S a a S a
* a a S a S S S S
* 5 S S S S S S


THE STRUCTURE OF FINANCIAL ACTIVITIES


Definitions . . .
Operating Equations . .
The Operating System Extended Over th
Period .


Planning


THE OBJECTIVE FUNCTION AND THE CONSTRAINT SYSTEM


The Objective Function
The System of Financial Ratio
Mathematical Formulation of th


standards
Entire System


. 44
48
59


THE MAN-MACHINE MODEL


S S a S a a S S S 564


System Definition
The Input/Output Elements of th
The System Logic .
The Man-Machine Interactive Pro

CONCLUSIONS AND RECOMMENDATIONS .


Conclusions


System


a a S S S a
S S S S S S S


a S S S S S












APPENDIX . . . . . .

BIBLIOGRAPHY. .. .


BIOGRAPHICAL SKETCH














LIST OF TABLES


Table

4.1


Page


The Financial Ratio Sensitivity Matrix













LIST OF FIGURES


Figure


Page


The corporate financial


system


The income statement


The balance sheet


General


system flow:


management control


simulator


The input/output element


The balance


of the


eet for the base period


a. 71


. . 73


Exogenous variabi


Input decision


The change of variabi


The value


process


of the objective func


S* .
tion . . .


Sensitivity analysis


S S S Ua a a S a a S S80


Pro forma


schedule


of changes


in working capital


. 82


4.10


Pro forma statement of sources and uses of funds


4.11


Pro forma income statement


S a a S a a a a a a85


Pro forma balance sheet


Ratio analysis


4.14


Program


logic of the management control


imul ator


4.15


Results of a simulation process


67














Abstract of Dissertation Presented to


Graduate Council of the University of Florida


in Partial


Fulfi llment


of the Requirements


for the Degree of Doctor of Philosophy


A THEORY OF COMPUTER BASED MANAGEMENT CONTROL

by

Heinz Dinter


March


, 1971


Chairman:


William V


Major Department :


Wilmot, Jr.


Management and Business Law


This study deals with a man-machin


system and the application


of the computer in top management financial


decision making.


An attempt


is made to determine the theoretical


basic


for a man-machine interactive


computer system in financial


management planning and control and examine


the process of computer based decision making in top management financial

planning and control.


The basis of thi


study is


the interaction between th


financial


manager of the business firm and a computer based decision making system


subject to the objectives


of determining the criteria for such a man-


machine relationship.


It is shown that heuri


and the computer subject to goal


orientation


stic interaction between man

is a feasible technique for


achieving a desired company objective.


A formalized man-machine system i


defined which serves as the











the feasibility of such a man-machine management control


system in the


form of the


"Financial


Interactive Planning Simulator," a top management


financial decision making simulation system which has been implemented


on a time sharing computer


tem and operates


in the complementary


mode


Thi


simulator demonstrates that the computer can effectively


complement the decision maker and,


in turn


the decision maker can


objectively complement the capabilities


of the computer.


The financial


istic model


assess


planning and control


of the corporate financial


expected consequences of changes


system i


based on a determin-


structure and allows th


in controllabi


user to


variables while


optimizing a chosen objective function over a given planning period.


The user interacts with the system in the conversational


time sharing terminal


mode via a


by making decisions which are tested by the system


against criteria specified in a dynamic financial


performance matrix.


The system analyzes


recommendation and


sensitivity of


supplies


a user-supplied financial


the user with feasible


decision


alternatives


improving the tentative deci


function.


sion relative to optimi


The user then has the option to modify h


zing the objective

is recommendation


and/or to accept changes


in the financial


performance matrix.


The system


leaves all decision making to the user and functions primarily as a

decision analyzer and performance measuring device in the financial


planning and control


process.















CHAPTER I

INTRODUCTION


The Nature of th


Problem


The purpose of this study is to apply the capabilities of computer


technology to


the area of top management financial


decision making and


determi n


theoretical


basis


for a man-machine interactive


computer


tem in financial management planning and control


The theoretical


basis will


then b


extended to a computer time


sharing


tern which i


to demonstrate the


feasibility o


this man-machine relationship in the


management deci


ion making process.


Computer Technology and the Financial Management Proces


The computer is


in the


eyes


of many a helpful


tool


for performing


routine tasks more efficiently than man can


In short,


electronic


computer is a


labor saving device.


Is that the


limitation of the com-


puter?


The answer was quite appropriate


'yes'


a decade ago.


However,


the functions of


the computer today entail


the performance of tasks which


will


have an


even greater impact than


its so-far-proven ability to do


very rapid


calculation


and to store and recall


large volumes of data


John Diebold


(1959) characterized this new capability by pointing


out that the utilization of the


computer is a way of "thinking as


much










information handling process


as an integrated system and not


as a series


of individual


teps.


Information process


ing has a


long history dating from the origin


of mankind.


Electronic information pro


cessing


on the other hand, has


been available for such a


hort time that its


implications are


till


widely understood.


Computer technology has changed very rapidly.


The first electronic


computer


built in the


1940


, is already history


Technique


of computer


uses


, pioneered in the


late


1950'


, are today obsolete.


Why?


Have


science


and technology advanced so rapidly and thus given the computer and the


methods for its use these


e phenomenal


growth characteristic


should


one argue that the outstanding potentials of the computer and the multitude


of applications


that can be


left to


its powerful


capabilities are only


lowly accepted?


There i


no doubt about the validity of the first argument


(Armer,


l 966)


Computer


peeds alone will


attest to this


technol ogi cal


advance.


In addition to the rapid increase in speed


, the computer has


acquired many other capability


rapid calculator, electronic data processing


Besides continuing to serve as a


teams of today serve as


central


control


points for communication network


by carrying out the


functions of network switching, data acquisition from and data dissemination


to distant


locations.


Computers serve as central


depositories for


large


volumes of data, and manipulate these data for the purpose of gaining useful

information.











the reason


slow acceptance of data processing.


This


lagging


acceptance becomes particularly significant when one realizes


the ever-


i ncre


asking involvement of computers


a college


student pursuing hi


in daily


educational


living


goal


-- whether it be


a scientist attempting


to find the answer to an unsolved problem, or a businessman searching


more effective techniques


for decision making.


prerequisite for successful


business management,


for example,


n today


compi


environment in no way implies


that the manager'


decision will


always result in


the use of th


computer for the


solution


of hi


busi


managerial


ness


and operational


decision requires th


probl ems


anal


It does


imply that a good


of realistic alternate


which


include among many such alternate


the utilization of computers.


That


computers are being utilized to an ever increasing degree


is demonstrated


by the


following


tatisti


(AFIPS


, 1966).


The total


number of digital


computers


installed in


1950 was approximately fifteen.


1965 this figure


had risen to thirty thousand.


During the five-year period beginning in


1965,


this number i


expected to double


Looking at this growth pattern


in term

rate.


of dollars


From an


invested


investment of


there i


again detected a phenomenal


.03 billion dollars


n 1950


growth


, data processing


growth ha


resulted in investments totaling 7.8 billion dollars


1970 thi


figure is expected to increase more


than


100 per cent


to 1


billion dollars.


significant growth


in the use of computers has been spurred











comprises


six distinct


1 ements


the manager who must ultimately decide which action to take,

and when;

the management information systems which provide the manager


with the data on which he bases hi


decisions;


models depicting various organic


national


aspects of the firm


which allow the manager to test alternate courses of action;

a feedback control system;


the computer; and


computer application technology


ts who incorporate the


computer into the


management control


tem.


It should be emphasized again at thi


point that the


subject of


this study i


the top


level manager and hi


corporate financial


decision


making function


In his capacity as a financial


manager the management


decision maker face


two objectives:


he must be sure that sufficient funds are available to


maintain current operations; and


he must work toward the maximization of long-run profits of


the firm.


In view of these objectives,


corporate financial management can be


divided into four distinct but interrelated deci


the operating control


it i


sion processes:


decisions:


imperative that the firm's operations are effectively











capital must be allocated to


investment proposal


the benefits


of which are realized at some future date;

financing decisions:


decision


must be made regarding th


source of capital


investment purposes, and,


in particular


a choi


must be made


between


long-term debt and common stock issuance;


the dividend decisions:


deci


ions must be made on the


level


of earnings paid out to


stockholders.

The decision maker is thus faced with the problems of:


detecting and correcting weakness


in the firm


financial


structure and operating


level


recognizing financial


strength


and applying them to increased


operating performance and to improving the financial


strength


of the corporate structure.


Prior Research


The nature of management


management


and in particular th


closely related to and can be identified


nature of financial

as a collection of


probl em


solving efforts


The process of problem solving has


long been a


parti


riy interesting challenge to researchers and has gained added


impetus with the advent of the


electronic digital


computer.


Opportunities


presented themselves


A.-' I- ,


now which allowed for the formulation of problems


I I I *


r% r' yr a a ~ a., n rr r* ai ISn fl n d n ." ni an 1r n t r ar tk rn I( *I r% nnfl fl Mn anr nn m


_~....











ment of the General


Problem Solving program (GPS).


In a paper given at


the International


Conference on


Information Processing


(Newell,


haw and


Simon,


1959) it was demonstrated that human behavior can be


simulated by


means of a computer program.


In particular,


model


was designed for


the purpose of solving symbolic


Problem Solving program to


logic problems by causing the General


imulate the human behavior demonstrated when


solving such a problem


n symbolic


logic.


It was recognized by the re-


searchers that each person behaves to


ome degree differently


However,


it was found in tests that the majority of persons utilized a common set


of basic process


involving the use of means-ends typ


analy


ses.


Hence,


authors have attempted to


incorporate the


strategic


of means-


ends analysis

An additional


into the problem so

attempt was made to


Living strategies of th


incorporate a


computer program.


second problem solving


technique


into the


computer model, namely


that of


bstracting a complex


problem into a


impler one.


Upon solving the


impi


r problem,


information


learned from this


problem execution i


then applied to the solution of


the original


comply


problem.


Newell


haw and Simon report


significant


success


in utilizing the General


Problem Solving program to solve symbolic


ogic probl


and trigonometric identity


However,


General


Problem


Solving program has not been employed in more general


problem solving


environments


uch as financial


management.


Newell


and hi


associates


conclude that the


behavior of a human can be understood as a product of


a complex but finite and determinate set of laws.


However


, the technique










and does


not render itself usefu


in applications other than very


specific problems


Other efforts


in the area of


imulating human behavior come closer


the area of management deci


ion making and,


in particular,


to the area


of financial


son (196


decision making.


A very significant effort i


who developed a computer model which


imulates th


that of Clark-


hnical


behavior of a trust officer who must make decision


in the trust investment


process.


Clarkson recognizes the


abundance of information which must be


evaluated prior to making an investment deci


sion


These


investment


deci


sons


are subject to constraints and


include


legal


restrictions as


well


as the


specific des


ires of the


client.


The model


presented is simu-


lating the


investment problem under uncertainty.


Clarkson relies upon the


theory developed by Newell


In developing the model,

, Shaw and Simon in


General


Problem Solving program.


The decision pro


cesses


simulated


are used iteratively and recursively


. The


logic


searches


industries


and companies for


specific attributes


creates sublists which are in turn


searched and again divided into


ublists


Upon continued divi


sion of


ublists


the search will


finally identify the common stock which meets


ired


the model


criteria.


In order to identify the behavior of the


incorporates basic rul


which resemble the


trust officer


characteristic


behavior of the officer in making portfolio


selections.


These rul


were


obtained by interviewing trust officers and observing their behavior by


reviewing past and future portfolio


section deci


sons.


Hence,


value




8





accuracy of the decisions which were observed among the interviewed


trust officers.


This portfolio selection model


represents a significant


step toward the automation of the


portfolio


selection pro


cess


However


the decision rul


implemented in the model


restrict the total decision


making pro


cess


to th


ese preconceived rul


the validity of which are


difficult to test and verify


A different approach to the portfolio


selection process


was taken


by Markowitz (1959)


He formulates a probability model which represents


the overall portfolio, expected values and expected returns of the port-

folio as well as measures of risks which are expressed as variances.


The input to his model


are probability beliefs, expected values as w


as variances and co-variances for each individual


security to b


analyzed.


The second part of hi


portfolio selection process


is represented by an


optimization model which utilizes parametric quadratic programming to


determine an optimum portfolio subject to given constraints.


The output


from the portfolio


selection pro


cess


is a portfolio with a maximum


expected value for the return which represents a minimum variance and also


satisfies all


constraints.


Markowitz bases his portfolio selection model


on the assumptions that there exists an uncertainty of returns from any


given investment and that there exi


returns.


ts a correlation among security


He argues that risks can be reduced by avoiding portfolios


whose


securities are all highly correlated.


optimization strategy


then follows the security investment objectives that high returns are











Probabilistic estimates are made of future performances


of security


The probabilistic estimates are analyzed to determine the


efficient set of portfolios.


From this

suits the


A portfolio i


efficient set a portfolio is


investor'


selected which best


preferences


considered to be efficient if it i


not possible to obtain


higher expected returns with no greater variability of return, or obtain


greater certainty of return with no


selection model


less


proposed by Markowit


average return


based on


. The portfolio


statistical measures


which are assumed by him to represent risk realistically.


The user of


the model must accept a


statistical


framework which determines functional


relationships


defines


risks and their respective


level


for given


securities and hence does not permit the introduction of risk factors

which may affect a security but has not been made an element of the

portfolio selection system.


Model


which describe


specific decision processes and relate to


a single business


problem are heavily challenged by research in the area


of model


building where the total


firm i


the basi


of the model


formulating total


firm model


specific emphasis


placed on describing


the functional


a firm.


relationships and interactions of the


gives


ubsystems within


rise to an examination of the results of having


elements of a business


system interact with each other.


Because of the











factor


Hence


, research efforts have been directed toward constructing


total


firm


simulation model


which are subject to abstracting


specific


functions and placing emphasis


on given subsystems at the expense


ignoring others.


A model


of a


firm which


imulates a hypothetical


company


, Task Manufacturing Corporation,


consist


teams for


functional


areas which compri


the total


firm and its environment


(Sprowl


and Asimow,


1960)


Each subsystem describes


the behavior


of individual


units within that system such


as purchasing or


shipping.


Hence,


Task Manufacturing


Corporation


imulator consists of a


collection of micromodels which represent the


various function


of the


firm.


simulation model


has been described by Sprowl


and Asimow


follows:


In a sen


each model


of a


subsystem i


analogous to


ack box" and if certain inputs


will


ear.


Some of the outputs


are specified,


outputs


are uniquely determined


ome are determined only in a stochasti


Just as a collection of sub


sense.


stems does not comprise


a business firm, neither does a collection of model


a representation of a business


firm.


coupled together to permit inputs and output


comprise


The subsystems must be


to come from


and exit to both the external world and other subsystems.


Formal


policies, managerial decisions,


which have developed from


the ways


in which these


set of human and material
ditioned by formal and ir
firm. Correspondingly, t


model


prises


and informal


policies


customs and traditions determine


coupling


Ifo


are allowed to occur.


ubsystems and the couplings con-
rmal policies comprise the business


;he set of separately programmable


of subsystems coupled by interconnecting programs com-
a representation of a business firm--a simulation firm


which can be manipulated on a computer.


The significance of this model


a a -


in the flexibility offered because


I I 1- -


- *.L.~-. 1. -I -. r~ .ui .. t3 -1 Ul U _.


..











forced to place equal


emphasis on the rest of th


system.


In addition,


model outputs can be determined non-stochastically whereas other outputs


are determined


stochastically


Another


simulation of a manufacturing firm is a model


proposed


by Bonini


(1963)


His model


is also a functional model


similar to that


propo


sed by


prowl


and Asminow.


However


Bonini


places emphasis


the information and decision


tem within the


firm.


A unique element


of hi


model


is the representation of behavioral


factors in the model.


These factors are given in the form of indi


of pressure on individ-


within th


firm which affect their performance and deci


ions.


example e,


index i


used a


the basi


for determining the mean and


standard deviation of the sal


distribution which determines


the sal


man'


monthly


sales rate.


The control


subsystem in the model


in the


form of sal


quotas and manufacturing standard cost


in addition to the


indices of pressure on individuals.


indices of pressure thus become


an indirect control


on the


firm's operations.


These felt pre


assures have


an effect on the


expen


level


of the manufacturing process


and the performance of the


staff.


ses,

The


admini


effect i


trative


measured


changes in the means and standard deviations of distributions from


which the values for given


simulation periods are chosen.


A pioneering effort in building a general


model


of the business


enterpri


which giv


the top management decision maker a tool


simulating the operations of the business firm i


Top Management




12





of the enterprise are incorporated and no aggregations of specific


functional areas are considered.


was implemented on the


Top Management Decision


computer in the form of a busin


imulation


game.


game is designed for team play and is


executed in an interactive and


competitive envi ronment.


Hence


, a key


element of the model


is the


exploitation of the competitive nature of business operations.


game defines


more than one firm and each firm receives


information


about its own operations


, information about the industry and the


specific market in which it i


operating.


An essential


element of such


a business


game i


the quantitative description of the market and the


determination of economic indices.


envi ronment


, in conjunction with


algorithmic procedures defines the constraint


tem of the model


outcomes of the simulation are influenced by the input decisions of the


user of the game as well


as the predetermined and nonvariable structure


of the market


and market forecasting process.


market mechanism,


perhaps,


is the weakest


link


in th


model


because, despite an appearance


of reali


tic behavior, no claims have been made that


uch market mechan-


isms do indeed exist in reality.


A great number of general


management games followed after the


initial


success of the


Top Management Decision Simulation developed by


the American Management Ass


ociation.


A noteworthy exampi


is the IBM


Management Decision Making Laboratory (IBM Corporation,


1963)


simulation model


which include the user as an integral


part of











such a man-machine model, research efforts have been


significant


in thi


area.


However,


the RAND Corporation has made a significant


contribution in the form of the Logistics


teams Laboratory (Gei


1960)


In the


laboratory, both the computer and the manager are active


participants in the


laboratory has


simulation process and both are an integral


been used to test various


part.


man-machine techniques


For example, one


laboratory problem was to investigate two alternative


management


structures; one in which material management is ass


signed


primarily to the weapon


stem manager and the other in which material


management is assigned to the inventory manager.


The objective of this


laboratory problem was


to examine


performance of logistics


systems.


Mattessich (1964), referring to efforts to build

models, emphasized the need for research in a specific

There cannot be any doubt that these endeav
ultimately benefit business practice and will in


run decisively influence the science
and management, but there is a need


of business


simulation


area:


ors will


the


long


administration


-- and perhaps a more urgent


for an entirely different way of simulating the firm.


One that is not directed toward "enterprise construction,
one that merely aims at improving the existing system of


operating budgets.
rigid decision rul


One that does not substitute more or


less


for middle management by means that are


set moderately enough to be immediately realizabi


in a


Real izable


large number of enterprises, even those of middle and small


size, where neither vast financial means nor electronic computers


are at the disposal of the individual


puter simulation as applied to th
us that a budget simulation model


firm.


The novelty of com-


enterprise may easily deceive
is nothing but a paltry or


diluted version of the management control models of th


just described.


the technical


However,


features,


the goals,


the expertnes


type


the range of expenses,


required,


the range of


application, and the effect on accounting, are entirely different
nn nc 4 thoen +an a nnzFr a rhn


" but










The Corporate Financial


System and the Needs


for a Simulation Model


The complexity of the corporate financial


problem can be visualized from Figure


management decision


1.1 which identifies the flow of


asset


and costs through the corporate financial


structure.


Financial


decision making relates to this corporate financial


system in the form


of the arrow


The deci


ion maker determines the dollar amount of flow


toward specific


sections of the


tem.


The interactions of balance


heet variabi


and income statement variabi


are controlled by


operating decision


and are kept in balance via the profit/loss flow.


Because of the multitude of sectional

system and the close interrelationship


relationships within the closed


of the operating and financial


position variables,


the management deci


sion and control


process becomes


very comply


and cannot be carried out


effectively without providing the


manager with new capabilities.


new capability will


hopefully be


found in the computer and quantitative techniques which,


in turn


take


advantage of computer capabilities.


An area of research which utili


the above described financial


system as the basi


and offers to bridge the gap


left by prior research


efforts


should address


itself to satisfying th


following needs of a


financial management


imulation model


The simulation process should be subject to exception


reporting.


can be accomplished by specifying control


limits upon variables, analyzing the system and then determin-
















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The simulation model


should provide for online comparisons


between model


trials.


The system


should examine results,


compare them with previous results, allow for the revi


of assumptions and then repeat the


imulation system should have the


simulation cycle.

flexibility which allows


user to assign values to all


are determined by functional


variabi


relationships


except those that

inherent in the


model.

The system should have the flexibility to allow for the

assignment of a new value to a variable when proceeding to the

next planning period without being restricted by algorithmic


procedure


which keep the dynamic nature of the relationship


of a variable in one period to the next planning period

rigid.


simulation model


must have the user in mind,


that i


simulation model must be easy to use and should provide for

flexibility in the manipulation of the model.


The model


respond with th


should avoid detailed


management deci


ubsystems which do not cor-

ion process at the corporate


level.


The system should have interactive capability.


This


interactive


capability should give the user the opportunity to revise


decision


without delay.










Postulates


and Hypothesis


Postulates Relating to Computer Technology


The trend toward the "computer utility" will


affect management


control


significantly (Business Week,


1968).


Aside from supporting


management through an efficient flow of information


, the computer begins


to take a more active

According to Drattell


role in the total management control


(1966)


process.


companies set a significant percentage of


their annual


sales aside for computer expenditures.


However,


should


also be real


zed that the


small


er company pays a much higher price for


the use of computer


service than


larger company.


i gni fi cancer


of the computer


expenditure decision warrants the assumption that most


effective computer use comes from the control of this activity by top

management.


Top management continues to take a more active


process


techniques


role in data


ing and is becoming more and more knowledgeable on data processing


The increasing knowledge of top management continues


support the trend toward top management involvement


in computer operations.


The most


"computer utility"


significant factor


in the user


supporting the evolution of the

s selection criteria on the basis


of computer performance (Hollander,


1967)


As pointed out by Finke (1965) before the U.


Senate Subcommittee


on Antitrust and Monopoly,


the computer


economic impact can best be


identified by the following three trends


II Lm I LII I I: AA11* 1IIA LI:Y










computer use is


increasing at a rapid rate.


The impacts of the computer and automation have introduced many

labor saving techniques which permit business organizations to cope with


the ever increasing volume of data to be processed.


The role of the


computer i


part of the


changing from that of a computational

synthetic process of decision making.


tool


to becoming a


Hence,


the assumption


is made that computer technology permits the utilization of the computer

as an amplifier of human intelligence and as an extension of human ability


to think and create.


The computer is


therefore considered as a congruous


element in the feedback control


loop of management decision making.


The introduction of new concepts within business organizations


presents problems because


of the manager's unwillingness to readily adapt


to change.


These problems,


it will


be assumed, are overcome because the


manager must realize that the


compl exi ti


of present day communication


systems within the organization jeopardi


effectiveness unl


adapts to technological change.

The application of computer technology in the management control


process becomes even more significant with the introduction of data communi


The remote access to the computer, hence, stimulates


more diverse utilization of computer capabilities.

relates to the computer-problem interface, the com


computer and the problem which i


A significant assumption


imon boundary between the


in the form of a computer program.


will be assumed that this interface problem can be overcome and result
*


cation capability











and the computer technology


processes


specialists.


Hence, complex management


can be translated into feasible computer procedures


In over-


coming the computer-problem interface


, it must also be postulated that


the direct use of the computer by the deci


ion maker i


feas


ible and


allows the decision maker to interact with the computer without the aid


of a computer technology


specialist.


assumption i


necessary if


the decision maker i


support his thinking process via a direct and


immediate a


access


to computing power to manipulate deci


ion variables


and respond to


tem feedback to obtain immediate information.


Postulates


Relating to the Financial


Management


imulator


The proposed financial management


ture of the corporate financial

the simulator are based on the


long-range financial


system (Fig


imulator i


based on the struc-


The capabilities


assumption that financial


planning consist of a combination of


management and

judgment and


analy


sis.


Therefore


the model


structure does not consist of a set of


rules governing actions


to be taken as a consequence of input.


On the


contrary,


it i


assumed that the simulator can be an effective management


tool


if t


decision maker himself becomes an integral


part of the


management control


simulation process.


It will


therefore be assumed


that the computer model

governing actions to be


can function effectively if,


imulator function


instead of rules


entirely on the


basis of those algebraic relationships which define the corporate


ai a S




20






of the computer system to give an effective response.


However


, the feasibility of the application of operating rul


upplied by the user of the simulator i


assured if the


assumption can


be made that the effectiveness of the decision maker is


not undermined


by the


complexity of the


operating rul


formulation pro


cess


It 1i


making capabilities


the results of hi


also assumed that the manager can


by formulating a financial


decision from th


improve his decision

decision and receiving


simulator subject to a system of


financial


constraints imposed on the organization.


The management simulator assumes that operating


level


do not


change from period to period unl


a given operating


the manager intervenes and changes


level.


The financial management simulator is a top management planning


and control


tool.


It is to aid in controlling the financial


soundness


of current operations and serve in the


long-range financial


planning


process.


Hypothesi


On the basis of the identification of the combination of unsat-

isfied needs for a financial management simulator and the assumptions


made,


this study sets forth a hypothesis which,


if proven valid, will


offer the top management decision maker a feasible system for management


planning and control


in the form of a financial management simulator.


-tr a -











Given today's


technology and accounting conventions,


it is


possible to design a computer based financial


simulation model based


upon the balance


heet,


income


statement and the financial


ratios


inherent therein.


Such a model, being deterministic and without


forecasting algorithms, can be made to


respond directly to the decision


maker


interrogation


in order to assist the deci


sion making process.


Scope and Methodology


The exploration of the feasibility of the application of


com-


puters to extend the top manager's deci


ion making capabilities


requi res


a thorough understanding of the dynamics of


impact of that technology on the manager


computer technology and the


s decision making environment.


This study deals with the question of whether the computer can be used


to assume management functions and/or extend th


management decision


process.


An investigation is made of the


feasibility of using the


computer to support the management deci


ion making pro


cess


in a real


time environment.


In conjunction with thi


investigation,


it 1


necessary to determine the feasibility of man-machine systems


management decision making pro


in the


cess.


The proposed final

the deterministic model


planning and control


of the corporate financial


simulator is based on

structure and allows


user to


assess


expected consequences of changes


in controllable


variables while optimizing a chosen objective function over a given


al Ki I


J


r -rr r .r 1




22







which are tested by the system against criteria specified in a dynamic


financial


performance matrix.


a user-supplied financial


deci


The system analyzes


the sensitivity of


ion recommendation and provides the


user


with feasible


financial


recommendations which enable


him to test feasible


alternatives


for improving the tentative decision


the objective function.


The user then has


relative to optimizing


option to modify his


recommendation and/or to accept changes


in the financial


performance


matrix.


The system leaves all


decision making to the user and functions


primarily as a decision analy


zer and performance measuring device in


the financial


planning and control


process.


The decision which become


input to the


stem may be the output


from a stochastic subsystem and


hence, may have been arrived at by


considering risk


The model


to be formulated does not consider the constraints of


uch subsystems


but accepts a given decision as "th


best we can do


for the moment.


However


the model


permits the decision maker to vary


input decision and thus offers him the opportunity to measure the


rewards of risk taking in the form of profit determined by the


subject to the exogenous


risk


level


controlled by him.


Hence, decision


may result from probabili


tic model


, but, when entered


into the financial


management simulator


In particular


decisions


it is


become deterministic.


hown how the systems analysis approach, based


-I 1 S *I 5 5 S SO 5












The top manager is able to utilize the simulator by


selecting a set


of performance measures which are consistent with company objectives

and ask "what if" questions pertaining to the testing of the operation-


strength of the


firm and the capabilities


for reaching a given


long-range objective


Relatively


little has been accomplished in designing effective


computer based planning and control


toward the design of model


on algorithmic procedures and thereby


systems because of th


which attempt to base the entire


excludes the judgmental


emphasis


imulation


capabil-


of the decision maker from the


imulation pro


cess.


management


simulator forces both the manager and the computer to complement each


other and thus makes the deci


ion maker an integral


part of the computer


based system.


This financial


management simulator is subject to the


decision criteria of the top manager and responds


to the decisions of the


user


, performs


sensitivity analyses


on the


basis of th


user-suppli


deci


sions and guides


the manager in analyzing and evaluating his decision.


The computer


system i


based on exception reporting,


that is


control


limits are entered into the


, an analysis


performed by the system


and,


in turn,


the system inform


the management decision maker when simu-


lated values exceed the control


limits.


Furthermore,


the system attempts


to aid the management decision maker by providing the capability of making


comparisons between th


current decision and previous decisions.


_ __ I 1




24







because of the assignment of decision making functions to the user of


the system


results of the


simulation process are more representative


of real


situations rather than decision outcomes based on abstract


relationships.


In addition,


computer


tern is


designed with the


user in mind.


In other words


the user i


not hindered in his decision


making process by complexities


of the


tem itself


Rather


, the


financial management


system i


easy to use and offers quick and easy-


to-interpret conclusions derived from the input decision.


Within the scope of this


tudy


an attempt i


first made to


formulate the structure of financial


In Chapter II


activity


the structure of financial


in mathematical


activity


form.


within the business


organization are identified.


Then,


in turn,


these


definition


serve


the basi


for designing th


man-machine simulation model which i


vehicle for demonstrating th


validity of the hypothesis


Upon defining


income statement,


the balance


heet and other financial


operating


activities, a system of mathematical


equations


formulated which


expresses all


financial


activity


that become elements of the simulation


model


This mathematical


formulation is then extended to the planning


horizon for the purpose of demonstrating the functional


which exist between financial activities


relationship


in various planning periods


In Chapter III a formulation of an objective function i


which will


offered


erve as a measure of accomplishment in the operation of the


a I a -


ri r r .












This constraint system consisting of financial


ratios forms the basis


for sensitivity analyses which are to aid the user of the management


control


tern in making his decisions.


The financial


ratios are


chosen for this purpose


financial


because


of the interdependent nature of the


system and the difficulty inherent in a financial


system for


measuring the activity

In concluding th


levels and controlling


mathematical


level


formulation of th


of performan


financial


system to be incorporated in the


is formalized and financial


simulation model


the financial


activities are combined through th


tion of the objective function and constraint


stem which result


formula-

ts in the


mathematical


representation of the management control


system


imulator.


The combined mathematical


stem


, hence, consi


sts of


an objective


function,


defi ni tional


equations for financial


activities and the constraint equations


which represent upper and lower bounds on financial


ratio


standards.


Based on the


Chapter


mathematical


IV is devoted to the design of th


formulation of the simulation system


computer based system.


computer program to be implemented i


designed in order to demonstrate the


validity of th


hypothesi


underlying thi


study.


First,


the general


system flow is developed.


This general


system


logic forms the basis


for the man-machine interactive model


and has an overriding influence


on the design of the input and output elements of the computer system.


tudy then proceeds


rpnilirpmpntc fnr thp qvctpm


to a detailed analysis of the input and output


ilnnn dppfinina thp rnmniiter ev



26






simulator is based on the interaction of man and machine during the

simulation process.


The computer based


imulation


stem is then utili


zed to demon-


state how the manager uses


stem in the management deci


sion


making pro


cess.


application also serves as a demonstration of


the validity of the hypothesi


and to verify the feasibility of man-


machine


interactive financial


decision making.


Expected Results


The computer as a


tool


of the


decision maker can serve a sig-


nificant function by participating in the management process


haring role and by ass


in a time


listing the manager in controlling the information


formation process


in the


company's operation.


Furthermore,


computer


can assist the manager in organizing and controlling the


multitude of


management deci


ion variable


These efforts are not


solely aimed at


benefiting the

assisting in th


large organization and are not specifically aimed at


analysis of the most complex type of problem a business


manager can face.


computer can only become a useful


tool


if it is


capable of being programmed for a wide range of problem applications.

The user of computers and the computer itself reach the maturity


which enables


both to work as a harmoniou


team to meet these


challenges


if the technical


aspects of computer technology can be effectively


implemented.




27





Despite the availability of the previously mentioned benefits of

increasing computer technology, one problem which has not been solved yet


very


success


fully is that of the "faith and understanding gap"


(Withing-


ton,


1966).


The technical


nature of computer use and the n


eed for highly


trained subject area


specialists make it difficult to find a person who


is well


versed in both areas.


The resultant void in the computer-problem


interface has caused many problems


in the past and will


continue to do so


for some time to come.


study sets out to


serve these


purposes with the premise that


the next


tage of data processing will


be centered around the


"computer


utility."


It will


hown that past and current methods are necessary


prerequisites and foster the evolutionary shaping of information process-


ing capabilities and requirements


A financial


management simulator is


presented as a demonstration of the feasibility of a computer based man-


machine interactive decision making system.


the validity of the hypothesi


system serves to verify


offered and verifies the theory of computer


based management decision making.














CHAPTER II

THE STRUCTURE OF FINANCIAL ACTIVITIES


This chapter


serves


to identify the structure of financial


activities.


These definitions will


serve as the basi


for the design


of the man-machine model


to be discussed in Chapter IV


set of


financial activity


not represent a complete set because such


undertaking would cause


the computer model


to be described later to


be unnecessarily complex


and cumbersome for the purpose of the study.


Completeness was therefore sacrificed in order to assure consistency


in the definition of the financial


active ty system.


ome equation


however, may have to be changed by the user to reflect his


Consistency in the description of the functional


situation.


relati onshi ps


financial


variables


is an essential


prerequi


site for the design and


implementation of the management control


has been maintained.


imulator.


In addition to avoiding compi


This consistency

exity, an effort


is made to eliminate the need for formulating deterministic financial


relationship


defini tional


which require that assumptions be made which are not

in nature.


Definitions


For the purpose of offering a mathematical


description of the











variables take on a unique definition within the general


that particular variable.


definition of


To identify a time dependent variabi


notation will


indicate such time dependence


of a variable by specifying


the time period a


a subscript following the variable.


The definitions of th


variable


are as follows:


Income statement variable for period t


Balance sheet variabi


x3..t

d.


at the end of period t


Other operating variable for period t

Exogenous decision variable


Time period


. *


Planning horizon


Financial

Financial


ratio

ratio standard


Slack variable
t


The income


statement consi


sts of sixteen variable


the definition


of which are given in the formulation of the


income statement displayed in


Figure


The balance


heet consists of twenty-two unique variable


The balance sheet


structure and the associated variables are defined in


Figure


In addition to income statement and balance sheet variables, other


variabi


must be defined in order to formulate the financial


These financial


activities will


system.


be defined by variables which are classified


as "other variables."


Their definitions are as follows:















xl01t.
x102t
xl03t

x104t

x104at


Sales


minus


minus


minus


mi nus


Cost of Goods


Selling and Administrative Expense


Depreciation

Amortization


equals:


xl 05t

x106t

x107t

x108t


plus:

minus


minus


Net Operating Income

Nonoperating Income

Nonoperating Expense

Interest on Loans


xl09t

xllOt


equals:

minus:


Net Income Before Taxes


Federal


and State


Income T


axes


xlllt

xll2t


equals:

minus:


x113t

x114,


equals


minus


Net Income


Dividends on Preferred Stock


Net Income on Common Stock Equity

Dividends on Common Stock


x1l15t


equal


Net Income Transferred to Retained Earnings


The income statement.





31






ASSETS


x201t


Cash and Equivalents


accounts


ivable


Inventori


Current Assets


x204

x205t

x206t


ecuri ti


Gross


Plant


Depreciation


Net Plant


x208t
x209at

x209bt


Gross


Intangibi


Assets


Amortization


x209t


Net Intangible


Assets


x210t


Total


Assets


LIABILITIES AND NET WORTH


t Loans


Payable


t A


accounts


Payabl


Taxes
t


current Liabil


Term Debt Unsubordinated


Term Debt


Preferred


Common


Paid in


Subordinated


Stock


Stock

Surplus


Retained Earnings











x301t


Cash Payment on Accounts Payabl


Cash Receipt on Accounts Receivable


Purchase

Purchase


(or Sale

(or Sale


of Security


) of Fixed Assets


Interest Earned on


curities


Nonoperating Income other than


Cash Payment on


Interest Earned


Taxes Payable


Short-term Loan Payment on Principal


(or Receipt of Loan)


Long-term Debt Unsubordinated Payment on Principal

(or Receipt of Loan)


x310t


Long-term Debt Subordinated Payment on Principal


(or Receipt of Loan)


Acqui si tion


(or Sal


) of Intangible


Assets


Number of Additional


Price per


hares of Preferred Stock Issued


hare of Preferred Stock


Number of


Additional


Shares of Common Stock Issued


Price per


hare of Common Stock


Production Cost on


Trade Credit


Other Production Expenses


The variables


so far defined represent activities which are deter-


mined by the activities of the financial


system.


A complete mathematical


description of the financial


structure of the business organization also


requires the definition of variables which are not controlled by the




33






Rate of Interest Earned on Securities Held

Rate of Depreciation

Scale Factor for Dollar Amounts

Rate of Amortization

Rate of Interest on Loans

Rate of Interest on Long-Term Debt Unsubordinated

Rate of Interest on Long-Term Debt Subordinated

Rate of Payment on Accounts Payable

Rate of Receipt on Accounts Receivable


Rate of Payment on


axes


Payable


Par Value of Common Stock

Number of Shares of Common Stock Outstanding at the


end of period t


Number of


hare


of Preferred Stock Outstanding at


the end of period t


Base


Year


Current


Year


Rate of Capitalization for Objective Function


On the basis of the definitions of income statement and balance


sheet variables,


the following two systems of balancing equations


represent income statement and balance sheet activity

INCOME STATEMENT EQUATIONS


xlO1t


- x102t


- x103t


- xl 04t


- x104 at


- xl 05t











x109 t


x113t


- xl10t

- x1l2t
- x114t


- xlllt
- x1i3t
- x115t


BALANCE SHEET EQUATIONS


x201t + x202t +
x204t + x205t +


- x204t
+ x209t


- x210t


x206 t
x209at


- x207t


- x209bt


- x208t


- x209t


x211t + x212t + x213t


- x214t


x214t + x215t + x216t + x217t+ x218t


+ x219t +x220t


- x210t


Operating Equations


The balance sheet, income statement and other activities are
combined to form the following system of equations.


x104t = d2(x208t _1 +

xl04at = d4(x209t_1 +


x105t
x305t
x106 t

x211t

x215t

x216t


Sx101 O


- x102t


= dl(x205t 1 +


= x305t +
= x211t-1

= x215t1

= x216t 1


.5x304t)
.5x311t)

- x103t

.5x303t)


- x-104t


- x104at


x306t
- x308t

- x309t
- x310t










xllOt


x109t


.22x1 09t


(xl-O~


111,


x113t
x115t


= x109t
- xllt

= x113t


- 25


- xllOt

- xl12t


,000)


+ 5,500


x109t


5,000


114t


= x2


101t
tr


= x2


= x2


= x2


02t-

03t-

05t-


x101t


- x102t


- x3


+ x3


+ x317t


1 + x3


= x2


x104t


x301t


= x2


+ d8


3l6t


= x2


12t-


1 x


01t+


x307t


= x2


= x2


+ d1Ox110t


xllOt


- x307t


x201t


= x2


Olt-


1 x


103t


- x301t

- x310t

- x317t


x106t


- x3


- xl 07t

- x303t

- x311t


- x108t


- x3


- x112t


- x3


x312tx31 3t


- x114t


- x3


+ x314tx315t


x209bt


09at


x217.


= x209bt

= x206t_1


= x209at_


= x217.


+ x104at


+ x304t


x311t


+ x312.x313_


x2


~09t











x220t


= x220t_i + xlOlt


- x107t


- x102t

- x108t


- x103t

- xll0Ot


- x104t

- x112t


- x104at

- x114t


+ x106t


x204t


= x201t


+ x202t


+ x203t


x208t


= x206t


- x207t


x209t


= x209at


- x2


09bt


x210t


= x204t


+ x2


05t+x208t


+ x209t


x214t


= x211t


x210Ot


= x214t


+ x2


15t + x216t


+ x217t + x218t


+ x219t + x220t


The Operating


stem Extended Over the Planning Period


The financial


activities


formulated in previous


sections must


now be combined into a


tem which extends over the


planning period T


and therefore considers


T time periods.


In combining the T


time periods


into one system of equations, several


simplifications


in the mathematical


formulation of the system are possibi


In general


consider an equation for


T periods:


- Yt-l


- wt


=0,


for all


The system of T


equations


is written as follows:


- YO


- Y2
- Y2


- wl

- W2

- W3


YT-1


- YT-2


- WT-1


+ x213t


3 ...,










stem of T


equations


recursively defined and can


therefore be


simplify


d into a


ingl


equation of the form:


- YO


S0.


Hence,


the system of equation


activities extending over the


representing the operating


planning period t


through t


can be written more compactly as follows:

T


x211T


x2155T


- x2110


- x2150


x308t


x309t


- x2160


x310t


x302t


x202t


d9x1 01t


x202T


- x2020


xllt


x302t


x203T


- x2030


xl 02t


- E
t=1


x316t


t=1


x317t


x205T


x207T


- x2050


- x2070


- Et
t=II


SE


x303t


x104t


x21










x2V31-


- x2130


xl l0t


x307t


+ t
t=l


x201T


- x2010


xl 03t


x106t


+ t=
t='l


T
+
t=l


xl07t


+ t
t=1


xl 08t


+
t=l


xl 12t


x114t


x301t


+2:


x303t


+2:
pgl


x307t


x308t


x309t


x31 0t


+ t=
t=l


+
t=1


x304t


x311t


x312tx31 3t


- E
t=1


x 314tx315t


+ x317t
t=l


x209 b-


x206-1


T
x209b0- I
t=1


- x2060


x104at


x304t


x209aT


- x209a0


t=l
t=1


x311t


x217T


- x2170


x312tx31 3t


- x2180


d11x314t


x219T


- x2190


x31 4tx315t


dl11x314t


T
+
t=l


+
t=l


x218T


x302t












x220r


- x2200


- I
t=1


xlOlt +


x102t +


xl03t +


x104t +


x104at


x106t +


x107t +


x108t +


xll0t +


x112t


x114t


x104t

x104at

xl 05t

x305t

x106t

xl 08t


x109t

xllOt


= d2(x208t.1 + .5x304t)

= d4(x209t_1 + .5x304t)


- x101o


- x102t


- x103t


- x104t


- xl04at


= dl(x205t_- + .5x303t)


= x3


05t + x306t


= d5(x211t_-


= x105t + x106t


.5x308t) + d6(x215t_1


.5x310t)

- x107t


.5x309t) + d7(x216t_-


- xl08t


if x109t


.22x1 09t

.48(x109t


if 0


- 25,000) + 5,500


< xl09t< 25,000


if x109t


> 25,000


xlllt

x113t

x115t
x301t

x307t

x204t


= x109t

= xlllt

= x113t


- x11Ot

- x112t


114t


= x212t_i + d8x316t

= x213t-1 + diOxll0t

= x201t + x202t + x203t


a a


a -











x210t
x214t

x210t


= x204t
= x211t

= x214t


+ x208t


+ x2


+ x2


+ x209t


+ x21


+ x216t


+ x217t


+ x218t


+ x219t


+ x220t


for all


The above


tem of thirty-seven equations can be simplified by


substituting equation


19 through 31


into equations


through


resultant


system consists of twenty-four equations.


x211T +


x215T +


x216T +


x308t


x309t


x310t


- x2110


= x2150


= x2160


x3Q02.t


d9x101t


x202 t


= x2020


x202T


(x101lt


- x302 )


= x2020


x203T +


Cx1Q2.t


- x316t


- x317t)


= x2030


x205T


x303t


xn7_ -


x1O4.b


= x2050


z ~r?7


. .











(x~loQ


- x307t)


= x2130


x201T +


(xl 3


- xl06t + x107t


+ xl 08t


+ x112t + x114t + x301t


- x302t
+ x304t

= x2010


+ x303t
+ x311t


+ x307t + x308t + x309t + x310t


- x312tx313t


- x314tx315t + x317t)


x209 bT-
t=l


xl04at


= x209b0


x206T


- t
t=1


x304t


= x2060


x209aT


x217T-


x311t


= x209a0


x312tx31 3t


= 2170


d11x314t


= x2180


x21 %.


(x314t31 5t


- d11x314t)


= x2190


x220%


(xl~l


-xlOZ,

-xl 8


- x103t
- xllot


-x 104t
- xll2t


- xl04at + x106t


- xl14t)


- x107t


= x2200


x204t


- x201t


- x202t


- x203t


x213T


x2181.











x209t


- x209at + x209bt


x2l0Ot


- x205t


- 24


- x208t


- x209t


x214t


- x211t


- x212t


- x213t


x210t


- x214t


- x215t


- x216t


- x217t


- x218t


- x219t


- x220t


for all t


= 1,


S.. ,


In an earlier section, a definition of the income statement and

balance sheet activities was given mathematically in the form of


balancing equations.


When extended over the planning period T, the two


balancing equations for each time period will extend into a system of

2T balancing equations as follows:


x101t


x201t


- x102t


+ x202t


- x103t

- x112t

+ x203t

- x212t

- x220t


- xl04t

- x114t


+ x2


- x213t


= 0,


- x104at + xl06t


= 0,


- x207t

- x216t


= 1,


- x115t

+ x206t

- x215t


for all t


- xl07t


for all t


+ x209at

- x217t


- x108t


=1,


- xll0t


. ..


- x209bt


x218t


Note that x220t


= x220t_1 + x115t, for all t


= 1, ..., T.


Hence, the system of 2T balancing equations can be written as a

single equation of the form

T


x220T-


= x2200 +


xll5t, or


- x211t

- x219t


* a s











This equation,


however,


is the eighteenth equation of the activity


system.


Hence


, the balancing equation is already represented and may,


therefore, be disregarded.














CHAPTER III

THE OBJECTIVE FUNCTION AND THE CONSTRAINT SYSTEM


The Objective Function


The management control

to maximize an objective func


system to be formulated will


:tion from within the system.


not attempt

It will be


assumed that the user of the

by attempting to control the


stem will


variables


control


the maximization process


in such a manner


as to maximi


whatever goal


user of the


tem attempts


to achieve.


The obj


ecti ve


function offered in this


study will


serve


trictly as a measure of


accomplishment and i


therefore not an interdependent element of the


mathematical


time tha


formulation of the system.

t, though the system extend


It must also be pointed out at


Ids over the planning period T


tem variables will


not interact


simultaneously over the


T time periods.


The simulation of the activities will


be carried out sequentially by


beginning the


simulation process with period 1


and stepping it through


the simulation, one time period at a time, until


the specified planning


horizon has been arrived at under manager control.


The specification of an objective function i


in support of the


simulation process and does not influence the simulation because

choice of the variables to be included in the objective function.


of the

The


objective function variables could easily be changed without affecting












For the purpose of thi


study, consider the following.


Maximize the sum of all net incomes on common stock equity for all


planning periods t


= 1,


. .


T projected to the planning horizon T.


Maximize


= (l + g)T-l


x1131 + (1 + g)T


x1132 +


+ (1 + g) xll3T-1


+ xl13T.


Maximize


(1 + g)T-t


xl13t,


where g represents the rate of return which determines the value of


all net income streams at the planning horizon T.


Hence, g is the


rate of return which the manager requires as a minimum.

It should be noted that the maximum horizon value differs from


the maximum present value only by a constant c as

identity:


(1 + g)T


1
(1 + g) t


hown by the following


where c


= (l + g)T-t


for t


= 1,


Consider the following identity.


xl1 t


- xlOlt


- x102t

- xllOt


- x103t

- x112t


104t


- x104at + x106t


- x107t


- x108t


x220t


- x220t_1


= x115t


= x101t


- x102t


- xl 03t


- x104t


- x104at


'' '1 .*n


, n-


=(l+g)T


r(~h


Inr


r










x220t


- x220t-i=


x113t


- x114t.


Hence,


113t


objective


= x220t

function


- x220t_1


can now be


x114t.


written


Maximi ze


Applying


(x220t


distributive


- x220t-1


this


+ x114t).


becomes


Maximize


(x220t


- x220t ,)


x114


Consider


function


(x220t


- x220tl).


Applying


distributive


again


expanding


summation


results


= cI


x2201


x2202 +


... + CT-22X220T-_2


CT....


x220T-_1


x220T


-Cl


x2200


- c2


x2201


- c3


x2202-


- CT-1


x220T


- cT


x220T_1


Upon


collecting


like


terms,


can now be


written


x2200


- c2)


x2201


+ (c2


- c3)


x2202


+ (CT-1


- cT)


x220T.


C1


+ (C1











- ct+1


- C


g)T-t


T-t-l
+ 9)


= C


+ g)T-t

+ g)T-t


- (1 +

(l + g)


+ T-t-
+ 9)


- ct+1


= g ct+1*


Substituting


above


= -cl


we obtain


x2202


x220T_1


Adding


subtracting


terms


CT+1


x 220T


does


change


value


-c-C


x2200


x2201


x2202


x220T_1


x220T


- CT+1


x220T


CT+I


x220T


Recall


that


- CT+1


CT+1'


Hence,


can be


written


aacC1


x2200


Ct+l


x220t


CT+1


x220T.


Since


ct+l


=0


= -c


x2200 +


CT+1


x220T


+ 9)


r


t x220t.
L t













x2200


+ g)


+ g)


x220T


+ g)


x2200


+ g)


x220T


+ g)T


x2200


+ x220T


x220t.


objective


Maximi


function


+ g)T


now takes


-1x2200


on th


form


+ x2


x220


114t


since


cons


tant


active


function


can be


written


as Max


= Max


0 where


Maximi


+97)


+ g)T-t


114t]


220T


+ x114T,


system of


Financial


Ratio


standard


feedback


control


tem will


form of


' a
, n~nj-~


a c~ l Innn nl ,n.n ., r rt'


... '.1


t (1


+ g)T


x220 t


+ g)T


+


+ g)T


+ g)i


x220t


1 nl.r~u


CiniinrlF


I H-n / I


~nrr


FyI r*ify*


I W











Because of the interdependent nature of the financial


system and


the corresponding difficulty inherent in this system for measuring the


activity


level


and controlling the


team's performance, a measuring


device i


necessary which permits a comparative analysis of all


variable


The financial


ratio was chosen for that purpose.


In particular,


financial


ratios will


utilized for the following


specific


purposes:


to permit the manager to set standards which become decision

making criteria;


to be used as an analytical


vehicle for sensitivity testing


and the


identification of those variable


which require


special


attention of the manager because of their weakness


in supporting desired activity

to test the standards themselv


level


against each other to


determine the


sensitivity of the self-imposed


standards


relative to desired financial


objectives.


It must be made clear that the financial


ratio


are not to be


considered as


andards which are sol


they are met or they are not met.


1y used in a dichotomou


These


ratio


fashion:


serve as catalysts in


the sensitivity testing of the system and are sol


ely an aid in identi-


flying variable


which require


specific management attention.


Therefore,


the ratios must be subject to change as well


as the financial


data which


are tested against the ratio standards.


Hence


, the manager must have the











The nature of the ratios becomes,


therefore, strictly a function


of the manager's objective and can be either industry or historical


standards.


The ratios are not an end in themselves.


Instead,


they are


the vehi cl


which permit the testing of the sensitivity of variables


in relationship to other variables


identify as


It i


s, therefore, desirabi


large a number of such relationships


ratios as possible in order to meet th


cation of the system of ratios


in terms of financial


requirement for the


which represents


identifi-


simultaneous system


of interaction


among all


financial


variable


manager, however


retains control


over each desired ratio by controlling its sensitivity


to each standard.


until


Thi s


a particular ratio i


accompli


hed by changing the ratio standards


forced into the set of


sensitive ratios


without


loosing sight of the objective function.


Hence, a given finan-


cial


ratio may be made inoperative or may be forced to dominate all


other ratios in the sensitivity analysis at the option of the manager.


The constraint system will


consi


st of twenty-eight financial


ratios,


the definitions of which,


LIQUIDITY RATIOS:


in addition to their bounds, are given below.

CRITERIA OF FINANCIAL SOUNDNESS


Current Ratio:

Current Assets


Current Liabilities

x204
x214


Quick Ratio




51





Inventory to Working Capital:


Inventory
Working Capital


x204


- x214


Cash to Current Assets:


Cash


Current Assets

x201
x204

Cash to Total Assets:


Cash


Total Assets

x201
x210


Current Assets to Total


Assets:


Current Assets >
Total Assets

x204 >
x210

Gross Plant to Total Assets:


Gross Plant <
Total Assets ~

x206 <
x210

Net Plant to Total Assets:


Net Plant
Total Assets




52






Current Liabilities to Total Assets:


Current Liabilities
Total Assets

x214
x210


LEVERAGE RATIOS:


MANAGEMENT DECISION CRITERIA


Debt to Total Assets:


Total Debt
Total Assets


x214 + x215 + x216
x210


Times Interest Earned:


Income before Interest and Taxes


Interest Charges


x105 + x106


- x107


x108

Current Liabilities to Net Worth:


Current Liabilities


Net Worth


x214


x218 +-x219 + x220


Fixed Assets to Net Worth:


Fixed Assets


Net Worth


x208
x218 + x219 + x220


Depreciation to Gross Plant:











Dividend Payout Ratio:


Dividends on Common
Net Income on Common


x114 > b15
xl13.

Capital Expenditure to Gross Plant:


Change in Gross Plant
Gross Plant at time t-l


x206t


- x206t_-
206t_1


ACTIVITY RATIOS


Cash Velocity:


Sales >
Cash

x101 >
x201 -

Inventory Turnover:


Sales


Inventory


xl01
x203


Fixed Assets Turnover:


Net Plant


xl01 > UI
x208

Average Collection Period:











Total Assets


Turnover:


Total Assets

x101
x210


PROFITABILITY RATIOS:

2. Gross Operating Margin:


Gross Operating Income


x101


- x102


xl01

let Operating Margin:


Net Operating Income


x105
x101


Sales Margin:


Net Income
Sales

xll1


Productivity of Assets:


Net Operating Income
Total Assets


x105


- Taxes


- xllO


x210


Return on Net Worth:


hl~r ._ Y rs. r.t. r. .












Operating Income to Net Plant:


Net Operating Income
iet Plant


x105
x208


Operating Expense Ratio:


Operating Expense
Sales

x102 + x103


x101


The system of twenty-eight constraints per time period representing

the financial ratios is written in the following form.


x204t


- b1 x214t


. x204t


- x2


- b2 x214t


x203t

x201t

x201t

x204t

x206t

x208t

x214t


- b3 x204t + b3 x214t

- b4 x204t

- b5 x210t

- b6 x210t

- b7 x210t

- b8 x210t

- b9 x210t


x214t + x215t + x216t


x105t+ xl 06 t


- x107t


- blO x210t

- b11 x108t


x2l4.,


- bl


x2l8,.


- bl


x219L


- bl


x220.


.


.










x2O06.


- b16 x206t _-


- x206t_1


xl01lt b17 x201t
xl01lt b18 x203t

xlOlt b19 x208t

360x202t b20 x1l01t

xlO1t b21 x210t


(1-b22)x101t


- xl02t


- x103t


x10 5t
xlI

x105t

x113t

x105 t


- b23 x 101 t
- b24 xlOt101


- xllOt


- b26 x218t
- b27 x208t


- b25 x210t


- b26 x219t


- b26 x220t


x102t + x103t


- b28 xlOl0


for all t=1,


x105t

xl 09 t


x113t


= xlOlt

= x101t


= xl 01t


- x102.t

- x102t

- x108t

- x102t

- x108t


- x103t

- x103t


- x103t

- xllOt110


- x104t

- xl 04t


- x104t

- x112t


- xl 04a t


- x104a t + xl 06t


- x104at + x106t


x204t

x208+


= x201t + x202t + x203t


= x206+


- x207+


Substituting


- x107t


- xl07t











x21O.t


= x201i ,


+ x202t


+ x203t + x205t


+ x206


- x207t


+ x209at


- x209bt


x214t


= x211t + x212t


we obtain


x201t + x202t


+ x203t


- blx211t


- blx212t


- blx213t


x201t


+ x202t


- b2x211t


- b2x212t


- b2x213t


- b3x201t


- b3x202t + (1


- b3) x203t


+ b3x211t


+ b3x212t


+ b3x213t


- b4) x201t
b5) x201t


- b4x202t
- b5x202t

+ b5x207t


- b4x203t
- b5x203t

- b5x209at


- b5x205t


- b5x206t


+ b5x209bt


b6) x201t + (1


- b6) x202t + (1 -b6) x203t


- b6x205t


- b6x206t + b6x207t


- b6x209at + b6x209bt


- b7x201t


- b7x202t


- b7x203t


- b7x205t + (1


- b7) x206t


+ b7x207t


- b7x209at + b7x209bt


- b8x201t


- b8x202t


- (1


- b8x203t


- b8) x207t


- b8x205t + (1


- b8x209at


- b8) x206t
+ b8x209bt


- b9x201t


- b9x202t


- b9x203t


- b9x205t


- b9x206t


+ b9x207t- b9x209at + b9x209bt


+ x212t


+ x211t


+ x213t


- blOx201t


- b10x202t


- b10x203t


- b10x205t


- bl0x206t


+ x213t


- -- -


- -









xlOlt


- x102t


- x103t


- x104t


- x104at + x106t


- x107t


- b11x108t


x211t + x212t + x213t


- b12x218t


- b12x219t


- b12x220t


x206t


- x207t


- b13x218t


- b13x219t


- bl3x220t


xl04t


- b14x206t


- bl5xl01t + bl5x102t + bl5x103t + bl5x104t + bl5x104at

bl5x106t + bl5x107t + bl5x108t + bl5x10Ot


+ bl5x112t + x114t


x206t

xl 01t

xlOlt

xl 01t


- (1 + bl6) x206t_1

- b17x201t

- bl8x203t

- b19x206t + b19x207t


- b2Ox10lt + 360x202t


xl 01t


- b21x201lt


- b21x202t


- b21x203t


- b21x205t


- b21x206t + b21x207t

+ b21x209bt


- b21x209at


- b22) xlOl1t

- b23) xlOlt

- b24) x101t


- x102t

- x102t

- xl02t


- x103t

- xl 03t

- x103t


- xl 04t

- x104t


- x104at

- xl 04at


xl Olt


- x102t


+ x106t

- x103t


- b25x202t

+ b25x207t


- x107t

- xl 04t


- x108t

- x 104at


- b25x203t


- xllOt

- xllOt


- b25x205t


- b25x201t

- b25x206t


- b25x209at + b25x209bt


xl101t


- xl 02t


- xl103t


- x104t


- xl04at + xl06t


- x107t










xl 01t


102t


- x103t


- xl 04t


- xl04at


- b27x206t


+ b27x207t


- b28x101 t


+ x102t


+ xl 03t


T constraints for the capital expenditure to gross plant ratio


(number


16) can be simplified into one constraint equation


x206t


- (1 + bl6) x206.tl


for all


t=1,


Rewriting the constraint, we obtain


x206t


1 (1 + b16) x206t_O1


for all


t=1,


(1 + bl6) x206t_-1


substituted for each occurrence of x206t


in the


system of T


constraints,


the inequality requirements are not violated


and we obtain


x206T


z (l


+ b16)T


x2060.


Mathematical


Formulation of the


Entire


system


The financial


system can now be formalized and financial activities


can be combined with the formulation of the objective function and the


constraint system to result in the mathematical


representation of the


management control


Maximi


system


imulator to be implemented in th


[g(l + g)T-t-1


x220t


+ (1 + g)T-t


next chapter.

x114t]


+ x220T


+ x114T


subject to

T


x211,.


x308..


= x211,


. .,


. .


+ C










x310


= x2160


x302t


x202T


d9x101t


(xlOlt


x202t


- x302t )


x203- +


(xl 2


- x316t


- x317t)


= x2030


x205T


x303t


x207T


xl04t


= x2050


= x2070


x212T- +


(x301t


x213T


(x10t


- x316t)


- x307t)


= x2120


= x2130


x201T +


( x O 3t


- x106t
- x302t
+ x304t
= x2010


+ x107t
+ x303t
+ x311t


+ xl08t
+ x307t


+ x112t
+ x308t


+ x114t
+ x309t


- x312tx313t- x314tx315t


+ x301t
+ x310t
+ x317t)


x209bT


xl04at


= x209b0


x216T +


= x2020


= x2020











x209aT


x311t


= x209a0


x312tx31 3t


= x2170


x218T


d11x314t


= x2180


x219T


(x314t315t- d11x314t)


= x2190


x220T


(x101t


- x102t

- x108t


- x103t

- xllOt


- x104t

- x112t


- x104at + x106t- x107t


- x114t)


= x2200


x204t

x208t

x209t

x210t
x214t


- x201 t


- x202t


- x203t


- x206t + x207t =

- x209at + x209bt


- x204t

- x211t


- x205t

- x212t


- x208t


- x209t


- x213t = 0


x210t


- x214t


- x215t


- x216t


- x217t


- x218t


- x219t


- x220t= 0


- x201 t

- x201,


- b3x201t


- ci


ci


- x202t
- x202t


- x203t + blx211t + blx212t + blx213t + slt


+ b2x211t


- b3x202t

+ b3x212t


- b4) x201t

- b5) x201t


+ (1


+ b2x212t
- b3) x203t


+ b3x213t


+ b4x202t
+ b5x202t


+ b4x203t
+ b5x203t
L- r-nr--m


+ b2x213t
+ b3x211t


+ S2t


+ s3t
+ s4t


+ b5x205t
* L /n


x217T










- b6) x201t


- (


- C,


- b6) x202.t


- C,


- b6) x203t


+ b6x205t + b6x206t


- b6x207t


+ b6x209at


- b6x209bt


+ s6t


- b7x201t


- b7x202t


- b7x203t


- b7x205t


- b7) x206t + b7x207t


- b7x209at


- b8x201t


+ b7x209bt
- b8x202t


- b8x203t


- b8x205t


- b8)


x206t


- Cl


- b8) x207t


- b8x209at


- b9x201t


+ b8x209bt
- b9x202t

+ b9x207t


+ s8t


- b9x203t


- b9x205t


- b9 x209at + b9x209bt + x211t


+ x212t + x213t


+ s9t


- bl0x201t


- bl 0x202t

+ bl 0x207t


- blO0x203t


- bl 0x205t


- blO0x209at + blO0x209bt


- bl 0x206t


+ x214t


+ x215t + x216t


10t= 0


- xl01t + x102t + x103t + x104t +


xl04a t


- x106t


+ x107t + b1x108t


x211t + x212t + x213t


- b12x218t


- b12x219t


- b12x220t+ sl2t= 0


x206t

xl04 t


- x207t


- b13x218t


- bl3x219t


- bl3x220t


- bl4x206t


+ s13t= 0

+ sl4t= 0


+ bl5x1014t


- bl5x1 02t


- bl5x103t


- bl5x104t


- bl5x104at + bl5x106t


- bl5x107t


- bl5x108t


- bl5xll0t


- b15x112t


- x114t


+ sl5t= 0


+ s7t


- b9x206t


11t= 0


+ (1









- xlOlt

- xlOlt


- xlOlt


- b20x101t


+ bl7x201t

+ b18x203t


+ b19x206t


17t= 0

18t= 0

19t= 0


- b19x207t


360x202t


+ s20t= 0


S- xlO1t


+ b21x210t

+ b21x206t


- b22)

- b23)


xlOlt

xlOlt


+ b21x202t

- b21x207t


+ x102t

+ x102t


+ b21x203t

+ b21x209at


+ x103t

+ x103t


+ b21x205t

- b21x209bt


+ s21t= 0

+ s22t= 0


+ xl 04t


+ x104at


+ s23t= 0


- (1


- b24) xlOlt


- x106t


+ x102t

+ x107t


+ x103t

+ x108t


+ x104t

+ xllOt


+ x104at


+ s24t= 0


- xlOlt


+ x102t


+ x103t


+ x104t


+ x104at


+ xllOt


+ b25x201t


+ b25x206t


+ b2


+ b25x203t

+ b25x209at


- b2


+ b25x205t

- b25x209bt


+ s25t= 0


- xlOlt


+ x102t


+ x107t


+ x103t

+ x108t


+ xl04-t

+ xllOt


+ x104at

+ x112t


- x106t


+ b26x218t


+ b26x219t


+ b26x220t


+ s26t= 0


- xlOlt


+ x102t


+ x103t


+ x104t


+ x104at


+ b27x206t


- b27x207t


- b28x101t


+ x102t


+ s27t= 0

+ s28t= 0


+ x103tl


for all


4. ~


The above system of fifty-three equations extending over the plan-


ning


period


T must now be incorporated into a computer based model.













CHAPTER IV

THE MAN-MACHINE MODEL


System Definition


The mathematical


model


specified in Chapter


III represents a set of


relationship p


that react and/or interact with the


conditions imposed by


the user of the system and the conditions imbedded within the system in


the form of a set of financial


ratio standards.


The model


is fully


deterministic and does not rely on probabilistic procedures.


Further-


more,


model


dynamic because


simulation outcomes are time dependent.


As such,


model


has been incorporated into a computer system


which


serves


ning and


as a management decision tool


control


With respect to financial


in financial


management plan-


planning, Johnson


(1959, p. 53)


points out that "


...plans must fit th


financial capability of the concern."


He goes on to say that "the financial


manager must therefore know how to


go about analyzing the concern's position and estimating its capabilities.


The proposed model


has thi


financial


planning and control


process


its object.


Emphasis i


however, placed on examining the interdependent


nature of the model


imulator to determine the reactions from introducing


the financial


plan of a


specific operational


level


into the model.


process of arriving at the


over a five-year period,


latter plan,


a plan for doubling sales


not included in the simulation.


The model











firm's capability for achieving thi


specific goal.


Hence


, the necessity


for making other planning studies


in the organization remains, and the


model


simulator can trigger other


of decision making.


simu-


lator will


attempt to discover what is necessary to meet a


pecified


target, but


leaves the


task of how to reach this


target to the correspond-


ing organi

the model

level mana


zationa

serves


1


unit such as the


both the planning and th


iger because it


seeks to establish


department.


control


compati


In this respect,


function of the top

ability of all sub-


analyses


with the entire financial


system and activity


of the firm.


Individual


plans are brought together and are then tested


strategy underlying the use of the model


then becomes


imul taneously.


the following


two-step procedure:


specific plan is


introduced into the model.


The plan is


tested to determine if it i


with respect to all


other financial


feasible


activities and the


financial


position of the firm.


A prerequisite for the


effective simulation is that the model


represents the real


world


, that is,


the actual


financial


activities and


position of th


firm


and that the model


an be used to


test this


tate


of reality.


For thi


reason


, abstract relationships


have been avoided


whenever possible.


When simulating the financial


system of the firm,


manager is


faced with making interdependent deci


sions


in a dynamic


environment








translated into FORTRAN code which,


handling,


in combination with


report generation and conversational


represents the programming


tem.


input data


interaction procedures,


In implementing the computer


programs, emphasis


was placed on developing all


procedures in


such


fashion that deci


sion making by exception could be employed by the user


of the system.


In other words


, the assumption i


made that all data


stored in the computer at any given time become the input to the current


period


simulation process


unless the decision maker intervenes and


changes any or all data which become input to the


simulation process


Furthermore,


the computer system offers th


flexibility to the decision


maker of repeating the


imulation of a given planning period as many


times as he desires without affecting the overall


result of the


imulation


process.


The manager can


therefore


make a


ingi


decision, cause the


system to simulate a planning period based on th


ingle decision and hold


all other variabi


xed.


gives him the ability to test the


sensitivity of this


single deci


ion on the entire operating pro


cess


the resultant financial


position of the firm at the end of that time


period.


The general


system flow is depicted in Figure 4.1.


Initially


, the


balance sheet data for the time period immediately preceding the first


simulated planning period are fed into the computer.


Hence,


simulation process will


be based on the actual


financial


position of the


firm


to be simulated.


Secondly,


the computer program


logic requires


that all decision values,


exogenous


variable data and financial


ratio





























CHANGE
ARIABL


CHANGE
VARIABLE
I


REPEAT
THIS
PERIOD


STOP


MULATI
?


LOAD
FINANCIAL POSITION DATA
FOR BASE PERIOD
INITIAL DECISION VALUES
EXOGENOUS VARIABLE DATA
FINANCIAL RATIO STANDARDS


PERFORM


SIMULATION


ADVANCE
TIME PERIOD
BY 1




68





because they are subject to change and can be modified by the user of


the system prior to the execution of the


simulation for the first


planning period.


Indeed,


the next


tep in the


logic is the


question by the computer to the deci


ion maker if the user of the system


desires to change any or all


variabi


exce


pt the


data representing the


balance sheet for the base period.


made by the decision maker


After all


desired changes have been


simulation of the financial


activities


of the firm goes


into effect.


The next step offers the user the


opportunity to repeat the


simulation process


for the current period.


The purpose of the repeat i


to change one or more variabi


determine the outcome of thi


change on the financial


operating results


of the firm as well


as the result in the financial


position


If the


decision is made not to repeat the


simulation of the present period,


the user has now the opportunity to terminate the entire simulation


process


An alternate decision at this point is


to advance to the next


planning period and repeat the


simulation process for the following


planning period


A given planning period c


as desired and as many planning periods a


an be repeated as

are desired can be


many times


simulated


sequentially


Hence,


the decision maker has the opportunity to extend


the planning horizon over as many planning periods as he wishes.


The Input/Output Elements of the System


The input to the simulation process consists of three types of


data:










manager controlled variables, and

computer controlled variables.


The simulation process produces the following outputs:


input decision comparisons


the value of the objective function

the sensitivity analysis,


schedule of changes


in working capital,


statement of


sources


and uses of funds,


the income

the balance


statement,


heet,


a comparative


analysis


of income statement and balance


sheet activity

the financial


es, and

ratio analysis.


The manager controlled variab1


require specific enumeration


because they are subject to


the manager's rational


decision making.


The manager controlled variables consist of the following major types

of variables and their respective elementary variables:


All exogenous variables


financial


ratio standards


Income statement variables:


Cost of Goods Sold

Selling and Administrative Expense










Other


vari


able


Purchase


Sale)


Securities


Purchase


Sale)


Fixed


Asset


Nonoperating


Income


other


than


Intere


Earn


hort


Term


Loan


Payment


on Principal


Receipt


Loan)


Long


Term


Debt


ubordinated


Payment


on Principal


Receipt


Loan)


Long


Term


Debt


ubordinated


Payment


on Principal


Receipt


Loan)


Acqui


ition


ale)


Intangibi


sset


Number of


Additional


Preferred


tock


. Number


Additional


hare


Common


tock


Price


hare


Common


tock


. Production


Other


on Trad


Production


Credit


enses


input/output


element


are pictured


Figure


4.2.


statu


imulation


process


repre


given


time


value


current


simulation


period


financial


position


period.


addition,


tatus


previous


imulation


cycle


preserved which


or may


previous


planning


period.


tern will


always


serve


financial


position


prevlou


planning


period


order


determine


financial


position


planning


period.


purposes


performing


sens


itivity


analyses











































C.,)
LU~

CE


L


LU
0S1-

Cu
en,


00-i~
LU PCfl
oor c
>CLJ


I


r










simulation cycle as well


as the outcomes of the previous simulation


cycle.


None of these data are saved permanently.


The only data that


are saved permanently in the computer are the base period balance


sheet,


the initial


financial


ratio standards


initial


exogenous decision


variable data,


the initial other variable data and the initial


income


statement variable data which are al


The financial


o manager control


data which identify the position of the firm at the


beginning of the first simulation period are identified and illustrated


in Figure 4.3.


The balance sheet for the base period thus becomes the


tarting point for the simulation of financial


activities over the


planning period.


An illustration of the exogenous variabi


stored in the computer


is given in Figure 4.4.


illustration


identifies the types of


exogenous variables as well as examples of the initial


input for these


variables.


The input decisions consist of six income


statement variables and


thirteen other variables.


The input decision variable


are illustrated


in Figure 4.5.


They are initially stored in the computer for the sole


purpose of having a set of input decision data but are subject to change


prior to initiating the


simulation for the first planning period.


The change of variable process


depicted in Figure 4.6.


First,


the decision maker has the choice of changing an input decision or leaving


it as it was at the time of the


last simulation process.


The values of















BALANCE SHEET AS OF 12-31-69


(AMOUNTS


1000000.)


CASH AND EQUIVALENTS
ACCOUNTS RECEIVABLE
INVENTORIES
CURRENT ASSETS
SECURITIES
GROSS PLANT
DEPRECIATI ON
NET PLANT
GROSS INTANGIBLE ASSETS
AMORTIZATI ON
NET INTANGIBLE ASSETS
TOTAL ASSETS


CURRY PREV
% %
12 12
17 17


SALE
%
10
15
4
29
0
66
8
58
0
0
0
87


8.
0.
8.
4661.


LOANS PAYABLE
ACCOUNTS PAYABLE
TAXES PAYABLE
CURRENT LIABILITY
LONG TERM DEBT U
LONG TERM DEBT S
PREFERRED STOCK
COMMON STOCK
PAID IN SURPLUS
RETAINED EARNING
TOTAL LIABILITIES


IES
SUBORDINATED
UBORDINATED



S
S AND NET WORTH


33.
533.
313.
879.
0.
459.
0O
272.
1039.
2012.
4661


Fig. 4.3.


The balance sheet for the base period.
















EXOG. VARIABLES



RATE OF INTEREST


RATE
SCALE
RATE
RATE
INTER
INTER
RATE


HAT
RAT
PAR
NO.
NO.


OF DEPRECI
FACTOR FO
OF AMORTIZ
OF INTEREST
EST RATE L
EST RATE L
OF PAYMENT


E OF RECEIP
E OF PAYMENT
VALUE OF C
OF SHARES
-OF SHARES


THE YEAR ENDING


EARNED ON


ATI
R D
ATI
T O
ONG
ONG
ON
ON
ON


ON
DOLLAR
ON


N
T
T


LOANS
ERM DE
ERM DE
ACCOUNT


ACCOUNT
TAXES


SECURITIES


AMOUNTS


12-31-69


0.0700


1000000.


BT UNSUBORD.
BT SUBORD.
TS PAYABLE
TS RECEIVABLE
PAYABLE


MMiON STOCK
F COMMON OUTSTANDING
F PREFERRED OUTSTANDING


BASE YEAR


5.0000
54.4482
0.0000
69.0000


Fig.


4114.


Exogenous variables.
















INPUT


DECISIONS


THE YEAR


ENDING


12-31-69


(AMOUNTS


1000000.)


SALE
COST
SELL
NONO


S
OF GOODS SOLD
ING AND ADMINISTRATIVE EXPENSE
OPERATING EXPENSE


DIVIDENDS ON PREFERRED STOCK
DIVIDENDS ON COMMON STOCK
PURCHASES(SALE) OF SECURITIES
PURCHASECSALE) OF FIXED ASSETS
NONOPERATING INCOME OTHER THAN


SHOR
LONG
LONG
ACQU
NO.
PRICE
NO.
PRICE
PROD
OIHE


T
TE
TE
IS
OF
E/,
OF


TERM LOAN
RM DEBT U
RM DEBT S
ITIONCSAL
ADD. SHA
SHARE OF
ADD. SHA


E/SHARE
AUCTION


OF
OST


PAYMEi
NSUBOR
UBORD.
E) OF


RES
PRE
RES
COM
ON


PRODUCTION


OF
FER:
OF
MOTi
TR


NT
D.


ON PRI


PAYM.


5345
2060
1114
0
0


INTEREST
NCIPAL


PRINC.


PAYM. TO PRINCE.
INTANGIBLE ASSETS
PREF. STOCK
RED STOCK
COMMON STOCK
STOCK
ADE CREDIT


EXPENSES


2000.


Fig. 4.5.


Input decisions.






76






DO YOU WISH TO CHANGE A VARIABLE
?YES

TO IDENTIFY TYPE OF VARIABLE OR END OF CHANGE TYPEt


NONE,


E1XOGi


RATI


INCO0 OR OTHER


VARIABLE TYPE
70THE

VARIABLE NO.
716


VALUE


?120


PRODUCTION COST ON TRADE CREDIT 1200.0000 TO


120.0000


-89%


VARIiABLE TYPE
?OTH

VARIABLE NO.
?17

VALUE
?100


VARIABLE TYPE INCORRECT


- TRY


AGAIN


VARIABLE TYPE
? OTHER

VARIABLE NO.
717

VALUE
?-100


OTHER PRODUCTION EXPENSES


2000.0000 TO


100.0000


-94%


VARIABLE TYPE
?NONE




77






If the user decides to change a variable, he must identify the type


of variabi


he wi


to be modified, which variable within th


to change and the new value of this variabi


specified type


In respon


input,


printing th


the computer will


description of thi


identify th


variable,


changed variable value


the value of the variable


prior to the


previous value.


change,


new value and the percentage change from the


The decision maker now has a record of his deci


Upon completion of a simulation cycle


, the computer will


ion.


print


the value of the objective function which


value of th


income on the common stock equity extending to the planning horizon.

The planning period covers the time period from the base period to the


planning horizon


itself.


Figure 4.7


depicts the printout produced by


the computer reporting the new value of the objective function.


Before the computer produce


completed simulation cycle


financial


the financial


reports covering the just


ratios are identified which have


been exceeded in the current


simulation.


These financial


ratios are


ranked by the percentage deviation of the actual


ratios from the financial


ratio


standards.


Hence


in relative terms


the ratio with the most severe


percentage deviation will


be printed first.


least sensitive


ratio


will


be printed last.


technique of ranking sensitive ratios does not


guarantee that th


ratio with the greatest deviation is the most critical


ratio encountered in the simulation.


This


is not possible because no


quantitative technique is available for ranking the ratios


in thi


manner.






















BEGINNING


12-31- 69*


VALUE OF THE NET


INCOME


ON THE COMMON


STOCK


EQUITY


COVERING


A PLANNING


PERIOD


YEARS


THROUGH


12-31-70


944.


The value of the objective function.












the decision maker in analyzing his performance.


Hence,


the relative


important


of the


ratios


not considered directly.


Rather


, a warning


initiated i f


standards are violated, and this call


for the objective


evaluation by the manager.


Aside from ranking those financial


constraint


ratios which exceed the ratio


the sensitivity analysis will also rank those ratios which


satisfy the ratio constraints by more than a


specified percentage


level.


ranking gives


the manager the opportunity to identify those ratios


which do not reach significant sensitivity


evel


because


of the


standards specified.


In conjunction with the identification of those financial


ratios


which have been violated, or which sati


sfy standard


by more than a spec-


ified percentage,


the sensitivity analysis


identi fie


corresponding


variables which constitute th


definition of the ratio in question


(Fig.


4.8)


Furthermore,


the sensitivity. analysis


determines from the


financial


value

rati o


sensitivity ratio matrix


should be


(Tabl


increased or decreased in order to


standard constraint


4.1) whether the given variable


fy the financial


The numbers printed next to these


recommenda-


tions identify the ratio to which this


The first financial


schedule of changes in working capital


recommendation relates.


reports produced by the simulator are the


and the statement of sources and


uses of funds


(Fig.


4.9 and 4.10)


Tkn nn at .C4 n-nn n: ,1


tann-q,-t 4


j- i~ a( nt-n~ CE. .-, Vt Jn 4l -


4. -l +4.In*


*E~r *Nu..1** .1C J-111 ~11rI I.l *1I ttlr tum.llhll.I.










THE FOLLOWING


RATIO(18)
RATIOC16)


RATIOS


HAVE


EXCEEDED BY
EXCEEDED BY


BEEN
262%
100%


EXCEEDED


THE PERCENTAGES


INDICATED:


THE FOLLOWING


RATIO(


RATIOC11)


RATIO(
RATIO
RATIOS
RATIOS
RATIOS
RATIO(
RATIO
RATIO(
RATIO


RATIOC17)


SATI
SATI
SATI
SATI
SATI
SATI
SATI
SATI
SATI
SATI
SATI
SATI


RATIOS


SATI


SFIED


SFIED BY
SFIED BY


SFIED


SFIED BY


SFIED
SFIED


SFIED BY
SFIED BY
SFIED BY
SFIED BY
SFIED BY


SFY STANDARDS
5040%
2700%


BY MORE THAN


100%:


922%
567%
486%
476%
286%


129%
113%
103%
100%


FOLLOWING


VARIABLES


CAUSE


SENSITIVITY:


SALES


INCR:
DECR:


COST OF GOODS


INCR:


SELLING


INVENTORIES


INCR:


17 22 23 25 26 27
SOLD
22 23 25 26 27


AND ADMINISTRATIVE EXPENSE


INCR:


23 25 26 27


DEPRECIATION


INCR:


AMORTIZATION
INCR: 1
NONOPERATI NG


25 26 27


DECR:
SECURITIES
INCR:


GROSS


PLANT


INCR:


16 25 27


DEPRECIATION


DECR:


GROSS


23 25 26 27


INCOME


DECR:


NONOPERATING


INCR
INTEREST
INCR


FEDERAL AND
INCR:


EXPENSE


ON LOANS


STATE
25 26


5 25 27


INTANGIBLE ASSETS


INCR:


AMORTIZATION


DECR:


LOANS


PAYABLE
INCR: 1


ACCOUNTS


INCOME


PAYABLE


INCR:


TAXES


TAXES


PAYABLE
INCR: 1


DIVIDENDS
INCR:
CASH AND E
INCR:
DECR:
ACCOUNTS R


INCR


ON PREFERRED


STOCK


COMMON


STOCK


INCR:


QUI VALENTS


PAID


IN SURPLUS
INCR: 26


RETAINED


RECEIVABLE


C 0=T


INCR


EARNINGS
: 26


a 1


*




























N



N.



'0 (4 NCM





N



t ('4(NJ
(NJ



- C (N (N (N
('



CINN
N


I- CM M N


- N ('4CM


(NJ


NNC


-i-- N N N N





- -- N N



w-r- ^-csjsj -- -- -- N e-N -('


4--c



---


to,



- r
LL
W.V



00



)4)


~- N N IU Nr N N


NNN















FORMA SCHEDULE OF CHANGES


IN WORKING


CAPITAL


THE YEAR ENDING


12-31-70


(AMOUNTS


1000000.)


CHANGES


IN CURRENT


ASSETS


CASH AND
ACCOUNTS


EQUI VALENTS
RECEIVABLE


INVENTOR ES


-1840.


TOTAL


CHANGES


LOANS


ACCOUNTS
TAXES PA


279.


IN CURRENT LIABILITIES


PAYABLE


PAYABLE


YABLE


-313.


TOTAL


-834.


WORKING


CAPITAL CHANGE


1113.


Fig. 4.9.


Pro forma schedule of changes in working capital.















FORMA STATEMENT
THE YEAR ENDING


OF SOURCES AND USES OF
12-31-70 (AMOUNTS X


FUNDS
1000000.)


SOURCES


NET INCOME
DEPRECIATION
AMORTIZATION
LONG TERM DEBT


944.
310.
2.
0.


1255.


TOTAL



USES


S PLANT
S I MTANG
DENDS ON
DENDS ON
ING CAPI


INCREASE
IBLE ASSET
PREFERRED
COMMON ST
TAL INCREA


INCREASE
STOCK
OCK
SE


TOTAL


Fig. 4.10.


1255.


Pro forma statement of sources and uses of funds.











each income


statement variable for the indicated planning period.


addition


report also prints the percent of sal


e for all


variabi


from the previous


imulation cycle


last column


reports the per-


centage changes


in the dollar values of the income statement variabi


from the previous


simulation cycl


to the current simulation cycl


should be emphasized again that th


ese comparisons are compare


sons with


the previous


simulation cycle and not with the previous planning period.


Because of these comparisons


the deci


ion maker can analyze the impact


of his decision more readily because h

a change in the input decisions from o

and not necessarily restrict his decis


decision making rests on making


ne simulation cycle to the next


ion making from one planning period


to the next.


The pro forma income statement i


illustrated in Figure 4.11.


The pro forma balance


firm at th


heet reports th


financial


end of the current simulation period.


position of the


report i


hown


in Figure 4.12.


Here again,


the financial


position of the previous


simulation cycle is used as the basis for reporting comparisons.


technique employed i

income statement. T


identical


to that described for the pro forma


he only difference i


in the calculation of the per-


centage relationships between balance sheet variable


Here, percentages


are reported in relation to the total


balance


assets.


last column of the


heet represents a comparison of the balance sheet variabi


with


level of sal


These figures are percent of sales for each balance


.sheet account.
















FORMA INCOME STATEMENT
THE YEAR ENDING 12-31-70


(AMOUNTS


1000000.)


SALES
COST OF GOOD
SELLING AND
DEPRECIATION
AMORTIZATION
NET OPERATION
NONOPERATING


NONOPER
INTEREST
NET INC
FEDERAL
NET INC
DIVI DEN
NET INC
DI VIDEN
NET INC


CURR PR
X


)S SOLD
ADMINISTRATIVE


EXPENSE


INCOME
INCOME


EATING EXPENSE
T ON LOANS
OME BEFORE TAXES
AND STATE INCOME


OME
DS ON
OME ON
DS ON
OME TO


TAXES


PREFERRED STOCK
COMMON STOCK
COMMON STOCK
RETAINED EARNINGS


5345.
2060.
1114.
310.


1859.
0.
0.
44.
1815.
871.
944.
0.
944.
142.
802.


Fig. 4.11.


Pro forma income statement.















FORMA BALANCE SHEET


AS OF


12-31-70


(AMOUNTS


1000000.)


CASH AND EQUIVALENTS
ACCOUNTS RECEI ABLE
INVENTORIES
CURRENT ASSETS
SECURITY ES.
GROSS PLANT
DEPRECIATION
NET PLANT
GROSS INTANGIBLE ASS
AMORTIZATION
NET INTANGIBLE ASSET
TOTAL ASSETS


2668.
802.


ETS


S


6.
4629.


CURRY

58
17
-35
39
0
76
16
60
0
0
0
100


PREV
S


CHG
%
388
0
-967
18
0
0
76
-9
0
0
-19
0


SALE
%
50
15
-30
34
0
66
13
52
0
0
0
87


LOANS PAYABLE
ACCOUNTS PAYAB]
TAXES PAYABLE
CURRENT LIABIL
LONG TERM DEBT
LONG TERM DEBT
PREFERRED STOCK
COMMON STOCK
PAID IN SURPLUS
RETAINED EARN Ii
TOTAL LIABILITY


ITIES
UNSUBORDINATED
SUBORDINATED


33
12
0
45
0
459


272
039


AND NET WORTH


2814.
4629.


Fig. 4.12.


Pro forma balance sheet.










This report is shown in Figure 4.13.


The ratio analysis


lists the


twenty-eight financial


ratios which are utilized in the sensitivity


analysis


report also prints the financial


ratio


standards which


are the basis for determining the ranking of sensitive


financial


ratios.


The actual


ratios determined in the


simulation are printed and their


relationships to the financial


or "greater than" symbol


symbol


ratios are indicated by the "less


An asterisk or a plus


indicating the direction of th


than"


ign preceding the


inequality identifies a ratio


which i


sensitive.


The asterisk


flags


ratios which do not


satisfy


financial


ratio standards


The plus


sign identify


ratios which


sati


fy the


ratio constraints by more than a specified percentage.


The System Logic


The program logic of the management planning and control


is based on the


simulator


interaction of man and machine during the simulation


process.


interaction will


be carried out in the complementary mode,


that is, assignment of tasks in the simulation process


to the user and th


computer will


be such as to utilize the best capability


in the


exec


ution


of the


simulation.


This decision i


based on the assumption that either


the user or the computer repre


sents one of the two mutually completing parts


necessary in the effective


simulation of financial


management decisions.


logic of the simulation i


trictly based on deterministic procedures


and utilizes the computer primarily as an analytical


manipulator for the purposes of accepting input deci


and as a data


sions and presenting





88









RATIO ANALYSIS FOR THE YEAR ENDING 12-31-70


ACTUAL


STANDARD


CURRENT RATIO
QUICK RATIO
INVENTORY TO WORKING CAPITAL
CASH TO CURRENT ASSETS
CASH TO TOTAL ASSETS
CURRENT ASSETS TO TOTAL ASSETS
GROSS PLANT TO TOTAL ASSETS
NET PLANT TO TOTAL ASSETS
CURRENT LIABILITIES TO TOTAL A
DEBT TO TOTAL ASSETS
TIMES INTEREST EARNED
CURRENT LIABILITIES TO NET WOR
FIXED ASSETS TO NET WORTH
DEPRECIATION TO GROSS PLANT
DIVIDEND PAYOUT RATIO
CAPITAL EXPENDITURE TO GROSS P
CASH VELOCITY
INVENTORY TURNOVER
FIXED ASSETS TURNOVER
AVERAGE COLLECTION PERIOD
TOTAL ASSETS TURNOVER
GROSS OPERATING MARGIN
NET OPERATING MARGIN


SALES MARG
PRODUCT I VI
RETURN ON
OPERATING
OPERATING


ASSETS


TH


10.43
'7.10
-.93
1.47
0.58
0.39
0.76
0.60
0.01
0. 11
11.99
0.01
0.68
0.09
0.15
0.00
2.00
3.24
1.92
.4.00
1.15
0.41
0.35
0.18
0.21
0.23
0.67
0.59


LANT


IN
TY OF ASSETS
NET WORTH
INCOME TO NET PLANT
EXPENSE RATIO


.00
*50
*50
.25
.10
.25
.85
.75
.25
.20
*50
.25
*00
.25
.10
.10


4.13.


Ratio analysis.





89





decide on the actions to be taken which initiate the simulation process,


which in turn results


in the presentation of simulated operating results


and the


corresponding financial


position.


Furthermore,


it will


be the


manager's task to react to the


outcome of a


simulation cycle by inter-


preting the results of hi


input decision or deci


sions


and to modify his


decision if an alternate decision is to be tested.


The computer responds


with the feed-back to these


managerial decisions on th


basis of the


simultaneous


interaction of all


financial


variabi


in the


tem.


Hence,


regardless of the type of deci


ion made,


imulator will


test this


decision against all


possibi


functional


relationship


in the


tem and


alerts the user to areas which may become ove


r-se


nsitive and require


managerial


logical


attention.


The flowchart depicted in Figure 4.14 represents


basis for the computer program.


steps outlined in the


flowchart are carried out by the computer except that the user is


required


interact for the purpose of deciding:


if a specific status report is


if a given variable i


to be printed;


to be changed


if the


simulation cycle for the


current period is to


be repeated with changes


if the next planning period i


input decision variabi


to be simulated.


The step-by-step outline


of the program


logi


is given below.


Actions


by the computer are indicated by the


letter C and the manager's actions










































YES
I II n i >


ri-


ES


NO



















F~--


YES
---- -->


Fig. 4.14.


(Continued)