an integrated computer-based system for financial and managerial decisions

Engineering Costs and Production Economics, 9 (1985) 291-291 Elsevier Science Publishers B.V., Amsterdam - Printed in The Netherlands

291

AN INTEGRATED COMPUTER-BASED SYSTEM FOR FINANCIAL AND MANAGERIAL DECISIONS

Marilyn Willis and Leila J. Pratt

University of Tennessee at Chattanooga, Department of Economics - UTC Chattanooga TN 37402 (USAl

The purpose of this paper is to develop a model that can be used to make both financial and managerial decisions relating to production in a manufacturing enterprise. To build a model of this type several questions must be addressed. Among the more relevant ones are : (1) What information to capture ; (2) how to build a data base of this captured information; (3) how to use this captured information and (4) how to process this captured information in a form that is useful to both financial and production managers.

Two types of information need to be captured. First, financial accounting information will be needed so that financial statements that meet Generally Accepted Accounting Principles (GAAP) criteria can be produced. Second, managerial accounting information will be needed so that managers can make decisions concerning planning, control and the evaluation of performance. Since this data overlaps, the accounting department can be given the responsibility of collecting all the relevant information. These data would in- clude information on raw materials (both pur- chases and requisitions), labor (both direct and indirect), and all factory overhead costs.

The information described above must now be used to build three data bases (see Table I). The first data base, the Standard Data Base, includes the standards agreed upon by management during the planning phase. These stan-

dards are usually related to capacity utiliza- tion and are formulated for all relevant production variables. Thus, this data base would in- clude information on standard quantities and standard prices for raw materials and direct labor as well as a standard application rate to be used for factory overhead.

The second data base is the General Ledger. It includes the actual quantities and prices for the production variables (raw materials, direct labor and factory overhead). As in- voices for raw materials are received from vendors, the general ledger accounts of raw materials inventory and accounts payable are updated. In addition, as requisitions from production are received the actual prices and quantities of the raw materials used are captured and stored. As time-cards from production workers are received in accounting, the payroll account in the general ledger is updated. Also, total direct labor (actual hours worked multiplied by the actual labor rate) is transferred to the direct labor account. Information on factory overhead is derived from many sources. Utility bills, tax bills, administrative salaries and allocations for depreciation are just a few. As these documents are received, or as information concerning these variables becomes known, the factory overhead account in the general ledger will be updated.

The third data base, the Production Data

0167-188X/85/$03.30 0 1985 Elsevier Science Publishers B.V.

292

TABLE 1

The model

Input variables Data bases

Standard

(based on normal capacity)

Financial reporting

general ledger

Managerial

production

Raw materials

Quantity Price

Direct labor

Quantity Price (rate)

Factory overhead Fixed

Variable

Normal capacity (in units)

Standard

Standard

Standard

Standard

Standard

Standard

Raw materials inventory

Accounts payable Actual

Actual Payroll account

Direct labor

Actual

Actual

Factory overhead

Actual

Actual

Work-in-process

Actual

Assigned

Actual Actual

Applied

rate

TABLE 2

Normal capacity on a monthly basis = 100,000 units of Crinkles

Direct materials

Direct labor

Factory overhead Fixed $100,000 Variable

Standard cost per unit

Standard quantity per unit of Crinkles

2 pounds

1 hour

Standard cost

per unit of Crinkles

$10

$ 6

$1 $3

$20

Base, is actually the work-in-process account that is contained in the General Ledger data base. As the production department requests and receives raw materials, the raw materials inventory account will be relieved and the work in process account will be charged with actual quantities and actual prices based on average, LIFO or FIFO flow of costs. Similar- ly, the direct labor charges from the payroll account is transferred to work-in-process.

Since the actual factory overhead cost is not known until the end of the fiscal year, this variable must be charged to work-in-process based on a standard application rate. At the end of the fiscal year, under or over applied factory overhead is determined and the appropriate adjustment is made in the General Ledger accounts.

The information contained in these three data bases provide all the information needed

293

both for financial and managerial decision making. The General Ledger data base con- tains all necessary data needed by the accounting department to produce acceptable financial statements. Management, on the other hand, can evaluate performance and make future plans by comparing the information contained in the Standard Data Base with the information contained in the Production Data Base.

To illustrate how this model can be used, assume that Evans, Inc. produces a product known as Crinkles. The production and indus- strial engineering staff have established the following standards for Crinkles (Table II). These standards are input by the accounting department and retained in the Standard Data Base.

During the ensuing accounting period, of the month of January, Evans, Inc. had the following activity as recorded by the accounting department.

(a) Purchased 400,000 pounds of raw materials at $2,200,000.

(b) Incurred payroll costs for the period of $600,000.

(c) Incurred actual factory overhead charges of $390,000.

(d) The production department requisi- tioned and was sent 200,000 pounds of raw materials.

(e) A tally of time cards showed $495,000 spent for 90,000 hours of direct labor for Crinkles.

(f) The number of units of Crinkles produced during the month was 95,000.

(g) All units were sold. Since Crinkles is a new product, there were no beginning inventories of raw materials or work-in-process. A selling price, which in ac- cordance with Evans’ policy included a mark- up of 40 percent of absorption costs, $28 (20 X 1.40) per unit was charged. In addition,

operating expenses of $500,000, which included $150,000 of fixed expenses, were incurred.

Table III shows how the information de- tailed above is captured and processed in the appropriate data base. Once the information has been stored the financial statements can be prepared and management can evaluate performance.

There are many other uses for this model. For example the information contained in the three data bases could be combined to produce income statements for financial reporting and managerial analysis (see Table IV), or it could be used to calculate an analysis of variance for raw materials, direct labor and factory overhead which is an essential component needed to make certain managerial decisions (see Table V). In addition, this model can be used to make decisions concerning the acceptance or rejection of a special order. For instance, assume Evans, Inc. receives a bid for 5,000 additional units of Crinkles at a unit selling price of $20 per unit. Since Evans, Inc. is currently operating at 95% of capacity, management is considering accepting the proposal but is concerned that the selling price is only equal to the standard factory cost. To help in making the decision, management can make use of the model to develop several predicted income alternatives using a contribution approach. As can be seen by examining Table VI management would de- cide to accept the order since its operating income would be increased.

The above has only touched on ‘a few of the many applications of this model and its accompnaying data bases. This model can easily be used in financial and managerial decision-making processes by any sized manu- facturer, from the large multinational firm to the small sole proprietorship.

TA

BL

E 3

The

cap

ture

an

d pr

oces

sing

of

var

iabl

es i

n th

e da

ta b

ases

Dat

a ba

ses

Stan

dard

(b

ased

on

100,

000

units

)

Qua

ntity

Pr

ice

unit

per

unit

per

unit

pric

e T

rans

actio

n

Gen

eral

led

ger

(in

thou

sand

s)

Prod

uctio

n w

ork-

in-p

roce

ss

Acc

ount

A

mou

nt

Com

puta

tion

Qua

ntity

Pr

ice

Tot

al

Raw

mat

eria

ls

2 po

unds

$5

Dir

ect

labo

r 1

hour

$6

Fact

ory

over

head

-

fixe

d va

riab

le

Fixe

d am

ount

=

$10

0,00

0 10

0,00

0 +

3 (

units

com

plet

ed)

Tot

al s

tand

ard

cost

= $

10

(a)

(d)

=$

6 (b

)

(e)

S 1

$ 3

(c)

U-I

- $2

0

Raw

mat

eria

ls

2,20

0 A

ccou

nts

paya

ble

2,20

0 (4

00,0

00

@ 5

.50)

Wor

k-in

-pro

cess

1,

100

Raw

mat

eria

ls

<l,l

OO

>

(200

,000

@

5.5

0) =

200

,000

5.

50

1,10

0

Payr

ol

600

Wag

es

600

Wor

k-in

-pro

cess

49

5 Pa

yrol

l <

??5>

(9

0,00

0 @

5.5

0) =

90

,000

5.

50

495

Fact

ory

over

head

39

0 Pa

yabl

es

390

Wor

k-in

-pro

cess

38

5 (1

00,0

00

+

=

Fact

ory

over

head

38

5 3(

95,0

00)

385

1,98

0

TA

BL

E 4

Inco

me

stat

emen

ts

Fina

ncia

l R

epor

ting

Man

ager

ial

Dec

isio

n-M

akin

g

Eva

ns,

Inc.

E

vans

, In

c.

Inco

me

stat

emen

t fo

r m

onth

en

ded

Janu

ary

31,

XX

In

com

e st

atem

ent

for

mon

th

ende

d Jn

auar

y 3

1, X

X

(in

thou

sand

s)

(con

trib

utio

n m

argi

n au

uroa

ch)

dSal

es

.bC

ost

of g

oods

sol

d:

Raw

mat

eria

ls

Dir

ect

labo

r Fa

ctor

y ov

erhe

ad

Adj

ustm

ent

for

unde

rapp

lied

over

head

Tot

al

Gro

ss p

rofi

t ,6

15

dOpe

ratin

g ex

pens

es

500

Net

inc

ome

175

- -

Mar

kup

perc

enta

ge

Mar

kup

perc

enta

ge

675

- =

34%

43

0 -

= 1

9.3%

1,

985

2,23

0

2.66

0

1,10

0 49

5 38

5 5

1,98

5 14

.6%

100%

dS

ales

bV

aria

ble

cost

s:

Raw

mat

eria

ls

Dir

ect

labo

r Fa

ctor

y ov

erhe

ad

Ope

ratin

g ex

pens

es

Tot

al

2,66

0 10

0%

1,10

0 49

5 28

5 35

0 2,

230

83,8

%

Con

trib

utio

n m

argi

n 43

0 16

.2%

25.4

%

18.8

%

6.6%

dLes

s:

Fixe

d co

sts

Fact

ory

over

head

O

pera

ting

expe

nses

‘Les

s:

Und

erap

plie

d fa

ctor

y ov

erhe

ad

- -

100

150

250

9.4%

-

-

180

6.8%

5

175

6.6%

-

- -

-

“Inf

orm

atio

n de

rive

d fr

om

Stan

dard

D

ata

Bas

e.

bInf

orm

atio

n de

rive

d fr

om

Gen

eral

L

edge

r D

ata

Bas

e.

‘Inf

orm

atio

n de

rive

d fr

om P

rodu

ctio

n D

ata

Bas

e.

dOth

er

Gen

eral

Led

ger

Acc

ount

s.

296

TABLE 5

Analysis of variance

Raw materials

Quantity variance Price variance

Labor

Rate variance

Efficiency variance

Factory overhead Spending variance

Efficiency variance

Volume variance

u9s,000(~2) ‘S.00 per lb. (n200,000 lb. - 190,000 lb.) = $50,000 Unfavorable

‘200,000 lbs. (cS.SO -“*S.OO) = 100,000 Unfavorable

c90,000 hrs. (cS.SO -n600) = 4s ,000 Favorable

‘$6.00 (‘90,000 - ‘9S,OOO) = 30,000 Favorable

b390,000- [=100,000 + 100,000(3)1

390,000 - 400,000

~400,000 - [~100,000 + ~9s,000(~3)1

400,000 - 285,000

285,000 -“$5‘+9S,OOO) 285,000 - 475,000

= 10,000

= 1 lS,OOO

= 190,000

Favorable

Unfavorable

Favorable

a Information from Standard Data Base.

bInformation from General Ledger Data Base.

CInformation from Production Data Base.

‘All other information input directly.

TABLE 6

Comparative predicted income decision alternatives - contribution approach (dollars in thousands)

Without special order

Unit Total

Special order

Unit Total

With special order

Total

Sales

Variable costs

aRaw materials

aDirect labor

uFactory overhead

Operating expense

Total

Contribution margin

Fixed costs

Factory overhead

Operating expense

Total

Operating income

$28 2,660 $20 100 2,760

10 6

3 3

12

Y

950 570

285

285

2,090

570

100

150

10 so 1,000

6 30 600

3 1s 300

* 285

- 95 2,185

7 575 =

100

150

250

320 =

250 -

325 = 5 Difference =

*None incurred.

aInformation derived from Standard Data Base.

297

REFERENCES

1 Brigham, Eugene F. and Pappas, James L., 1976. Manage- rial Economics 2d. ed. Hinsdale, IL, Dryden Press.

2 Financial Accounting Standards Board, 1983. Accounting

Standards. Stanford, McGraw-Hill.

3 Fireworker, Robert B. and Konzet, Jeffery, D., 1982.

Trends in data base management systems. Journal of

Systems Management, May.

4 Haseman, William D. and Whinston, Andrew B., 1976.

Design of a multidimensional accounting system. Ac-

counting Review, January.

5 Horngren, Charles T., 1982. Cost Accounting, A Manage-

rial Emphasis 5th ed. Englewood Cliffs, NJ, Prentice Hall,

Inc.

6 Louderbeck, Joseph G. HI, and Dominiak, Geraldine F.,

1982. Managerial Accounting 3rd ed. Belmont, CA, Kent Publishing Company.

7 McCarthy, William E., 1980. Construction and Use of Integrated Accounting Systems with Entity-Relationships

Approach to Systems Analysis and Design. North Hol-

land, Amsterdam.

an integrated computer-based system for financial and managerial decisions

Documents