AN INTERACTIVE PRODUCTIVITY MEASUREMENT MODEL USING SPREADSHEET SOFTWARE

Howard W. Oden

Worcester Polytechnic Institute

ABSTRACT

Previous computerized productivity measurement models to assist firms in computing productivity measures from a set of input data have been constructed using procedural languages, primarily Fortran and Basic. These models have a number of shortcomings which have detracted from their usefulness. First, these models must be modified to adapt them to the organization and data available from a particular firm. Modification is expensive and time consuming since it requires a detailed knowledge of the structure of the model and the language in which it is programmed in addition to a detailed knowledge of the firm. Second, data entry is not only difficult and time consuming but the user has no indication of what is happening between the input of data and the output of the final productivity measure.

This paper describes the development of an interactive multlfactor productivity measurement model using Lotus 123. With the spreadsheet software the model can be easily adapted to fit the needs of the firm by the firm's industrial engineer with a only working knowledge of Lotus 123. Changes in data can be made easily by using the features of the spreadsheet software, and the effects of the changes can be seen easily and rapidly on various aspects of the model.

KEYWORDS

Productivity, Productivity Measurement, Productivity Measurement Model, Spreadsheet, Spreadsheet Template, LOTUS 1-2-3

INTRODUCTION

Productivity is the relationship between the outputs generated from a system and the inputs provided to create those outputs. Inputs in the general form of labor (human resources), capital (physical and financial assets), material, enery, and data are brought into a system. These resources are transformed into outputs (goods and services). Productivity is the relationship between the amount produced by a given system during a given period of time, and the quantity of resources consumed to create or produce those outputs ove the same period of time. Defined simply: PRODUCTIVITY = OUTPUTS/INPUTS.

If all the outputs and all the inputs for a given system are included in the above equation, that would constitute a total factor productivity measure. Any measure that compares output to only one of the inputs, such as labor, is a partlal factor productivity measure. Any measure that compares total output with more than one of the input factors is called a multl-factor prod%ctlvlty measure. Partial productivity measures provide useful information but do not give a complete picture of an organization's performance with respect to productivity. A total productivity measure would be desirable, but time and cost to identify and measure all inputs is sometimes prohibitive. Oftentimes the best compromise is a multl-factor productivity measure which captures the most significant inputs in an overall measure and at the same time computes and tracks a number of partial productivity measures.

DESCRIPTION OF AVAILABLE COMPUTER MODELS FOR PRODUCTIVITY MEASUREMENT

This section is not intended to be a comprehensive survey of available productivity measurement methods and computer models. Readers interested in such a survey are referred to Sumanth (1984) or Sink (1985a, 1984). Rather this section will provide a brief description of the most recent, well known, and widely used computer models.

Sumanth's Total Productivity Model (TPM)

Sumanth (1980, 1984) developed a Total Productivity Model that was programmed, first in FORTRAN (Hassan, et al, 1981) and later in BASIC (Sumanth amd Martinez, 1985). The only significant difference between the two computer models is the fact that the FORTRAN model required the external preparation and

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326 PROCEEDINGS OF THE 8TH ANNUAL CONFERENCE ON COMPUTERS AND INDUSTRIAL ENGINEERING

use of an input data file, while in the BASIC model the input data could be entered from a terminal in an interactive manner.

Sumanth's Total Productivity Model considers zne impact of all input factors on all output products. It can be used to calculate both total and partial factor productivity ratios and indexes for both the total firm and each product or product organization. It does not include a capability for automatically adjusting the values of inputs and outputs due to price changes; this has to be done manually before inputting the data.

Sink's Multi-Factor Productivity Measurement Model (MFPMM)

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Sink (1985a) developed the Multi- Factor Productivity Measurement ModeI(MFPMM) by modifying the Total Factor Model developed for an by the American original work by Davis (1958). Sink made the following modifications to the APC model to simplify it and make it more usable by practioners: (i) removed capital as an input variable, (2) removed variance analysis, and (3) added a "what if" simulation routine to aid the manager in analyzing the effects of changes.

The essence of the MFPMM model is portrayed in Fig. i. A change in profit from one period to the next can be the result of a change in productivity, a change in price recovery, or combination of the two. The model allows the

user to separate the effects of productivity from the effects of price recovery for each

• particular input factor. Changes in profitability due to price recovery reflect the degree to which input cost increases are passed on to the customer in the form of higher output prices. Changes in profitability due to productivity improvement reflect the organiza- tion's ability to absorb cost increases by improving the ratio of output quantities to input quantities.

Fig. 2 depicts the formulas and the sequence of calculations used by the MFPMM model in computing productivity ratios and indexes. As you can see, productivity ratios are calculated by placing measures of output from a given system over measures of inputs for that same system for a given time period. To calculate productivity

indexes, the model takes producivity ratios for period k and divides by the same productivity ratios for period J.

The MFPMM computer model is programmed in both FORTRAN and BASIC. Quantity and price for each output and input of the organization being analyzed are required

ODEN: I n t e r a c t i v e P r o d u c t i v i t y M e a s u r e m e n t Model u s i n g S p r e a d s h e e t S o f t w a r e 327

to run the model. This information can be entered into the model by reading it from an existing file or inputting it interactively. If the data are input interactively, the user has the option of running the model only once with the data or sending the data to a file to be saved for future use.

After the data are entered, the model displays the data to the user for verification. As each data section is displayed, the user has the opportunity to change any of the data for that execution without changing the data in the file. When data verification has been completed, and the model run, the output is provided in the format shown in Fig.3, but broken up into three tableaus for viewing and printing on an 80-column monitor and printer.

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APPLICATION OF LOTUS 1-2-3 TO PRODUCTIVITY MEASUREMENT

As one can readily see by looking at Fig. 3, the output format for the MFPMM model looks very much like a spreadsheet. Couple this with the fact that all the calculations in the model shown in Fig. 2 are nothing more than simple arithmetic, and one has an ideal application for LOTUS i-2-3.

The current version of the template is what is referred to as an "open matrix" template (Urschel, 1985), which provides a spreadsheet (the matrix) filled with interlocking formulas without any driving macros or menus. This type of template is the simplest to develope but requires that the user know how to use LOTUS 1-2-3 in order to operate the template, since no prompts or helping menus are provided.

The format shown in Fig. 3 was simply duplicated using the features of LOTUS I- 2-3, The formulas shown in Fig. 2 were placed in the appropriate cells of the spreadsheet. The template solutions to several sample problems were compared with manual solutions to verify the accuracy of the template.

The LOTUS i-2-3 template that was developed was intended for classroom and development purposes. As presently configured, it has 40 rows and 40 columns which provides space for six outputs, six labor inputs, four material inputs, and four energy inputs.

Both the MFPMM 1-2-3 template and the MFPMM model programmed in BASIC was made available to a class of thirty graduate students taking a course in Productivity Management. For those students who had some experience with LOTUS 1-2-3, the template proved to be the fastest and easiest means of solving the assigned productivity problems. The students who had no experience with LOTUS i-2-3 found the BASIC MFPMM model easier to learn than LOTUS, and opted to use the BASIC model.

Although the BASIC model procured from the Virginia Productivity Center was

328 PROCEEDINGS OF THE 8TH ANNUAL CONFERENCE ON COMPUTERS AND INDUSTRIAL ENGINEERING

extremely user-friendly, the students who were familiar with LOTUS found it much easler and faster to enter and change data in the LOTUS template.

AREAS FOR FURTHER RESEARCH

Based on the encouraging results to date, several areas for additional research are envisaged. These areas will be described in the following paragraphs.

Development of Templates for Additional Productivity Measurement Models

The template development described above was for the Multi-Factor Productivity Measurement Model, a macroscopic model for measuring productivity at the total firm level which uses the firm's accounting system to collect data. Template development is planned for a number of other models that can be used for groups within the firm which use different methods of collecting data.

The Normative Productivity Measurement Model (Sink, 1985a) is not Dased on the firm's accounting system, but uses information collected by the group itself. In this model, the measures of productivity are determined by the members of the group. The computer model for this method must be extremely flexible to be useful for all the different quantities and types of measures developed by various groups.

The Multi-Criteria Productivity Measurement Model (Sink, 1985a) is very similar to the Normative Model described above, except that it provides a mechanism for developing an aggregrate productivity measure when confronted with multiple outputs or objectives.

All three of these models could be used in the same firm if desired, realizing that they would use different types of data, collected by a different methods, analyzed in a different manners, and utilized for a different purposes. However, the method of entering data, the method of entering changes, and the method of outputting data would all be the same, since all models could have the same underlying structure, that of Lotus 123.

Refinement of the MFPMM Open Matrix Template

The open matrix template provides an excellent vehicle for the development of further refinements to the MFPMM model, since it is so easily changed. The following refinements will be implemented and evaluated:

Substitute Productivity Ratios for Cost/Revenue Ratios. In the current version of the template, which follows Sink's (1985a, 198Sb) model, the productivity ratios are never calculated. The template goes directly from Weighted Change Ratios in Column 7 to the Productivity Index in Column 14 without computing the Productivity Ratios. The items labeled Productivity Ratios in Columns 12 and 13 are actually Revenue/Cost Ratios and are the reciprocals of the Cost/Revenue Ratios in Columns I0 and 11. In the planned refinement of the template, Columns 12 and 13 will be relabeled Revenue/Cost Ratios and the Cost/Revenue Ratios in Column i0 and ii will be replaced by true Productivity Ratios.

Provide Capability for Inputtinq Values and Calculatin~ Quantities. As the template is currently configured, the user inputs the Quantities and the Prices for each output and input in Columns i, 2, 4, and 5 and the template calculates the Values in Columns 3 and 6. However in many instances, and especially if the inputs are obtained from the accounting system, the dollar values are known and the quantities must be calculated. In the current version of the template, this must be done manually.

Provide a Capability for a Total Factor Model. In the current version of the template, only the labor, material, and energy costs are listed as possible inputs. In order to provide a Total (Input) Factor Model, the template should have the capability for inputting Capital Costs and Other Costs, the latter being a catchall for all costs not included in the other four categories. The fact that the template has the provision for inputting all input costs does not mean that the user has to actually provide all input factors for the model to work, but the capability would be there if the user wants to use it.

Provide the Capability for a Multi-Product Model. In the current version of the template, the outputs are aggregated into one composite product for purposes of computing productivity ratios and indexes. There is no provision for calculating productivity ratios and indexes for individual products. It is planned to develop a separate multi-product multi-factor productivity measurement template, which could be used by those companies having more than one product division.

Development of Improved Data Entry Capability

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In semiautomatic data entry (Ursche], 1985) the power of the macro is used to provide menu options on the 1-2-3 command line. These features serve mainly to position the cursor logically for each data entry task and to shuffle calculated results automatically to the appropriate areas in a spreadsheet. However, the semi-automatic templates do not provide true data entry screens or entry validation; data is entered directly into the individual cells using i-2- 3's data entry procedures.

In fully automated data entry, ~ data entry screen is provided that thoroughly isolates the user from the spreadsheet. The screen prompts you for the type of data to be entered and then tests the entry to make sure it is the right type. It then sends the validated data to the correct spreadsheet cell. Thus the user can operate the template without having any knowledge of how the I-2-3 operates. When the refinement of the open matrix template is completed, it is planned to develop semiautomatic and automatic data entry for testing and evaluation.

Development of Semiautomatic Simulation Capability

In the current version of the template the user can ask and obtain answers to "what if" type questions, by manually changing the entries in the input data cells and observing the resulting spreadsheet changes. Although this is a simple and effective method of simulation it is extremely time consuming for the user and requires a good knowledge of 1-2-3 on the part of the user. It is planned to develop a simulation procedure using macros that will enable the user to answer "what if" type questions in a much simpler and less time consuming manner.

Deyelopment of Semiautomatic Graphical Capability

LOTUS 1-2-3 has a tremendous graphical capability. However, the user must have a fairly good grasp of 1-2-3 to take advantage of this capability. It is planned to develop a set of macros that would make graphing the significant variables of the model and well as the printing of these graphs much easier for the user.

CONCLUSION

Productivity measurement systems to be most effective should be developed and understood by the people who are going to use them. Then, and only then, will the measurement system be fully accepted and utilized. Adherence to this principle results in each organization having a productivity measurement system that is unique to their organization. If a computer model is to be truly effective in assisting firms to implement their productivity measurement systems, then that computer model must be easily adapted to a number of different measuring systems. The flexibility of the LOTUS 1-2-3 template will make this possible.

REFERENCES

Davis, H. (1955), Productivity Accounting, The Wharton Industrial Research Unit, Univ. of Pennsylvania, Philadelphia, Pa. (Reprint 1978)

Hassan, M.Z., P. Shanthakumar, and D.J. Sumanth (1981) The Total Productivity Model (TPM), A User's Manua ~. A & M Printing Inc., Chicago.

Miller, Harry (1986). More Power to You, PC World, January, 177-189 O'Malley, Christopher (1985), Your Own Spreadsheet Templates, Personal

Computinq, September, 49-59 Sink, D. Scott (1985a), Productivity Management: Planning, Measurement and

Evaluation, Control and Improvement, John Wiley & Sons, New York Sink, D. Scott, and Chell A. Roberts (1985b), A User's Guide to the Multiu

Factor Productivity Measurement Model, Virginia Productivity Center, VPI, Blacksbury, VA

Sink, D. Scott, T.A. Turtle, and S.J. DeVries (1984). Productivity Measurement and Evaluation: What is Available?, Productivity Review, Summer, 265-287

Sumanth, David J. (1984), Productivity Engineering and Management, McGraw-Hill New York

Sumanth, David J. and M.Z. Hassan (1980), Productivity Measurement in Manufact- uring Companies by Using a Product-Oriented Total Productivity Model, Institute of Industrial Engineers Conference Proceedings, Norcross, Ga, 225-266

Sumanth, David J. and Juan Martinez (1985), An Interactive Computerized Approach to Total and Partial Productivity Measurement, Computers and Industrial Engineering, Vol. 9, Supplement I, 89-93