Picture this: It is 1980, and your boss has just told you that you are responsible for developing organizational, customer, and line-of-business profitability measurement for your bank. You cannot hire any more staff to do it, and it needs to be done by the end of the year.

Your first thought is that you wish your office were higher than the second floor so that you would do more than just break your leg after jumping out the window.

Now it is 1995, and you have been given the same charge. Your response is cool, calm, and collected. Why the difference?

Clearly the interest in profitability measurement issues is more advanced now than in 1980.

Understanding how individual organizational units, products, customers, and lines-of-business contribute to overall profitability has become an imperative for those institutions in the last half of the last decade of the 20th century.

In addition, there are more management accountants than ever before engaged in profitability measurement. This growing cadre of specialists can give banks advice, as can a growing number of trade associations that are now providing education on profitability matters.

But the most important difference between measuring profitability in financial institutions in 1980 and in 1995 is the amount of technology available.

This technology is on the management accountant's desk, in the form of a powerful personal computer and the improved application software for loans, deposits, and general ledger functions. It also includes improved profitability measurement systems and better tools to extract and manipulate data.

Let's look at some specifics.

Prior to the widespread use of the PC, it was possible to construct mainframe- or minicomputer-based profitability measurement systems that could do what PCs do today.

But such construction was difficult. Getting enough data processing resources to build and maintain these systems was something that only the larger institutions could afford. Indeed, the majority of the serious, early profitability measurement efforts in commercial banks were at institutions with more than $5 billion of assets.

With the versions of the PC available in the early 1980s, there was not enough computing power or disk storage space to get past a certain rudimentary level of measurement.

And besides, most PCs in financial institutions in the early 1980s were busy doing asset/liability management calculations.

Not until the 386 PC processor arrived, along with 100-plus megabyte hard disks, was it possible to consider measuring profitability for an entire multibillion dollar institution on a monthly or quarterly basis.

And even then, without the ability to extract data easily from a bank's core application systems, it was difficult to feed the measurement process enough good data to make it part of the regular monthly or quarterly reporting process.

But things have changed dramatically in the past few years, and the connection of PCs to mainframe data bases has proliferated. The question now is not whether it can be done but rather how best to approach and organize the massive, often overwhelming amount of data that is available to the management accountant.

It is no longer necessary to build allocation methodologies and formulas into spreadsheets and data-base tools. There are now commercially available tools for those functions.

The challenge facing banks in this area is making sure these systems meet all of the defined allocation needs of a particular profitability measurement effort.

Perhaps the single biggest impact that technology has had on the profitability measurement process is in the area of funds transfer pricing - also known as cost accounting for the net interest margin.

The preferred methodology among management accountants is the so-called matched maturity funding method, which requires that funds charges and credit be applied to the individual loan or deposit transaction level and that those charges and credits be tracked over the entire life of the instrument.

For a 30-year mortgage loan, this means that a lot of historical data is going to have to be kept somewhere to accomplish this particular management objective.

On top of that, even medium-size institutions - those with between $500 million and $2 billion of assets - can have several hundred thousand such individual accounts. These need to be accessed on a monthly basis to calculate their contribution to the institution's net interest income.

Only recently have PCs offered enough power, disk storage, and mainframe connectivity to make this a practical application to build or buy and maintain.

Without the ability to download each and every loan and deposit account to the PC, the manual task involved in simply getting the data ready to calculate would overwhelm the process to the point that it could not be done successfully.

Going forward, the increases in power, storage capacity, mainframe connectivity, and availability of end user tools for PCs will only work to improve the efficiency and effectiveness of the profitability measurement process.

This is, of course, no panacea.

Technology by itself cannot produce organizational, product, customer, or line-of-business profitability measurements.

But technology is a tool that can be used by knowledgeable management accountants to define and implement good profitability measurement and reporting systems.

And these tools can be used to integrate these profitability measurement efforts with data used to support other processes designed to improve overall profitability, such as interest rate risk management.

So, good luck as you march off, PC and data in hand, to slay the profitability-measurement dragon. A good system may be your ticket to the top.

But even if it is not, you can rest easier knowing that you have a much better chance of implementing and maintaining a good profitability measurement system than any of those that have come before you.

Happy allocations!

Mr. Weiner is chairman and chief executive officer of Interactive Planning Systems Inc.

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