The increasing amount of data, available not only from your financial department but from personnel, marketing and operations, facilitates monitoring and tracking various law firm indicators.  However, the quantity of data can be overwhelming at times.  This is especially true when trying to make a decision with conflicting information.

One of the best ways to make complicated decisions, where a lot of data is available, is to use computer modeling techniques.  A computer model, which is a specific set of variables and their interrelationships designed to represent a situation, helps assess data and simplify the decision-making process.  Computer modeling is fast becoming one of the preferred methods in making decisions. 

Computer modeling is no longer relegated to the financial department.  In fact, computer modeling is an asset in every functional area: in human resources when deciding to hire additional personnel and at what level, in payroll for calculating bonuses, in marketing when deciding on which industries to target, in operations for determining capacity and growth scenarios, in strategic planning for identifying potential partners, and in finance when deciding on which potential clients have a low risk of defaulting on their fees.  Using available data or estimates, computer modeling is helping law firms make better decisions.   

A variety of computer modeling tools are available: spreadsheets like Excel, Lotus and Quartro-Pro; databases such as Access, Fox-Pro and DBASE; programming languages like Visual Basic, C++, SAS and UNIX; and commercial tools such as Pro-Formas for Professionals, @Risk and iThink. 

There are four basic steps in building a computer model: 

State the problem.  The first step in computer modeling is to determine the exact problem and state it as a question.  For example, Joe Smith is the managing partner of a law firm.  His firm is growing so fast that he has more work coming in the door than the staff can handle.  He needs to hire additional people, but he doesn’t know at which level.  Should he hire a senior attorney, junior attorney, paralegal, secretary or clerk?   

All of his employees claim to be very busy and need more help.  But Mr. Smith realizes that fast growth may go hand-in-hand with bloated growth and inefficiency.  He doesn’t want to hire more people just because his current employees are busy.  He would like some way to demonstrate the appropriate level of person who should be hired, so that he can grow efficiently and still maintain his high profit margin.   

The second step is to define and collect the data.  Critical to answering the question, which has been posed, is to develop a list of relevant data that will affect the decision.  In this case, Mr. Smith needs to know from all the employees who are doing work for the firm, what tasks they perform and how much time they spend on each task every day.  Although gathering this information may be a daunting project, the results will be well worth the effort. 

Next, choose the modeling tool.  Select the tool based on your customization needs and the amount of data that you will be processing.  If the data is voluminous, a database may be necessary; however, if you have a small project, a spreadsheet may be the tool of choice.  If an off-the-shelf tool suits your needs, then by all means, use it.  But if you require a considerable amount of customization, then a commercial tool may not suffice and you may have to create the model yourself or outsource the work. 

In our example, Mr. Smith selects the flexible Excel spreadsheet, because it’s easy to use with good explanatory graphs that can be developed. 

Build the model.  Now you are ready to start building your computer model, which will answer the question that you posed.  There are six components of a model: 

1.  Input sheet, where the user enters and modifies the data.

Mr. Smith’s input data are the various tasks, the level of employees completing the tasks, the amount of time each task takes and the order that the tasks are completed.  Critical to the analysis is not only the level of employees who do the work now, but who should do the work in the future.  So Mr. Smith designates levels for each task based on who should do the work (support staff, secretary, paralegal, junior attorney and senior attorney) not who actually performed the work.  Employees track their time on various tasks during the data gathering period. Another input is the forecasted growth of work by practice area and the associated effort by level of person required to complete the work.

2.  Results sheet, which indicates the numerical conclusions based on the inputted data.

Mr. Smith creates a results sheet, which is automatically populated from the input sheet.  He uses color-coded cells for people who are performing tasks that are above or below their level of competence. 

From the model, Mr. Smith sees that attorneys are performing paralegal work and secretaries are doing clerical work.  For example, attorneys are doing all of the research work, some of which could and should be done by paralegals.  The results sheet also indicates that the secretaries are photocopying and preparing messenger packages -- tasks that should be performed by the clerical staff.  The result is that the firm is paying salaries to people who are performing simple tasks for which they are overqualified.  Furthermore, the firm’s profits are eroding with people who are not aligned with the appropriate level of task.   

3. Charts and graphs are the visual representations of the results.

If a picture is worth a thousand words, then a graph is worth at least as much.  A graph visually depicts the statistics on the results sheet.  Using the graphs, Mr. Smith easily sees that the number and level of employees that he should hire based on his current workload and his forecast of future work.  The charts indicate the relationships or ratios between the levels of personnel.  For example, one graph reflects the number of paralegals for each attorney based on the tasks’ levels of work that was identified in the data gathering process.    

4.  Changing variables and “What if?” scenarios.

The advantage of using a computer model is that the data is not static.  If you change the data, then the results sheet and the graphs and charts can change automatically.  A computer model allows the user to change variables, to alter scenarios and to calculate sensitivities that may affect decision-making. 

Mr. Smith can calculate how an increase in work will affect his hiring decisions.  He can change the input data to reflect growth scenarios and the graphs automatically are updated so that he can see how the alterations will impact the firm.  This tool gives him the flexibility to experiment with various modifications to determine how the results will be affected.   

5.  “Sanity check,” which determines if the inputs and calculations make sense. 

Every computer model needs a sanity check to ensure that formulas and calculations are realistic.  The user can’t lose sight of the logic in developing the computer model.  One small error in a formula can throw a computer model into the realm of improbability.

Mr. Smith reviews the tasks and their time allocations for reasonableness.  He does not accept the computer model as the “end all,” but instead examines the inputs and the formulas to ensure accuracy.  He is satisfied that all his conclusions are sensible.   

6.  Usability -- the menus, macros and other automation features that make using computer model easy and simple.  With Visual Basic programming, which runs in the background and is not apparent to the user, a computer models can be an uncomplicated tool for attorneys and managers to use. 

Mr. Smith designs a few simple interfaces that facilitate use of the computer model.  He designs a menu that will provide easy access to the various spreadsheets, such as input sheet and results sheet.  He explains the computer model to his office manager, who is able to continually update the model and provide reports on a quarterly basis.

A major advantage of the computer model for the law firm is its ability to answer complicated questions.  If you are stymied by a question that appears unanswerable, chances are that a computer model can assist your assessment and provide a solution to your dilemma.  As more unknowns become facts and as assumptions change to reality, the computer model evolves and adapts, which creates a dynamic and robust tool for decision-making.