March 28, 2023

 Erica White

 Radoslaw Gabryl

law departments Consulting law firms best practices AFAs alternative fee arrangements

As detailed in our two previous articles (Part I here and Part II here), alternative fee arrangements offer numerous advantages – if done correctly. Success requires applying best practices to select, implement, and measure the performance of your chosen AFAs. With that in mind, this article provides an in-depth guide to developing a data-driven AFAs program using data analysis and modelling.

Getting Started: Analysing Historical Data

Building a successful AFA program begins with internal stakeholders aligning on an AFA ’menu.’ This involves analysing different AFA structures to identify which will work best for your organisation. The suitability of a particular AFA paradigm depends on factors like the type of matters in question, the internal appetite for setting up the billing/invoicing structure of the AFA, and historical billing practices.

Getting things right means analysing historical billing data to identify AFAs that would work for your department, a particular matter type, or even a specific firm. Consider the scenario of hiring outside counsel for an intellectual property matter. Best practice is analysing data from multiple previous IP matters before you select a firm or an AFA. As you compare data (e.g., billing rates, staffing leverage, estimated budget vs. final amount billed, work performed in each phase, etc.), valuable insights will emerge. Perhaps one firm’s billing rates significantly exceed the industry average. Or one firm tends to utilise partners 50% more often than the other firms. These sorts of findings can help you select the AFAs most likely to achieve your desired outcome, whether bringing a firm’s billing rates in line with industry averages or encouraging the use of lower-cost practitioners like associates and paralegals.

The Next Step: Modelling 

Another fruitful use of historical billing data is modelling to compare rate paradigms. By inputting data into a suitable model, you can get data-driven insights on how various AFAs perform compared to each other and traditional hourly billing. A model that combines data and industry benchmarks can provide insights into general differences between AFAs and traditional hourly billing. But, by using actual historical billing data, you can transform the model into a custom analysis and prediction tool. Since no two law firms or law departments are the same, there tend to be noticeable differences in the billing and staffing practices. If implemented correctly, a model can help you navigate the differences and possibilities without being overwhelmed by all the variables and nuances of manual analysis and financial calculations.

To get started with an AFA model, you must select or input some basic assumptions, such as matter type and the estimated budget under traditional hourly billing. You can then dive in deeper by inputting other variables such as the desired flat fee, desired hourly rate for each timekeeper classification (Partner, Associate, Paralegal, etc.), or desired volume discounts. The model allows you to immediately see how changes to these variables could affect the bottom line and which AFAs would most likely result in the desired outcome (e.g., savings, greater predictability, etc.).

Use of Modelling by Law Departments

Both law departments and law firms can benefit from AFAs modelling. For law departments, modelling can automate the process of historical data analysis and allow for quicker evaluation of firms’ historical billing and staffing practices. Law departments can then use the model to set up parameters for various AFAs and compare the estimated cost of a matter under various AFAs to the actual historical cost of that matter. This activity can help you select AFA structures for future similar matter types or particular firms based on their past performance.

Law departments can also use the model’s outputs to have data-driven, collaborative AFA conversations with their outside firms. Proposing a particular AFA to firms then becomes more about trying to achieve a particular outcome in response to actual, historical practices. Once the matter has concluded, law departments can again use modelling to evaluate the performance of implemented AFAs and then compare a particular AFA’s performance to projected results under different AFAs or traditional hourly billing. This can help refine AFA selection on future similar matters.

What About Law Firms?

Law firms also benefit from AFA modelling and historical data analysis. For example, consider when a client proposes one or more AFAs or issues an RFP asking for AFA proposals. A firm can input its billing data for similar past matters into the model to compare AFA structures to each other and traditional hourly billing. It can also see the impact of any changes to billing rates, staffing leverages, fixed fees, and more. The use of modelling provides firms with a better understanding of whether a particular AFA would add predictability, affect their revenues, or necessitate changes to staffing utilisation. Modelling can also help law firms engage in data-driven AFA negotiations, including proactively selecting and proposing AFAs to clients and analysing the performance of an AFA at the close of a matter.

Best Practices for Designing AFA Models

Maximising the power of an AFA model starts with designing and building it to be automated and easy to use without ongoing technical support. The best models only require setup once; after that, the model should allow you to select the historical billing data you would like to analyse, with the model automatically loading the data and running the analysis. The model should make it easy to re-run analyses whenever you modify your assumptions and tweak variables (as discussed above). A model with a consolidated dashboard displaying the results and showing head-to-head comparisons allows you to quickly and easily see the estimated savings and benefits of each AFA structure.

When deciding on and implementing AFAs, both law departments and law firms can benefit from historical data analysis and modelling. The transparency and predictability that models provide can foster collaborative, results-driven negotiations. By helping law departments and law firms leverage and review data to make data-driven decisions, modelling can make AFAs a win-win approach.