Law-firm pricing and the shift to AI-enabled strategies
When looking back over the past decade, there have been a number of key shifts in law firm behavior when it comes to the pricing of their services.
Prior to 2008, most legal services were billed rather than priced —in other words, rates were agreed up front and, upon completion of work, invoices were sent based on hours worked at the agreed rates. However, as clients actively sought greater certainty of their legal spend, they started requesting estimates. For many, these were quickly treated as being either fixed fees or capped fees.
This became a catalyst for a number of progressive law firms, leading to our second behavioral shift. These firms began to make a considerable investment in better understanding the costs of different matters, thus enabling them to create more accurate estimates, avoid losing work (by quoting too high), or having to absorb major write-offs (by quoting too low).
The third behavioral shift came when firms realized they needed to optimize their pricing, determining the most profitable way to deliver their legal services using the respective firm’s various resources whilst simultaneously addressing more explicit client demands for greater efficiency. This led to the development of various matter-profitability modeling technologies, often developed in-house. Although these solutions contributed to developing better pricing outcomes, they were often impeded by limited functionality and integration, as well as by limited user adoption, especially for those tools which resembled complex spreadsheets or had “too many pricing options.”
Which brings us to the major challenges that remain today and leads us to our fourth — though still embryonic — behavioral shift. The question now is how to best use the combination of the vast amounts of available matter data and imperfect information within law firms to guide more insightful pricing decisions. The creation of accurate estimates and the use of matter-profitability modeling works well where matters are reasonably homogenous. But for many firms, this only addresses a small proportion of matters, especially where (as in most legal environments) no two matters are exactly the same.
This is where the use of AI and machine learning can greatly assist those responsible for pricing. It enables them to harness imperfect information and then use it to more accurately predict costs in an uncertain world. Given no lever has a greater impact on the profitability of a law firm than price, the investment in such technology is likely to become essential to leading law firms.
With many AI solutions still in their functional infancy, those solutions with already strong AI and machine-learning capabilities are standing out from the crowded marketplace. For those firms who are ahead of the chasing pack and embrace these new tools, the opportunity to capture more value through a combination of happier clients (through more accurate estimates) and better financial returns (through stronger profitability) awaits.
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