If to fix a fee for somewhat complicated legal services is too difficult, such as a major lease negotiation, perhaps law firms should explore algorithmic pricing. To stay with the example (and to indulge in some fanciful speculation), the algorithm might be $50,000 multiplied by an index for square feet involved and further multiplied by the age of the building, all divided by the anticipated lease term.
OK, I hope you get my meaning. Algorithmic pricing is not fixed as in “Any lease re-negotiation is $74,000 in fees” but is fixed in that the components will vary but the formula stays the same to alculate the fee.
To reach a point where a law firm can rely on and advertise its algorithmic pricing, a firm will need to mine its internal data and figure out the cost drivers and the regression formula. It will need to know what aspects of the matter drive fees and to what degree. Sticking with our example, a driver might be the total square footage owned by the landlord or the landlord’s revenue. Another driver might be the type of use to be made of the leased space. A third could be the quality of the law firm representing the landlord. Each of these components – and all components – can be summarized as an index figure or some other variable in the algorithm.
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