An Empirical Analysis of Lateral Lawyer Trends from 2000 to 2007: The Emerging Equilibrium for Corporate Law Firms

During the last several decades , the legal profession's definition of a "large" corporate law firm has gradually shifted. The rise of mega-firms, with broad geographic platforms and highly sophisticated, specialized, and profitable practice groups, has been expedited by the steady erosion of the norm against lawyer movement between firms. This change in market structure and professional ethos is attributable to a confluence of factors, including the bureaucratization of corporate legal departments ; the publication of law firm financials; the delineation of individual lawyers by prominence in various regional, national, or global markets; and the challenges of maintaining shared cultural values and long-term time horizons in the face of perpetual growth imperatives driven by the promotion to partnership tournament.

To date, commentators have described this process without necessarily articulating a logical endpoint. The purpose of this essay is to assemble the empirical facts of the "age of lawyer mobility" and, in tum , to offer some preliminary observations on: (a) the internal economic logic that propels the growth strategies of most large U.S. law finns; (b) how these strategies collectively produce a value proposition increasingly less attractive to clients and young lawyers; (c) structural problems within most large firms that inhibit their ability to effectively adapt to changing market conditions; and therefore (d) why many large law firms are vulnerable to small and mid-sized competitors who, by virtue of their size, have the flexibility to emphasize cost, collegiality, innovation, collaboration, and shared risks, both within the firm and with clients. Although a substantial number of large firms will continue to prosper, primarily by attracting lateral partners with the most lucrative and loyal clientele, most large firms (i.e., Am Law 200 or NU 250) will likely have to retool their business models in order to survive.

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