Leveraging Legal Analytics and Spend Data as a Law Firm Self-Governance Tool

This paper discusses the advantages that law firms can get by using legal analytics (big data) to analyze how they do their work for their clients (and how their clients can benefit as well). We discuss the external forces that are reshaping the economics of today’s legal industry; the types of decisions, in determining how best to represent a client in a given matter, that tend to drive up costs; the possible reasons for those decisions; how law firms can use data-analytics tools to examine their own choices; and the benefits that stem from a data-driven analysis of those choices

Networking Effects on Cooperation in Evolutionary Snowdrift Game

The effects of networking on the extent of cooperation emerging in a competitive setting are studied. The evolutionary snowdrift game, which represents a realistic alternative to the well-known Prisoner's Dilemma, is studied in the Watts-Strogatz network that spans the regular, small-world, and random networks through random re-wiring. Over a wide range of payoffs, a re-wired network is found to suppress cooperation when compared with a well-mixed or fully connected system. Two extinction payoffs, that characterize the emergence of a homogeneous steady state, are identified. It is found that, unlike in the Prisoner's Dilemma, the standard deviation of the degree distribution is the dominant network property that governs the extinction payoffs.Comment: Changed conten

Spreading gossip in social networks

We study a simple model of information propagation in social networks, where two quantities are introduced: the spread factor, which measures the average maximal fraction of neighbors of a given node that interchange information among each other, and the spreading time needed for the information to reach such fraction of nodes. When the information refers to a particular node at which both quantities are measured, the model can be taken as a model for gossip propagation. In this context, we apply the model to real empirical networks of social acquaintances and compare the underlying spreading dynamics with different types of scale-free and small-world networks. We find that the number of friendship connections strongly influences the probability of being gossiped. Finally, we discuss how the spread factor is able to be applied to other situations.Comment: 10 pages, 16 figures, Revtex; Virt.J. of Biol. Phys., Oct.1 200

Billing Judgment

In most situations, when a lawyer sends a bill to a client, the client pays the fees. When the client believes that a fee or expense is unreasonable, the client will ask for reductions. Conscientious lawyers review a bill before sending it to the client, exercising judgment in terms of what fees and expenses are reasonable. But in bankruptcy cases, the estate pays the court-appointed professionals\u27 fees and expenses out of unsecured funds or from a cash collateral carve-out. Thus, the responsibility for scrutinizing the fees and expenses falls not to a particular client, but to the court, per 11 U.S.C. § 330. The debtor-in-possession isn\u27t particularly motivated to pay attention to line items on a bill, especially in a bet-the-company case. Moreover, most debtors in possession aren\u27t sure what activities are necessary or which level of professional should be performing which tasks. Creditors might pay attention to the overall burn rate of fees, but often, the cost of objecting to a fee application outweighs the potential benefit in filing the objection. The United States Trustee or a fee examiner can evaluate line-item entries, raising issues about reasonableness; however, those parties question line items months after the time has been recorded. That Monday- morning quarterbacking is not nearly as efficient as is exercising judgment at the time that the professional is doing the actual work. Time written off is time that a professional can\u27t redeploy. We argue that developing a mindset that focuses on billing judgment at the time of performing the work, whether for a bankrupt estate or a solvent client, is better for the bankruptcy estate or client and better for the professionals themselves. The trick lies in how to deploy data and social science to nudge people into developing a better billing judgment mindset

Using Data Analytics to Predict an Individual Lawyer\u27s Legal Malpractice Risk Profile: Becoming an LPL Precog

The power of data analytics is revolutionizing the way that business is conducted in nearly every industry. The medical industry, the consumer/retail space, and the banking and financial industries are taking their business operations to the next level by leveraging the power of big data. Despite radical transformations in nearly every other aspect of the legal industry, though, the approach to preventing, predicting, assessing, and resolving malpractice claims hasn\u27t really changed. Malpractice insurers and their law firm clients continue to take an old-fashioned approach when it comes to legal professional liability. Unlike the insurers pricing automobile policies, the vast opportunity that LPL insurers could use hasn\u27t been used well--at least not yet. LPL industry experts have confirmed that most legal malpractice insurers aren\u27t leveraging advancements in technology and legal analytics in order to predict risk areas. Instead, LPL carriers primarily are reacting to actual events or using the broad brush of simple demographics to set rates. Consequently, the all-in malpractice costs for insurers and law firms continue to escalate, even though risk and costs should both be decreasing. This is the wrong result for everyone directly or peripherally involved in the legal industry and, more specifically, the wrong result for the LPL industry as a whole. Our paper posits that a progressive, data-driven approach to legal professional liability will reduce the overall cost of malpractice claims, thus helping law firms to recognize potential pressure points before those intimations of problems become full-blown blisters. Part I analyzes the underpinnings of malpractice claims. Part II discusses how malpractice insurers and their law firm clients have historically assessed, underwritten, and resolved malpractice claims. Part III explains why historical malpractice metrics fall short. And Part IV proposes a new data-driven analytic schema by which malpractice claims might be predicted, managed, assessed, and resolved

Legal Analytics, Social Science, and Legal Fees: Reimagining Legal Spend Decisions in an Evolving Industry

This article discusses how legal analytics can help law firms and clients understand, monitor, and improve the components that comprise bills for legal fees and expenses