Project Distribution Goes High Tech

Case Studies in Work Allocation

Over the past two decades, advances in logistics technology that have reshaped entire sectors of the economy have left legal practice untouched—until now. Work allocation technologies that have matured in recent years provide case studies in how law firms can slash the overhead costs that stymie efforts to improve firm profitability. The more clients question the value of their legal spend, the less firms can get away with following yesterday’s best practices. Embracing technologies that help firms allocate work efficiently will prove crucial to attracting and retaining business.

The problem of allocating legal work efficiently has three layers, and for each of them, a recent technology illustrates the future of best practices. The first layer is attorney assignment: ensuring each associate has a full workload by giving partners the tools to search across the firm’s whole associate pool to find those attorneys whose skills and schedule make them the best fitted to each matter.

Here, firms should look to how ridesharing services like Uber and Lyft have supplanted traditional taxi services as the model for how to better help partners match assignments to associates. Using a traditional taxi service, a rider must choose arbitrarily between several small services that may or may not have any drivers nearby. Then a dispatcher coordinates back and forth between the drivers before sending one to the rider. This cumbersome process means that riders often face long waits, and the unbillable transit time between riders forces taxis to charge higher rates to break even. Because taxicab companies require a dispatcher to serve as the middleman, their growth is limited to the number of cabs a dispatcher can manage—even though a large network of cabs would lead to shorter waits for riders and less downtime for drivers.

The genius of ridesharing services is that they solve all these problems at once by tracking drivers’ positions in real time. First, this eliminates the need for a middleman because the service knows where all drivers are at all times without asking each driver individually for updates. This in turn means that the only ceiling on the number of drivers it can coordinate is the number of potential riders in each market. Larger networks of drivers and efficient matching of drivers and riders minimize drivers’ downtime and offer riders both shorter waits and lower fares. Also, the system is more transparent for riders: The app gives them a bird’s-eye view of drivers in the area along with accurate estimates of wait time, arrival time, and price.

Law firms can make a comparable leap in efficiency by keeping track of associate workloads in real time. Currently, partners looking to assign matters are like riders calling a taxi company: They can only access a small subset of the firm’s associate pool because, whether personally or through an administrator, a partner can only reach out to so many associates, and this time-consuming process means partners must wait longer before associates can be put to work. This especially hampers interoffice collaboration, leaving large firms functioning more like loose associations of regional firms than cohesive organizations. If, instead, firms used a platform that keeps track of associate workloads in real time, a partner could type in the qualifications required and immediately find the attorneys who need the work the most, even across offices. The final associate chosen can start working right away, and this process also helps keep workloads level both attorney-by-attorney and office-by-office.

The main challenge is that keeping track of attorney workloads is more involved than attaching a GPS to a driver. Someone—partner, associate, or support staff—needs to input each assignment into a platform to keep the workload data timely. But this is less of a burden than it might appear, because attorneys already enter assignment data into their billing software once their work is complete. To keeping track of assignments, attorneys must instead input that data before getting to work. (This also means that attorneys have less to enter into a billing system later, when they prefer to move on to the next project.) Some commitment to adapt is required, but the benefits far exceed the transition costs.

The second layer of the work allocation problem is in better handling the firm’s knowledge internally so that attorneys spend less time researching issues their colleagues have already encountered. Law firms create redundant work for associates by treating each piece of attorney work product as its own separate thing rather than a part of the firm’s network of knowledge. Firms keep electronic copies of documents their attorneys write, but there is no practical way for someone drafting a new document to know whether another attorney at the firm has already written something on point. Instead, attorneys start each new assignment from scratch or, at best, from a template that only includes boilerplate. This inevitably means that attorneys waste hours researching issues someone else may have already addressed.

Here, firms should look to Wikis: databases that allow any user to create pages that can be read or edited by any other user, as the case study for how to share the fruits of their research among attorneys. In a Wiki, a user who has information to share creates a searchable page for it, with citations. Then anyone reading the page can expand on it or correct it. Whenever a page uses a term that also has its own page, it includes a link. This creates a network of related topics so that a reader who is new to a particular subject can use any page as an entry point and trace a path of research from there.

While Wikipedia is the most famous example, the case studies relevant to law firms are the smaller Wikis focused on particular subjects that have proliferated across the internet. By making one small contribution at a time, groups of experts or hobbyists amass exhaustive but well-organized repositories of information, allowing anyone to satisfy his or her curiosity even on obscure questions within the subject of the Wiki. These Wikis are proof of concept that groups on the scale of a law firm can develop a Wiki that has real value as a resource.

Maintaining an internal Wiki at a firm means that, in addition to whatever value work product provides the client, each piece also becomes part of an ever-growing body of internal knowledge. When researching a new issue, an attorney would start at the firm’s Wiki and find out whether another attorney had encountered it in an earlier matter, use the citation to go to the document the earlier attorney produced and adapt any relevant language and citations to the new assignment. Particularly for junior associates or attorneys working in an unfamiliar area of law, this allows skipping past the basic issues and focusing on the novel or difficult questions posed by a matter. And then once that work is done, the attorney can add a link to the new work product to the Wiki in case it comes up in a future matter. Editing a Wiki is a painless process, and firms could encourage attorneys to contribute to it as a routine part of finding new research that might be useful in other matters.

The third layer of the work allocation problem is finding better ways to identify and farm out work that is not an efficient use of an associate’s (or paralegal’s) time. Firms already do this with their document review process, having contract attorneys examine documents for relevance before associates look at them. But associates, especially junior associates, end up spending time on work that is difficult to justify to clients, leaving partners with the choice between paring back the associates’ hours billed or risking friction with the client.

The case study for solving this problem is microtasking, as found in platforms like Amazon’s Mechanical Turk. The historical Mechanical Turk was a fake chess robot operated by a man hiding underneath it, and the concept of microtasking is similar: The user interacts with a microtasking platform through an interface resembling a search engine or other automated system, but the request is posted on the microtasking site to be completed by an anonymous person for a small fee—often pennies. Because these requests are ad hoc and do not require any other interaction, people can and do choose to complete these tasks for nominal fees. It has the ease of use of something like Google, but can resolve tasks or queries an automated system cannot.

Firms could take advantage of microtasking to facilitate certain basic research questions and other rote work to provide better client value and allay client concerns that they are overpaying for what amounts to on-the-job training for junior associates. For example, in the course of working on a memo, an associate might try and fail to find a case with a particular fact pattern and decide that spending further time on a potentially fruitless search would waste the client’s money. While moving on to the next issue, this user could post the question to the microtasking platform in case another user already knows the answer or is willing to research it for a small incentive. This need not involve law-specific microtasking: An attorney could come across a foreign-language web page that an automated translation system mangles, then use microtasking to request a human translation rather than going to the expense of hiring a professional service. A firm that adopts microtasking as a practice gives its attorneys a Swiss Army knife for a variety of tasks that machines cannot handle.

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