Building up Reports on LawRD
Nelson Teixeira,
February 24, 2010
Post by Nelson Teixeira, muchBeta’s Chief Data Officer:
LawRD’s reports are devised so that any law firm manager gets an immediate answer on data submitted to the system.
To that end, we’ve identified in the system, the main Entities to which data is associated to. These are: Clients, Matters, Lawyers, Rainmakers and Performance. These entities can be individually used as value aggregators or combined as data filters.
Next, we’ve also identified all numerical Pointers on: how much we have forecast on costs, how much are we actually spending and how much are we profiting. We have also crossed these basic pointers with invoices status and the partial amonts of these dedicated to expenses and tasks. This data allows us to know, among other important issues, the Net Worth logged in the system the Plan Accomplish Ratio or the Time Productivity.
This data analysis will enable the end user with a tool for spotting, in an analytic fashion, the causes for an atypical billing period, a decrease on revenue, growth or slowing trends. When examining the issues we’ve mentioned, LawRD’s reports will tell us about: Who, to Whom, What, When, Brought by Whom, under Whose Responsability and the ever wanted HOW.
In order to ease the equation of problems, reports are sorted by Entities, each having four analysis groups: Money, Time, Profitability and Productivity. Every group contains a set of pointers clustered by the entity previously chosen. If willing to do so, users can also filter data through a form containing all six entities.
Example: lawyer John presents a 25% decrease on productivity for this month. Given his quite up to standard and regular performance over the past few months, I’m having some trouble pin pointing what is the cause for that. The issue may present three possible angles:
- John is losing focus and is just not keeping up with his usual performance, as the productivity report states.
- The firm is going through a rough spot. That can easily be concluded by the time line of the report on Turnover.
- Jonh is working on a matter that turned out to be a black hole. To check on this case, I must select the matter entity, the Time analysis group and the filter lawyer John. A discrepancy between the logged time and the billed time will sort the cause for this problem.
Given the large amount of data used in every report, which involves nearly all application’s data structures, we had to devise a strategy of data cache in order to simplify and streamline data selection. The sole minor issue here is that, data is not displayed in real time (updating happens every half hour), but when it is imperative, users can override this by manually updating it in a single click.





















