Larry Bodine recently blogged about Attorneys Flocking to Twitter listing the the following reasons:
- Because lawyers don’t have time to update their own bios.
- They don’t have time to write articles.
- They don’t have time to update a blog.
Larry Bodine recently blogged about Attorneys Flocking to Twitter listing the the following reasons:
- Because lawyers don’t have time to update their own bios.
- They don’t have time to write articles.
- They don’t have time to update a blog.
Since the first day I walked into a large law firm, I have been amazed at the vast amount of information that is compiled within the four walls of each of these firms. Even more so, I’m am amazed at the normalization of the data that is compiled. Each office has a specific designation number; as does each employee; each vendor; each client; each matter; each saved document; so on and so on. This type of information can and should be the Holy Grail when it comes to building a knowledge tool and a competitive intelligence resource that will leverage existing information against the firm’s future challenges. Remember, it sure helps to know where you are going, if you know where you’ve already been.
How can I link this new information to my existing information?
Thomas Kuhn’s paradigm shift theory says that once a system (usually a scientific school of thought) has answered all the questions it can and then created a bunch of questions it cannot answer, a shift occurs and a new system emerges designed to answer these new questions. These shifts occur over time as schools of thought are born, grow and die.
The legal profession is of course not immune to this idea, but it does tend to hold on to morbid systems longer as its main paradigm is precedence. This paradigm of precedence looks back, and as such remains blind or at least blissfully ignorant to many things in the future (and some things in the present). For quite some time (at least since 1994) I have wondered when the paradigm of the billable hour would mature and die enabling a shift to a new approach. Client pressure would surely force law firms to open their eyes and make the shift. Clients might even demand a new pricing approach. Well, three recent events have caused a shift in my thinking on this topic.
1) Ron Baker’s post on the billable hour debate makes the point that pricing model changes come from sellers, not buyers. This of course challenges my theory that clients will drive change to firms. Ron makes solid points on why customer driven price pressure does not change the pricing model, merely the price.
2) … which is playing out in large firms right now. Clients are really ramping-up the pressure for rate freezes and discounts. Neither of these actions change the pricing model, they merely increase the financial stress on law firms. Firms are initially reacting within their known field of comfort, doing all they can to hold the line on expenses. These efforts will buy firms time. One might argue that the length of the current economic downturn will be pivotal. Firms may ride out the downturn like they have in the past. Things always go back to normal, to the way they were. Don’t they?
3) Maybe not this time. Susan Beck’s article notes that seven of the best leveraged law firms in the US have announced layoffs or even dissolved this year. What? Leverage is the bedrock of profitability for for firms. Beck comments on leverage:
It seemed like a sure-fire way to make money. But high turnover and rocketing salaries ate into profit margins. Now, the whole pyramid model is looking fragile.
The combination of these three things brings me to a new position on the billable hour. Law firms shifting to non-billlable hour pricing will come from profitability pressure, brought in part by client rate pressures. Clients can bring certain pressures to bear on profitability, but they are not in a position to dictate law firms’ business models.
Which brings us to profitability. Law firms do not measure profitability. This statement may and should sound crazy. Firms measure billable hours, utilization, realization and hopefully leverage. But none of those measure profitability. Even Profits Per Equity Partner (PPEP) is not a profitability measure. That measure does not tell you the margins a firm has on revenue, only the average pay of an equity partner.
My Theory: Financial pressures on firms will shift the focus away from leverage to profitability. This focus on profitability will shine a bright light on the limitations of the billable hour. And this in turn will open the door to law firms seriously exploring alternative billing methods.
Having touched on Semantic Search in general terms, this post explores it in a bit more detail. Having watched a series of webcasts from Semantic Universe on the tools of Web 3.0, I have been on the lookout for interesting semantic applications that shed more light on the power of Web 3.0. From my subscription to the Web 3.0 social network site Twine, a daily digest led to Thinkbase, which is actually a visual representation of Freebase. These three sites are all built on Web 3.0 platforms, utilizing RDF datasets. In English, this means they are next generation sites that allow semantic-type searches on stores of information. Freebase is in part an RDF-formatted version of the information in Wikipedia – one of our favorite information sources. Thinkbase draws the information from Freebase and displays it in a Mind or Concept Map. The searched subject (Texas in our example) shows as the central concept, with lines connecting it to various related topics. These lines are drawn from the “predicate” portion of an RDF Triple. As a reminder, these triples are in the format: subject – predicate – object. The predicate aspect is the connection between the other two (thus the line connecting them). The map extends out as objects become subjects for the next extension.
Thinkbase is a nice illustration of Web 3.0. It’s fun to watch the maps expand as the system makes the next generation of triple connections. This system will obviously benefit from more RDF datasets, but even at this level it is quite interesting. And this application provides a real-world example of how semantic search tools will work and provide value. I’ll keep watching for more Web 3.0 / Semantic tools and concepts to show. The more I dig into these concepts, the more interesting they become.
When Lisa, Toby, and I decided (mostly on a whim) to start a blog way back in July, we had no idea that it would be as successful, or as fun as it has turned out to be. We’ve written on issues of Web 2.0 and even 3.0; Knowledge Management in law firms; Search Engine Optimization; Technology Tool Reviews; law library resources; and, compiled a list or two of must read blogs or must follow people on social media sites. It is fun to be part of a great team of people, and I think that we have challenged each other to look at issues from a different perspective than we would have alone.
I ask a simple question, and I get a simple answer (173 answers to be specific). It all started out with me thinking of some of the posts that we wrote here at 3 Geeks and a Law Blog, that probably only got read by a dozen or so people. I thought that I’m probably not alone in this, so I asked those that follow me on Twitter to let me know if they had something they wrote, or read, that they thought more eyes should look at. Well, they didn’t fail me.
The compilation below was word of mouth (or Tweet of Twitter) only. And, I’m very happy that so many of you replied (some more than once!!)
The only order to this list is the date the original post. Other than that, they are simply those articles that folks I know through Twitter felt were worth reading. Some are legal; some are library; some are technical, while others are only a sentence or two; some are funny, some are angry and others sad; most are this year’s, but a few are last, with one being five years old. I’ve enjoyed compiling the list and skimming over most of these articles (and sitting down and reading some two or three times.)
The list is rather long, but I felt that splitting it up would take away from the overall feel of what I was trying to do. You don’t have to digest this all at once. Feel free to bookmark this and come back from time to time when you want to read something you know was good enough for someone to recommend. Thanks to all who contributed and wrote these posts. Happy reading!!
I decided earlier this week to ask my Twitter friends a question. In the process I’ve learned a lot of what works, doesn’t work, and that you can hit a Direct Message Limit on Twitter (who knew??) What Works:
Direct Messages (w/Personal Feel)- I liked adding the person’s actual name (even if I had to search around to find it.) Ask The Question – Get to the point, and ask the direct question. After all, it is called “Direct” Message.
Tell ’em Why You’re Asking – I made the mistake of sending out a number of questions without saying what my purpose was. I had a lot of “why are you asking” responses.Follow-up When Needed – Look for follow-up questions, and quickly respond.
Survey Monkey – I thought I’d “make it easy” and create a link to a survey monkey survey with a quick and easy form to fill out. Got about one response from Twitter folks, and a couple from my library list serv community. So, that lead balloon didn’t fly at all!!Badly Worded Question – The initial idea was to get people to promote a blog entry that they wrote, that they felt more people should have read. So, I initially posted this: “What Was the Best Blog Post of 2008 That No One Read?” — Cue Crickets!! [chirp — chirp]Generic Question to My Entire Twitter Followers – Again, cue the crickets!! Very little response to this one.
One of my favorite things about the end of the year, is the lists of Top 10 [insert inane subject here] of 2008. I just can’t stop myself from stopping everything I’m doing to scan these lists to see what folks though was the best (or worst) of the year. And this year, I don’t just have to view these lists on VH1.
My prior musings on search tools started from a discussion on how keyword searching has reached its limits. Courts and lawyers are struggling with the immense amount of information involved in discovery and hoping for more cost effective ways of finding relevant case information without breaking the bank.
The effort to improve search goes well beyond any legal discovery issues and straight into the heart of knowledge management (KM). KM’s sister struggle works from two angles. First there is an effort to better structure information as it is captured. Second, there are efforts to create structure out of chaotic information (a.k.a. BLOBs), which is where next-generation search tools come into play.
Previously I lumped concept and semantic search into the same broad category. This time I will differentiate between the two and take the discussion another step. For now I will break search into three categories: Keyword, Concept and Semantic.
Keyword or word searching, for this discussion, is that of searching for exact word matches. This can be a complete word, such as Nation, or an extension of the root word into variations such as National, Nations or Nationalistic. The main technical feature of keyword search is that the computer is looking for binary code matches to a search query. This method has been extended and improved by adding search by data type (in a structured database) or search for multiple words within a defined proximity (e.g. within 10 words, etc.) and with known connectors (e.g. and, or, not …). The keyword method has been very useful to-date, especially when searching within large structured databases. It allows users to search by date, location, category, etc., to come up with useful results.
The problem with keyword searching is the expanding mass of unstructured information we now have. Keyword searching has become inadequate and at times counter productive to finding the right information quickly and affordably.
Concept search is one method for solving this problem. My definition: The ability to extract structure from unstructured data. In English, this means the tool can evaluate text and break it down into its component parts and ascertain their structure. As an example, feeding this article into a concept search engine, would result in defining paragraphs, sentences, nouns, phrases and perhaps even proper names and dates and numbers. This allows a database-like search, where the user can search for Name = Brown (and not get color references) or Date = December 25 and get back useful results. Concept searching is just coming into the market, with players like Recommind, Autonomy and Collexis. As an emerging technology, the challenge is good implementation. Companies and firms are attacking this problem now, so I would expect this challenge to diminish over time.
Semantic search is truly Web 3.0. Sir Tim suggested this concept over a decade ago and now efforts are under way to make it a reality. My definition: Attach meaning to each piece of data. In practice this means describing each piece of information by its relationship to another piece. In the geek world this is referred to as “subject, predicate, object” and is defined with a standard called RDF (more on that in another post). To give a very simple example: Mary has son Dave. This is referred to as a “triple.” In our semantic world we will move away from structured databases to a store of these triples. Extending our example with another triple: Dave has spouse Judy. Combining these two triples, a computer can determine that Judy has mother-in-law Mary. The result is that the machine can understand the data. In fact in this environment the machine can discover knowledge. By connecting all the triples via their relationships, the machine will answer questions we never ask. This is a quantum leap ahead of keyword searching.
Semantic search currently lives mostly in the minds of geeks and venture capitalists (with some exceptions). Still, it is a viable and growing world. What it needs are more standards and some time to develop. Its potential is tremendous, but as yet undefined.
Well … that’s my attempt to capture the past, present and future of search technology in a blog post. Future posts will delve deeper into this, as it is such a critical aspect of KM and will define KM’s future.
I get to look at hundreds of client alerts and articles written by attorneys each week, and I usually come across some pretty good articles that discuss law and technology issues. Rather than keeping those hidden in my own brain, I thought that it would be a good service of the 3 Geeks & a Law Blog to share what we think is the best article for the week.


Don’t send an email unless you would be happy to see it on the front page of a newspaper — or all over the Internet.
Excellent advice. By the way, my variation is “don’t post anything on the Internet that you wouldn’t want your Managing Partner or your Grandmother to see.” Basically a variation of what should be called “The Golden Rule of Internet Communications.”