by Simon Pecovnik, VP of Product Management, iManage
If you’re like most people, at some point over the past couple days, you probably used Google to find an answer to a question – and it’s likely that you didn’t find the experience to be overwhelming or confusing. You simply plugged in your search terms and a highly relevant set of results appeared, gathered from the vast expanses of the internet.
On the shopping front, you might have used Amazon to effortlessly find the perfect item for your needs. And if you’re a music lover, you might have used Spotify to find a specific song to listen to – and, in the process, found recommendations for other great songs you’d like.
The seamless and frictionless experience of these consumer apps – the ease with which they give users exactly what they’re looking for – serves to highlight the value of a consumer app-style approach to knowledge management for lawyers.
Room for Improvement
The concept of knowledge management isn’t new to the legal industry, but in many organisations, it has historically remained an informal activity – and not necessarily a wholly efficient one either.
Amongst Fortune 500 companies, analyst firm IDC finds that 50 percent of company data is unsearchable, and 30 percent of employee productive time is wasted re-creating existing knowledge assets. It’s safe to say that law firms and legal services providers don’t fare much better on this front.
While there are numerous challenges in undertaking knowledge management, the biggest one is the fact that data is located in disparate locations – ranging from paper files, to individuals’ laptops and internal drives, to more formalised repositories like SharePoint and document management systems.
The net result? While a wealth of intelligence, insight, experience, expertise and knowledge exists in the law firm, it can’t be leveraged for meaningful business advantage and client benefit.
It doesn’t have to be this way. With the right approach, law firms can make finding this valuable knowledge as easy as finding a piece of information on Google, a product on Amazon, or a song on Spotify.
Unlocking the Knowledge
Let’s say that a fee earner wants to find the very best example of a real estate transfer agreement within the firm to use as a template for a matter they’re working on.
At most firms, this task is not as easy as it seems because even if data has been centralised within a single repository, much of the data is unstructured and thus unsearchable. For all intents and purposes, the various documents are just a bunch of “letters on pages,” and there’s no easy way to tell a real estate transfer agreement from a loan agreement from an employment contract.
Categorising and tagging all of the available documents – in the same way that Google, Amazon, and Spotify have indexed and categorised all of their available items so that you can easily find what you’re looking for – helps bring order to this unstructured data, instantly making it more searchable and valuable for knowledge management purposes. It should be noted here that expecting humans to manually tag and classify all of the available documents isn’t always realistic, so AI is of great use in carrying out this task.
Another thing consumer apps like Google, Amazon, and Spotify do behind the scenes in order to deliver results as effectively as they do is to constantly interpret various signals to make sure they’re delivering up-to-date, relevant results. For example, Google uses a metric like the number of websites that link to a particular article as a “signal” of that article’s usefulness and authoritativeness. Amazon and Spotify use cues of their own to serve up results that they think will be most useful or relevant to you.
Knowledge management works best when it is able to take a similar approach and leverage not just explicit information – like tags, classifications, and other metadata – but also implicit information, like how people interact with the documents and the relationships that exist around the documents.
Making sense of this implicit information – often through AI – helps identify where knowledge lies within the organisation.
For example, looking at the time and billing system and seeing that a particular professional devotes most of their billable hours towards European clients and employment law matters will automatically identify them as an expert in European employment law. Similarly, if a particular European employment law template has been downloaded hundreds of times by dozens of different people throughout the organisation, that’s a clear signal that that particular template is one of the best pieces of content for other legal professionals to leverage.
One other thing that consumer apps are very good at is personalisation. The more you use the various consumer apps, the more they get to know you and offer up items that are of the most relevance.
Knowledge management should follow a similar path. Understanding user behaviour – what topics a user has searched for in the past, what files they’ve clicked on or downloaded, what types of matters they tend to work on, and so on – enables the system to provide richer, deeper, and more precise results to the user over time. As a result, it can offer up results that are most relevant to their daily work, as well as helpful suggestions for other resources they might wish to consult.
The Right Direction
In order to genuinely be successful in knowledge management, a smart, consumer app-style approach to the function is needed. Adopting some of the hallmarks of consumer apps – including frictionless search across all data, behind-the-scenes interpretation and categorisation of that data, and powerful personalization – will be a step in the right direction for any firm that wants to make knowledge management a priority.
About the author
Simon co-founded RAVN Systems and is currently the product manager for iManage Insight. He works closely with iManage customers to understand their needs, provides input on product strategy and manages the planning and design of new capabilities that will transform how professionals work.
