Losing insight of data

There are many ways of describing a firm’s relationship with data, with ‘data-led’ and ‘data-driven’ being some of the most popularly used terms. There are implications for relying on these two methods, as decisions based on data with limited context can lead to poor outcomes or inaction. Any findings and conclusions are necessarily short-term and tactical rather than long-term and strategic. Data is by nature siloed, meaning it lies within the system of record. Drawing conclusions based on a single dimension of data can limit the efficacy of any resulting action.

A more effective approach is to become ‘data-informed’. Related and impactful data in other silos of data can improve outcomes because a bigger picture can be drawn around it, offering improved insight about what the data is telling you. This combination of related data results in information, and reliable information allows your firm to develop strategies that are informed by data rather than driven by it. A firm can optimise its operations using data contextualised against an established, optimum goal.

Let’s take user adoption in a document management system as a simple example. Traditionally, adoption is measured by a count of documents or emails created in the system – this information is measured by individual, department, practice area, or location. However, does it matter if a particular user creates 100 documents a week compared to someone in another department who creates five? Would you infer that one works harder or uses the document management system (DMS) better than the other? Of course not. But when you only have raw data from a single silo (the DMS), that is often the only conclusion you can draw. The type of work will be radically different, and one practice will generate more documents than the other. A count of documents alone does not provide sufficient insight to draw conclusions.

Firm knowhow can be enhanced by providing better information about usage for knowledge lawyers to review. These data points are often from different silos, but, when combined, they provide information to improve how we work

Augmenting document filing information with data from other systems – adding context – can lead to something more meaningful. For example, if a lawyer creates 10 documents a week in the DMS but 20 outside of it, adoption of the DMS is low despite what the raw number of 10 properly stored documents suggests. Answering this question requires integrating data between systems and surfacing it in a meaningful way.

When considering the risk inherent in exactly how data is handled, compared to how the firm needs the data to be handled, not connecting data from various sources can create additional data analysis dysfunction – and perhaps risk. For instance, a firm may be required to have unique controls to ensure that all data is adequately secured as agreed to in outside counsel guidelines. Issues arise when low user adoption levels result in documents stored outside the controls put in place. Combining data will be your best chance of catching problems before they are out of control and out of compliance.

Back in context

Today, firms use technology to help combine data from other systems, including from outside sources, with the goal of transforming data into information. Firms aggressively using enterprise search technology, for example, can federate search results from a number of sources at once. For example, searching for the topic “Fraudulence Conveyance” will return results from documents and emails, as well as which matters, clients, and which lawyers have experience in the topic. Enhanced metadata products can provide even more information, like judges, courts and experts who have dealt with the subject. Firm knowhow can be enhanced by providing better information about usage for knowledge lawyers to review. These data points are often from different silos, but, when combined, they provide information to improve how we work.

Although combining data allows for better, more data-informed decisions, the proliferation of data can also lead to ‘analysis paralysis’, where too much data to sift through from too many sources will result in complexity that can prevent a truly data-informed outcome. Modern data analytics tools are great at managing the ‘too-much-data’ conundrum, however. Consider the user adoption question again – eSentio’s third-generation DMS adoption tool uses Microsoft’s Business Intelligence (MS BI) system to provide a layered, drill-down solution. A variety of simple, high-level graphs paint the firm-wide picture by practice area, department, office, country and so on. You can quickly drill down into smaller groupings, alternative groupings, and ultimately the individual user when something looks interesting. This kind of simple, powerful interface encourages the habit of being data-informed.

Developing a data strategy requires information to be combined in novel ways across systems using analytic tools, data lakes, data fabrics and other data integration techniques. Firm intranets, deal databases, and marketing systems that can extract relationship strength, for example, are all tuned to building information from raw data across many systems.

Look at which business goals your firm wants to achieve and what data is needed to support those goals, as being data-informed can only help you achieve them.

To find out more, visit: www.esentio.com