Overview

  • Leading Australian Consumer Law Firm
  • Proud history of providing a voice for Australians who need access to justice
  • Over 800 Employees
  • $160M+ annual revenue

The Challenge

After moving the company from loss-making to profitable over a period of four years, an inquisitive and analytical leadership team at a leading Australian law firm saw the opportunity that advanced data techniques presented for their firm.

Inspired by legal companies in the UK who have had their hands forced through reform and US software companies who automate litigation insights, the Chief Financial Officer saw three opportunities for analytics to influence the ultimate organisational goal of “delivering the best outcome for clients in the shortest possible time”:

  1. Predicting and improving the outcome of a case
  2. Predicting and improving the duration of a case
  3. Putting knowledge in the hands of lawyers

An initial assessment by the client pointed to a low level of maturity across required data components to adopt legal analytics, and the inhouse data and analytics team were already at capacity, which led to the engagement with Ignite.

Our Solution

Many organisations looking to improve their data and analytics capabilities take an “architecture led” approach – defining a target architecture for each component and then migrating all data elements. This approach helps build out strong foundations but can be costly without any immediate return.

Others opt for a “use case led” approach, focusing on identifying and filling data gaps that deliver value upfront. However, this approach has a proven track record of leaving a history of “production prototypes” in its wake, and if poorly selected, the value derived from the use cases could be trivial and jeopardise the need for change.

We approached the project with a best of both world’s approach. In eight weeks, Ignite:

  • built a prototype analytical model through their Proof of Value methodology, to predict the likelihood of case outcome, but more importantly provided learnings to inform what is required to deliver use cases at scale.
  • future-proofed these learnings through our Analytics Pathway methodology, and created an improvement pathway that allows the client to lift their data and analytics capability, whilst focusing on delivering results incrementally and continuously.

“For leaders, understanding the risk of adopting models and the risk of not adopting models is vital.  We could be the first to adopt and get it wrong, or be the last to adopt and miss the opportunity.”

Results

Proof of Value

Ignite’s Proof of Value methodology, allows for the determination of project success within time-boxed scenarios, ensuring feasibility of a project without monetary or time wastage, while allowing for the exploratory nature of data science.

One of the key outputs of the Proof of Value methodology is an evaluation in business terms. By their nature predictive models are not 100% accurate — understanding and articulating the inherent business risk of adopting these techniques is key. It answered three key questions to take the project to maturity:

  1. What is the opportunity that data science presents?
  2. Is the opportunity feasible?
  3. Tools to help practitioners act upon their portfolio


Predicting the outcome of a case and helping practitioners analyse their portfolio provides a potential material improvement in the overall win/loss ratio for the client. In an industry driven by “No win, No fee” this presents a substantial upswing for both the firm and its clients. This in turn became the foundation for the required investment in data and analytics.

Analytics Pathway

From the outset, the focus was to extract learnings from the use case, and inform the improvement pathway required to realise potential value at scale. Ignite’s Analytics Pathway focused on three key areas:

  1. The ideal analytics architecture leverages capability that is already available to the client, and incorporates leading capabilities such as Microsoft Power BI. With an existing strategic investment in Salesforce, the potential for bleeding edge capabilities such as Salesforce Einstein was also evaluated and positioned for future horizons. 

  2. The legal industry has a relatively small amount of structured data, which if not captured efficiently, can make the use of advanced data techniques impractical. Furthermore, the industry is rich in unstructured data, which can lose accuracy during translation. An outcome of the Analytics Pathway was to inform how data capture processes at source needed to improveto maximise the potential of ongoing return.

  3. An area often underestimated by organisations looking to introduce advanced analytics capability is the impact on its people. The Analytics Pathway work assessed the desired outcomes and architecture to provide organisational capability recommendationsthat mitigate risks anticipated from potential skills shortages, capacity constraints and gaps in governance.

Where to next?

This leading consumer law firm has made an opening statement in the case for legal analytics. The use of big data and predictive analytics in the legal field is a relatively new concept, with the legal practitioners ultimately delivering the verdict.  But with the rapid advancement of data analysis techniques like Machine Learning, Optical Character Recognition, and Natural Language Processing, it is only a matter of time before any reservations are overturned.

Technologies

We believe the best results come when data enables people.

Contact us to find out how we can enable yours.