Profitable Sustained Growth Aided by AI and Machine Learning

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Established in Sydney in 1827, today MinterEllison is a multinational top tier law and professional services firm with fifteen offices operating in five countries. By number of lawyers, it is the largest law firm in Australia. MinterEllison also operates in Hong Kong, mainland China, Mongolia, New Zealand and the United Kingdom through a network of integrated offices and associated offices.

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The firm rolled out its 2025 strategy with a holistic approach to its business growing profitably and sustainably. 

Although it understood current and historical performance, the strategy called for a more sophisticated, predictive lens about what might happen, particularly as COVID impacted the firm. To achieve this, MinterEllison turned to DataRobot AI Cloud platform and automated decision intelligence solution to complement its existing data analytics platform.

Shaheen Saud is the firm’s Head of Data and Analytics working on the firms Change and Transformation team. He said: “We put innovation and digital transformation at the heart of our strategy, and collaborate with our clients and people in a unique way. This demands a really good understanding of performance and opportunities.”

It prompted MinterEllison to take an innovative look at its IT and digital services infrastructure as part of the modernisation of the nearly 200-year-old law firm.

Critical Predictive Element Delivered by DataRobot

Shaheen highlighted the questions facing the firm: “How do we go beyond analysing and reporting historic and current performance and provide insight to every stakeholder on what might happen? This is the critical predictive element where DataRobot has really started to deliver value for us.

“Using a machine learning platform allowed us to learn, experiment, and fail much faster. It resulted in reducing some of the risks by taking a more incremental agile approach rather than starting with a traditional large-scale project. We started with some key performance metrics such as utilisation, work in progress (WIP), and profitability. We used the AI to make some elementary predictions. This was a sound way to help our firm begin to understand some practical uses for data science.”

With DataRobot, we flipped the traditional scenario of looking at what the technology could do for us. This time, we identified the business outcomes we were trying to achieve and then looked at the potential technology solutions and delivery models.
Grant Coutts

Chief Transformation Officer, MinterEllison

Shaheen was focused on having an agile delivery model for the way MinterEllison works with the DataRobot account management team. “They engage with our executive leadership team and drill down to what we really want to achieve. This leads to the design of the predictive model, all of the time liaising and keeping our key stakeholders in the loop.

“The agile way DataRobot immerses itself into the process while working with us has meant a shorter period between development and delivery. That level of ongoing engagement which leads to adoption is also much higher now.”

He recalled that the perceived wisdom about AI and machine learning is “that it can be an overcomplicated and massive investment of finance, manpower and resources. However, DataRobot AI Cloud is a user-friendly intuitive platform which allows non data scientists, and particularly business users to come up to speed and start delivering results quickly. Especially with the help of the DataRobot support team.

DataRobot is a user-friendly intuitive platform which allows non data scientists, and particularly business users to come up to speed and start delivering results quickly. Especially with the help of the DataRobot support team.
Shaheen Saud

Head of Data and Analytics, MinterEllison

Minimal investment to recoup range of benefits

So, with fairly minimal investment in time, resourcing and dollars, the firm adopted the AI machine learning experiment successfully with executive leadership sign off and endorsed use cases and delivery tangible outcomes.

“The firm’s executive leadership and broader finance teams now have easy to produce predictive models around performance measures like WIP, profitability and utilisation. This is strengthened by greater insights around business performance which in turn has improved decision making,” said Shaheen. 

He summed up: “The ability to translate questions into tangible outcomes using data in an ethical way is where we wanted to be. Now thanks to DataRobot making it so intuitive and easy, we are able to answer those questions.”

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ME Horiz Pos BlkRed CMYK
Industry
Law and Professional Services
Geography
ANZ
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