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Analytics and custom scoring matrix used to focus large review for fast, defensible results

Salient applies iterative improvement to analytics and custom scoring matrix to focus the review of disciplinary hearings and case documentation to help a law firm rapidly investigate wrongful dismissal allegations for their government department client.

Client Sector: Law
Technology Used: AI, eDiscovery, Reveal
Democratising ediscovery

The Challenge

Review case documentation and prioritise where to focus

The client approached Salient Discovery (Salient) after being mandated by a government department to review five years’ worth of employee disciplinary hearings and cases. This was in response to public allegations that the department had been purging employees who were believed to be in disagreement with the current leadership.

To successfully determine potential unfairness, the client would need to not only review the formal case documentation, but also valuable ancillary information relating to role players, case outcomes, the nature of offences etc. stored in a separate Human Resources (HR) system.

Deadlines were tight – reviewing the case documentation, alone, would take too long and only deliver half the picture. The client’s challenge to Salient was to provide a solution that would help prioritise disciplinary cases based on the likelihood of unfairness, and leverage insights from all the available sources, including the separate HR system.


  • Tight deadlines
  • Five years’ worth of documentation to investigate
  • Multiple data sources included formal case documentation and ancillary information stored in a separate HR system


  • Salient’s analytics and custom scoring matrix enabled:
    • The identification of cases with the highest likelihood of impropriety/unfairness for review
    • The elimination of cases with the lowest likelihood of impropriety from review
    • The defensible reduction of the review burden for a shorter project timeline
  • Client was able to complete the review within deadline and substantiate their findings through the scoring matrix and subsequent review of case documentation.
Our solution

Through the initial use of analytics and Salient’s scoring matrix, the client was able to identify cases with the highest likelihood of impropriety and unfairness. These were prioritised for review.

The scoring matrix was also able to identify cases with the lowest likelihood of wrongdoing. These were eliminated from the review, reducing the total number of cases under investigation and shortening the overall project timeline.

As a result, the client was able to complete the review within deadline and substantiate their findings through the use of the scoring matrix and subsequent review of case documentation.

Expert insights

To reduce the time needed for review, Salient used the case information from the HR system to build an analytical “scoring matrix” and visualisation of potential unfairness, based on allegation, process followed and outcome. The various tests used by the analytics were developed with the assistance of labour law specialists and senior counsel.

Prioritised review

The matrix assisted the client in identifying high-risk cases, as well as trends across criteria such as chairperson, department, allegation, outcome and more. It enabled the prioritised review of the likeliest cases of impropriety, and the identification of a secondary subset of cases for review based on their association with strongly identified trends and/or similarities.

Accelerated analysis with risk scoring

All disciplinary case documentation was loaded into our SaaS eDiscovery platform and overlaid with disciplinary case metadata extracted from the HR system alongside the risk scores calculated by our scoring matrix. Labour law specialists then reviewed and coded the documents for possible impropriety and/or unfairness. This coding decision was fed back into the analytics to refine the scoring matrix and iteratively improve its accuracy.