Al Qubaisi: Our plan is to eventually implement SAS’s solutions across all the businesses and eventually replace all the older systems all in the future.
The Abu Dhabi Judicial Department (ADJD) is leveraging data to transform the justice delivery process.
Judicial systems world over are true embodiments of a massively complex data environment. The vast amounts of structured and unstructured data collected through multitudes of case types, spanning from civil to criminal case types along with the thousands of digital touch points daily across multiple channels and courts, make a Judicial ecosystem a highly intricate data environment. In a journey that started four years ago, Abu Dhabi Judicial Department (ADJD), one of the most advanced Judicial systems in the Middle East region, set in motion a process aimed at delivering visibility and analytics to its vast trove of data, in conjunction with SAS.
Established in 2007, under the Chairmanship of His Highness Sheikh Mansour Bin Zayed Al Nahyan, ADJD is today a trailblazer when it comes to Justice systems – not only in the UAE but also globally when it comes to data-driven innovation. ADJD has constantly been on the lookout to unravel value from its multitudes of data assets. While agencies struggle with first generation data analytics on structured data, ADJD’s multi-year program with SAS has passed this stage and is today tackling the new frontier of unlocking value from its treasure trove of unstructured data.
The initial implementation had humble beginnings in 2014, with a program titled “The Briefing Room” project, where ADJD selected SAS Visual Analytics coupled with SAS Data Management, a solution that enabled ADJD to discover and explore all their data spread across more than 40+ data sources. With SAS, users could discover new patterns in their business delivered through rich visuals. More importantly, they could gain insights using automated analysis.
These SAS solutions were a tool to help the department augment its reporting process with rapid data discovery, explained Khawla Al Qubaisi, Director, Information Technology, Abu Dhabi Judicial Department.
With the success of this data analytics phase as a benchmark, ADJD and SAS set about implementing a unified data management platform around its complex data sources, an initiative that culminated in the implementation of SAS Master Data Management (MDM) solution, with an objective of having a single golden truth data source.
Judicial data stored in multitudes of databases is worthless unless integrated and accessible for the decision-makers in an easy to use manner.
The challenge at the beginning of the engagement was that the ADJD data were in silos. All this massively valuable judicial data had to be extracted, standardized, transformed and loaded into a common repository that laid the foundation for reporting or advanced analytics.
With SAS, ADJD built a data warehouse for all its core systems. This platform provided its business units with access to their specific data and enabled them to generate their operational reports, insights and visualisations on their data, and ultimately make more informed decisions using SAS Visual Analytics. “Furthermore, the tools will be used by top management to visualise and discuss decisions based on reliable data and analysis,” explained Al Qubaisi.
Data has become extremely crucial for businesses all over the world. More than ever, successful government-citizen engagement comes down to the availability of high-quality, well-integrated data and not only on digital touch points. Any AI-driven analytics project starts with data; having the right quality data is very important for a machine to be able to predict the probability of future events or scenarios, and building a scalable and extendible data ecosystem was a critical business need to help drive future data-driven innovations
For SAS, a key value proposition is the leveraging of artificial intelligence for evidence-based government policy and decision making.
Based on certain real business challenges faced by ADJD around case analysis & consistency of judgements, an AI & Machine Learning approach was presented to ADJD last year at a regional SAS summit and ADJD then invited the SAS team to undertake a pilot to prove the concept. “We were very happy with the trial results. All the data requirements to implement machine learning was already available in our data platform foundation developed by SAS, which made the implementation and production transition easier,” explained Al Qubaisi.
With ADJD, the goal was to reduce their time to decision-making by leveraging the AI capabilities of SAS, said Alaa Youssef, managing director, SAS Middle East. “This is a true success story. We feel very proud of such initiatives that touch citizens directly, while also reducing the load on judicial decision-makers,” said Youssef.
“Artificial intelligence has evolved from the hubris of big data strategy discussions, which failed to live to its billing. Big data, however, provided the stepping stone to AI, because it’s impossible to build AI capabilities without having the facility to process huge amounts of data”, Youssef observes.
One of the most important use cases for AI is augmenting the human effort. Instead of staff at ADJD manually sifting through mountains of cases and selecting those to be sent to the appropriate channels, AI tools undertake this, said Youssef. “The system will intelligently sort through these cases and automatically guide them to the respective channel. All this happens in the backend, which reduces a lot of effort within the ecosystem in terms of the number of people needed to process or manage a case,” Youssef added.
AI is evolving from a trend to an actual enabler of seamless business transformation, however, the foundations of this lie in developing a data management strategy, and spans the full analytics lifecycle. ADJD fully understood that analytics is not a project, but a multi-year transformation program that starts with developing a data management strategy that allows judicial data to be accessible by multiple people across business units and enabling them with tools to drive insights.
The early SAS solutions deployed in Phase 1 helped ADJD in preparing customised, real-time reports for the management. “We sought to create solicited reports to top management and customers, providing them with all the needed information in one report and in real-time,” explained Al Qubaisi. “Additionally, this initiative was put in place with the intention of achieving overall quality and consistency of judgements,” she added.
ADJD then got into working on cross-reference analysis where data from different systems will be correlated and analysed; including ADJD operations, social and economic trends identified based on the department ’s services, eventually benefitting the Abu Dhabi government as a whole and not only ADJD, Al Qubaisi explained.
The department is also using the SAS-generated analytics across the business. “Our plan is to eventually implement SAS’s solutions across all the businesses and eventually replace all the older systems all in the future,” she added.
The SAS engagement over the past four years was phased out in three main phases: Phase one is based on creating visualisations, which involves viewing the operational performance of the organisation, gaining performance insights and ad-hoc analysis. Phase two involves the more complex data governance, which entails improving data quality, and producing a single customer data record or master data management – eventually, data synchronisations. The Third phase is the application of AI & Machine Learning models on real-world business challenges within the Judicial System starting with case analysis, involving case relationship discovery, case summarisation and identifying and predicting certain case trends.
The solution is delivering on set objectives, said Al Qubaisi. “The main aim is to eventually integrate all the reporting processes and involve all the business departments, so we can deploy SAS’s solutions across the organisation; this will happen only when all the business departments are involved in the process,” she added.
Youssef said SAS is proud of the work with ADJD which goes beyond business intelligence, to applying machine learning and AI models to help to augment and support the judicial leadership. “We have been able to tap into the massive reserves of data about individuals that is collected by the judicial department, help them analyse that to be able to understand certain trends and insights into things like criminal behaviour and civilian case behaviour, a one of kind use case in the region,” said Youssef. “We are thus leveraging historical data using AI to detect the future,” he added.
“The ultimate success of the project will be when we succeed in producing a single complete view of the entire judicial ecosystem for our business units. We initially had to provide different reports on our customers, but now we can provide one solicited ‘golden’ dashboard which consists of all the required information. To sum it up, these solutions by SAS has helped us develop a world-class Judicial data platform that helps us identify our customers, cases and transactions and the relationships with a high degree of accuracy; and process the requests for insights and information in “timely manner”, she added.
The ADJD project was never a ‘tick-a-box’, kind of implementation, said Youssef. “We have always aligned the various aspects of the project – from business intelligence initiatives to data management, to machine learning initiatives, to the organisational goals,” she said.
One of the goals of ADJD, highlighted in their strategy map and vision, is quality and consistency of judgments. “The application of ML that we have applied has a direct reflection on the consistency and quality of judgments. This is the crux of what we are trying to do – to align any data initiatives to the strategic initiatives of the organisation,” Youssef concluded.