Australia lifted the ODI Cricket World Cup for several reasons. The visible hard work and the skills of the players were crucial in this achievement.
But the rest can be attributed to an iceberg of data and analytics below the surface.
What started with footage from videotapes in the 90s is now real-time data available on cloud for pre- and post-match analysis that’s done with the help of AI. Today, the true power of AI, especially generative AI (GenAI), is based on how data is harnessed effectively.
The availability of different datasets to coaches and players has helped change traditional cricket strategies, enabling the extraction of meaningful insights, while uncovering patterns to make informed decisions on and off the field.
HCLTech’s Data Engineering and AI services have been giving Cricket Australia real-time data analytics to help gain advantages over competitors. With the transformation of its digital platform, these AI-driven data are driving strategic changes while improving player performance and fan engagement.
Not just cricket, harnessing data to unlock the power of AI is relevant across industries with a vast range of use cases.
For example, AI-ML solving real-world problems in healthcare, natural disasters, education, agriculture and many more areas rely on the vast amount of data organizations store in cloud. Here, data is stored across data lakes, data warehouses and data marts.
Store, process and action
- Data lake: Storing unprocessed data
- Data warehouse: Storing data ready to be analyzed
- Data mart: Where analyzed data resides and teams can gather actionable insights
These storage solutions represent three steps necessary for data modernization.
Among the compelling reasons behind creating a data lake, data mart and data warehouse are the need for data sovereignty, customization, predictability or predictive power and innovation. These help organizations to maintain control over their sensitive data, before analysis and insightful action.
The role of an IT partner
AI works best for an organization when it comes to harvesting and harnessing quality and unbiased data from its data warehouse.
Besides ensuring data quality, hurdles include security and compliance concerns, challenges around scalability, which includes storage and computing power, data governance and a lack of AI expertise.
Training an AI model on these inputs provides accurate results. However, this is where an IT partner comes into the picture.
Through partnerships, technology companies like HCLTech provide invaluable guidance and support. The journey starts with data modernization, which is the process of transferring data from legacy databases to modern databases like cloud. This is followed by data platform modernization, which brings siloed data together to delivery of actionable insights and AI applications.
While unlocking the full potential of data and AI, an IT partner drives revenue expansion and operational efficiency through data-driven strategies and customer-centric experiences.
It revolutionizes customer experiences through analytics-infused insights, personalization and seamless interactions, while leveraging data monetization with analytics and increasing employee productivity with data-driven automation and optimization from specific data marts.
A partnership can also help optimize costs intelligently with analytics-driven insights and efficient resource management while safeguarding businesses with analytics-powered risk mitigation and proactive fraud detection strategies.
How data and AI enhance CX
When it comes to turning siloed enterprise data into business value, creating a data lake is just the first of the many steps.
Leveraging AI in digital or customer experience (CX) transformation strategies gives an organization a 360-degree view of a customer and helps with hyper-personalization.
Alan Flower, Executive Vice President – CTO and Global Head, Cloud Native & AI Labs at HCLTech, said: “As all our clients start this journey of exploration with GenAI, they’re now reaching this point where they realize it’s all about the data, and the gravitational pull of the data is really dictating where the AI capability is executed. We would expect that to move around a hybrid or multicloud environment too.”
AI models bring together a customer’s digital touchpoints that include channel preferences, decision time, satisfaction levels, interactions with bots/reps, transaction history and next preference for purchases.
“Clients now expect AI to modernize applications faster, [and] more modernized applications can [now] be brought to cloud. They’ve also realized that they can use AI to automate the way they operate it,” Flower added.
For example, a North American pharmaceutical company partnered with HCLTech to revolutionize its internal auditing system using GenAI as its rule-based system proved costly and lacked user-friendliness.
HCLTech developed an Azure OpenAI-based, user-friendly interface to add PDFs and business rules, simplifying audit report generation and identifying document gaps using GenAI. This reduced manual auditing.
While gap prediction accuracy was improved by 95%, there was 60-75% less development effort for new document types/rules and 50% higher readability score in gap summaries.
“Clients desperate to adopt practices like site reliability engineering, need a particular skillset to master that. If AI can be used to reduce the pressure so that reskilling is not needed completely, AI will fill the gaps. That seems to be of particular interest to clients,” Flower said.
“There’s excitement around GenAI in the leadership. When a client sees that it has the right data, connected to the right AI capability, it can experience something that was unachievable in the past,” he added.
