Technology as an Enabler of Decision Intelligence

By Michael Yesudas,
Chief Technology Officer,
SunTec Business Solutions
Ranjit Palkar,
Partner – Principal,
Ernst and Young
Ranga G.K,
Principal Solution Architect,
The ability to take quick and accurate decisions is critical for business success today. Organizations are increasingly relying on technologies like AI, automation, and advanced predictive analytics to base their decision-making process and glean insights from highly disparate data residing globally and across business lines. Decision intelligence is an emerging field that comprises a range of techniques and practices that help to design, implement, and monitor decision-making models and practices. SunTec Confluence 2022 delved deeper into the strategic role of technology as an enabler in driving decision intelligence via a panel discussion. Moderated by Michael Yesudas, Chief Technology Officer, SunTec Business Solutions, the panel included Ranjit Palkar, Partner – Principal, Ernst and Young, and Ranga G.K, Principal Solution Architect, AWS.
Organizations looking to improve decision intelligence mechanisms must consider technology transformation at the foundational level as technology impacts every channel and touchpoint across the organization ecosystem. Technology, especially Cloud, has evolved and made it easier to manage, monitor, deploy and use data well. For example, enterprise data strategy has moved away from creating data warehouses and data lakes every time there is a need for intelligence. Organizations now have the option of working with data mesh architecture, published data sets and more to enable analytics and intelligence. And with advancements in cloud technology, organizations can use tools like Snowflake to store data better and access it faster and more efficiently to integrate intelligence into decision-making. It is now even possible to connect to the events engine to use real-time data and make information available at key decision points. Investing in technology across the enterprise is no longer a matter of choice, as it is a critical driver of better decision-making and business success. C-suite leaders must now focus on revamping architecture enablement on priority with the help of ecosystem management solutions.
Today most organizations and CXOs understand that technology transformation is inextricably tied to process efficiency, cost reduction and long-term business growth. Even leaders who were previously skeptical or hesitant to invest in digital technology solutions are now changing their minds after seeing how it can improve processes at lower costs and even expand the possibilities of the business offerings. Scalable, reliable, and secure technology frameworks allow organizations to experiment with practices and methodologies that facilitate decision-making, better ways of doing business and improved customer satisfaction. For example, a typical e-commerce engine would make recommendations to the customer based on their purchase history which did not really work. Today, advanced data analytics platforms in use by these companies can correlate customer data from across the world to make recommendations based on other similar behavior patterns by customers across the world. This offers customers a much wider, more varied, and relevant experience which ensures satisfaction and repeat business.
Legacy monolithic systems cannot integrate relevant data from across the organization. Neither are they scalable enough to offer different kinds of data storage and access options. Modern technology platforms allow organizations to manage data based on scale, merit, and performance needs. For example, an organization may have data that is highly durable but not necessarily high-performance. They may want to access it in batches and process it on demand. It can be put on low-cost storage platforms. It can easily be moved to a different platform for real-time analytics if required. Legacy systems do not allow such easy, seamless movement of data and neither do they provide options for storage and management based on need.
Regulations and risk management requirements do not hamper the use of technology for decision intelligence. In fact, most modern technology architecture has risk and compliance embedded in them. This is particularly important as businesses become orchestrators of customer-centric ecosystems. Multi-region, multi-industry compliance requirements will come into play in a diverse ecosystem that only technology platforms with integrated regulatory mechanisms can address. For example, an organization that provides healthcare insurance and financing will need to meet not just the regulations pertaining to the insurance and lending sector but also HIPAA. With a robust technology framework in place, the company should be able to manage multiple compliance requirements easily and, in a cost-effective manner.
The process of driving technology adoption across the organization remains a challenge. And sometimes, seeing the impact and benefits of technology implementation can help. For example, a few years ago, the CEO of an organization decided against moving to cloud technology because he felt the auditing process would become complicated. He was surprised to hear that compliance certificates are already embedded in the system and accepted by auditors. This simple availability saved the organization four months of efforts and simplified the auditing process exponentially. The CEO is now accelerating the organization’s move to the cloud and playing a crucial role in driving awareness and acceptance across the organization. Technology leaders have played a crucial role in driving comfort and confidence across organizations. And as companies across sectors continue to deepen their investments in technology, leaders must continue to build trust with key stakeholders – customers, vendors, partners, and employees, or rather focus on the entire partner ecosystem.
The direct correlation between technology and better decision-making and business success was evident even before COVID hit the world. But two years of the pandemic have changed the equation further. People are comfortable with using technology to communicate and work. They are using largely digital technology solutions to conduct their business and want secure hyper-personalized on-demand access to services and products. Organizations now know that leveraging comprehensive customer data, along with AI, automation and advanced predictive analytics is critical for decision-making. They also understand that this is an opportunity to push the boundaries and try out new business models and strategies to connect with their customers in new ways. And they will increasingly rely on technology-based decision intelligence models to innovate and grow.

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