Using current and past data to making educated predictions about the future can boost business survival in the post-COVID-19 world.
Advanced analytics is an umbrella term for several sub-fields of analytics that work together using predictive capabilities to project future trends, events, and behavior.
This gives organizations the ability to use advanced statistical models such as ‘what-if’ calculations, as well as to future-proof various aspects of their operations. The key areas of advanced analytics include predictive data analytics, Big Data, and data mining.
DigiconAsia: Which sector can benefit most from advanced analytics?
Jason Loh (JL): Analytical solutions are beneficial to all industries and organizations of any size and structure. Data-driven work is going to be the way forward. Organizations must treat analytics as strategic assets that are central to their functions, roles, and processes.
Examples of sectors that can benefit from advanced analytics include:
- Financial industry/banking: It is crucial that advanced analytics be used in supporting banks in compliance in credit loss, credit scoring, the risks of doing business, and protecting customers from fraud. Advanced analytics can also be used in driving customer-intelligence initiatives to predict customer behavior, which can help in customer segmentation and marketing campaigns for better customer engagement.
- In governments: advanced analytics can support and enhance the government-citizen experience, improving the outcomes for citizens. Advanced analytics support government law enforcement for crime investigations and public safety by providing strategic analyses and by identifying persons of interest for behavioral monitoring.
- Public Health: During the pandemic, governments have also used analytics to track and predict infection patterns to plan resource allocation. A case in point: in the Philippines, the Southern Philippines Medical Centre used a visual analytics dashboard to optimize critical hospital bed capacity and medical resources and to anticipate strain on the healthcare system.
- Manufacturing: The sector can perform the necessary pre-emptive maintenance of equipment, ensuring the machines are running efficiently and preventing downtime or delay.
DigiconAsia: Are most businesses, regardless of size or clientele, equipped to incorporate advanced analytics into their operations?
JL: Businesses of any size or clientele can incorporate advanced analytics into their daily activities with ease. It is just a matter of adapting to a new set of systems and processes that eventually make managing the working structure much easier.
DigiconAsia: Have advanced analytics been proven to play an effective role in the recovery of businesses during the pandemic?
JL: We have seen advanced data analytics help businesses across several industries in the recovery process during the COVID-19 pandemic.
Retail: A global consumer goods company needed to understand COVID-19 impact on sales and production forecasts of key products with supply chain restrictions and staff shortages. With advanced analytics and scenario forecasting, we helped to analyze consumer behavior based on historical patterns, created multiple scenarios based on supply chain constraints and other inputs, and predicted future sales volume by product and geography.
Banking: With rising unemployment and disbursements of COVID-19 stimulus funding, one financial institution needed to mitigate the risk of third-party fraud and first-party credit abuse in order to keep access to credit available. The bank rapidly deployed new analytic-driven rules to redirect high-risk applicants into a different authentication process. Through enhanced customer profile assessment, they can now keep the product open on the market in order to fulfill the short-term financial needs of their customers.
According to Loh, the pandemic has accelerated the adoption of analytics and cloud-based solutions, but the APAC region was already heading in this direction before the global crisis. His advice is for organizations to take a three-pronged approach to any crisis:
- Respond: Use rapid data management and analysis to quickly assess and understand the crisis landscape, build situational awareness to adjust to, respond to and mitigate disruptions.
- Recover: Assess needed changes to ensure the organization has the ability to adapt and modernize for operations in the new landscapes of business and public sector environments.
- Reimagine: Looking to the future, advanced analytics solutions can help customers proactively plan for new industries, new operational models, and new personnel needs. This will build the capabilities needed for resilience to future challenges.
“At the end of the day, data without analytics is value not realized—many companies have volumes of digital data but are unable to derive value from it, and that is where data analytics plays a crucial role,” Loh concluded.