AI and analytics trends are shaping the companies’ operations, embedding data-driven decision making, to deliver promised business resilience.
Global businesses are quickly evolving into something that they could have never anticipated before COVID-19. Enterprises are realizing the importance of building intelligence-based capabilities to prepare for, sense, and respond to upcoming disruption. They are, today reassessing their use of AI and analytics to ensure that the businesses are resilient enough to endure further shock from such future black swan events.
The ability to collect, organize, analyze, and react to data will be the new differentiator in business operation. The radical changes in personal, professional, and societal routines have resulted in unparalleled shifts in consumer behavior. Consequently, the historical data that fed many of the analytical models have quickly become outdated, incomplete, and unsound, even obsolete.
Organizations will look forward to conducting model and data audits to identify weaknesses and errors in operational, financial, and risk areas. Sustaining this will have a new emphasis on data governance. Enterprises must take a forensic approach to the real-time data capture across all formats and forms, both externally and internally. Cloud computing allows data to be verified and stored securely while being available across multiple zones for deep insights and analysis.
Analytics led operations
Before the pandemic, there was a frequent disconnect between an organization’s analytics and its strategic priorities. Now, the non-digital-native firms must put analytics at the very core of their operations. Time and data will form the backbone of all existing business units, from sales and performance forecasts to supply chain optimization and procurement. To achieve this, organizations will have to develop an analytics-led culture.
Businesses are able to seize the opportunities brought in by digital twins to improve their predictive powers while bringing down the cost of service. As industries emerge from the pandemic, more organizations will henceforth turn to digital twins of their supply chains to better prepare for unanticipated shocks, and to build a resilient and intelligent ecosystem.
However, with the sudden increase of real-time data from rapid digitization, the adoption of digital twins is expected to grow across supply chains and manufacturing units across modern business operations.
When faced with black swan events, the most calibrated and well-honed models also quickly lose their predictive power. Several organizations are looking to multiply the quantity and diversity of data available by leveraging machine learning techniques to create ‘synthetic’ data for model development. Such vast sets of realistic data can be leveraged to train predictive systems, calculate risk measures, and stress test portfolios. Much of such work is still at the research stage, but industries can expect a growing interest in this area as the world grapples with the impact of unprecedented events like COVID-19.
It is evident that this pandemic has forced business leaders to reassess and reconsider their analytics capabilities to accelerate their digitization journey. In the world ahead, business leaders need to embed data-driven decision making at all levels of their organizations to gain greater resilience and intelligence.