Today’s interconnected world makes global crises more likely. COVID-19 has highlighted a new kind of resiliency — Digital Resiliency, necessary for enterprises to survive and thrive during such crises. Digital Resiliency is a company’s ability to rapidly adapt to disruptions by leveraging digital capabilities to restore business operations and capitalize on the changed conditions.
The IDC Digital Resiliency: The Role of Data, Analytics, and Artificial Intelligence builds upon the earlier framework and takes a closer look at the role of data, analytics, and AI in enabling an organization's crisis response and supporting digital resiliency in the future.
"The COVID-19 crisis emphasizes digitalization's role in resiliency, but it has an important side effect — never before has data and the analytical insights it generates, been so critical to enterprise survival," says Dr. Chris Marshall, associate vice president for data and analytics at IDC Asia/Pacific.
Companies often rely on their strengths in various organizational dimensions to accelerate out of a crisis, but it is their weaknesses that usually bring them down.
Data, analytics, and AI are the foundations of a digital technology platform necessary for achieving digital resiliency across ALL dimensions of an organization — whether it be operations, finance, customers, ecosystem, or even its leadership.
Shared data, analytics, and AI enable C-suite leaders, including the CIO, to accurately assess and quickly respond to changing operating environments.
Priorities in phases
As a crisis unfolds, leaders must change priorities, and with this, their informational demands for data, analytics, and AI must shift in lockstep, as summarized below:
Phase 1: Respond and Restore – At this stage, survival is everything! As such, organizations look to their data, analytics, and AI to provide fast insights into different dimensional threats across the business and help them prioritize the urgent and important.
Phase 2: Expand and Optimize – Survival is no longer at stake and there is more time to plan and analyse, so data, analytics, and AI priorities inevitably shift. Limited investments in remedial fixes are now possible around weaknesses exposed by a crisis. This may include improving financial forecasting, fixing operational issues, or supporting remote employee decision making.
Phase 3: Accelerate and Innovate – Data, analytics, and AI priorities shift again to adapt to the new business environment engendered by a crisis. Bigger investments become necessary to remain competitive. Typical initiatives include building intelligent customer databases, smart monitoring of partners within supply chains, and enterprise data control planes to support business processes and stakeholders.
