Creating Organizational Change Resilience with Data Analytics
Identifying and anticipating the unknown creates a competitive advantage when aligned with organizational change capability. Growing revenue amid uncertainty amplifies the need for organizations to make data-driven decisions. This past year every organization's ability to respond to significant disruption was tested. A recent study on the economic impacts of COVID-19 found that small businesses were among the hardest hit. Over a third of the small businesses in the United States in the leisure and hospitality sector reported no financial transaction data between January to September 2020.
Organizational Change Resilience is "the ability to respond productively to significant disruptive change and transform challenges into opportunities" (Witmer et al., 2016).
A scientific study of 101 companies revealed that big data holds a key for helping organizations detect and respond to disruption. Descriptive data analytics improve sensing, and predictive data analytics enhance a company's ability to change and seize new opportunities.
Descriptive Data Analytics: The interpretation of historical data to understand better changes in a business. Examples include social media usage and engagement, organizing survey results, and operational efficiency data trends.
Predictive Data Analytics: uses historical data, statistical algorithms, and machine learning to identify the likelihood of future outcomes. Examples include predicting customer preferences based on past purchasing behaviors, predicting employee retention flight risk based on assessment data, and predicting workforce staffing levels based on seasonal trends.
One theme with organizations that remain resilient amid change is sharing data with decision-makers openly. According to the International Organization for Standardization (ISO) on the principles and attributes of organizational resilience (ISO 22316:2017), knowledge and information need to be:
accessible, understandable, and adequate to support the organization's objectives;
effectively shared to enable decision-making;
recognized as a critical resource of the organization;
created, retained, and applied through established systems and processes;
shared in a timely manner with all relevant interested parties;
applied in organizational learning.
Although not easy to implement, data analytics investments provide competitive advantages by using data to foster growth and improve decision making.
An organization's ability to improve its organizational change resilience and data analytic decision making is connected to its culture.