Innovation, agility and customer-centricity frequently top the list of companies’ strategic objectives, and now the most urgent priority is resilience. Given this new urgency, it’s worth taking a close look at the underpinnings of resilience and how they could be applied in any industry.
In retrospect many are not surprised that Amazon, the now-global technology giant, survived the “dot com bubble” as an early online marketplace. More recently it has become a critical business partner for many companies and a lifeline for individuals and families around the world during the COVID-19 pandemic. With operations across many industries, Amazon is in a unique position to respond more quickly and nimbly than so many other companies in part due to their skill at predicting the next shopping experience, by optimizing their resources to delight customers, and as a result of investments in innovative technologies.
To say COVID-19 has disrupted daily life and every aspect of companies’ operations is an understatement. Organizations of all sizes and types have felt the impact of changes to staff availability, shifts to online marketplaces, a practical halt to air travel, renegotiations with suppliers and financial concerns.
Turn to analytics to improve resilience
Lean manufacturing practices have not held up to the stress. Cost-cutting initiatives has been implemented at every link in supply chains, resulting in overreliance on a few suppliers and distributors. But why have shortages affected certain products’ availability more than others? What tactics have emerged that leave some companies in better financial shape than others?
While leadership, vision, and ability to execute are all contributing factors, one similarity across companies who are surviving the pandemic is a mature analytics foundation. They are demonstrating key elements of resilience by using trusted data and analytic capabilities during the crisis in significant ways:
- A global life sciences company measures engagement in a new online learning system for health care providers.
- An energy company analyzes shifts in load demands from commercial and industrial customers in order to balance power contracts.
- A global consumer packaged goods company navigates changes in near real-time to supply chains, source materials and forecasted demand to keep products on the shelves.
- A grocery store uses heat-mapping technology to monitor room capacity and identify high-touch areas that may require more frequent cleaning.
- A drugstore chain optimizes personal communication for customers to keep them informed through the right channels.
- A financial lender rapidly adapts fraud detection models to cut identity theft by 80% and keep lines of credit available.
Find COVID-19 answers with data and analytics
Read more about how SAS has helped all types of organizations respond with agility, recover effectively and reimagine the future with analytics and AI.
The five pillars of organizational resilience
And even with the confidence in their decisions made possible by applying advanced analytics techniques to critical areas, a key part of resilience is ongoing positive impact. In order to get that lasting effect, organizations can build the foundation for future resilience in five ways.
Integrate and safeguard data. This pandemic has revealed the inefficient workarounds that many companies have used to fill gaps in data quality and completeness. Resilience for the future requires capabilities to easily connect to the data you need, whether in the cloud or on site. Companies need a comprehensive understanding of how governed data is being used across the enterprise and the ability to analyze it for data-driven decisioning. Building such a data and analytics strategy will ensure that the analytics that unlock the value in normal times are resilient no matter what the nature of the disruption is.
Mitigate financial risk and fraud. Every day, companies are tasked with being vigilant stewards of capital and personal information. During a pandemic, it is even more important to evaluate financial interactions across the entire customer life cycle to reduce the risk of identity and digital fraud. Analytics can provide insights that protect all parties, while monitoring changes of customer behavior that indicate heightened risk.
Upskill in forecasting and predictive modeling. Organizations that have already established competencies in forecasting and predictive modeling know where to go for answers. Advanced analytic solutions augment this process by making models more repeatable and governed.
Evaluate and adapt the “optimal” supply chain. Estimate more quickly and accurately the impacts to product availability and revenue and overall costs for various demand scenarios due to COVID-19 and other disruptions. Determine business plans that are consistent across the enterprise and can guide the operational decisions in detailed planning solutions to balance objectives. Create a set of consistent and synchronized plans for all supply chain components.
Analytically savvy leadership. This final pillar may be the most important. It is the challenge of any leader to determine the path forward in the face of uncertainty. Whether entering new markets, determining product design or adapting during a crisis, companies use analytics to model various scenarios and predict operational impacts. Even the most accurate prediction still has some potential margin of error, so a leader’s willingness to test and learn is critical to success. Leaders will embody corporate resiliency through their communication and actions.
It is unlikely that our global economy will rebound evenly across all sectors. There will be lumps and bumps due to the aftermath of the pandemic as well as larger social and geopolitical dynamics. Today’s “new normal” may persist for months and years to come. For companies of all sizes it’s clear that a foundation in data analytics results in stronger, more resilient organizations for the decade ahead.
Even the most accurate prediction still has some potential margin of error, so a leader’s willingness to test and learn is critical to success.
- A data scientist’s views on data literacyGet a data scientist and teacher's perspective on the value of having foundational knowledge so you can more easily tell data fact from data fiction.
- Saving lives during a global pandemic through medical resource optimizationCleveland Clinic is operationalizing analytics to combat COVID-19, creating innovative models that help forecast patient volume, bed capacity, medical equipment availability and more.
- AI in manufacturing: New opportunities for IT and operationsAn AI survey reveals that leaders and early adopters in AI are making important advances and are identifying and expanding on what works as they use AI in more ways and more parts of their organizations.