Analytics and resilience, what we can learn from a pandemic
By: Olivier Penel
Tags: Analytics, Resilience, Data4good, Data Science

Driven by necessity, changing for the best

As storms rage, organizations must adapt fast if they want to survive and recover quickly. However, the real challenge is in the long term. Once the crisis is over, nations and corporations will need to reconsider how they operate. They will need to learn from those organizations that managed this crisis better and use their experience to build more resilience in their own operations. Changes will be widespread and likely to fundamentally transform certain aspects of conducting business. In many cases, this transformation will involve a more extensive and systematic use of data analytics to drive more automated business decisions.

This evolution starts with individuals, driven by necessity, in a situation of lock-down. Even the less tech-savvy people have ‘gone digital’, adopting technologies they were not using before, for instance to stay in touch with their family and friends, to work remotely, to use digital services for banking, shopping, virtual doctor visits, administrative procedures, gym and music classes, etc. This massive rush to the on-line world is boosting the development of digital services and triggering a sharp increase of registrations and the associated data available for analysis.

Effectively, the crisis is proving to be a catalyst for change in business practices, and an accelerator of digital transformation across all industries. I believe that this momentum will be sustained over time and amplified by the subsequent quest for greater resilience.

Marketing departments will revisit their go-to-market approach as they become more reliant on their digital marketing strategy to the detriment of trade shows and exhibitions. When all touch points with prospects and customers are turning digital, the role of data, analytics and customer intelligence becomes even more critical.

Supply chains will become more agile. Analytics will help design factories for greater adaptability, allowing scaling up or down production or re-purposing production lines at short notice (as LVMH did when they decided to switch production from perfume to hand sanitizer). Fully digitized supply chains will make it easy to move production from one factory to another, to provide alternative sourcing and logistic network options, or to adopt a ‘made-to-order’ approach, connecting design and merchandising teams with manufacturing facilities to streamline lead-time production. We will look at better integrating demand forecasting and planning with POS data and using machine learning technologies to predict shifting consumer trends at short notice. Integrating data from social media and using sentiment analysis can also be used to anticipate stock replenishment strategies based on the possibility of panic buying behaviors. Retailers can use this insight to make sure they keep up with the demand, but also to communicate with customers when and where they can shop or to optimize staff assignments across POS and warehouses. What is encouraging is to see how those capabilities introduced as part of the response to the COVID-19 crisis will deliver benefits far beyond the crisis itself. For instance, the use of analytics to optimize medical resources during the crisis will carry on overtime and make healthcare systems more efficient in the long run.

With regard to financial resilience, I think that we will see an increased focus on financial risk management, especially when it comes to liquidity and cash reserves. Scenario analysis, contingency planning and stress testing will go up on the list of board-level priorities. Forecasting and predictive analytics will play a key part in strengthening organizations risk assessment and readiness and allow them to better plan for the unknown. This will happen not only in the financial services sector, which is heavily regulated already, but also in other industries that have less maturity or experience in this area.

Fraud and cybersecurity represent another type of risk that is amplified in a time of crisis, especially when large numbers of people and businesses are turning to the digital realm to carry on with their lives. Opportunists looking to exploit a crisis like this for personal gains must and can be stopped at the gate. Again, financial services tend to be well equipped and mature in their approach to protect themselves and their customers against cyber criminals, but in other industries such as retail and communication, the pandemic is an opportunity to raise the bar against various types of fraud, and the benefits of doing this will remain in the long term.

This list is certainly not exhaustive, but one thing is certain: for those changes to be effective, organizations will need, more than ever, reliable data and advanced analytics to create actionable insight and make the right decisions.

Data should be readily available and reliable so it can be used to fuel decision making. Self-service data visualization and exploration capabilities can help to quickly extract hidden insight from the data without having to call on specialized technical skills. Predictive analytics and decisioning capabilities are critical instruments for Captains to steer their ships in the storm and beyond. How successful they are will depend on how quickly they can access the data they need and how effectively they can use this data to make informed and timely decisions that will save lives, jobs, and businesses.

To carry on the conversation, join me on June 23 for a short webinar.