In the post-COVID-19 era, your analytics programme may encounter a significant issue: extremely limited data. Analyse this. Customer behaviour was substantially different during the shutdown than it was before 2020. Is it feasible to predict consumer behaviour using this data when we emerge from the lockdown? If not, we will be unable to revert to pre-lockdown data. Customer behaviour has changed significantly over the past 18 months; the data we currently possess may no longer accurately represent current behaviour.
To be clear, there are no simple solutions to this dilemma. However, there are methods to optimise available resources and still extract insightful insights, even in the face of a “data shortage.”
⦁ Analytical efforts must be consistent with corporate objectives
Only 30% of companies connect their analytics strategy with their wider company strategy, according to the study. Businesses that have successfully grown AI are almost four times as likely as others to align these tactics. Organizations’ quick reaction to COVID-19 issues demonstrates that this is probably the most important stage in creating impact using analytics.
The first step in the COVID-19 reaction was to identify the new business problems that arose overnight. To solve these problems, several companies established central nerve centres, combining business and analytics resources to create new data streams, report on business-critical issues, and forecast the future of their company, customers, and suppliers.
In the face of everyday COVID-19 difficulties, businesses were ready to implement analytics-driven solutions that would help leaders change course and plan for the future.
⦁ Despite appearances, functional silos are more flexible than they seem to be-
Before the crisis, studies indicated that those reaping the most benefits from AI were more inclined to form cross-functional teams to address business issues (62 per cent, compared with 23 per cent). During this crisis, many companies immediately assemble cross-functional crisis response teams with all key stakeholders to create analytical solutions for quicker reaction.
After collaborating on a forecasting tool that anticipates sales by market and vehicle type across several dimensions, including COVID-19’s macroeconomic impact, consumer acceptance of new automotive technology and trends and regulatory policies, one auto-parts supplier’s leaders could quickly adjust production capacity. Before COVID-19, these business divisions operated separately and seldom interacted. To their surprise, marketing had already gathered and routinely utilised this data. Disconnects between these teams during the crisis would have delayed reaction times and perhaps caused supply-chain bottlenecks.
⦁ Simplify operations by prioritising hybrid cloud use and shifting more business activities to the cloud.
We can’t afford to be lazy or nostalgic. There is no going back to normal. The stakes are too high and the dangers too severe. Business leaders must prepare their organisations for perpetual uncertainty, upheaval, and change.
⦁ Full decision-making authority is required for frontline staff-
People on the front lines making data-driven decisions rather than top-down decisions is another necessary culture transformation for analytics-enabled companies. Change is difficult for many companies because it disrupts well established corporate procedures and attitudes. During a crisis, companies have easily given frontline workers decision-making authority.
⦁ Prepare yourself for model drift by being familiar with data flaws-
A new set of data problems emerged as a result of the crisis, resulting from changes in economics and consumer behaviour. For one, data problems linked to the pandemic challenged the resilience of even well-honed and calibrated models. The results of one major industrial firm’s model for predicting worldwide demand no longer fit inside the model’s limits. So, the company had to reset model boundaries, use new modelling methods, and add new data sources.
Leaders also had to admit that although current data was not perfect, it might nevertheless provide valuable insights when combined with human judgement.
The Bottom Line
After all, fast change is necessary for company survival. Certainly, certain issues will take time to resolve. We think that leaders that learn from COVID-19 reactions, accept that the future will be different, and build on new—and pragmatic—ways of working will not only survive but also flourish.