The Covid crisis has put tremendous levels of stress on analytics/models. To remain competitive, businesses must reshape their approach with more sophisticated practices and tools, our research reveals.
Covid disrupted supply chains, shifted vast numbers of employees to remote work, changed consumer behavior dramatically, and drove abrupt shifts in demand. With companies increasingly relying on analytics/models to chart their course through the world, these whiplash-inducing shifts have underscored a key reality: Analytics/models and the data they depend on are “perishable.”
Our recent survey of 600 executives, conducted in September 2020, examined how the Covid crisis has impacted the way organizations handle data management and analytics/models. It underscored the extent of these disruptions; a significant number of companies are now reshaping their approach to analytics.
Some of the survey findings include:
- Our research found that 83% of companies have either completed Covid-driven assessments on their analytics/models (37%) or have them in process (46%). The most common issues identified were analytics/models being overly weighted toward pre-Covid data (51%) and not being flexible (46%).
- Roughly two-thirds said that since the emergence of Covid, they have been developing new analytics/models, evaluating and refreshing their existing analytics/models, refreshing databases and integrating new data streams such as geo-location, social media and cell phone data.
- Three-quarters said that since the crisis, they had started relying more heavily on scenario planning to assess the potential impact of extreme events, while 71% said they were making greater use of real-time data and 67% had increased their use of descriptive analytics of current trends.
The ability to work with current, accurate and relevant data and models that seamlessly adjust to change will be a vital business capability – and critical to informing advanced artificial intelligence (AI) capabilities needed to drive performance. Ultimately, those companies that successfully make the transition to new, more agile approaches to analytics – what we call intelligent decisioning – will be in a better position to navigate a volatile world to stay one step ahead of change.