The Elements of VUCA & What They Mean for Data Management in 2020

While 2020 has seen a radical economic shake-up, it’s only the latest development in what many business analysts see as a growing trend. First coined in the late 1980s, the acronym “VUCA” (volatility, uncertainty, complexity, and ambiguity) has been rising in popularity since the Great Recession as a succinct description of the “new normal” for the global economy.

 
During these difficult times, the need for good data and analytics is greater than ever. Intelligent, data-driven decisions and accurate forecasts can help you weather the storm and come out on the other side in one piece.

Below, we’ll discuss how each element of VUCA is affecting businesses, and why reliable, accurate data is a must-have in this tempestuous economic climate.

1. Volatility

The jagged graphs of stock market indices in 2020, indicating cyclical patterns of crashes and recovery, are the most obvious evidence that the economy is more volatile than ever. In March 2020, the Dow Jones Industrial Average recorded daily losses and gains between 1,000 and 3,000 points—including a loss of 2,997 points on March 16, the most ever on a single day.

Yet the stock market is just one indicator of potential volatility in the underlying economy. In 2018, for example, the United Nations predicted: “As the normalization of monetary policy in the United States and other developed economies gains momentum, financial markets may be subject to large corrections and sudden spikes in volatility.”

Meanwhile, new business models have shaken up entire industries while former giants grow obsolescent.

2. Uncertainty

In times of volatility, the best recourse is to rely on the cold, hard facts—yet too many organizations are challenged by unreliable data that causes conflicting opinions and a splintering of organizational truth.

According to the Harvard Business Review, only 3 percent of executives met the minimum acceptable data quality standards (97 or more correct data records out of 100). Gartner estimates that poor data quality is costing businesses an average of $15 million annually.

The good news is that more and more organizations are taking the issue of data quality seriously. 86 percent of data and analytics leaders cite “defining data and analytics strategy” as their top responsibility.

3. Complexity

Data and analytics leaders face difficulties not just with data accuracy, but also with the volume and variety of their enterprise data sources. Many have lost confidence in their own ability to maintain basic quality standards as the complexity of their data increases.

In a 2019 survey, one-third of marketing professionals cited “data complexity” as among their greatest challenges—more than any other issue. Another survey by Workiva found that 97 percent of CFOs worry about their financial reporting process, including issues with data integrity and too much manual work.

4. Ambiguity

With data quality issues and spiraling complexity, ambiguity is greater than ever before. When causality is nearly impossible to pin down, financial planners can only experiment by turning dials, without knowing what actually worked and what next steps to take.

Cutting through the fog of ambiguity has therefore become one of business leaders’ top priorities. However, not every organization is ready to confront this issue head-on. According to a DDI survey, 31 percent of HR professionals believe that their company leadership is unprepared for the challenges of an ambiguous business landscape.

VUCA gives us a big-picture view of the situation we’re in – and some of the challenges companies are facing. Download our white paper, “Smart Financial Planning in a Stormy Economy,” to learn about the steps you need to take to prepare for what 2020 may hold.