Big on data: Study shows why data-driven companies are more profitable than their peers
Head of Portfolio Marketing, Data Cloud
A Harvard Business Review survey of more than 360 executives reveals how data leaders use AI and analytics to power decision making and thrive in crisis.
It’s becoming a common belief that moments of economic challenge are also some of the strongest times to invest in innovation. More than a decade ago, a major study from the Harvard Business Review showed how, among the thousands studied, it was the companies that strategically invested in their futures during the previous three recessions that came out as leaders on the other side.
And the same holds true today. A new study conducted by the Harvard Business Review (HBR) for Google Cloud found that organizations that took a data-driven approach to their work during the COVID-19 were best positioned to navigate the unrelenting upheaval of the past few years. In particular, using high-quality data that was accurate and integrated across the organization proved instrumental in real-time decision making at critical moments..
The focus on improving technology proved to be widespread, as 81% of the 366 executives surveyed agreed that their companies responded to the pandemic and supply shocks and labor shortages that followed by increasing their investment in data and analytics initiatives overall. Furthermore, 58% of respondents increased their investment in AI initiatives.
Crucially, those investments must be properly utilized, and not every organization found they were able to successfully do so. When it came to extracting business value from data using analytics and AI, only 45% of respondents gave themselves a rating of 7 or higher on a scale of 0-10.
HBR categorizes this group as data-to-value leaders.
These data and AI leaders achieved higher scores across all key performance indicators, such as profitability, market share, and customer satisfaction. Among companies surveyed by HBR, data and AI leaders outperformed their peers across a range of key business metrics, such as operational efficiency (81% vs. 58%), revenues (77% vs. 61%), customer loyalty and retention (77% vs. 45%), employee satisfaction (68% vs. 39%), and IT cost predictability (59% vs. 44%).
One factor grounding this success appears to be the strategic value leading organizations put on their technology investments.
Leading organizations are using data, analytics, and AI as fuel for the rest of their organization’s objectives. In total, 84% of data-and-AI leaders say their organization has a clear enterprise strategy for managing and extracting value from their data, versus half of other respondents.
And when it comes to defining and executing a data strategy, the gap between leaders and late adopters is most stark in AI. In that instance, 57% of leaders have an enterprise strategy for using AI to augment decision-making, compared to just 17% of others.
We are at a tipping point for AI technology maturity, where it can deliver tangible business value in every industry. Leaders are way ahead of their industry peers in taking advantage of AI to augment their decision-making capabilities.
The survey also revealed that 91% of respondents agree that democratizing access to data and analytics is important to the success of their organizations, and 76% agree that democratizing access to artificial intelligence capabilities is crucial.
Some 91% agree that democratizing access to data and analytics is important to the success of their organizations.
Simply put, data and AI investments unlock business value, which drives data and AI leaders to be more profitable than their peers, as the HBR research underscore. Being a data and AI leader helps enhance organizational goals, the data found, such as speed of new product development, and customer satisfaction, which in turn leads to greater profitability.
To succeed in today's business environment, companies must prioritize data and AI investments and work to democratize access to these capabilities across their organizations.