Has Progress on Data, Analytics, and AI Stalled at Your Company?

It’s time for Fortune 1000 companies to rethink their investments in data, analytics, and AI. Of course, companies should be investing in these critical business capabilities and differentiators. What they need to take a hard look at is how they’re investing, and whether these investments are leading to the kinds of gains and the levels of business value that companies are aspiring to achieve.

Responses to a recently released survey of Fortune 1000 and global data and business leaders show that data, analytics, and AI efforts have stalled — or even backslid. Since 2012, when I launched the survey to investigate organizations’ investments in data initiatives, the survey has expanded into related topics such as analytics, AI and machine learning, the role of the Chief Data Officer, and data ethics. This year, the survey captured the perspectives of chief data officers (CDO), chief data and analytics officers (CDAO), and other senior data and business leaders from 116 Fortune 1000 companies and global leaders, across financial services, retail, consumer packaged goods, health care, life sciences, and more. The responses revealed troubling trends.

Consider the following findings and implications from the 2023 survey:

• Just 59.5% of executives reported that their companies were driving business innovation with data, compared to 59.5% four years ago — no change.
• A disappointing 40.8% of executives reported that their companies were competing on data and analytics, a decrease(!) from 47.6% four years ago.
• An unsatisfactory 39.5% of executives reported that their companies were managing data as a business asset, a decline from 46.9% four years ago.
• Just 23.9% — under one quarter — of executives reported that their companies have created a data-driven organization, down from 31% four years ago.
• Finally, and most discouraging, a meager 20.6% of executives — barely one in five — reported that a data culture had been established within their companies, a nearly 50% decrease from the 28.3% of companies reporting having established a data culture back in 2019. Regression, not progress.

These findings are not great news. Consider that 87.8% of executives reported that their companies had increased investments in data, analytics, and AI during 2022, and 83.9% expected this investment trend to continue in 2023. While 91.9% of respondents said that this investment is creating measurable business value, it’s apparently not enough to move the needle on these key metrics of organizational transformation.

What should companies be doing differently to achieve a different outcome? What are successful outlier firms doing differently? Given the economic headwinds on the horizon, companies need to be smarter about how they invest in data, analytics, and AI, and track their investments to sustainable business progress.

Having been a firsthand observer of the growth and adoption of data, analytics, and AI in the corporate world for four-plus decades, here are some recommendations for any company that aspires to leverage data, analytics, and AI to transform their businesses and reposition themselves for the long haul.

Focus on Cultural Change and its Business Impact

If you want your investments in tech to pay off, you also need to invest in your culture. This, however, is often overlooked. It should come as little surprise that 79.8% of the executives surveyed identified cultural impediments, not technology, as the greatest barriers to becoming data-driven companies. While companies pointed to investments in laudable technology initiatives such as data modernization, data products, and AI/ML initiatives, only 1.6% of executives highlighted data literacy as their top investment priority.

Cultural barriers might stem from education, communication, business processes, organizational alignment, skills development, training, or all of the above. Change and transformation are never easy for a large organization, but perhaps it’s time for companies to invest more time and attention — and funding — to change thinking, mindsets, and the ways in which companies use data, analytics, and AI, if they are truly serious and committed to transforming their business and not just following the pack.

Instead of Boiling the Ocean, Start Small

Too many companies undertake massive technology infrastructure investments intended to improve access to data — data warehousing, master data management, cloud migration — that fail to deliver commensurate business value. Experience suggests that companies that start small, with a focus on delivering immediate business value and establishing a foundation one step at a time, have been most successful in building data-driven organizations for the long haul.

Investing in modern data environments can be wise from a long-term infrastructure and platform perspective, but if companies cannot show business value from their data investments at every step along the way, data leaders run the risk of losing business confidence, commitment, and trust. This has been a recurring pattern for many organizations and a contributing factor to the short and unstable tenures of corporate chief data officers. Data leaders cannot afford to make unforced errors.

Build Strong Business Partnership and Sponsorship at Every Stage

Like any area of professional expertise, data, analytics, and AI has acquired a specialized language of its own, with terms like “data mesh” and “data fabrics.” Regardless of the potential value of such approaches, too often these technical terms ring of impenetrable jargon that may put off other business leaders or result in a lack of trust. This is particularly true if investments in these areas do not produce clear business value in the intermediate term. Without a foundation of credibility that is built on delivering business results, initiatives lose momentum and their proponents lose organizational support. This is a pattern that too often repeats itself.

Successful data leaders blend into the organization, communicating in clear, concise, simple, and benefits-oriented language. By speaking in terms of business results, successful outcomes, and customer satisfaction — the language of business leaders — they build the trust of their business colleagues. This helps them identify and collaborate with strong business sponsors. Together, they work hand-in-hand to deliver data, analytics, and AI capabilities that produce very specific and measurable business outcomes — more customers, happier customers, successful new products, entry into new markets — which are directly attributable to data, analytics, and AI capabilities. These CDOs and CDAOs successfully embed themselves within the business fabric of the company.

Don’t Forget About Data Ethics — Your Customers Won’t!

Lastly, companies would be wise to seriously invest in establishing well-understood policies and practices that ensure the ethical use of data by their organizations. With just 40.2% of executives reporting that their companies have well-established data ethics policies in place, and just 23.8% saying that the industry has done enough, a growing critical mass of pundits are calling this out as an area for urgent attention.

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Companies have every opportunity to use data, analytics, and AI to transform their businesses. Now is the moment to rethink how these investments are being made. It is time for data leaders to deliver transformative business outcomes. This is the moment to move forward and learn from the lessons of the recent past.