managemnet company strategy managemanet Has Progress on Data, Analytics, and AI Stalled at Your Company?

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

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

It’s time for Fortune 1000 companies to rethink their investments in data, analytics, and AI. Of course, companies must invest in these critical business capabilities and differentiators. What they should look closely at is how they invest, and if these investments lead to the kinds of profits and the level of business value that companies aspire to achieve.

Answers to a recently released survey of Fortune 1000 and global data and business leaders indicate 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 to 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 views 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 results and implications from the 2023 survey:

  • Only 59.5% of executives report that their companies are driving business change using data, compared to 59.5% four years ago – no change.
  • A disappointing 40.8% of executives report that their companies compete with data and analytics, a decrease(!) from 47.6% four years ago.
  • A disappointing 39.5% of executives report that their companies manage data as a business asset, a decline from 46.9% four years ago.
  • Only 23.9% – less than a quarter – of executives report that their companies are creating a data-driven organization, up from 31% four years ago.
  • Finally, and most discouragingly, a measly 20.6% of executives – almost one in five – reported that a data culture had been established within their companies, a nearly 50% decrease from 28.3% of companies who reported building a data culture in 2019. Regress, not progress.

These findings are not good news. Consider that 87.8% of executives report that their companies will increase investments in data, analytics, and AI during 2022, and 83.9% expect this investment trend to continue in 2023. While 91.9% of respondents says this investment creates measurable business value, it is apparently not enough to move the needle on these key organizational change metrics.

What should companies do differently to achieve a different outcome? What do successful outlier companies do differently? With economic hardship on the horizon, companies need to be smarter about how they invest in data, analytics, and AI, and track their investments in sustainable business growth.

Having been a personal 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 looking to leverage data, analytics, and AI to transform their businesses and position. themselves for a long time.

Focus on Culture Change and its Business Impact

If you want your technology investments 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 executives surveyed identified cultural barriers, not technology, as the biggest obstacle to becoming data-driven companies. While companies are focusing investments on laudable technology initiatives such as data modernization, data products, and AI/ML initiatives, only 1.6% of executives emphasize data literacy as their top priority. investment priority.

Cultural barriers can come from education, communication, business processes, organizational structure, skill development, training, or all of the above. Change and change are never easy for a large organization, but maybe it’s time for companies to invest more time and attention – and funds – to change thinking, thinking, and ways where companies use data, analytics, and AI, if they. really serious and committed to changing their business and not just following the pack.

Instead of Boiling the Sea, Start Small

Too many companies have made huge investments in technology infrastructure intended to improve data access – data warehousing, master data management, cloud migration – that have failed to deliver the equivalent value of business. Experience suggests that companies that start small, with a focus on delivering immediate business value and establishing a foundation one step at a time, are most successful in building organizations that are driven by data for long haul.

Investing in modern data environments can be smart from a long-term infrastructure and platform perspective, but if companies can’t demonstrate business value from their data investments every step of the way, data leaders run the risk of lose business confidence, commitment, and trust. This is a recurring pattern for many organizations and a key factor in short and unstable terms of corporate chief data officers. Data leaders cannot afford to make unforced errors.

Build Strong Business Partnerships and Sponsorships at Every Stage

Like any area of ​​professional expertise, data, analytics, and AI have acquired a special language of their own, with terms like “data mesh” and “data fabrics.” Regardless of the potential value of such approaches, often these technical terms ring with impenetrable jargon that can put off other business leaders or result in a lack of confidence. This is especially true if investments in these areas do not provide clear business value in the intermediate term. Without a foundation of credibility built to deliver business results, initiatives lose momentum and their proponents lose organizational support. It’s a pattern that keeps repeating itself.

Successful data leaders blend into the organization, communicating in clear, concise, simple, and benefit-oriented language. By speaking in terms of business results, successful outcomes, and customer satisfaction – the language of business leaders – they build trust with their business partners. This helps them to identify and collaborate with strong business sponsors. Together, they work together to deliver data, analytics, and AI capabilities that produce more specific and measurable business results – more customers, happier customers, successful new products, entering new markets – directly related to data, analytics, and AI capabilities. These CDOs and CDAOs have successfully positioned themselves within the company’s business.

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

Finally, companies would be wise to seriously invest in establishing well-understood policies and practices that ensure the ethical use of data in their organizations. With only 40.2% of executives reporting that their companies have well-established data ethics policies, and only 23.8% saying the industry is doing enough, a growing critical mass of the experts. called it as a place for immediate attention.

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

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