It’s time for Fortune 1000 companies to rethink their investments in data, analytics and AI. Of course, companies should invest in these essential business capabilities and differentiators. What they need to consider carefully is How? ‘Or’ What they invest, and whether those investments lead to the kinds of gains and levels of business value that companies aspire to achieve.
Responses to a recently released survey of Fortune 1000 and global data and enterprise leaders show that data, analytics and AI efforts have stagnated or even receded. 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 data manager and data ethics. This year, the survey collected the views of chief data officers (CDOs), chief data and analytics officers (CDAOs), and other senior data and business leaders from 116 Fortune 1000 companies and world leaders in financial services, retail and consumer packaged goods. , healthcare, life sciences, etc. The responses revealed disturbing trends.
Consider the following findings and implications of the 2023 survey:
- Only 59.5% of executives said their companies are driving business innovation with data, up from 59.5% four years ago — no change.
- A disappointing 40.8% of executives said their companies compete on data and analytics, a decrease (!) from 47.6% four years ago.
- An unsatisfactory 39.5% of executives said their company manages data as a business asset, down from 46.9% four years ago.
- Only 23.9% (less than a quarter) of leaders said their company had created a data-driven organization, down from 31% four years ago.
- Finally, and most discouragingly, a measly 20.6% of leaders – just one in five – said a data culture had been established within their company, a drop of almost 50% from 28 .3% of companies claiming to have established a data culture in 2019. Regression, not progress.
These findings are not good news. Consider that 87.8% of executives said their companies increased their investments in data, analytics, and AI in 2022, and 83.9% expected this investment trend to continue in 2022. 2023. While 91.9% of respondents said this investment creates measurable business value, apparently moving the needle on these key organizational transformation metrics is not enough.
What should companies do differently to get a different result? What do successful outliers do differently? With economic headwinds on the horizon, companies need to be smarter about how they invest in data, analytics and AI, and track their investments for sustainable business progress.
Having been a first-hand observer of the growth and adoption of data, analytics, and AI in the corporate world for more than four decades, here are some recommendations for any business that aspires to leveraged data, analytics and AI to transform their businesses and reposition themselves for the long term.
Focus on cultural change and its business impact
If you want your investments in technology to pay off, you must also invest in your culture. This, however, is often overlooked. It’s no surprise that 79.8% of executives surveyed identified cultural barriers, not technology, as the biggest hurdles to becoming data-driven companies. While companies highlighted investments in laudable technology initiatives such as data modernization, data products, and AI/ML initiatives, only 1.6% of executives listed data literacy as their top priority. investment priority.
Cultural barriers can 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 maybe it’s time for companies to invest more time and attention – and funding – in changing the way of thinking, mindsets and behavior. how companies use data, analytics and AI, if any. really serious and determined to transform their business and not just follow the pack.
Instead of boiling the ocean, start small
Too many companies make massive investments in technology infrastructure designed 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 creating immediate business value and building a step-by-step foundation, have been most successful in building long-term data-driven organizations. .
Investing in modern data environments can make sense from an infrastructure and platform perspective in the long run, but if companies can’t demonstrate the business value of their data investments every step of the way , data stewards run the risk of losing business trust, commitment, and trust. . This has been a recurring trend for many organizations and a contributing factor to the short and volatile tenures of CDOs. Data leaders can’t afford to make straightforward mistakes.
Build a strong business partnership and sponsorship every step of the way
Like any field of professional expertise, data, analytics and AI have acquired their own specialized language, with terms such as “data mesh” and “data fabrics”. Regardless of the potential value of such approaches, all too often these technical terms sound like inscrutable jargon that can put off other business leaders or lead to a lack of confidence. This is especially true if investments in these areas do not produce clear medium-term business value. Without a foundation of credibility based on the production of business results, initiatives lose momentum and their promoters lose organizational support. It’s a pattern that repeats itself too often.
Data leaders successfully integrate into the organization, communicating in language that is clear, concise, simple, and benefit-driven. By speaking in terms of business results, success and customer satisfaction – the language of business leaders – they build the trust of their 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 results – more customers, happier customers, successful new products, entry into new markets – which are directly attributable to AI data, analytics and capabilities. These CDOs and CDAOs are successfully integrated into the business fabric of the company.
Don’t forget about data ethics – your customers won’t!
Finally, companies would be wise to invest seriously in establishing well-understood policies and practices that ensure the ethical use of data by their organizations. With just 40.2% of executives saying their companies have well-established data ethics policies in place, and just 23.8% saying the industry has done enough, a growing critical mass of experts are calling this is an area needing urgent attention.
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Businesses have every opportunity to use data, analytics and AI to transform their business. Now is the time to rethink the way these investments are made. It’s time for data leaders to deliver transformative business results. Now is the time to move forward and learn from the recent past.