NewVantage Partners has released its 7th annual survey of senior corporate c-executives on the topics of Big Data and Artificial Intelligence (AI) business adoption. The survey was first conducted in 2012 in response to Fortune 1000 business and technology c-executives who sought to understand the potential impact of Big Data and its implications for leading companies. This year, c-executive decision-makers comprised 97.5% of the survey participants, with nearly 65 Fortune 1000 or industry leading firms among the participants.
In recent years, Fortune 1000 companies have come to recognize that to compete with highly-agile data-driven competitors, mainstream firms must become more adept at leveraging their data assets – 91.6% of executives report that the pace of investment in Big Data and AI is increasing, while 87.8% report a greater urgency to invest. Yet, mainstream companies face challenges in becoming data-driven.
Most companies are still not data-driven, and won’t be anytime soon
It should not come as a shock that while Fortune 1000 companies are investing in Big Data and AI, many are not seeing commensurate results. Though Big Data and AI investment has increased sizably, the percentage of firms claiming to have created a data-driven organization is down – to 31.0% this year. Even more concerning is that this number has steadily declined over the past few years from 37.1% in 2017 and 32.4% in 2018 – when it should be heading the other direction.
Figure 1 summarizes the current state of Big Data and AI initiatives for leading Fortune 1000 firms entering 2019.
On every metric except “driving innovation with data”, firms ranked themselves as failing to transform their businesses:
▪ 71.7% of firms report that they have yet to forge a data culture
▪ 69.0% of firms report that they have not created a data-driven culture
▪ 53.1% of firms state they are not yet treating data as a business asset
▪ 52.4% of firms claim that they are not competing on data and analytics.
While 62.2% of the executives reported that their firms were achieving measurable results from their Big Data and AI investments, less than half reported success on critical metrics – only 47.6% of firms were competing on data and analytics; a modest 31.0% have created a
data-driven organization; a relatively meager 28.3% have forged a data culture. Though executives report that the pace and urgency of their investment in Big Data and AI initiatives is accelerating, for many firms the benefits have not been commensurate with the level of investment.
Leading companies are struggling with data-driven business transformation
A majority of companies -- 77.1% -- report that business adoption of Big Data and AI initiatives remains a major challenge. Business adoption of Big Data and AI initiatives must be viewed through a long-term lens. Companies must view this transformation as a process and a journey.
Figure 2 highlights the principle reasons executives cite for failing to achieve greater success with transformation initiatives.
Executives cite multiple factors -- organizational alignment, agility, resistance -- with 95.0% stemming from cultural challenges (people and process), and only 5.0% relating to technology. It is noteworthy that the biggest challenges to the business adoption of Big Data and AI initiatives stem from cultural issues – business process and people – not from technology. If companies hope to transform, they must begin to address the cultural obstacles.
In the Foreword to the 2019 report, we posed the question of whether the glass for Big Data and AI initiatives is half-full or half-empty. We concluded that “while there are still signs of emptiness, over all we see a glass that is half full and filling up slowly. Compared to, say, a decade ago, an impressive number of enterprises are data-driven today”.
Yet firms cannot afford to be complacent. Digital companies have disrupted longstanding business models with speed and force. Ultimately, we hope that companies will view the survey findings as a call to action. Though the glass is half-full, the findings underscore the conclusion that progress is gradual, and that many leading companies are progressing slowly in pursuing their commitment to data-driven transformation.
