Why Your Investments in Data May Not Be Producing Results
You would be hard-pressed to find a CEO in 2022 who does not openly speak of a desire to cultivate a ‘data-driven culture’ for their organization. According to a recent survey of Fortune 500 executives, 92% said they are investing more in analytics, AI, and machine learning than ever before. The survey, conducted annually by NewVantage Partners since 2012, has demonstrated ever increasing budgets for analytics and data science. However, after years of investing in talent, tools, and infrastructure, only 27% of Fortune 1000 CEOs feel that their organization has achieved its goal of becoming ‘data-driven.’
So why, after nearly a decade of breathless hype and millions of dollars invested in analytics, data science, machine learning, artificial intelligence, etc., are CEOs of some of the world’s most celebrated businesses still struggling to achieve this perceived state of data bliss? If they can’t succeed with deep pockets and world-class talent, what hope is there for small to mid-size businesses who want to harness the “power of data” for themselves? Has pouring more and more money into new data initiatives become a kind of fool’s errand? The answer to that question is a resounding yes! But also no. Let me explain.
In the decade since Harvard Business Review famously declared that the role of data scientist has become the ‘sexiest job of the 21st century, organizations scrambled to jump on the data hype train before it passed them by. In their minds, that train was packed with competitors who were now using the magic stardust of data to gain the advantage. Why then are so many CEOs feeling let down by the results? In our experience, the answer comes down to two issues:
1.) Lack of a coherent data and analytics strategy.
The use of data and analytics is an integral part of marketing, sales, and operational strategies. Ironically, data teams themselves often lack a well-thought-out roadmap for sustained growth as a business function.
2.) A bias towards the novel at the expense of the foundational.
Executives are being pummeled by messages from industry experts, salespeople, and the business press introducing new and exciting data-driven possibilities every day. This leads to top executives asking questions like: “Shouldn’t we go all in on the Internet of Things?” “Are we doing machine intelligence? What about artificial learning?” “Have we invested in deep-thinking-something-or-another yet? Why not?”. Knee-jerk decisions and short attention spans often steals resources from developing a strong, scalable foundation for data. The result of these two shortcomings are organizations that are taking a proverbial “shotgun approach” to data and analytics, generally hitting all around the target but somehow completely missing the mark.
How can organizations, especially ones that are early in their journey with data, hope to become more data-driven when so many others struggle? How do the leaders of these organizations know where to invest resources…or whether they should invest at all?
The good news is that a path does exist for improving the outcome of your data and analytics efforts. That path will look different for every organization, but any organization can benefit from following a well plotted course towards becoming ‘data-driven’. The concept of Agile Analytics first emerged as a means of applying the language of software development and project management to data initiatives. However, the definition of Agile Analytics can be, in fact must be, expanded beyond the narrow scope of project management to become a framework for how businesses of all sizes across any industry can successfully uncover the value in their data.
Throughout this blog series, we’ll unpack the strategies, techniques, and talent required to find success in your organization’s data efforts. We will define what success can look like, how to set realistic expectations, and how to take those critical first steps. We will highlight the characteristics of what a ‘data-driven’ organization really is and discuss how to measure and optimize data efforts in a way that maximizes value to the organization. Our goal is to inspire leaders to change the way they think about data and analytics, shifting it from a state of confusing hype to one of strategic opportunity.
- 1 Data and AI Leadership Executive Survey 2022, NewVantage Partners (A Wavestone Company).
- 2 ‘Data Scientist: The Sexiest Job of the 21st Century’ by Thomas Davenport and DJ Patil. Harvard Business Review. October 2012.
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