As the era of Big Data wanes, its underlying value and tensions linger, particularly as organizations transition towards an AI-driven future. When Big Data initially emerged, it was a significant innovation in the IT landscape. However, contemporary IT leaders are increasingly reluctant to use the term. Despite this shift, CIOs should not dismiss the underlying technologies and techniques that were prominent during Big Data’s peak from 2005 to 2015. There is still substantial value to reap from straightforward data management practices.
Futurists, often criticized for their dramatic tendencies, can hasten trend adoption by emphasizing obsolescence or new technologies. Trendy technologies like quantum computing and drones captivate executives. However, the real challenge for executives is creating stakeholder value, and data remains a fundamental part of this process. There’s a risk of dismissing Big Data as outdated or insignificant, yet CIOs and digital leaders must ensure it receives proper attention.
When tackling long-term data challenges, one effective approach is to audit current mental models. During a discussion with senior executives, participants were asked to classify their thinking styles: Swallows having big ideas, Hedgehogs with singular views, or Moles focused on short-term projects. Few identified as Hedgehogs, likely due to the absence of a universal framework for creating value with data. However, value was often found when ambitious data goals were clearly linked to practical projects.
At the Gartner Data and Analytics Summit 2024, it was noted that companies emphasizing data analytics and AI in strategic discussions often outperformed their peers. A similar classification exercise with data practitioners revealed few Swallows or Moles, and more Hedgehogs, indicating a disconnect between business executives and data professionals.
Blending business and data perspectives is crucial. Data professionals should integrate more closely with business operations, moving beyond merely delivering insights to driving value-creating behaviors. Modern tools have democratized data science, enabling more executives to utilize these tools effectively. Nevertheless, many executives suffer from data defeatism, mistakenly believing that deriving data value necessitates advanced degrees.
Executives need ready access to data professionals embedded within the business. This will alleviate the unnecessary distinctions made between traditional analytics, Big Data, and AI – ultimately, data is a singular entity. Executing this integrated approach is essential for creating stakeholder value.
Source: Rethinking ‘Big Data’ — and the rift between business and data ops.
