READ MORE: The data-driven enterprise of 2025 (McKinsey & Company)
By 2025, smart workflows and “seamless” interactions among humans and machines will likely be as standard as the corporate balance sheet, and most employees will use data to optimize nearly every aspect of their work.
Wait — that’s less than three years away. Is your business anywhere near becoming data-driven?
Analysts at McKinsey have created a guide the forecaster thinks that most, if not all companies — including telcos and broadcasters — should be implementing.
Notable technologies include AI and cloud computing to speed data processing and analytics.
Companies already seeing 20% of their earnings before interest and taxes (EBIT) contributed by AI, for example, are far more likely to engage in data practices that underpin these characteristics, it finds.
By 2025, data will be embedded in every decision, interaction, and process, McKinsey predicts.
“Organizations are [in 2025] capable of better decision making as well as automating basic day-to-day activities and regularly occurring decisions. Employees are free to focus on more ‘human’ domains, such as innovation, collaboration, and communication.”
The data-driven culture fosters “continuous performance improvement” to create what the analyst calls “truly differentiated customer and employee experiences,” as well as enabling the growth of sophisticated new applications that aren’t widely available today.
“Data marketplaces enable the exchange, sharing, and supplementation of data. Altogether, barriers to the exchange and combining of data are greatly reduced, bringing together various data sources in such a way that the value generated is much greater than the sum of its parts.”
— McKinsey & Company
Right now, only a fraction of data from connected devices is ingested, processed and analyzed in real time due to the limits of legacy technology and the high computational demands of intensive, real-time processing.
Three years from now, vast networks of connected devices will gather and transmit data and insights, often in real time. It’s not spelled out, but presumably this is dependent on the rollout of 5G networks and wider deployment of cloud infrastructure.
“Even the most sophisticated advanced analytics are reasonably available to all organizations as the cost of cloud computing continues to decline.”
We can also look forward to leveraging more flexible ways of organizing data, particularly unstructured and semi-structured data. This accelerates the discovery of new relationships in the data to drive innovation, McKinsey says. “This enables sophisticated simulations and what-if scenarios using traditional ML capabilities or more-advanced techniques such as reinforcement learning.”
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There will be a bigger role for the chief data officer in organizations. Their responsibilities will widen from tracking compliance to a fully fledged Profit & Loss division.
“The unit is responsible for ideating new ways to use data, developing a holistic enterprise data strategy (and embedding it as part of a business strategy), and incubating new sources of revenue by monetizing data services and data sharing.”
None of this can happen if data remains siloed and inaccessible to sharing. By 2025, data-driven companies will actively participate in a data economy that facilitates the pooling of data to create more valuable insights for all members.
“Data marketplaces enable the exchange, sharing, and supplementation of data. Altogether, barriers to the exchange and combining of data are greatly reduced, bringing together various data sources in such a way that the value generated is much greater than the sum of its parts.”
McKinsey’s final note is around data protection. It forecasts that organizations will have fully shifted toward treating data privacy, ethics, and security as areas of required competency (driven by legislation such as GDPR, and California Consumer Privacy Act (CCPA).
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Automated, near-constant backup procedures ensure data resiliency; faster recovery procedures rapidly establish and recover the “last good copy” of data in minutes, rather than days or weeks, thus minimizing risks when technological glitches occur.
Also, AI tools will become more effective at data management — for example, by automating the identification, correction, and remediation of data-quality issues.
“Altogether, these efforts enable organizations to build greater trust in both the data and how it’s managed, ultimately accelerating adoption of new data-driven services.”