Data and analytics have become increasingly important to businesses and have attracted significant investment from business leaders. However, to maximize ROI, data leaders must adapt to their organizational structure, the strategies they pursue, and the types of technologies they purchase to drive measurable and tangible business value.
Digitization has accelerated the need for IT leaders to pay close attention to their data, artificial intelligence, and analytics. Beyond the need to meet business objectives to create more compelling customer experiences and optimize operations.
The Good
The data organization is now a value organization, with 83% of companies reporting they have appointed an executive to drive their data strategy. This represents a growth of approximately 700% in 10 years (in 2012, only 12% of companies had chief data officers (CDOs) ). 70% of these data leaders report to the company president, CEO, COO or CIO, allowing them to focus on what creates business value rather than activities that seem like a cost center.
Additionally, technology executives are structuring their teams to support the creation of data products, this can reduce the time it takes to deploy data into new use cases by up to 90%, lower total cost of ownership by up to 30% and reduce the risk and burden of data governance.
The bad
Data leaders are misunderstood, while 92% of companies say they are reaping benefits from investments in data and AI, only 40% of companies said the CDO role is currently successful within Her organization. o 62% of bosses of data leaders report that they feel their role is not well understood. They point to the typical problems of fledgling organizations: overly inflated expectations, unclear bylaws, and difficulty in influencing. Nearly 75% of organizations have failed to build a data-driven organization.
There is a need for data leaders to structure their organizations in a way that adds visible value to their employers.
The Ugly
What's worse is that the average tenure for data leaders is less than 950 days.
From a technology standpoint, there will be three key changes that data leaders will need to make:
Shift from data warehouses to data lakes to cost-effectively support increasing data volume, variety, and velocity and reduce costly and time-consuming data movement.
The transition from siled business intelligence dashboards to data products that work at the enterprise level. o Increase focus on real-time and AI operationalization.
Delivering compelling customer experiences requires an organization's data and analytics infrastructure to be optimized for real-time decision making. Unfortunately, there is too much data and too much input for data teams to provide the support they need.
Source: Venture Beat
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