The importance of data to today’s businesses can’t be overstated. Studies show data-driven companies are 58% more likely to beat revenue goals than non-data-driven companies and 162% more likely to significantly outperform laggards. Data analytics are helping nearly half of all companies make better decisions about everything, from the products they deliver to the markets they target. Data is becoming critical in every industry, whether it’s helping farms increase the value of the crops they produce or fundamentally changing the game of basketball.

Used optimally, data is nothing less than a critically important asset. Problem is, it’s not always easy to put data to work. The Seagate Rethink Data report, with research and analysis by IDC, found that only 32% of the data available to enterprises is ever used and the remaining 68% goes unleveraged. Executives aren’t fully confident in their current ability—nor in their long-range plans—to wring optimal levels of value out of the data they produce, acquire, manage, and use.

What’s the disconnect? If data is so important to a business’s health, why is it so hard to master?

In the best-run companies, the systems that connect data producers and data consumers are secure and easy to deploy. But they’re usually not. Companies are challenged with finding data and leveraging it for strategic purposes. Sources of data are hard to identify and even harder to evaluate. Datasets used to train AI models for the automation of tasks can be hard to validate. Hackers are always looking to steal or compromise data. And finding quality data is a challenge for even the savviest data scientists. 

The lack of an end-to-end system for ensuring high-quality data and sharing it efficiently has indirectly delayed the adoption of AI.

Communication gaps can also derail the process of delivering impactful insights. Executives who fund data projects and the data engineers and scientists who carry them out don’t always understand one another. These data practitioners can create a detailed plan, but if the practitioner doesn’t frame the results properly, the business executive who requested them may say they were looking for something different. The project will be labeled a failure, and the chance to generate value out of the effort will fall by the wayside.

Companies encounter data issues, no matter where they are in terms of data maturity. They’re trying to figure out ways to make data an important part of their future, but they’re struggling to put plans into practice.

If you’re in this position, what do you do?

Companies found themselves at a similar inflection point back in the 2010s, trying to sort out their places in the cloud. They took years developing their cloud strategies, planning their cloud migrations, choosing platforms, creating Cloud Business Offices, and structuring their organizations to best take advantage of cloud-based opportunities. Today, they’re reaping the benefits: Their moves to the cloud have enabled them to modernize their apps and IT systems.

Enterprises now have to make similar decisions about data. They need to consider many factors to make sure data is providing a foundation for their business going forward. They should ask questions such as:

Is the data the business needs readily available?What types of sources of data are needed? Are there distributed and diverse sets of data you don’t know about?Is the data clean, current, reliable, and able to integrate with existing systems?Is the rest of the C-level onboard with the chief data officer’s approach?Are data scientists and end users communicating effectively about what’s needed and what’s being delivered?How is data being shared?How can I trust my data?Does every person and organization that needs access to the data have the right to use it?

This is about more than just business intelligence. It’s about taking advantage of an opportunity that’s taking shape. Data use is exploding, tools to leverage it are becoming more efficient, and data scientists’ expertise is growing. But data is hard to master. Many companies aren’t set up to make the best use of the data

Read More

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By: Janice Zdankus, Anthony Delli Colli
Title: Getting the most from your data-driven transformation: 10 key principles
Sourced From: www.technologyreview.com/2021/10/14/1037054/getting-the-most-from-your-data-driven-transformation-10-key-principles/
Published Date: Thu, 14 Oct 2021 16:08:28 +0000

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