David Linthicum
Contributor

Why do businesses suck at using data?

analysis
Jul 22, 20223 mins
AnalyticsCloud ComputingData Management

Few enterprises can effectively leverage their data inside or outside of the cloud, and a new study says that's still the case. It's time to make a plan.

fail frustration laptop user head desk
Credit: Thinkstock

Many enterprises hope cloud computing will allow them to leverage their own data as a true force multiplier that will transform them into innovators and leaders in the marketplace. Or, at the very least, they hope they can finally optimize their data.

Snowflake just released a study that identified a few key issues that most enterprises still seem to have with their data, cloud-enabled or not. According to their findings, only 38% of businesses can extract value from their data and use it to inform their decisions. Worse, only 6% of global businesses use, access, and share data in a way that grants them all the business benefits provided by a sound data strategy.

How did things get this bad in the age of cloud computing?

First, many enterprises just move data to the cloud and hope for the best. Moving poorly used data from your data center to the cloud gives you poorly used data in the cloud. Nothing changes.

Second, there is no regard for data integration, and access to data is still a core problem that has yet to be solved. Right now, the concepts of data integration and its tools are decades old. It’s surprising that many enterprises have not yet figured out how to use them.

Finally, enterprises do not leverage their own data to make their own business decisions. This includes rudimentary analytics such as sales forecasting, but also real-time decision-making automation that can support a near-real-time supply chain automation such as inventory depletion processes.

There is no magic technology to fix this issue. The only way to improve the use of data is to create a multiyear strategy that divides the enterprise’s data into domains and plans how to deal with each domain, one at a time.

There should be two main data objectives.

First, figure out how to find the data you need to externalize and provide interfaces that will find and extract it. This needs to be done in secure and scalable ways with the understanding that you need to leverage data that provides a single source of truth.

Second, figure out what abstractions you need from that data. These are “calculated points” for use within core business processes, such as combining inventory information with supply chain planning information, which provides valuable insights into systems that need both, such as sales order systems. If you’re wondering why your supplier can’t accurately tell you when materials and products will be available, it’s because they don’t have these kinds of insights. Do your customers have these insights into your products?

Many enterprises have not yet addressed data use because of the time and costs. Also, data complexity has greatly increased in recent years as enterprises layer complex data on top of already complex data without a vision of how to extract and use it.

When you’re in a hole, stop digging. It’s time to fill in the data hole with a solid data plan.

David Linthicum
Contributor

David S. Linthicum is an internationally recognized industry expert and thought leader. Dave has authored 13 books on computing, the latest of which is An Insider’s Guide to Cloud Computing. Dave’s industry experience includes tenures as CTO and CEO of several successful software companies, and upper-level management positions in Fortune 100 companies. He keynotes leading technology conferences on cloud computing, SOA, enterprise application integration, and enterprise architecture. Dave writes the Cloud Computing blog for InfoWorld. His views are his own.

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