4 ways to use data to make better business decisions

It's more important than ever to be able to make informed choices in your company. Data can help with that.

Among the reasons for poor decision making in business are lack of strategy, a poor decision-making process, lack of communication, and information loss. I'd add poor data quality and business data practices.

As we navigate through the COVID-19 crisis, data quality and sound business practices for using data are more important than ever. They're critical in the trials of drugs and vaccines; in predicting where and when the next disease outbreak will be; in assessing the availability of resources and personnel; and in evaluating economic impact.

In all of these endeavors, analytics, artificial intelligence, and machine learning play key roles— but data quality and sound business data practices are equally important.

On the IT side, companies achieve quality data by using a master data management (MDM) methodology that defines how data is collected, aggregated, matched, consolidated, checked for quality, and distributed. 

There are numerous tools and automation solutions available for master data management. They reduce the tedium of manually culling through data, normalizing it, deciding what should go with what, and who gets which data. The tougher part of the job is enacting sound business data practices that lay the groundwork for the work of data preparation that IT does with MDM.

Here are four business data practices that are vital for any organization striving to deliver the highest quality data for decision making. 

Dark data is data that is available but never used. It can exist in the form of a paper-based document created by the business years ago, or as sensor-generated IoT output that isn't used. 

IBM estimates that 90% of the data companies possess never gets used, and is Dark data.