High-quality data management can dramatically reduce a company’s operating and overall data costs by speeding the process of using data, but also by providing a truly accurate view of operations. With trusted data, analysts spend less time cleaning and finding data, and more time putting it to use to generate insights that support the organization. Companies also spend less to store and gain insights from their data. Automation and optimization are vastly accelerated when everyone knows that the data truly reflects the state of the company.
Data management should be connected to overall business outcomes that can help to optimize operations and lower costs by:
Inefficient operations cost businesses money. With Infoverity as a data management partner, companies can streamline their operations, optimizing performance and how they run the business. More accurate data leads to improved analytics and reporting, which enables companies to leverage more value and revenue from their data as well as expand automation.
When companies suffer from poor data quality, they waste money and resources. Quality data management increases the value of analytics by optimizing data usage. Businesses spend less while achieving more value and insights. They can also leverage AI and machine learning in new ways to optimize analytics even further.
A study by West Monroe Partners found that companies that prioritize data during an M&A transaction can achieve up to 50% more revenue growth than companies that do not.
Gartner has found that companies that implement effective data management strategies can reduce IT costs by up to 25% and increase operational efficiency by up to 30%
According to a study by McKinsey & Company, companies that prioritize data integration during an M&A transaction can achieve 30% more cost synergies than companies that neglect this aspect.
According to McKinsey, 56% of M&A deals fail to deliver the expected value due to issues with data management.
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