Critical processes in the life sciences are increasingly dependent on high-quality data.
The impact of any digital process transformation programme relies heavily on the quality and reliability of the data that feeds into those processes. If that data is patchy, inconsistent, out of date or even incorrect, risks will be magnified each time someone re-uses that data.
Operationally, inconsistent information exchanged with the regulators will lead to non-compliance risks, risks of poor quality and, ultimately, a risk to patient safety and public health. More strategically, it will limit companies’ ability to perform useful data analytics and increase their business efficiency – reducing the time to market and patients.
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