Poor data quality is the leading cause of digital transformation failure. It’s time to prioritise data transformation!
- by 7wData
In a digitally empowered age, businesses across the globe have grand ambitions of leveraging the power of AI, big data, and machine learning. Innovation is happening at a rapid pace. Companies are investing millions of dollars in building data lakes, moving to the cloud, hiring data scientists and chief data officers to run their digital transformation plans.
Yet, they fail. Spectacularly. Plenty of reports and surveys show that over 85 per cent of big data projects are failing with varying causes.
Enough has been written lately about how business cultures and unchecked ambitions lead to big data project failures. This piece will focus on how poor data quality is often overlooked and makes for one of the leading cause of digital transformation failure.
Data transformation, the process of transforming raw data into a usable format is often, incorrectly, juxtaposed with digital transformation. Companies assume that because they are implementing data lakes, data centres or new ERPs, (which are all part of digital transformation), they are transforming their data.
This is a dangerous assumption. It takes the focus away from the real problem and gives companies a false sense of security. New systems are expected to resolve problems and help achieve transformational objectives but fails to do so.
The new ERP your company implemented six months ago, does not boost operational processes because data issues in the legacy system were not addressed. The new CRM your marketing team invested in to get in-depth customer insight doesn’t return the expected ROI because the team does not have data governance or data quality framework in place.
Understanding the difference between digital and Data transformation can save a company from making costly mistakes. If organisations want to be data-driven, they have to start by understanding their data, fixing inconsistencies & transforming their data. Digital transformation is the end of the process – data transformation is the start!
We’ve worked with Fortune 500 clients who prioritised digital transformation only to find out their data was not ready for it. Some of the most common issues usually are:
Poor data, bad data or dirty data is data that is the result of all these causes.
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