Supercharge your Data Strategy
Most Data Projects Fail
Data is the New Gold…
But most companies fail in the journey
Extracting value from data can often prove challenging and overwhelming. Have you ever experienced being immersed in a data project, only to discover it lacks direction? This sensation is more prevalent than one may assume:
- In 2017, Gartner estimated that 60% of big data projects fail. Nick Heudecker Gartner’s former analyst tweeted the failure rate could be as high as 85%.
- VentureBeat reported that 87% of data science fail to reach production.
- Gartner predicted in 2018 that by 2022, 85% of AI projects would deliver erroneous outcomes.
Data Strategy needs a Product Vision
Bad data strategy and bad product strategy have a lot in common.
Numerous articles and studies have been written, dissecting the reasons behind Data project failures. There’s a key insight to get from them:
Product Management gaps are in the root of most Data project failures
At Supercharge we apply Product Discovery, Lean Product Management and Working Backwards principles to setup organizations for a successful data journey.
Our vision aligns with the emerging paradigms of Data Mesh and Data-as-a-Product (DaaP), where the value for customer, even if the customer is internal is treated as the key to success.
Why do data products fail?
Data Strategy Jobs to Be Done
Empathy to bridge all gaps
The concentric circles illustrate the interconnected nature of various components required for a successful data strategy. At the heart is the concept of Data-as-a-product, emphasising the need to treat data with the same importance as any other product. Data product managers play a crucial role in bridging gaps between all stakeholders, ensuring that the vision and strategy are aligned, and that data products meet the needs of the business.
Trusted by Industry Leaders
Supercharge’s Founder has successfully worked with Industry Leaders, to start projects and teams from the ground up!
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