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Highlights
- An enterprise’s success hinges on its diligence to institute a robust data and analytics foundation that improves data maturity over time.
- Technology leaders have an important role to play in helping their businesses champion a data-driven culture across the organization.
- High-performance digital organizations (HPDOs) invest in data analytics to improve their data literacy, processes, and governance.
In this article
In this article页面内
Why a data-driven culture?
Data-driven behavior is a pre-requisite for businesses to thrive.
With an abundance of data available at various levels, it is vital for organizations to take a holistic view on their data and analytics landscape to stay ahead of the curve.
Poor data and analytics frameworks and low automation could balk an enterprise’s chances of successfully monetizing its data insights. Digital businesses win by putting technology and data to its best use on their transformation journey—to become data-driven high performance digital organizations.
Becoming a high-performance digital organization requires an adjustment in strategy, partner collaboration, and leveraging analytics insights to pursue growth and transformation ambitions.
Surveying Dutch enterprises
We partnered with Tilburg University/TIAS Business School, ICT Media and surveyed 62 organizations about their data maturity levels.
This HPDO survey aimed to assess and benchmark an organization’s data maturity. Many of the surveyed organizations had a low analytics cloud computing score. Analytics needs cloud computing, and so having a good score on this front is the first step to data maturity.
Many of these organizations did not have a good data maturity foundation. Poor data management and analytics automation, limited use of open and external unmanaged data combined with low usage of active data warehouses and data lakes required immediate attention.
When we compared the insights of the Dutch survey with our experiences in implementing our TCS Datom™ assessments, we learnt that the data and analytics maturity in the Netherlands was slightly higher than the global average. Yet the Dutch maturity was still at the ‘low to medium’ range. This puts them at a disadvantage when it comes to improving business performance. Only 15% of Dutch organizations are increasing their business effectiveness by leveraging data and analytics.
Those that are data-driven high-performance digital organizations have anchored this priority at the board level and implemented a data-driven mindset and culture across the board.
Data maturity across sectors
Understanding adoption levels across five aspects—data management, analytics automation, types of data, analytics platforms, and cloud adoption—helps us recognize the challenges they face.
None of the surveyed Dutch organizations qualified as best-in-class on all the above aspects. Eight organizations qualified as laggards on all five aspects, which are in the following sectors:
- Government and public services (2)
- Life sciences and healthcare (2)
- Consumer goods and distribution (1)
- Insurance (1)
- Manufacturing (1)
- Others (agriculture) (1)
The remaining organizations have large diversity in data and analytics basics. In conclusion, most Dutch surveyed organizations need to take immediate action towards their data maturity. The effectiveness of how they conduct business must be improved by leveraging data and data analytics—to disrupt and avoid being disrupted.
Organizations must ensure that their data and analytics abilities are aligned within the business’ value chain. Increased focus on data literacy, analytics automation, and modern data governance techniques will help them achieve the required data-driven results.
Our data maturity model
In this research study, our data and analytics model TCS Datom was used to assess data maturity. This model contains five maturity stages.
- Siloed: This is the first maturity level. Seven out of 12 sectors are represented.
- Simplified: Nearly 50% of the surveyed organizations have ‘Simplified’ as the second maturity level meaning some data is shared across the organization.
- Scaled: About one-third of the surveyed organizations have ‘Scaled’ as the third maturity level.
- Synergized: Only three organizations (less than 5%) participating in this research project have the fourth maturity level as ‘Synergized’.
- Self-optimized: Only two organizations (3%) have the highest maturity level of being ‘Self optimized’.
What we learnt
The two organizations at the highest maturity level surprisingly belong to the energy resources and utilities sector with a revenue over €1,000 million.
By contrast, in the global enterprise assessments (total number being 103), the highest maturity level in the utility sector is ‘Scaled’ (stage 3 of maturity).
Only one retail company operated at the ‘Self optimized’ maturity level. The average data and analytics maturity of the Dutch surveyed organizations is different from the globally surveyed organizations, indicated by a higher average maturity score of 1.82 for the Dutch surveyed organizations (total number being 62) versus. 1.67 for the globally surveyed organizations (total number being 103).
Media partner
ICT Media
Academic partners
ICT Media and TIAS School for Business and Society
Knowledge partners
This blog was written in partnership with ICT Media and TIAS School for Business and Society.
Josu Devasia (Managing Director & Head, TCS, Netherlands)
B.V. Dinanath Kholkar (VP and Global Head, Analytics & Insights, TCS)
High performance digital organizations are built around data. It shouldn’t come as a surprise that their CIOs and CDOs have an important role here. They are the nexus between data (rich, high-priced information), the boardroom, and the supervisory board. These tech leaders are outward-looking and understand their stakeholders: end users in the business, B2B customers, business partners, and consumers.
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