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At a time when data is often referred to as the "new black gold", ensuring its proper governance has become a priority for companies worldwide.

However, many companies plunge headlong into the subject of data governance without proper preparation.

Data governance can then become ineffective, or even counter-productive, wasting efforts and resources that could/should have been avoided.

This article looks at these challenges and proposes a practical approach to tackling them.

1. The rush to data governance

1.1. Cutting corners

Keen to harness the power of data as quickly as possible, many companies are rushing to implement data governance axes even before they have the right tools or organizational structures in place.

It's like building a house without laying the right foundations.

This is mainly due to the pressure of the market, which demands results even before a clear plan has been drawn up. The result? An endless cycle of new Data strategies that drain resources without delivering tangible results.

The root of these problems often lies in a gap between strategic vision and practical implementation.

Data transformations, often carried out by external consulting firms, tend to generate endless changes, with no really concrete end goal and very costly consulting expenses for the company.

This over-reliance on consulting services prevents companies from focusing on practical, scalable solutions from the outset. By adopting a more pragmatic approach, avoiding the trap of completely overhauling every process, companies can achieve a more effective and sustainable data governance model.

1.2 Navigating in a compartmentalized environment

A fairly common scenario encountered in companies is the cohabitation of departments operating in silos with obsolete IT systems, significantly complicating the data governance process.

Yet, according to a McKinsey report, effective data governance can reduce the time employees spend on non-essential tasks by 74%.

Underlying risks :

- Data inconsistencies and inaccuracies, different definitions for different users.

- Reduced confidence in data-driven decisions.

- Increased complexity due to the absence of a unified data strategy.

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2. The illusion of data governance built by external service companies

Many companies turn to external service companies to set up data governance because they feel they lack in-house skills.

However, this approach can lead to high costs and uncertain results, mainly for three reasons:

(1) generic solutions that do not meet specific business needs,

(2) high consulting and maintenance costs, and

(3) limited internal buy-in and knowledge transfer to company staff.

Underlying risks :

- Devoting financial resources without a clear return on investment.

- Introduce even more complexity into an already cumbersome data landscape.

- Delaying the company's progress in digital transformation.

3. A pragmatic way forward

3.1. End-to-end data management solutions

Rather than dealing with problems on a service-by-service basis, companies are well advised to adopt global solutions that manage data end-to-end.

This approach, supported by state-of-the-art technology, ensures that data governance is seamlessly integrated into the entire data lifecycle.

By leveraging technology tools and platforms, companies can manage data more effectively, from collection to storage, processing and visualization, making data governance an essential part of their business.

Advantages :

- Greater data consistency and reliability

- Streamline data operations and reduce redundancies.

- Better visibility of data flow and governance.

    3.2 Progressive implementation

    Instead of attempting a massive "big bang" style transformation, companies should consider a step-by-step implementation.

    By tackling challenges one by one, companies can ensure smoother transitions, better manage risks and budgets, and achieve faster results.

    Advantages :

    - Reduced disruption to existing operations.

    - Progressive gains that boost stakeholder confidence.

    - Flexibility to adapt and pivot as the digital landscape evolves.



      Vigilance is essential when it comes to Data Governance. Yes, today's enterprise must be Data-Driven, and Data Governance is an indispensable step towards a high-performance enterprise, making full and intelligent use of its Data.

      However, the key to navigating the labyrinth of data governance lies in recognizing the shortcomings of current practices and adopting a pragmatic, solution-oriented approach to serving end-users.

      This will enable companies to truly harness the power of their data, and move confidently into the future.

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