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John Smith
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Data Scientist, USA
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Cloud-Ready Data
Digital Transformation
Data Governance

The steps to a successful business transformation

Blog ParisSeminar

Revised October 1, 2020  / original: Jan 25, 2019

Recently, Collibra organized a seminar in Paris for analysts from firms such as Gartner and Forrester, and data managers from the financial, retail, transportation, and logistics industries to discuss the role of data in digital business transformation.

 Digital business transformation remains a central initiative that relies on data. Initially, data functions were focused on regulatory compliance, however, many executive teams now want to see continued innovation and results from the Chief Data Officer that generate value and growth for the company.

What is business transformation?

Business transformation at its core refers to how an organization reshapes its model or operations in order to address new business challenges and opportunities. New competitors, product releases, technological advancements, regulations, and more are causing business needs and requirements to alter. Consequently, businesses also need to alter the ways they function.

What are the types of business transformation

Organizations can take different routes for business transformation. There is no one size fits all approach, nor are these approaches mutually exclusive, but most transformation projects can funnel up to one, two or all three of these types:

  1. Organizational transformation consists of remodeling a company’s culture or structure in order to address challenges and unlock new opportunities. Organizational transformation might include restructuring a team’s roles and hierarchies or rebuilding a corporate culture.
  2. Operational transformation focuses on upgrading the way a business operates to improve productivity. A common example of operational transformation is an engineering team adopting the agile methodology. When data teams lead operational transformations, they often implement new workflows, policies and standards.
  3. Technological transformation involves the use of technology to unlock new opportunities. The paradigm of technological transformation is digital transformation, which leverages digital technologies and data to meet business objectives.

Transformation is important to a business

Organizations choose to undergo a transformation for a number of reasons, but they always funnel up to a strategic imperative, usually revolving around: 

  • Increasing revenue or market share
  • Improving customer satisfaction and retention
  • Reducing costs
  • Enhancing productivity

To stay afloat and lead in today’s ever changing markets, organizations need to transform how they operate. Data needs to be at the center of any business transformation program. The most successful and innovative companies have data governance as the foundation to their business transformation initiatives. 

The future of business transformation

Henry Peyret, Principal Analyst for Forrester who presented at the seminar, proposed an analysis of the role of data governance in the digital transformation of companies.

What Forrester describes as “Data Governance 2.0” goes beyond the customer-centric model and regulatory constraints. This future form of data governance is shifting towards a model in which end customers form their own ecosystem centered around their own values. Customers are no longer only consumers of data, but they contribute through platforms and social networks as well. 

By adapting to the specific needs of the customer based on the data collected, the customer experience can be enhanced. According to Forrester, Governance 2.0 will lead organizations to implement a “Data Management Continuum,” enabling continuous improvement of the company’s products and services. Improvements such as added transparency to customers, better control of the rules shared between producers and consumers of data, and user-centric data lifecycle management.

The CDO and business transformation

Data governance, which initially was driven by regulations (especially the GDPR), is now at the heart of business transformation for organizations in all sectors. 

The Chief Data Officer (CDO) works to place data governance in the center of all initiatives from supporting business and digital transformation projects to ensuring the deployment of a data culture at all levels of the company. Once data governance is launched, it acquires a range of services, including tools, not only to improve the knowledge and understanding of the information assets, but also to contribute to their quality.

This controlled information asset becomes a strategic element, especially if it is shareable and directly usable by trades. In this way, access to data knowledge is no longer limited to analysts/experts.

The CDO and his or her teams are responsible for creating and facilitating data governance roles and responsibilities. The formalization of job descriptions is not enough to motivate potential stakeholders. The people involved are the custodians of new norms, standards, and spokespersons for governance within their entities. These are significant issues and it’s sometimes difficult to demonstrate to employees who may perceive governance as a new constraint. The support of data teams with these stakeholders is crucial to their success, especially since few data stewards, data owners, and data managers are 100% affected in their data function. Whatever the chosen format (videos, MOOC, events, etc.), education and training are essential as data governance and related functions are still new to many companies.

To encourage support, roles must be thought of as “trades,” designed to evolve and adapt to the needs of the situation. A use-based approach promotes stakeholder participation (business, IT, legal, etc.), thus allowing the identification of a sponsor and the delivery of results (financial gain, operational efficiency, or risk management) on a defined business scope. This approach provides flexibility to facilitate the deployment of roles; especially since the notion of sole proprietor of any given data proves difficult in organizations.

The deployment of a data governance workflows has several payoffs, like enabling collaborative work (and thus increasing productivity), accelerating the decision-making process, and making the roles for each actor a reality. The most mature companies implement them to move from theoretical governance to operational and active governance.

Wrapping it all up

Collibra would once again like to thank Henry Peyret, participants of the round table: Renato Aganippe (CDO AXA Banque), Pascal Bourcier (BPCE Tools and Access Manager), Pierre Guillemin (CDO Natixis), Julien Iris (Mission Director, Fab Big Data SNCF), as well as the many participants in this event, whose success demonstrates companies’ growing interest in engaging data governance issues.

Related resources

Whitepaper

The new data governance approach

Analyst report

Transform your business with a governed data catalog

View all resources

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