Tips & Tricks for Implementing Data Governance to Drive Business Results

Every business today has access to data. But are they using it to optimise their results? Before relying on analytics for all or part of your strategic decision-making, it’s critical to implement suitable processes to ensure data flows smoothly through your organisation while preserving its quality, accessibility, usability and security.

Here are a few tips and tricks to set up a system that drives results for your business.

Diagnose the data assets within the organisation

For data to be fully profitable for an organisation, you should know how to select, collect, store and use it effectively—especially as data is both abundant and easily lost. You can start to do this by taking inventory of all the data present in the company, identifying its various sources (your management systems, websites, social networks, marketing and advertising campaigns, etc.) and then defining the points of friction where there is a loss of value due to poor data quality.

Unite the whole enterprise around a common data governance strategy

In addition to carrying out the data diagnosis, it is important that all company departments are involved in the use of data, from general management to the operational and field teams, including all team leaders. All employees should fully understand the challenges and benefits of shared, quality, de-siloed data.

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To involve the whole company in this transition, consider these phases:

• Individual or group interviews with the different company departments to better understand the current data situation, determine specific organisational requirements and take into account any expectations regarding data governance
• Practical workshops to collaborate on a framework for deploying data governance
• Real use cases analysing, with the support of a range of company employees focused on a specific or recurring business problem associated with a specific data scope

The key is to generate interest and launch the data governance project with employees who are receptive, in demand and invested. After you establish and communicate strategic objectives, outline all of the organization’s performance indicators so everyone understands their role in the governance model.

Choose a data governance operating model that is both appropriate to your structure and agile

When launching a data governance project, you should avoid falling into the trap of trying to tackle all the technical, organisational and regulatory issues at the same time. Don’t underestimate the time needed to obtain the first tangible results. Establish a precise roadmap, validated by the stakeholders, with intermediate milestones to evaluate the efforts and progress made so far.

Following the same principle, bear in mind that several different data governance models exist. Choose the one that is best suited to your environment, your needs, your human and financial resources and your data maturity stage.

Select stakeholders and identify all data actors

In the past, there has been a tendency to place data governance solely under the responsibility of IT teams. In today’s data-driven organisation, governance should be implemented and supported across all business units, as each has a role to play when it comes to data oversight. A chief data officer may be responsible for data governance throughout the company. You should also consider assembling a multidisciplinary group that may include data owners, data stewards, data custodians and more.

Create steering bodies and remove data silos within the company

Once you have assembled your data governance project team, you can bring them together in a dedicated data governance office, a committee that makes strategic decisions about the implementation within the various business units of the company. They approve data policies and standards and deal with any data management, security and quality issues that arise.

A horizontal mode of governance can put data at the centre of your activity and your business issues. Based on this principle, you can, for example, accelerate the removal of silos between direct marketing, advertising and customer service, and bring together CRM and media expertise and technologies within organisations, brands and their agencies.

Document the project and write shared resources

To successfully implement a data governance project, establish standard processes and adopt a common language within the organisation. Provide your teams with a data map, or a comprehensive topography of all the data collected and used by the company in the various information systems. This allows the identification of data assets, their flows, their storage and their processing methods, with a goal to make the data fully accessible and understandable to all employees.

Ensure the quality of your data to improve your decisions

In a data-driven organisation, data steers most of your decisions, like the nature and timing of promotional operations or communication campaigns, the segmentation of audiences and the reliability of targeting, the correction or addition of functionalities on a website or mobile application and more. To carry out all these actions, you must have complete confidence in the quality of the data.

It is important to be vigilant at all stages of the data life cycle, starting with the critical moment of data collection, because this phase is permanent. And each modification or update of the website or tracking inevitably poses a risk to the quality of the collection. Put in place effective methodologies and tools to orchestrate and document this process.

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Ensure the regulatory compliance of the data

With the implementation of the GDPR in 2018, CCPA in 2020 and the French CNIL guidelines in 2021, companies are becoming increasingly aware of the importance of respecting the protection of users’ personal data on their various digital platforms. It is critical to take steps on your websites and mobile applications to ensure that your visitors’ consent is properly collected in a free and informed manner. To do this, you need to choose an analytics provider that has rigorous data management and full respect for global legal regulations.

Democratise the use of data internally

The democratisation of data within the company is essential in a data governance approach. Adopting a data-driven culture means making available all the information and resources necessary for teams to carry out their missions and create value. Organising training sessions and internal workshops help guide users in the operational use of the tools and in the use of data for specific use cases. To encourage employees to use the data available to them, your data team can also design dashboards dedicated to the management of each key activity.

Evaluate the performance of your data governance system on an ongoing basis

Once you have laid the first bricks of the foundation of your data governance strategy, it is essential to measure the satisfaction of internal staff, to evaluate the performance of the measures taken and to progressively iterate and improve the processes according to your maturity curve. Nothing is set in stone in the deployment of data governance​​—quite the opposite, actually. Be as agile as possible to ensure that the methods applied are in line with the objectives pursued.

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