Whether it’s to accelerate your time-to-market, address your customer experience challenges, or put your company on the path to operational excellence, you’ve entered the data-driven era. At the heart of your approach is a demanding discipline: data governance. Here’s a complete overview of this essential discipline of your data strategy, from vision to definition to methodology.
Data governance is an essential discipline to adopt for companies that want to become data-driven. It was already a priority in 2021 and will be even more so in 2022.
At Zeenea, we define data governance as the exercise of authority with decision-making power (planning, monitoring, and enforcement of rules) and controls over data management.
On the one hand, ensuring effective data governance guarantees that data is consistent and reliable, and not misused. On the other hand, data governance allows you to ensure that your data is well-documented. The challenge is to never expose your company to the risk of data that does not comply with new data regulations.
Indeed, a company’s data is a “shared asset” and must be treated as such. That’s why data governance is essential. But data governance is more than just a concept or a code of conduct, it is a strategic activity that sets the ambitions, the path to follow, and the technical solutions needed for your data-driven strategy.
Why is data governance important?
In the past, data governance implementations within organizations were rarely successful. Data Stewards have too often focused on technical management or strict control of data.
For users who aspire to experiment and innovate around data, governance can evoke a set of restrictions, limitations, and unnecessary bureaucracy. These users sometimes have frightening visions of data locked away in dark catacombs, accessible only after months of struggling with administrative hassles. Others painfully recall the energy they wasted in meetings, updating spreadsheets, and maintaining wikis, only to find that no one benefits from the fruits of their hard work.
It’s clear that companies are conditioned by regulatory compliance: ensuring data privacy, security, and risk management. However, it is crucial to undertake an offensive axis that tends to improve the uses of a company’s data – by guaranteeing useful, usable, and used data – and to value this asset.
Offensive vs. defensive data governance strategies
There are two approaches to data governance: defensive and offensive. It is about orienting business strategy towards IT requirements in terms of data security while promoting data exploitation and analysis to generate business value. Here are some examples of the objectives set by each of these two strategic approaches to data governance:
Defensive data governance:
- Undertake compliance with country authorities to avoid penalties, such as the General Data Protection Regulation (GDPR) implemented in May 2018.
- Meet internal obligations and rules to which the organization’s data is subject.
- Ensure data security, integrity, and quality for proper use.
Offensive Data Governance:
- Increase a company’s profitability and competitive position with the help of data.
- Optimize data analysis, modeling, visualization, transformations, and enrichment.
- Increase the flexibility of the company in the use of its data.
What are the main benefits of good data governance?
The more data occupies an important place in corporate strategies, the more it is subject to demanding standards and regulations: SOX in the United States, the GDPR in Europe… On the one hand, it is essential not to expose yourself to the wrath of the legislator, and on the other hand, it is essential not to betray the trust of your customers and partners who accept that you collect and use data.
Data governance allows you to continuously monitor data compliance at all stages of its life cycle (from collection to exploitation). Ensuring data compliance has other benefits as well. Compliance with regulations mechanically contributes to the strengthening of data security. Data governance includes tasks such as locating critical data, identifying the owners and users of the data.
Data governance also sets the framework for data quality. More quality means a more efficient and effective use of data, especially in decision-making processes. Good data governance is also an asset for reducing and controlling management and storage costs.
Who are the key players in data governance?
Ensuring good data governance requires a little bit of methodology. To begin with, it is recommended that a precise charter of values be drawn up: A charter that sets out the principles and defines the means and technical solutions to be implemented in order to begin the data governance process.
But data governance is also a matter of people, whose actions contribute to the excellence of your strategy. While the Chief Data Officer obviously plays a key role, they must be able to rely on Data Owners and Data Stewards. While the CDO supervises the entire system and reports directly to the CEO, the Data Steward is responsible for data quality. The Data Stewards are responsible for ensuring that the principles laid down in your charter are respected, but also for distilling the message to all the teams. Because, on a daily basis, data governance is everyone’s business!
are responsible for ensuring that the principles laid down in your charter are respected, but also for distilling the message to all the teams. Because, on a daily basis, data governance is everyone’s business!
