Trust is the first victim to fall at the hand of ungoverned data, failed or underperforming data initiatives.

A Precisely/Corinium report on data integrity trends 2021 (https://www.precisely.com/resource-center/analystreports/data-integrity-trends?utm_source=Referral&utm_medium=Press-Release

), shows the magnitude of the problem: Only 34% of the staff generally trust data-driven insights.

Looking at other results from this report it’s easy to conclude that most of the organizations inquired already have a degree of maturity, concerning the handling and usage of data, above average. Which means that the overall situation should much worse.

The lack of trust, leading to an avoidance of data-driven decision and a preponderance of the gut feeling in the decision-making process, is often grounded on a perception of what can be seen as a kind of data obscurity, or opacity.

The need for some degree of control on the who’s, what’s, why’s, when’s, where’s and how’s of the data being fed into the decision processes is one of the major causes that undermines trust and leads to poor decision making.

At the basis of this problem, we have an asset that is not being managed, and this lack of trust is born out of a feeling of lack of control over something that is critical for the organization.

If data can’t be trusted, work on data – make it trustable.

This raises a few questions:

· How many business decisions are being made without the support of reliable data?

· How many business decisions are being made without any data support at all?

Considering the number of decisions being made daily, from the more operational level to the more strategic, the impacts on business must be impressive.

From day one, data is being created, compiled, collected, stored, and distributed. Data is present in all the organization’s processes, from risk or regulatory compliance to routine operations.

Every organization is fully dependent on data; providing trustable, quality data that is essential to improving insights and driving substantiated business decisions must be a priority.

Data trust is addressed removing the causes that lead to data mistrust and building confidence on how data is managed - To build a data driven culture, to be able to leverage all the insights that can be derived from data, these issues must be faced and tackled – To build the trust. To get the best data driven decisions.

Data is a critical and strategic asset for any organization, making essential that the right information is available at the right time to the right people to enable the organization to compete and win in the emerging, data-driven economy.

Organizations need to have a clear stand on managing its most important asset – data.

The goal of data governance is to ensure that an organization’s business objectives are accomplished, by guaranteeing that data is available as needed for business purposes, but also secure, private and in compliance with regulatory requirements.

An organization must know and trust the data on which it relies.

· Knowing data means a governance program and an intended data strategy.

· Trusting data means validating and monitoring the quality and state when it is applied in the business processes.

This is the only way to mitigate regulatory compliance risk, to engage customers, partners, and stakeholders, to optimize the results of key business initiatives, and to apply analytics to support the decision processes and long-term strategy.

Everybody knows trust is easier to destroy than to build, this leads us to what I believe are the most critical success factors for any data governance initiative, data governance is established top-down and develops bottom-up.

· In a data-driven economy, CEOs and executive leadership must promote the organizations’ data strategy into the business and out of the IT context, as any other asset data’s purpose is to create value, so any data strategy must be oriented towards the organization's strategic priorities and key business objectives.

· Business objectives must drive the development of the data strategy, focusing on use cases that support business objectives, creating traction and increasing the awareness across the organization and will end-up acting as the motor from within the organization for a Data Governance structure that will grow organically.

Data Governance is a fundamental part of business, not a set of technological projects. The development of the data strategy cannot depend on the limited resources and throughput of IT. Business users must be enabled to a data management approach where they can improve and control the quality of data and address and mitigate problems.