Moving into data-driven business models is crucial for organizations to thrive in increasingly complex, dynamic, and competitive markets. Becoming a data-driven creates the capability to generate new efficiencies within existing business models, optimizing assets and resources, reducing costs, increasing profitability, improving customer engagement, and enabling new business models.

Being data-driven enables organizations to act effectively and swiftly to increasing demands from their business, their customers, and the market.

Driving innovation with data, investing on analytics, managing data as a business asset, developing well-articulated data strategies, and creating a data culture are priorities.

Yet this is not the reality for most organizations that started this journey. It is important to be aware that for most organizations the results of digitalization processes fall short from the objectives and will settle for dilution of value and mediocre performance, confronted with a situation where they simply assume that the investment was wasted and worse than that, accept to live with mediocre, under-performing solutions – expensive failures.

Instant Gratification

The available data increasing and the technological solutions available unleash an enormous, so it makes sense that there’s an enormous appetite in top managers for new dashboards and analytical tools to support their decision processes.

Nothing is more delighting than a new dashboard.

But is it helpful to the decision processes? No, it works only as an instant gratification.

There is no new dashboard that can create trust on data, and without it, no value can be derived from it.

At the root 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.

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.

There is no one-size-fits-all approach to data governance and implementing good data governance is challenging. That is why so many programs fail.

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.