Extreme Data Ownership
The business landscape is rapidly evolving - with the emergence of new business innovations and new forms of competition, catalysed by advances in digitization, analytics, artificial intelligence, machine learning, internet of things or robotics - the availability of quality data is more than ever a critical requirement.
Data is an essential component of the interaction with customers, partners, and other key stakeholders, it 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.
Poor quality data has tangible financial, performance and reputation impact, and organizations cannot afford to manage it arbitrarily, data can turn from a business asset into a business liability, it can mean the difference between surviving and not.
Governing the data asset
Organizations need to have a clear stand on safeguarding 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 know and trust the data must 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.
Ensuring that the data strategy supports business is the responsibility of the senior management. Failure to provide leadership and direction will make any data initiatives hostage to tactical objectives within the organization.
Possibly the problem starts here, as the most frequently pointed causes for failure are related with lack of leadership buy-in and commitment, alignment with business goals and benefits, or cross organization involvement.
Make data an asset not a liability
The title from this article was inspired in Jocko Willink’s “Extreme Ownership” and I quote:
“You can’t make people listen to you. You can’t make them execute. That might be a temporary solution for a simple task. But to implement real change, to drive people to accomplish something truly complex or difficult or dangerous—you can’t make people do those things. You have to lead them.”
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.
Project graveyards are cluttered with stalled data governance projects that did not deliver clear ROI, with a strong leadership and business focus, data initiatives will pay for themselves by adding real ROI to business initiatives.