What data?
“In God we trust, all others must bring data.”
W. Edwards Deming
It’s never too much to stress the importance of data on any decision-making process, and Deming’s quote pinpoints that importance, informed decisions must be founded on reliable data.
Contrary to what is expected in a time where being data-driven seems to be a priority for every organization, very few decisions are data-driven, many business decisions are being made without the support of reliable data or without any data support at all.
Many business decisions are still made ignoring data or supported on gut feelings – This happens either because decision makers feel that data can’t be trusted, or trust on its own experience surpasses trust on the available data.
There are many causes for decision process to be seriously impaired by lack of trust on data, and most of them are more frequent than should be desirable, and each of these have a severe impact on the capability of top-level executives to trust the data that is made available for them to make informed decisions.
Most of these problems are part of our daily lives, and end-up being accepted as normal or even inevitable.
We’ve all been in situations where we’re asked to use data that we know is not enough to generate new insights, coming from sources that are no integrated, that has defects, errors, is missing or incomplete, that is not adequate to a business case, that belongs to rogue data sets, that can’t be traced to source or that has been generated by undocumented transformations.
Bringing data under these conditions makes it really challenging to build trust on data or to derive any kind of trustable insights.
So, what data?
For those who bring the data, as Deming puts it, the ultimate purpose is to assure that timely, consistent, and trusted data is provided business to support critical decisions.
It also means that 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.
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.
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.