The Enemy Within

Just came across a poll from Wakefield Research on “Data Culture”, the results although not surprising are disturbing, showing how many organizations are working on a data blind spot.

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?

“Data quality remained the soft underbelly of data culture, resulting in decision-makers questioning data. According to the report, 90% of those polled said that the C-level executives at their company at least sometimes question the data that they use, with more than half (56%), saying this happens often or all of the time.

Two-thirds (67%) of data leaders said that their company’s C-level executives ignore data when making business decisions, relying instead on gut instinct. The top reason data professionals said their C-levels ignore data is because they believe their gut instinct is the differentiator (42%). Another 35% said it’s because there’s not enough collaboration and 35% said it’s because they are used to doing things their own way.”

Looking at these conclusions we can’t avoid thinking that serious structural problems exist on the usage and handling of data for corporate decision processes.

The outcome of these decision processes, made without trust on data or without trustable data, can’t be much better than common guess work, however educated it might be.

What’s undermining trust?

What got us here is here is commonly known, and we can easily relate with the situations listed below:

  • Data that is not enough to generate new insights.

  • Data sources that are no integrated.

  • Data that is not available on time.

  • Data that has defects, errors, is missing or incomplete.

  • Data that is not adequate to a business case.

  • Data belonging to rogue data sets.

  • Data that can’t be traced to source.

  • Data generated by undocumented transformations.

Each of these situations undermines trust, each of them is more frequent than desirable – Making it hard for top level executives to fully trust the data that is made available for them to make decisions – It’s not surprising that trust on data is deeply undermined and the decision process severely impaired.

Govern the data asset

At the basis of this problem, we have an asset that is not being managed, and the 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.

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.

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.