It’s All in the Data – My, My, Hey, Hey

Data-ColumnWelcome to my new column on the new pages of TDAN.com. This quarterly column will address data from a personal perspective and is written to get you to think about the importance of data in our daily lives. I cannot tell you how often I tell people, after lengthy discussions about seemingly unconnected subjects, that “It’s all in the data”.

Neil Young waxed poetically when he proclaimed that “It’s better to burn out than it is to rust” in his 1987 rock and roll anthems “My, My, Hey, Hey” and its alter-ego, “Hey, Hey, My, My”. On the surface, the statement may seem to tell us that “rock-and-roll is here to stay”. At second or maybe tenth glance the statement tells us that it is better to be active and encourage activism then it is to sit around and do nothing. It is better to burn out from giving all you’ve got than it is to sit around and rust away. Think about this in terms of everyday life and the “be all you can be” slogan used by the United States Army. Think about this statement in terms of how your organization manages and uses its data for competitive advantage.

I have opined in the past about the need to recognize data as a valuable asset of the organization. Data drives finance, sales and marketing, research and development, production and distribution – a representative list of primary corporate functions. Data drives industries such as finance, manufacturing, retail and education, just to name just a few. Your organization should recognize data as an asset. It’s all in the data.

My, My, Hey, Hey – The value of data is here to stay. That is, unless we refuse to look for ways to make data valuable. It all starts with good data. And good data starts with formal accountability to make the data good. While the word “good” means different things to different people or parts of the organization, the execution and enforcement of formalized accountability is necessary to make the data good.

Let’s look at what makes data “good”:

  • To those people responsible for protecting the data or following the rules (internal or external) associated with the data – good data is data that is protected perfectly and follows every rule to the letter of the law.
  • To Marketing and Sales people – good data improves customer intimacy, advances relationships, and ultimately leads to more sales.
  • To Researchers and Developers – good data is trusted, validated, and certifiable from reliable and documented sources.
  • To Financial people – good data is timely, exact, easy to access and easy to analyze and report.
  • To Health Insurance and Healthcare providers – good data is everything stated above. In fact all of the good data above crosses industries and can be leveraged toward every aspect of people and organizational health and wellness.
  • To Senior Leadership, Management and Analysts – good data is data that they feel comfortable using to make decisions that dictate the organization’s ability to achieve success.

In order to achieve good data, or data that is used efficiently and successfully, organization are looking for ways to execute and enforce authority over the management of their data and data-related assets through the formalization of accountability for data across the enterprise. That seems like a mouthful, and the truth is that it is a mouthful.

It has never been optional for organizations to execute and enforce authority for things like privacy, security and classification. Executing and enforcing authority are known as Governance. We can thank regulators for data governance and that is the way it needs to be. It has become optimal for organizations to centralize and deliver high-quality data assets (through their Big Data, Master Data and Business Intelligence efforts) for decision-making purposes and to achieve single-point-of-truth when it comes to data and information. To make the data good requires authority that is executed and enforced effectively.

Good data is a result of holding people formally accountable for their relationships to data. Definers must describe data for purpose, producers must generate accurate data and users must know how to use and protect the good data. This accountability is labeled as data stewardship, a term given to people that define, produce and use data in their job responsibilities.

Going back to the rusty theme, things rust when attention is not paid to them. Your data gets rusty when it is ignored. And nobody wants rusty data.

On the other hand – let’s make a case for burning out data-wise. Burning out comes from use – a lot of use – some may say too much use. When Neil Young said that “it’s better to burn out then it is to rust” he likely was not talking about data. But he could have been. Neil’s a high-tech guy (have you heard his Le Noise album?). He could be telling us to get more use and value (basically burn out) from our data.

Data is a valuable asset. Organizations must focus on getting the most value from their asset. This includes Big Data and small data, structured and unstructured data, business and technical data, customer and transactional data. The volume, variety and velocity of data are shifting into a pattern of more, more, more. How do you like it?

The ability to analyze data – to strengthen decision-making – is separating smart organizations from the less smart. The ability to know the customer – to strengthen customer relationships – is paramount to maximizing customer lifetime value. The ability to protect data – to guarantee that data is lawfully shared – keeps organizations off the front page for the wrong reason. The ability to improve data quality – to trust that the answers you get from your data are accurate – leads to efficient and effective organizations.

In this expanding data-centric world we live in – it’s better to burn out than it is to rust. There’s more to the picture then meets the eye. Hey, Hey, My, My… It’s all in the Data.

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About Robert S. Seiner

Robert S. (Bob) Seiner is the publisher of The Data Administration Newsletter (TDAN.com) – and has been since it was introduced in 1997 – providing valuable content for people that work in Information & Data Management and related fields. TDAN.com is known for its timely and relevant articles, columns and features from thought-leaders and practitioners. Seiner and TDAN.com were recognized by DAMA International for significant and demonstrable contributions to Information and Data Resource Management industries. Seiner is the President and Principal of KIK Consulting & Educational Services, a data and information management consultancy that he started in 2002, providing practical and cost-effective solutions in the disciplines of data governance, data stewardship, metadata management and data strategy. Seiner is a recognized industry thought-leader, has consulted with and educated many prominent organizations nationally and globally, and is known for his unique approach to implementing data governance. His book “Non-Invasive Data Governance: The Path of Least Resistance and Greatest Success” was published in late 2014. Seiner speaks often at the industry’s leading conferences and provides a monthly webinar series titled “Real-World Data Governance” with DATAVERSITY.

  • Richord1

    Managing data in organizations requires behavior change. If we look at previous examples of behavior change in organizations we come across the example of quality.
    When Japanese car manufacturers were taking away market share from US manufacturers there was an uproar. Not an uproar about quality but about market share. So US manufacturers continued to turn out subpar cars and attempted to control the market through slick advertising (governance) such as; “Quality if Job One” and regulation, import taxes and restrictions. That didn’t go according to plan.

    Like quality, data can’t be “regulated” or “governed”.

    An organization has to decide whether their data is critical or not. They can’t be governed or regulated to make that decision. Data privacy is a case in point.
    In some domains such as health, data privacy is regulated. Breaches however abound and the consequences? If we can’t regulate or govern data privacy why do we think we can regulate or govern other aspects of data?

    Much of the data in organizations is a commodity not an asset. Differentiating which is which is the first step. Then applying data management practices to the “valuable” data can be accomplished.
    Many people in organizations spend much of their time pushing around commodity data so a reduction in the volume of commodity data (much of which ends up as big data) can also help reduce costs. That’s good data management without requiring regulation or governance.

  • http://www.decisionlab.net Daniel Upton

    All true, so let’s not allow ourselves, as data professionals, to become ‘comfortably numb’. This also dovetails nicely with the recent ‘Data Professional Introspective’. Thank you.

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