Other times the term is used to describe a methodology platform, an integrated set of best practices that enables the organization to manage its data as a corporate asset in order to achieve superior business performance.
Data governance is an example of a methodology platform, where one of its central concepts is the definition, implementation, and enforcement of policies, which govern the interactions between business processes, data, technology and people.
But many rightfully lament the misleading term “data governance” because it appears to put the emphasis on data, arguing that since business needs come first in every organization, data governance should be formalized as a business process, and therefore mature organizations should view data governance as business process management.
However, successful enterprise data management is about much more than data, business processes, or enabling technology.
Business process management, data quality management and technology management are all people-driven activities because people empowered by high quality data, enabled by technology, optimize business processes for superior business performance.
Data governance policies illustrate the intersection of business, data, and technical knowledge, which is spread throughout the enterprise, transcending any artificial boundaries imposed by an organizational chart, where different departments or different business functions appear as if they were independent of the rest of the organization.
Data governance policies reveal how truly interconnected and interdependent the organization is, and how everything that happens within the organization happens as a result of the interactions occurring among its people.
Michael Fauscette defines people-centricity as “our current social and business progression past the industrial society’s focus on business, technology, and process. Not that business or technology or process go away, but instead they become supporting structures that facilitate new ways of collaborating and interacting with customers, suppliers, partners, and employees.”
In short, Fauscette believes people are becoming the new enterprise platform – and not just for data management.
I agree, but I would argue that people have always been – and always will be – the only successful enterprise platform.
Factories, shipping companies, banks all operate on the basis of a set of core algorithms that lie somewhere within the organization's elaborate facade. Social networks and other forms of collaboration media are novelties that distract the people from interfering with the algorithms.
We Facebook, twitter, blog and e-mail while the algorithms keep the business running.
Risk is measured using algorithms, performance is measured using algorithms, production scheduling, yield and supply chain management all rely on these algorithms.
People, except those developing the algorithms, are overhead, performing those mundane tasks that the rocket scientists have not captured in an algorithm.
To an algorithm a "customer" is a "commodity". A relationship with a customer is the number of touch points, the number of transactions and the retention rate. To Amazon a customer is a commodity. No one in Amazon knows anything about you the person. But Amazon's algorithms know a lot about you as a commodity.
Algorithms essentially run Wall Street and the global economy. Algorithms run our utilities.
We talk about artificial intelligence as an unachievable goal. IBM's Watson is a manifestation of numerous algorithms optimized to play Jeopardy. That's as artificial as you can get to intelligence. Watson has no personality, no moods, and no emotions. It's "intelligent" and it's artificial.
Our organizations are increasingly algorithm centric.
Algorithms don't need data governance. They are data dictatorships!