It seems that not too long ago, any discussion regarding data management would have invoked one of three reactions: (1) eyes glazed over; (2) a faint recognition of the importance of data management, but little support or investment; or (3) an assumption that data management is a tech-only challenge and should be passed over to technology. Today, things have changed. Businesses large and small, across all industries, are coming to grips with the need to recognize, prioritize and manage data, as one of the most fundamental business assets of their institutions. What has changed? And what is yet to be understood?
We have seen a dramatic shift towards understanding data as a result of several key events. The financial crisis of 2008 was one such event and a turning point for the data management discipline. Data was not the cause of the crisis, but not being able to aggregate, compare, and truly understand the data that was before us impacted our ability, or the ability of the key decision makers, to react and respond. Imagine the best alarm system in the world installed in your home or office, that when activated, shouted commands to you in a foreign language that you could not understand. All of the data provided by the alarm system would have been correct. The delivery of the data was on time and on spec. But the ‘meaning’ of the data was missing. And without meaning, without that understanding, your response to the data would have been flawed, resulting in potentially fatal outcomes. The financial crisis brought this reality home. Understanding our data was suddenly promoted from the back office, to the c-suite. Data practices were being discussed in industry, across government agencies, and built into regulations. Data, data standards, and data management could be heard in testimony to Congress! The knock-on effect of not-knowing what our data was telling us became real.
And while events such as this were taking place, data itself was growing. If not understanding our data was bad enough; this same data was multiplying at enormous rates. Systems capturing hundreds of thousands, millions, or billions of events or transactions, are flooding into business systems. Databases are growing, capacity is expanding, but is the know-how to ‘understand’ and make sense of all this data, keeping pace?
Fair to say, we now know that data is important. We now know that data is critical to our everyday activities. Understanding our data is critical to running our business processes more efficiently, to controlling our costs, to creating better and more innovative products, and to servicing our customers better. But do we really know how to realize the true value of data? Do we really know the monetary impact of our data management decisions (or lack thereof)?
The bottom line is – data is the new currency. Yes, an expression that is being used quite a bit of late, but it is very relevant in discussing the importance of data and the methodologies by which we manage it. And like any currency, how we manage it determines its true value. Like any currency, it can be managed wisely, or it can be managed foolishly. It can be put to good use, or it can be squandered away. The question is – what factors determine the path that we take? How do we properly manage this asset and realize its full value and potential?
In Monetizing Data Management, Peter and Juanita explore the question of how to understand and place tangible value on data and data management. They explore this question through a series of examples and real-world use cases to exemplify how the true value of data can be realized. They show how bringing together business and technology, and applying a data-centric forensic approach can turn massive amounts of data into the tools needed to improve business processes, reduce costs, and better serve the customer.
Data monetization is not about turning data into money. Instead, it’s about taking information and turning it into opportunity. It’s about the need to understand the real meaning of data in order to extract value from it. And it’s about achieving this objective through a partnership with business and technology. Data management is not a discipline reserved for technology alone. Data management requires business understanding and an understanding of the subject matter at hand, coupled with innovative and supportive technology, to fully realize the true value of data – to inform, expose, and direct business activity to better serve its intended use. In Monetizing Data Management, the authors address these objectives and demonstrate how true value can be realized from our data through improved data centric approaches. Enjoy the read but make use of the examples …
John Bottega
Chief Data Officer for a large financial institution