Recent technological advances have yielded an explosion in the creation of data, as well as in the number of companies employing newly-available operational and customer data as critical drivers of business value. A full 90 percent of all the data in the world has been generated in the last few years, and this trend will only accelerate—total global data is estimated to grow by a factor of 10 by the year 2020. A single office building can collect tidal waves of data per minute from smart technology, e-mail messages, audio, video, sensors, meters, RFID tags, social media, and so on.
Properly analyzing big data leads to more confident decision making. It boosts operational efficiency, while reducing costs and risk. But most organizations fail to fully realize the value available to them. Why? Big data is generally high volume, transaction-based, and unstructured. It arrives in real time, and often shows trends and periodic peaks. And most companies have not developed or attracted sufficient talent with the expertise required to translate their big data into digestible information. It is estimated that, in the United States alone, more than 1.5 million data-savvy managers are currently needed to enable organizations to take full advantage of big data.
As they seek to navigate the new frontiers opened by big data, smart company leaders are honing in on key questions: how can I identify which information is relevant? What models can I use for valuing or pricing the data I have? How can I leverage idle data into a productive asset?
To help companies quantify the value of their business data, Doug Laney of Gartner created the theory of Infonomics. This theory has drawn significant public attention and has become a milestone of progress in the industry. Simply put, Infonomics provides a framework for CEOs to value, manage, and wield information as a real asset in generating revenue.
Infonomics empowers business leaders with a framework for pricing their information assets. This knowledge informs decision making and clarifies the gap between a company’s realized and potential information value. Unfortunately, applying Infonomics models effectively is far easier said than done. But after years helping clients harness the potential of their data, we have derived several key recommendations for business leaders who are interested in putting the Infonomics theory into practice.DOWNLOAD WHITEPAPER
 Selinger, D. (2013, January 15). Big Data: Getting Ready For The 2013 Big Bang. Retrieved from https://www.forbes.com/sites/ciocentral/2013/01/15/big-data-get-ready-for-the-2013-big-bang/
 Manyika, J., Chui, M., & Brown, B. (2011). Big data: The next frontier for innovation, competition, and productivity (p. 105). McKinsey Global Institute.
 Analyst Profile – Douglas Laney. Retrieved from https://www.gartner.com/analyst/40872/Douglas-Laney
 Tucci, L. (2013, May 8). Putting a price on information: The nascent field of infonomics. Retrieved from https://searchcio.techtarget.com/opinion/Putting-a-price-on-information-The-nascent-field-of-infonomics