...studies show that new forms of unstructured data remains an untapped resource, with only about one-third of it being properly used for strategic decision-making.
Data sources seem to be growing by the minute. While BI initiatives tend to focus on the information contained in ERP and CRM applications, relational databases, data warehoused and mart, and other enterprise systems, other important data sources have emerged, such as machine-generated, mobile, location, social media, and web monitoring data, which contain a wealth of crucial insight and potential competitive advantage.
Organizations that are best positioned to not only leverage these new sources of data but combine these new sources with traditional data, will out-perform their competition. Despite this, studies show that new forms of unstructured data remains an untapped resource, with only about one-third of it being properly used for strategic decision-making.
Companies who choose to ignore these sources do so at the risk of missing important opportunities. For example, vital insight into consumer sentiment can be found on Facebook and Twitter. Location data enhances the study of purchasing patterns, service consumption, and other activities by demonstrating the role geography plays. In addition, sensor or RFID data can alert you to potential manufacturing or supply chain problems.
Our customer, Michigan State Police (MSP), leverages our 3i platform to join traditional data with new data sources to better analyze drug, crime and crash predictions. For example, they combine the monitoring of past crime activity with predicted crime hot spots. They also enable command to map trooper car GPS signal patterns in relation to drug seizure hot spots and to analyze location pattern changes over time through animation. And, they are continually looking to incorporate new data feeds and analytics to improve trooper insights as they are available. This effective use of ALL available data is putting MSP on the leading edge of crime prevention.
This concludes our 5-part series on the top five worst practices in BI and analytics. Missed an installment? Catch up here: Part 1, Part 2, Part 3, Part 4.