Data and information silos are a significant problem for organizations getting full value from data. Data silos are separate databases or data files that are not part of an organization's enterprise-wide data administration. An information silo is where parts of the information management system is unable to freely communicate with other information management systems. A siloed application is an application that does not interact with other applications or information systems.
The data science revolution depends on collecting, storing, analyzing and distributing massive volumes and varieties of data to turn into knowledge and valuable, actionable insights. The real value is from mixing different internal and external data sources and sharing information within a culture of collaboration.
Strong evidence suggests that organizations utilizing a variety of both internal and external data sources - in conjunction with data science and business analytics - outperform firms that only rely on internal data and have data silos that prevent data science practice, information sharing and collaboration.
Unfortunately, managers have strong incentives to silo information to maintain power. As a result, organization leadership must have an information management strategy and policy of sharing information to break the deadly "data silo" status quo.
Data and information silos often exist because managers control the flow of information and access to the silo, and they perceive (1) their power and careers depend on information control; (2) there is not enough benefit from sharing information; (3) information might not be useful to folks in other systems; (4) costs to integrating the information systems is not justified.
In addition, data silos are a danger to data integrity increasing the risk that current (or more recent) data will accidentally get overwritten with outdated (or less recent) data. When two or more silos exist for the same data, their contents might differ, creating confusion as to which repository represents the most legitimate or up-to-date version.
According to a recent CompTIA survey:
To fully benefit from the data science revolution, organizations must change the incentive structure for managers to hoard and control information and prevent data and information silos from impeding the quest for competitive advantage.
See: http://bit.ly/1kXsipc
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The data science revolution depends on collecting, storing, analyzing and distributing massive volumes and varieties of data to turn into knowledge and valuable, actionable insights. The real value is from mixing different internal and external data sources and sharing information within a culture of collaboration.
Strong evidence suggests that organizations utilizing a variety of both internal and external data sources - in conjunction with data science and business analytics - outperform firms that only rely on internal data and have data silos that prevent data science practice, information sharing and collaboration.
Unfortunately, managers have strong incentives to silo information to maintain power. As a result, organization leadership must have an information management strategy and policy of sharing information to break the deadly "data silo" status quo.
Data and information silos often exist because managers control the flow of information and access to the silo, and they perceive (1) their power and careers depend on information control; (2) there is not enough benefit from sharing information; (3) information might not be useful to folks in other systems; (4) costs to integrating the information systems is not justified.
In addition, data silos are a danger to data integrity increasing the risk that current (or more recent) data will accidentally get overwritten with outdated (or less recent) data. When two or more silos exist for the same data, their contents might differ, creating confusion as to which repository represents the most legitimate or up-to-date version.
According to a recent CompTIA survey:
- Eight (8) in ten (10) organizations report high or moderate degrees of data silos - collections of data that have grown across the organization or within specific departments which are not connected in a cohesive plan.
- Only thirty-one percent (31%) report being able to provide a comprehensive single customer view (SCV), meaning potentially valuable customer data points are not fully integrated.
- Two-thirds of organizations report definitely or probably experiencing some degree of shadow (or rogue) data repositories, whereby staff may be maintaining their own contact or prospect list.
To fully benefit from the data science revolution, organizations must change the incentive structure for managers to hoard and control information and prevent data and information silos from impeding the quest for competitive advantage.
See: http://bit.ly/1kXsipc
0 Comments
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