Enterprise Feedback Management

Enterprise feedback management (EFM) is a system of processes and software that enables organizations to centrally manage deployment of surveys while dispersing authoring and analysis throughout an organization. EFM systems typically provide different roles and permission levels for different types of users, such as novice survey authors, professional survey authors, survey reporters and translators. EFM can help an organization establish a dialogue with employees, partners, and customers regarding key issues and concerns and potentially make customer-specific real time interventions. EFM consists of data collection, analysis and reporting.

Modern EFM systems can track feedback from a variety of sources including customers, market research, social media, employees, vendors, partners and audits in a privatized or public manner.

EFM systems can be applied by companies operating in different fields: e.g., systems provided by Confirmit, CXGroup, InMoment, MaritzCX, Clarabridge, Medallia, NICE Systems, Netigate, Qualtrics, QuestBack, Verint are used by more than half of the Fortune 100 companies from business services, consumer goods, financial services, government and public services, healthcare, manufacturing, media and communication, non-profit and other associations, research and professional services, retail, technology, and travel, hospitality, and restaurants industries.

The term enterprise feedback management was coined by Perseus Development in 2004 and was first popularized in 2005 by Gartner. Their definition of it was "formal tools for data collection and output analysis".

Prior to EFM, survey software was typically deployed in departments and lacked user roles, permissions and workflow. EFM enables deployment across the enterprise, providing decision makers with important data for increasing customer satisfaction, loyalty and lifetime value. EFM enables companies to look at customers "holistically" and to better respond to customer needs.

Enterprise feedback management systems root from PA technologies. It is possible to infer about the PA that they represent a part of such a vast field of knowledge as data mining. The forecast of the current and future tendencies is based on the data already acquired. PA implies various types of modeling: clustering (cluster analysis), decision trees, regression analysis, artificial neural networks, text mining, hypothesis testing, etc. Predictive Analysis technologies are actually tools to transform data to information and then to knowledge. This transformation was partly described in the article As We May Think written by Vannevar Bush in 1945.

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