The Benefits and Costs of Using Metadata to Improve Enterprise Document Search

Abstract

The literature shows that there are many problems with enterprise document search. Studies reveal that typical knowledge workers spend between 10% and 20% of their time searching for documents they never find. While many argue that metadata can improve enterprise document search, in reality few organizations use metadata. This represents a missed opportunity. This article describes the results of two experiments that use simulation to evaluate the actual impact of metadata on the costs and benefits of enterprise search. The first study provides quantitative evidence of the increase in recall and precision that stems from the use of metadata-enhanced document searches. The second study demonstrates that simple metadata structures can be nearly as effective as complex ones, implying that the cost of creating and maintaining metadata is likely to be lower than generally thought. This is the first study to provide explicit quantitative evidence of the gains that can be achieved from the use of metadata, and one of only a handful of studies that examines the cost of creating and maintaining metadata.

Enterprise search and discovery capability: The factors and generative mechanisms for user satisfaction

“…Evidence from Enterprise Search deployments indicate lack of tags (and a lack of culture for metadata tagging by staff) is a factor for dissatisfaction [9,32,92]. Tagging is often considered challenging (pg.…”

“…The importance of meaningful titles (of documents or web pages), avoiding duplicate documents [91] and the value of user added metadata [32,92] are cited as information quality factors which tend to lead to more successful Enterprise Search user satisfaction [91]. However, enterprise users may often ‘deposit’ rather than ‘publish’ information, giving little thought to its future use or intended audience [59].…”

“…Evidence from Enterprise Search deployments indicate lack of tags (and a lack of culture for metadata tagging by staff) is a factor for dissatisfaction [9,32,92]. Tagging is often considered challenging (p. 4), ‘Any capture of metadata that took more than ten seconds to saving a file was considered problematic’ [97].…”

Stakeholder sentiment in service supply chains: big data meets agenda-setting theory

“…For example, big data have been used to personalize product offerings, prices, and display assortments through the utilization of downstream attributes including geo-localization, demographic information, and the time of day (Cohen 2017 ; Zhan and Tan 2018). Other benefits involve, customization in electronic retailing (Thirumalai and Sinha 2009 ), the use of metadata for enterprise document searches (Schymik et al 2015 ) targeted promotions and campaigns which reduce the costs involved in procurement, the use of service robots in the hotel industry impacting assurance and reliability (Chiang and Trimi, 2020 ), as well as predictive modeling and analytics aiding product and process modeling (Cohen 2017 ; Duan et al 2018 ). These capabilities have prompted service inseparability allowing for downstream entities to actively participate in service production and delivery which can lead to increased customer satisfaction and service productivity (Ahn and Rho 2016 ).…”

Design and evaluation of a video retrieval environment for exploratory searches in a learning context

“…Hence, the results list in the conceptual prototype follows the structure of YouTube results list, differing in the type of metadata presented. Azzopardi et al (2018) examined the utility of different element types, such as advertisements in the results, images, and news, in the search engine result list while Schymik, Corral, Schuff, and St Louis (2015) showed that when a search was enhanced with metadata, the success rate was improved in an enterprise document search.…”