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Today many organizations are finally seeing the light on the importance of centralizing information in enterprise content management systems rather than on public drives, file-sharing tools and so on. It hasn't been an easy road, in some cases, with change management necessary along the way.
But with knowledge comes acceptance. Some have adopted technologies such as Microsoft SharePoint to facilitate access from anywhere to meaningful business data. And with the growth in data being forecasted at 44 times its current volume a year, this offers significant opportunity for organizations to analyze their data within their enterprise content management (ECM) or Web content management system.
One of the key roles of an ECM system is delivering the information for which users query. But the results are not always accurate.
Content analytics applies business intelligence (BI) and business analytics, or BA, practices to digital content. Companies use content analytics software to provide visibility into the amount of content that is being created, the nature of the content and how it is used.
There are significant insights to be extracted from structured and unstructured data within ECM platforms, which content analytics, or ECM analytics, can provide. Data residing in these systems can range from discussion boards, project sites, document libraries, page visit trends and other digital content. This information provides a wealth of actionable data for enterprises.
The benefits of ECM analytics
In terms of the benefits from ECM analytics, many organizations cite the following as the most relevant.
Smarter enterprise search capabilities. One of the key roles of an ECM system is its ability to deliver the information for which users query. But the results are not always contextual and accurate. However, with natural language processing and advanced processing of unstructured data, some analytics tools can process digital content and extract and return the right data that may come from diverse internal and external data sources.
By combining the power of ECM with some of the analytics tools in the marketplace, finding information goes beyond simply retrieving documents that reference keywords from a search box; rather, it's about providing recommendations based on the context and meaning of the request. When a hiring manager searches for "offer letters," the system may return additional links for a new employee checklist or new employee packet, because the system identifies them as related as useful documents.
Advanced content classification. When it comes to ensuring the success of an ECM system, implementing strong document or content classification is a key component. Unfortunately, it can become cumbersome for users who may be required to manually classify some of the documents they publish or store within an ECM system. However, with some of the text analytics tools available, content-specific identifiers can be preconfigured to classify content by extracting document meaning and context automatically. This improves document classifications and enhances the capabilities of the system.
Next-generation interactive BI engine. Dashboards, key performance indicators (KPIs), reports and other measures are critical data points. With them, users can gain deeper business insight from data. But in many organizations, numerous reports, spreadsheets, dashboards and other business summaries are dispersed among business units, which makes it difficult to identify the right information when it's needed. Many analytics applications can integrate with BI platforms and provide access to the right reports and information without users having to browse and drill down in the system. An executive might ask the system to "display the sales trends in the past six months by country and business unit," and the system could retrieve the sales report and add the appropriate parameters to provide the executive with the correct results.
System use and visitor behavior monitoring. Most ECM systems track content authoring, visitors and some of the interactions happening on a website. Much like analytics tools that monitor and interact with social media sites, some tools target enterprise systems to gain insight into how employees seek information. This can lead to useful information concerning which content users use frequently, as well as areas that need improvement because they lack visitor traffic.
The challenges of ECM analytics
Using analytics tools in an ECM system presents new challenges as well. Organizations must weigh the usefulness of the data against costs and other concerns that come along with ECM analytics.
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Additional processing power and storage. In this era of large data consumption and the ever-increasing need to retain system logs and other information, organizations require faster processing and more storage. An effective ECM analytics strategy means investing in a computing environment powerful enough to sustain near-real-time analysis of rapidly growing volumes of data. And while storage is getting cheaper, having enough to support an information-intensive ECM system can be costly.
Ethical considerations. The ability to learn from employee behavior and sentiment requires closely monitoring every click and interaction. In some cases, managers can use these techniques to measure employee performance. While the productivity and staffing benefits may be high, companies need to avoid encroaching on employees' privacy.
Security concerns. As we continue to mine information more efficiently, concerns about data security grow. Managing different data pools, user access and data integrity become greater burdens and concerns in the era of big data.
An ECM platform can assist companies in data sharing and collaboration, and new social components -- like Yammer in SharePoint -- promise to enhance these capabilities. Whether the content being managed is structured or unstructured, these systems offer real benefits to organizations. With the addition of advanced analytics tools, an ECM system can offer an intelligent and sophisticated way for knowledge workers to extract data and make business decisions.