Concept Searching Surfaces Intelligent Content in Context
Concept Searching, multi-term metadata generation, auto-classification, and taxonomy management software provider, announced that the platform now enables its users to automatically generate intelligent content in context in order to improve the workplace, increase task productivity, and reduce costs.
The difference between intelligent content in context and traditional enterprise search queries is that relevant content is surfaced at the point of need. In other words, highly resembling content is delivered, based on a particular process step, decision point, or user interaction. Martin Garland, President of Concept Searching, commented, “Many organizations have been using the same workday processes and often the same core applications used 15 years ago. They are now seeking technologies that can tie silos of information together, and are evaluating approaches to improve employee satisfaction and to implement software and new processes that improve the bottom line, without losing their investment in infrastructure and core applications.”
Intelligent content in context is the output of the platforms and products that make up the Smart Content Framework, deployed as an infrastructure metadata layer, enabling the identification and surfacing of intelligent content in context to any business application able to consume it.
The Value of Intelligent Content in Context
The costs of searching for information to companies has been underestimated, but actually it is a big deal. According to IDC, 40% of employees can’t find information to do their jobs while 15% is spent duplicating information. Also, 85% of relevant information is never retrieved in search. The study shows if a worker cannot find the information they are seeking within 4 minutes they will either recreate it, use older content assets or interrupt a co-worker. It costs companies, not only because of the extended time workers spend searching for information online, which is estimated at least 10 hours a week, but also because of the fact that between 3% and 5% of an organization’s files are lost or misplaced. Annual losses to a Fortune 1000 company with one million files is $5M, according to Information Week data. On the other hand, if the median Fortune 1000 company were to increase the usability of its data by 10%, company revenue would be expected to increase by $2.02 billion, based on InsightSquared’s study.
Manual tagging system has been commonly used in over 93% of organizations, according to Concept Searching. The problem with this system is that it’s mostly incorrect, subjective, and outdated. It is also ineffectively used as the majority selects the first option from a drop-down list, regardless of whether or not it is applicable. Since the end user is mostly the reason of dysfunctionality, the solution would be eliminating human factor from the process. After all, an organization shouldn’t rely on end users in hopes they readily know all the record codes. The auto-classification capability tags content and identifies the most relevant knowledge assets for repurposing and reuse. Therefore, Concept Searching provides conceptTaxonomyWorkflow enabling organizations to automate the classification of documents of record. How does it work? For example, when a classification criteria is met for a document of record, it triggers the rule to send it to the records management application and to the owner of the record, and the SharePoint environment will automatically change the content type to the type of record, listing the multi-word terms that were used to classify the document. Using metadata tagging and auto-classification results in qualitative content optimization.
Finding any content at the point of need is great and benefits an organization in many ways but there is some content, such as financial statements, engineering drawings, or new product information, which shouldn’t be widely accessible via a search for the sake of confidentiality. At this point, Concept Searching also provides the ability to associate text with the descriptor. With this flexibility, the platform allows users to remove the item from search, send to a secure repository or application, prevent portability, or send to the person responsible. It is important because 80% of employees use insecure file sharing methods, putting corporate data at risk, according to the data provided by Workshare. Once it’s happened, the average cost of a data breach is $4 million, and 70% of data breaches are caused by internal employees, says Ponemon Institute & IBM. Compliance, policies, and processes should all be automated through auto-classification where the end user is removed from the process so organizations can make sure that no records are omitted or mistagged.
As we all know by now, customer satisfaction goes hand in hand with employee satisfaction, and they have such a direct influence on each other. Since customers and prospects expect personalization, responsiveness, competency, and convenience from their vendors, it is safe to say that accurate and relevant information throughout the sales and customer service life cycle is crucial. That’s why the metadata environment has a ripple effect on customer satisfaction as sales and support in organizations implementing data quality solutions can build brand loyalty through providing consistently accurate data to their customers in a short period of time.
According to Concept Searching, one of their clients, a provider of market intelligence and advisory services for the information technology market, needed to deliver qualitative, verified content in context for its 1,100 analysts and clients. The company deployed the conceptClassifier platform to build a metadata environment for all research and published information for its analyst and client facing portals. The ability to now identify content in context ensures accurate and relevant information is retrieved at the point of need. Only 6 months after the deployment of the metadata environment, client satisfaction increased from 62% to over 80%.
Searching for expertise or knowledge within the organization shouldn’t cost organizations, instead it should improve productivity, response time, and brand equity. The purpose of using intelligent content in context is to improve search, record management, identification and protection of confidential data, intelligent migration, secure collaboration, content optimization, and text analytics.