Using Data Connection to Find the Expert and Reduce Hiring Costs

subject matter expert reviewing knowledge base with data connection

Subject matter experts are hard to come by when looking to hire in specialized areas. However, many companies do not realize that the specialties they are seeking already exist in their organization. Thus using data connection to find the expert and reduce hiring costs.

With proper data connection powered by artificial intelligence and machine learning, subject matter experts can be identified internally, which helps to – reduce costs and get the most out of your existing workforce.

In addition, data connection and a holistic approach to knowledge management give other employees the ability to know what the experts know with just a few clicks.

Seeking Unique Information Within Your Organization

Valuable data sits all around your company in different data sources. Ensuring your company uses a solution equipped with connectors and out-of-the-box knowledge collection techniques is the first step to finding technical information and relationships.

For example, a pharmaceutical company preparing to launch a new drug needs a wide range of materials from different departments – administration, research, development, regulatory, compliance, and more. Linking data and breaking down silos permits current workers to establish relationships and find patterns between relevant information in all areas of the operation.

Machine learning techniques like entity recognition, knowledge extraction, classification, semantic relations, proactive insights, and natural language processing automates the tiresome hunt for knowledge.

Using such techniques gives every necessary employee assigned to a specialized project the capacity to learn at a very high-level and intake an outstanding amount of knowledge. These tools directly reduce the need to hire expensive workers because they create more experts within the company.

Sticking with the pharmaceutical example, researchers looking for details related to a similar drug undergoing preparation will gain access to all relevant documentation and materials within the company’s datasets. The terminology and categories they are searching for will be extracted and filled with insights, whether it be regarding side effects, dosage information, treatable illnesses, and more. It is important to note that this goes well beyond the pharmaceutical industry and can be applied to any project in any industry that requires specializations.

Finding the Existing Expert

Data connection powered by machine learning can be used for all sorts of relationship-finding. Included in this is pinpointing the existing expert. A company launching a product aimed at a new business vertical may think they need to hire a veteran of that industry. Little do they know; the expert may already be within the corporation, and high hiring costs can be avoided.

Genuine subject matter experts are identifiable by analyzing the digital footprints of your organization. In compliance with data privacy laws, information from personnel files, internal collaboration platforms, and previously authored documents are united to highlight the “expert.”

Knowledge graphs are crucial in showing the connection between the subject and the expert. Knowledge graphs are an organized graph-structured model linking people to files created, support tickets solved, and other created content by the individual. Quickly and simply, management can see their workforce’s whole experience relating to a given subject.

Perhaps, a particular individual has worked on a similar project in the past and can take on the role of consulting or overseeing the new business case.

Without artificial intelligence, the company would never realize employees’ expertise, and valuable time and resources would be spent inefficiently.

The Importance to Companies and their Bottom Line

With labor hard to come by and specialized employees being fairly expensive, companies need to use everything in their toolbox before making a large spend or using valuable time recruiting. Equipping management teams and other members of the workforce allows dedicated workers to become the experts themselves while also shedding light on skills that are already present. Without the proper approach to data connection, endless possibilities in staff management may go unrealized and vital assets in your organization may feel under-appreciated.

So, before making that next huge hire, I urge you to look within and see what you already have. Doing so may save you a lot of dollars and time while feeding your workforce more intelligence and proactive insights on specialized projects or assignments.


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As Mindbreeze’s CEO, founded in 2005, Daniel Fallmann is a living example of high quality and innovation standards. From the company’s very beginning, Fallmann, together with his team, laid the foundation for the highly scalable and intelligent Mindbreeze InSpire appliance. His passion for enterprise search and machine learning in a big data environment has fascinated not only the Mindbreeze employees, but also their customers.