05 Dec

Expertise Analytics Platform

  • Intelligent Software Applications

Global presence causes geographically dispersed companies, institutes and organisations to have in-house experts across the globe who may never have met in person. In combination with the trend toward expertise specialisation, this dispersion creates an inherently difficult quest for the right, available multi-disciplinary team. Keeping track of your organisation's expertise can be make or break when competing in a global market.  So how do you locate those in-house experts? Searching the company’s intranet for relevant documents? Skimming through internal folder structures trying to estimate their relevance? Asking the company’s senior staff and relying on their typically localised network? In a world of interconnectivity, make the right connection quickly by mining the untapped resource of structured and unstructured data that underlies every organisation!

Your untapped data is a goldmine of opportunity!

Most companies have invested the last decades in their information systems: their documents are digital, stored in a document repository system and accessible through the intranet. Information on project execution is stored in a project management system that often offers capabilities to plan and allocate human resources, find optional usage, etc. In many companies, an additional plethora of databases for additional tasks is available: customer-relation databases, manufacturing databases, human resource databases, etc. Apart from the internal data sources a whole range of external data sources is available to find additional information on competitors, latest developments, etc.

We at S[&]T have developed an expertise analytics platform that automatically constructs an up-to-date expertise profile for employees based on the documents to which they are 'linked'. The S[&]T Expert Platform is an on-premises solution that allows you to locate that one invaluable expert with just the right combination of expertise, experience and availability. Even – or perhaps especially – when you have to find that person from a globally dispersed population of over 100,000 staff. We use machine learning to analyse all your existing documents: intranet/s, CV repositories, reports, presentations, professional social media profiles, and more.

For each employee, the platform creates expertise profiles, allowing you to:

  • Match CVs with vacancies
  • Build optimal cross-department project teams
  • Find a subject matter expert within international enterprises
  • Analyse the impact of mergers, acquisitions, and divestments on expertise position
  • Track trends over time regarding your expertise position
  • Define and monitor recruitment targets for their expertise
  • Visualise expertise assets
  • Assess competitive landscape from scientifically documented links
  • Create an intracompany network of specialists or scientists

Ontological Analysis

Ontology: a crucial concept in data mining

An ‘ontology’ is a data structure that describes all relevant search terms as well as the relationships between those entities. The relationships differentiate it from a simple database of entities. For instance, the ontology defines a “narrower-than” relationship between “renewable energy” and “wind energy”. The ontology can be largely created from readily available databases and documents and can also be adjusted to match the client’s domain. 

The expertise analytics platform exploits the ontology relationships in the matching process: the search query is automatically expanded with narrower defined concepts; searching for people that have “renewable energy” in their expertise profile would automatically include those people that have “wind energy” in their profile. Candidate concepts not yet covered by the ontology are automatically captured by the term extraction software.

Text is analysed using a suite of semantic tools developed by S[&]T to extract metadata such as named entities (people, organisations), location information (city, country), phone numbers and email addresses. Mentions of known concepts, defined in an ontology, are extracted and so are mentions of new, interesting ontological terms that are not covered by the pre-defined ontology.