Recruiters spend countless hours figuring out what to write in job descriptions correctly; working closely with hiring managers to ensure that the required skills, background, qualifications, experience and training are appropriate.
Those same recruiters then spend days more reading resumes and cover letters, scouring online resume postings and social media platforms. The recruiters are looking to match what they read in cover letters, social media profiles and resumes with those same job descriptions. Even with automated keyword-search systems, the process is tedious and time consuming.
Recruiters and other human resource staff at companies large and small want one thing: to find the candidates who best match the needed skills quickly.
The problem is that, often, keyword searches don't really do the job. Using keyword-based search to match supply with demand has serious limitations. Keyword search does not provide relevant results in many cases. Keyword search does not understand the context and semantics around the words. It does not cater to the real-world need of advanced search. It cannot consider multiple attributes and complicated conditions on these attributes.
Spire's Contextual Intelligence platform contextualizes i.e., generates meaning from both demand and supply documents, searches and maps the relevant supply documents and also ranks the relevancy of results. It has the capability to process data of any format, in this case textual documents (resumes, job descriptions, job applications) in a human-like manner, which machines normally are not trained to since they mostly work only with quantifiable data, i.e., numerical.
Spire’s contextual capability stems from two unique features that the core platform has.
First, it can comprehend any type of unstructured data, of any format and from any source by generating its meaning, the context of it. Unstructured data, in particular refers to the type of data which cannot be quantified and which is typically in textual form.
Second, the platform performs contextual analysis of unstructured data. It generates context of the demand and supply data and interprets it intelligently in the form of comprehensive analytics which bring forth a host of valuable insights.
The above two capabilities in addition to ‘contextual search and match’ drill down thousands of resumes and select only the most relevant candidates in a matter of few hours or days. Companies get to invite only the most relevant candidates for interviews and increase their interview-to-select ratio to a proven 70%. The prevailing ratio is less than 30%.
Spire Acqura can be applied in the talent acquisition process for selecting the most relevant resumes. As a result recruiters can save time, costs and reduce operational effort. Acqura can also process resumes of different formats, from different sources simultaneously.
Spire TalentVista is a social networking and collaboration tool that operates in the world wide web space. It searches, locates and engages with relevant professionals by amassing data from the entire web. Companies can create their own social ecosystem to engage with potential candidates well in advance and convert them into employees.
Both of the above make life easy for recruiters by eliminating their routine woes.
Confidence! The matching capability is 80% accurate and the search is 95% accurate, the highest ever recorded amongst such available tools in the market.
Recruiters get more time to focus on their core HR functions as they spend 50% less time screening and matching resumes. Acqura users have reported 40 % reduction in time-to-hire. This time can be better spent using TalentVista to engage in meaningful relationship building, mentoring and counseling with passive job seekers in social style.
Contextual technology converts any type of talent data into real-time intelligence, into valuable insights, also particularly for Chief Executives.