We partnered with a large global consulting firm to classify their inbound applicants with their unique lens on talent. Their recruiting department saw a major boost in efficiency and their talent database became a valuable asset.
Salesforce, Jobscience (Bullhorn)
A global consulting firm has been manually tagging employees and applicants in their talent database for several years. The goal was to get a snapshot of individuals that would represent their skills, capabilities, experiences levels, and industry experience. From there, users would be able to segment and group individuals easily in order to streamline talent-related decisions. The hope was to make activities like measuring resources, assembling teams, or creating the perfect shortlist of candidates easier by leveraging their database.
However, with numerous tags split between several different groups and nearly 100 individual tagging options, the process became unwieldy. It was difficult to stay consistent with the definitions around each tag and when or when not to apply a tag to a specific contact. The database was rapidly growing with new contacts and it became exceedingly difficult for employees to keep up and stay consistent with the manual tagging. More issues were introduced as tag consistency and usage decreased. After the initiative slowed and the database was no more useful than it had been previously, they realized it was time for automation.
But, how do you automate a task that relies on the cognitive ability of an individual or team?
The solution required a set of custom intelligent neural network AI models. Partnering with Vettd enabled our customer to utilize their own tagged resume documents to train a series of custom NLP models. They integrated and deployed those models to evaluate every new contact added to their system according to their unique view on talent.
Using Vettd Studio, the tagging taxonomy was added and the applicable training data was imported. Within a matter of weeks, the first versions of each model were created, validated, and tested. Utilizing Vettd Hub, the Vettd team built out a complete end-to-end solution for them including:
The result was 100% tagging automation for every new and historical contact in their database. The accuracy of the models had been evaluated and approved within Vettd Studio prior to deploying and models to production. All processed data can be monitored and tracked in Vettd Hub and further used to re-train and update their models as needed. This company now has a complete, consistent and continuously updated database of tagged talent available to their team. Not only did this improve the organization and accuracy of their talent database, but they've reduced the time required for their team to manually tag the 1,000's of applicants that come into their system each month.