CASE: Gradu8

Gradu8 are specialist recruiters for the global construction sector.

With projects in the UK, the Middle East, and Africa – and more than 15 years’ experience – Gradu8 places its priorities in excellence of service, speed and accuracy of results, and a peerless candidate experience.

“We need a system like eBoss, and here’s why…”

THE TASK:

The customer approached us with a straightforward question: how do we work on a database efficiently when we are inundated with candidate CVs?

This is a common question among recruiters. A database with thousands of candidates can mean traditional search techniques become bogged down in data. Consultants are either left to sort manually through thousands of qualified candidates, or forced to create arbitrary search rules, such as ignoring candidates who have been on the system for more than six months. But what if there is a perfect CV among those older profiles?

Early on in our consultation, we established that software limitations were not the issue in this case. In fact, all of Gradu8’s needs could be met with their existing account settings. There was no need to upgrade their system or introduce new features.

What would be required was a course of direct coaching to promote efficient use of the eBoss technology.

Our user experience team built a learning package to address the specific needs of the customer.

“With any CRM, there is a temptation that, when you get a new candidate, you immediately dump them onto the system.”

“We were aware that we weren’t always using that data effectively and our eBoss account manager showed us how to.”

~ Chris Pye, Gradu8

The deliverables for this case would include:

A course of one-to-one training webinars to ensure the whole Gradu8 family was familiar with key features.
Semantic search technology that would enable the firm to retain its growing database without slowing down its operations.
Communications tools to maintain relationships with candidates and ensure all stored data was relevant and accurate.

Success would be determined by the following outcomes:

Reduced times for completing a search of the database.
Reduced times-to-hired on live job orders
A recruitment software database that would allow the company to easily access, manage, and search through thousands of candidate profiles.

THE PROCESS:

We began with an initial one-hour group consultation. The Gradu8 team shared issues they encountered while managing an extensive CV database. And our consultant listened to the firm’s objectives, and preferred outcomes.

At the end of the first session, the client signed up for a further five hours of one-on-one training sessions.

Subsequent tutorials focused on workflows, database features, and methods of managing data to ensure easier searches.

The client found that semantic search was capable of retrieving only relevant documents – regardless of the volume of the database.

“After the first training session, we decided to stick with it.”

“We were not using eBoss to even 10% of its worth.”

In fact, over a course of six weekly one-hour sessions, the Gradu8 team quickly got to grips with some of the more advanced features of our system – semantic search, bulk communications, and automated matching.

After the sixth session, Gradu8 team leader Chris Pye was happy to report that his staff would require no further coaching – and that he was delighted with the quality of care he had received from our support team.

OUTCOMES:

Success was measured in performance data.

Gradu8 has increased its usage of the system – from data management, to communications tools, to deep searches on every job order.

But beyond the anecdotal evidence, there is clear proof that increased engagement with the eBoss system has benefited the company. These include:

• An 80% reduction in search times

Prior to training, Gradu8 would measure database search times in days, not hours.

Because the brand holds itself to such exacting standards, its consultants must ensure that no CV is left unchecked for relevance to an open job order. As database volume grew, this meant that initial longlisting could take two to three days to complete.

Now, working with semantic search, their longlists are ready in under four hours. And that is with a guarantee that all candidates on the database have been checked and qualified.

• A 40% reduction in times-to-hired for top roles

Gradu8 expects times-to-hired of 8 to 10 weeks for the most competitive roles. This is a typical timeframe for a new candidate to go from submitting a CV to ultimately receiving an offer.

For complex appointments, smaller time-saving tools make the biggest difference. An incremental improvement in basic admin or communications can add up over the period. In fact, with greater usage of the eBoss system, Gradu8 has improved their times to hired on top level appointments by 40%. The company now estimates the candidate journey at around six weeks – meaning a huge cost burden being lifted form the recruiter, the candidate, and the employer.

“We have reduced our times-to-hired on this type of job order down to six weeks from the candidate’s CV being uploaded, through interview, to an offer being made.”

“That six weeks is only achievable with eBoss. Without eBoss, that same process took 8 to 10 weeks.”

WHY SEMANTIC SEARCH?

In this case study, eBoss semantic search was the key feature which helped to resolve the client’s issues.

Semantic search is an advanced type of search engine which harnesses artificial intelligence and Big Data to produce more relevant search results. Semantic search allows eBoss users to retain an extensive CV database without removing data, and without wasting time on slow, manual searches.

How does semantic search work?

A standard (boolean) search looks for direct matches against your search terms. This can be useful, but it often leads to false matches being returned.

Gradu8 works in the construction sector. In 2020, that industry is just as likely to need data architects as it does building architects. A boolean search of the database for “architect” will return both types of candidate.

But a semantic search engine understands that the same search term does not always share the same level of relevance. Semantic search will return only the type of “architect” which fits the current job description.