What makes Elements Intelligence different?
Big market research reports are costly and take months to produce. Talent analytics software packages use incomplete datasets that can’t be customised to individual needs. Against this backdrop, four key characteristics that set Elements Intelligence apart.
1. Exhaustive & customisable range of inputs
We extract data from over 60 separate sources to address the precise scope of each engagement. This ensures that we reflect the realities of the talent landscape as accurately and relevantly as possible.
2. Rigorous quality control
Location data are missing or inaccurate in more than 30% of Linkedin profiles. We use human rigour to ensure data inputs (and thus outputs) are as complete and consistent as possible.
3. AI-Augmented ethnicity insights
We have exclusive access to third party AI that derives gender and ethnicity from name and location with over 95% accuracy. Most solutions offer no ethnicity insights. None offer any better.
4. Speed & recency of outputs
Since we pull live datasets for each engagement and produce results within 4 weeks, our insights are more recent and reliable than the big market research reports.
A meticulous methodology that guarantees high-quality results
Not all talent insights are created equal. The accuracy and reliability of outputs is dependent on the quality of the methodology used to produce them. Our methodology applies unparalleled rigour to ensure the insights we produce are as accurate and representative as possible.
1 Partner Discovery
Every engagement begins with a thorough discovery process to highlight the full range of insights available and define the precise scope of the project.
2 Data Extraction
We extract live candidate data from multiple sources to ensure we’re accurately reflecting the latest realities of each talent pool.
3 Data Cleansing
We then apply human rigour to the combined dataset to ensure that duplicates are consolidated and omissions rectified.
4 Data Augmentation
We have exclusive commercial access to AI developed in collaboration with the University of Chicago and trusted by the United Nations. This uses self-declared datasets to derive gender and ethnicity from name and location with over 95% accuracy.
5 Analysis
The consolidated, cleansed and augmented dataset is analysed to identify key findings that address the key challenges defined in the discovery process.
6 Presentation
We use third party data visualisation software to present findings, commentary and recommendations in a format that can be easily digested, shared and scrutinised by multiple end-
users.
Bespoke insights + expert commentary in a format that is easily digested and shared
Our reports follow the scientific method, beginning with the hypothesis that is being tested, detailing the methodology employed, presenting the findings and concluding with a recommendation from our team of expert talent market consultants. They are presented in an interactive format that can be easily digested, shared and scrutinised by multiple end-users.
