H&S is an Executive Search Firm.
We are looking to develop a pilot that analyses large pool of unstructured data to provide insight into the success of H&S search and as a result the success of the placement within the client’s organization.
The tool will use data from H&S systems, such as email communication, latitude data, assessment tools, notes etc and potentially augmented by a short survey of placements (1-3 years post placement date). Using this data the tool will highlight themes emerging from machine learning capabilities.
This is a intended as a pilot (proof of concept). Once the concept is proven, we may wish to expand this tool to a larger and broader set of applications and questions.
QUESTIONS TO ADDRESS
The tool will be driven by themes that emerge from the data, but there are a few broad questions to be considered:
1. How good are we at predicting a successful candidate?
2. What are the main predictors how successful a placement will be once placed?
3. Where are the opportunities for us to improve our hiring hit rate? Efficiency?
INPUT DATA SOURCES
All from H&S:
• Data captured during the search process: age, years of experience, tests (WAVE etc), notes by
• Email communication with candidates
• Meeting requests and meetings held
Following placement (H&S data sources)
• Length of service at the job / at the same company
Consider a quick-fire survey to past placements asking 5-10 questions
• How happy are you in your role?
• What the key drivers to your success?
• Have you been promoted (considered for promotion)?
The tool will display a set of themes both in qualitative and quantitative form, identifying sources of success in placing candidates, correlation factors etc.
We would like to work with UK-based developers, as we expect close cooperation in developing the tool.