Difference between revisions of "04 job es2j063d produce report scored potential pred succs"
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'''Job Features and Functions''' | '''Job Features and Functions''' | ||
| − | + | <small>''' | |
| + | *Identifies likely potential predecessors and successors | ||
| + | *Calculates a probability score of predecessor/successor linkage | ||
| + | *Score is based on common characteristics in predecessor and successor, such as EIN, city, phone geocode, county, NAICS, and ZIP Code | ||
| + | *A higher score indicates higher probability of predecessor/successor link | ||
| + | *Job requires a Wage Summary File; | ||
| + | **States lacking a Wage Summary File cannot run this job | ||
| + | '''</small> | ||
Job 063D is used to apply a scoring algorithm to the potential predecessor/successor relationships, using such factors as the employment levels, the physical address, name, etc. Those with the highest scores are the most likely matches between the potential predecessor and successor pairings. | Job 063D is used to apply a scoring algorithm to the potential predecessor/successor relationships, using such factors as the employment levels, the physical address, name, etc. Those with the highest scores are the most likely matches between the potential predecessor and successor pairings. | ||
Latest revision as of 17:22, 13 April 2020
Job ES2J063D - Produce Report of Scored Potential Pred/Succ's
RUN THIS JOB - As required.
This job executes the following programs (click to link to each program description):
Job Features and Functions
- Identifies likely potential predecessors and successors
- Calculates a probability score of predecessor/successor linkage
- Score is based on common characteristics in predecessor and successor, such as EIN, city, phone geocode, county, NAICS, and ZIP Code
- A higher score indicates higher probability of predecessor/successor link
- Job requires a Wage Summary File;
- States lacking a Wage Summary File cannot run this job
Job 063D is used to apply a scoring algorithm to the potential predecessor/successor relationships, using such factors as the employment levels, the physical address, name, etc. Those with the highest scores are the most likely matches between the potential predecessor and successor pairings.
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