Saturday, March 14, 2009

Developing the Job Offer Evaluation

We developed the Job Offer Evaluation for an example of what you can do with FactorHub. Do we think it is perfect? In no way. Will it accurately predict a salary for a job in consideration? Maybe.

So let's explain it how we built it:

During our research we found over 250 factors people should consider when researching a job. We were amazed - we thought at most 20 factors.

Only 100 or so factors made it into the Job Offer Evaluation. We felt these were the broadest factors to consider when evaluating an offer. We have another Template we may expose later that trims the 100 factors into 60 of the most significant factors.

Narrowing down to the 100 we used, we eliminated things like:

• Factor: Desperately seeking another job. Should that lower or raise your salary requirements?

• Factor: Person left job to go to another company. Is that a red flag that you may be a short timer or not work out because of the position duties or manager?

We also had factors that described your new manager, and integrated them into choosing a job. What we realized was we could do a whole other Template just about a person's manager. ;)

The lowest salary possible is based on the 2009 United States Poverty Line - approximately $11,000 a year. Hopefully your offer comes in well above that, and here is additional explanation to interpret the salary results:

Let's say the model returns $70k a year, but your job offer is in the neighborhood of $30k a year:

We feel this job has too many negatives or you may be over qualified. You may consider asking for a higher starting salary to compensate for things like lack of healthcare or vacation benefits.

Let's say the model returns $30k a year, but your job offer is in the neighborhood of $70k a year:

This is much better than it looks. It means that all of the benefits and other factors around this job are so good - the salary doesn't need to be so high to compensate. However the lowest salary could mean that you are not qualified for the job.

Overall, it will be interesting to see the aggregated results to create newer models.

What factors do you think people should consider when evaluating a job?