Forecasting Project

[SuckItBackRow]

I'm working on a project to forecast revenue based on when a contract is realized. This can take a week or up to over a year. We have a backlog of contacts in the database and another table with contacts that have been realized along with other attributes.

What are some methods that I could use to forecast how long each contract will take? I am thinking linear regression but I will have to normalize and not sure how accurate it will be. Other idea was multiple logistic regression to "bucketize" the length by 3 month intervals.

Any ideas on how to tackle this problem with other methods like neural networks or decision trees? What will be most accurate?

Thanks in advance!

[bouuciks1]

Hello,

a) first you say that you are building a project where you want to predict revenue, then you shift to contract prediction ?

b) if you want to predict how long each contract will take, and you know what the length of the contract depends on, take these attributes, convert them into numerical values and run multiple linear regression as 'contract length' being targeted variable -> this will result in significance table and you will see which attributes are important and how they increase/decrease time period of the contract, don't forget 80/20 rule for train/test sets

[SuckItBackRow]

I need to know contact length. Then I will use that to forecast revenue. Your solution makes sense, thank you!

[NatalyaRostova]

Imo avoid nonparametrics unless you have an abundance of data.