Creating weighted scoring based on two attributes

Hello,

I am trying to generate a score for each company in my dataset that is based on two attributes - i.e., project count (the higher the better) and the average project size in MW (the higher the better).  My original dataset has individual projects mapped to each company, so each company may count one or more projects.  Each project then has a project size associated with it, so I could either calculate total size of a company's project portfolio in MW or an average project size in MW.  Because I am interested in identifying the top 20 companies that have both the highest number of projects and the largest projects in my dataset I assume I need to create a weighted composite score.  However, it is my understanding that I first need to normalize, or scale, my values.  This is where I am stuck.  I need help figuring out the best approach to creating the weighted composite scores so I can rank the companies in my dataset.

Would appreciate any advice!

Thanks~

Marina