Hope someone can help me with some fairly favourable pointers on this subject.

I have historical data to draw from and wish to forecast possible turnover according to parameters I can use taken from these existing analogues.

My historical data consists of the performance of outlets before and after they were assigned an business investment, as below.


a) Old turnover
b) Business investment type a)
c) Business investment type b)
d) New turnover
e) Turnover uplift percentage
f) Old size of outlet
g) New size of outlet
h) Turnover by size of outlet
i) Value of customer market
j) Old percentage share of market
k) New percentage share of market

With a number of records to draw this information from, am I able to 'plug' this data into a template regression model to then make forecasts from?

When creating a new forecast and to place a figure against parameters d), e), h) and k) I would have available to me the other parameters in place, namely:
a), b), c), f), g), i) and j)


I have no previous experience of creating/adjusting a regression forecast model so really am after some in-depth help here.

Many thanks in advance.