after doing a few of these plans and working out some predictions here is what I can say. There are two ways of looking at this, one is TOP down witch is a common mistake Ex: the population of the world is 7 billion people so I should be able to sell 1 unit to each and thus shall sell 7 billions units.
The better approach is Bottom up, that means figure out what is required to sell a single unit. (I.e. Time, money, production, etc.) then understand your growth pattern, so if you want to sell 10-100-1000 etc. what is required and at what point do you need additional support staff and structure. once you have that than you can build a sales plan and a revenue plan.
Remember if I sell space shuttles, no matter how great I am I wont be able to build more than 1 at a time and if it takes 5 years, my plan is to sell 1 in the next 5 years max. the rest will be back ordered.
in conclusion, we can make numbers say whatever we want, just keep it realistic and make sure you can back them up easily.
A couple of insights...(in advance sorry for the length)
a) As Jeff points out, a real model is necessary - setting a target and working back is inherently flawed ...revenues are the result of company activities across all functions, not the other way around.
b) If you are looking at SKUs, read company reports of competitors and interview previous sales/operations/marketing execs. Most of the time they are willing to help if at all possible. including introducing you to others that might have more insights. This applies to all products and services.
c) In a case near and dear to me..and still percolating, we have the same issue for a new product that fits between categories so how do you come up with a reasonable sales forecast? We learned what the minimum "shelf volume" was and built a business case based on meeting the minimum velocity the channels required to stay listed while also using purchase intent scores that were derived by a multibillion channel retailer. So we know the propensity to buy, we know the minimum needed to stay listed, and created a model based on these and other data points published in reports, earnings statements, etc.
Point being is there is always a way to define what is the minimum needed to stay "alive" which can be bounced off other data points to see if they corroborate or conflict each other. Caution is better than projections that can never be supported.
If a web app, then acquisition/retention metrics are CRITICAL. You can find some clue if you use services like App Annie or Tower or other app metrics service providers to see how many downloads there are of competing solutions, as well as estimated ad revenues and value of the app itself. It is a ballpark SWAG but it is at least an educated SWAG. And in almost every case you can find a proven consultant, who has worked in the industry and knows the dynamics, that can look at the model and suggest ways to make it "better".
And, given the unknowns on newer products/services, build a sensitivity tool that shows how changes, good and bad, usually in 5% increments +/-, impact the pro forma and ROI. These can also be strung together to show a compounded scenario of multiple parameters changing at the same time. And if you know a good quantitative analytics guy/girl they can build a market simulation model that lets you do this quite easily, once it is set up.
Last, be upfront. Explain the assumptions behind the major line items and the risks the company faces. Be ready to review how the strategy addresses these risks and if they materialize the story of how you will recover. Offer up the modeling worksheets for them to chew on...which most won't do beyond a cursory scan. Above all, remember, facts tell, stories sell.
Disclaimer - I do this kind of work for a living so easier said than done..but if you take the time to learn you can always come up with a defensible model..which is what investors look for.