"Annual income twenty pounds, annual expenditure nineteen six, result happiness. Annual income twenty pounds, annual expenditure twenty pound ought and six, result misery." - Charles Dickens David Copperfield
"A nickel ain't worth a dime anymore." - Yogi Berra
After reviewing costs, sales projections, and compiling our cash flow projections over the previous 3 weeks, we turn this week to analyzing our statements using sensitivity analysis and discussing the use of different financial scenarios.
Now that we have our completed financial projections we can begin playing with the numbers to better understand our company. First we need to think about the figures we just developed and try to determine the key assumptions that were made. Do we think that everything hinges upon the sales price we used? Maybe we think it is our ability to secure a certain cost of materials, or to charge and collect a certain amount of shipping revenue?
If, for example, our figures were created with a sales price of $10.00 per unit, what happens to our cash needs (from Part V of our series, the amount of money needed to get our company to a cash flow positive state) if we can only sell our item for $9.00? We need to understand how vulnerable our company is to changes to our assumed figures. It may be that a change in sales price from $10.00 to $9.00 makes it impossible for this company to ever become profitable. It may be that the change has virtually no effect. If the change is drastic than we know our company is very sensitive to the sales price, but maybe we can find something to alleviate that sensitivity (maybe increasing shipping fees or find an additional source of revenue) or maybe the company is a no-go due to that sensitivity. Either way we would want to know prior to moving forward.
The other thing that sensitivity analysis can do is uncover hidden dangers. Perhaps we are certain about our cost of materials but find out that a slight increase in those costs could be devastating. Once we've studied our company's sensitivity to our assumptions we can make changes to our assumptions, or even modify the company's business model.
In this manner we need to play with our spreadsheet, alter the numbers in our assumptions, or alter combinations of our assumptions (e.g., what happens if we adjust our sales price and our rent?) and see the effect these have on our projections. This helps us to understand the interplay between the components making up our revenues and costs.
Now we can also create separate financial projections for different scenarios. We can make full sets of projections with different assumptions to show what could happen if we have to sell for $9.00, or if our material costs are higher than estimated. This can lead to "optimistic", "pessimistic" and "most likely" scenarios.
After conducting sensitivity anaylsis and compiling different optimistic, pessimistic and most likely scenarios you may begin to wonder just what are your actual cash needs? Well there are a few ways to answer that question. You can simply use your original financial projections and chalk the extra work up to better understanding the key characteristics of your company.
There are also a few methods others have suggested for what to do with your different scenarios. Say you have a pessimistic scenario with cash needs of $25,000, an optimistic scenario with cash needs of $10,000 and a most likely scenario with cash needs of $22,500. Which should you use as the real cash need for your company when considering whether or not to start this business?
One is to simply take the highest number, but this may be the least realistic of any approach as it does not take into account the likelihood that this would be your true need. In our example the highest cash need comes from the pessimistic scenario but how likely is this scenario to happen?
Another method is to take the average of your pessimistic, optimistic and two-times your most likely scenario. So in our example: $25,000 + $10,000 + 2x$22,500 = $80,000 / 4 = $20,000. This method factors in the pessimistic and optimistic scenarios while weighting the final number with the most likely cash need.
Another method we've heard of is to take the greater difference between either your most likely and optimistic, or your most likely and pessimistic, and then add that difference to your most likely number. So $22,500 - $10,000 = $12,500 (most likely minus optimistic); $25,000 - $22,500 = $2,500 (most likely minus pessimistic). The greater of the two is $12,500 and we add that to our most likely number $22,500 + $12,500 = $35,000. This method is designed to provide more of a safety net.
You can also simply weight each scenario based upon your understanding of the true likelihood of each scenario and come up with your figures that way.