Once you’ve identified several potential solutions for your problem, you need to choose at least one. To help you, consider comparing their expected value.
To do that, you evaluate whether you can and want to implement this solution.
Test whether you can implement the solution: The first part is about identifying if you can do well in the key success factors of each solution. Do you have the people/savoir-faire, infrastructure, money, brand, time to do it? If it requires someone else to do something, do you have the leverage to make them do it? Is it allowed (as defined by the law or by the elements in the out-of-scope section of your problem identification card)?
Test whether you want to implement this solution: Would implementing this solution actually solve your entire problem? Would it have an attractive costs vs. benefits bottom line? In particular, would it create a significant problem elsewhere? Does it have a high cost of opportunity; i.e. if you do it, would it prevent you from doing something more beneficial
When testing the attractiveness of a solution, make sure that you have the right criteria. As an illustration of the wrong approach, consider the (almost) true story of a program director reportingenrollment figures to his dean: “I had to pay professor Smith $10,000 to give his course this semester, but only two students attended, each paying $2,000. The way I see it, each of these students cost me $3,000.” The dean replies: “Good thing you didn’t get more students then.”
If you pick the wrong criterion, you’ll make the wrong decisions. In the joke above, obviously, you can’t extrapolate the variable cost to other students.
Imagine that you are considering launching a new marketing campaign. That would increase your overall marketing cost, so if your criterion for attractiveness is to keep your overall cost low, you’ll disqualify this option. But what if launching that new marketing campaign will bring more revenue than it will cost? Shouldn’t you consider it? If your criterion for attractiveness is a positive benefit/cost ratio for any new measure, you’ll pursue it.
Also, make sure that you understand the true value to you of each option in your situation (source). Imagine that you have $15 in your pocket. You get out of your house and someone offers to sell you a disposable cigarette lighter for $10. Would you do it? Probably not because you could get the same lighter for a dollar at the nearest convenience store. But what if your boat sank while cruising in the Pacific Ocean and you miraculously made it to a desert island? Cold for days, would you trade $10 for the ability to start a fire? The point is that you shouldn’t look at the absolute cost of an option but, rather, consider its value to you in your specific situation.
You should also consider the cost of opportunity of pursuing a solution. If implementing one solution could give you a high return but is so labor intensive that it would prevent you from doing anything else, maybe you would be better off pursuing several other options that you could do at the same time.
Ignore sunk costs. You having already spent significant time/effort/money implementing a potential solution, shouldn’t push you to see it as more attractive. Imagine that you’re driving and you missed a turn a few miles back. You shouldn’t carry on on your current trajectory just because you have already driven these few miles. Instead, you need to compare if it’s more advantageous for you to carry on on the current trajectory and correct your mistake further down the road or make a u-turn to get back to the original intersection. You already made your mistake: you started implementing your solution without checking that it was the right thing to do; don’t compound it with continuing in that direction because you’ve already made good progresses.
Place the results of your analysis on a map: Since we have reduced the elements that you need to test to two dimensions, you can use a 2×2 to show your results graphically. If you have the luxury of implementing several solutions at the same time and none are high/high, consider balancing the portfolio, having some highly likely with lower payoff and some with higher payoff but not so likely.