This blog outlines a way of ranking options when each option satisfies a set of confounded interests in different ways. The method is described in *The Manager as Negotiator* by Lax and Sebenius. My advice is to apply it as an aid in decision-making, but not to be wedded to it. The example used is a house purchase. The same method can be equally applied in complex high-stake negotiations to help establish preferences.

Say you are buying a house. Certain features of the internal layout are a must; that is, you won’t buy a house without those features. In this analysis those are put aside because they are non-negotiables. However, in this example you could be left with three confounded interests that vary between choices and are therefore difficult to sum or assign preferences to when comparing houses. They are:

Cost of house

Size of garden plot

Commuting time from downtown

__Step 1__ – Estimate possible ranges of each interest

Estimate the expected range in your market for each of these interests. You might arrive at the following figures:

Cost – $500,000 to $600,000

Size of garden plot – 30 square metres to 100 square metres

Commuting time from downtown – 10 minutes to 30 minutes

Ideally you would find a house that maximally satisfies your interests:

Cost – $500,000

Size of garden plot – 100 square metres

Commuting time from downtown – 10 minutes

__Step 2__ – Allot 100 points to the interests

You have 100 points to allot in total to these three interests. You have to rank them in importance by allotting the 100 points. You do this by first considering three different scenarios in which one of these interests is maximally satisfied and the others are minimally satisfied. You must then rank these three possibilities proportionally by dividing up 100 points.

Scenario 1

Best: Cost – $500,000

Worst: Size of garden plot – 30 square metres

Worst: Commuting time from downtown – 30 minutes

Scenario 2

Worst: Cost – $600,000

Best: Size of garden plot – 100 square metres

Worst: Commuting time from downtown – 30 minutes

Scenario 3

Worst: Cost – $600,000

Worst: Size of garden plot – 30 square metres

Best: Commuting time from downtown – 10 minutes

You realize that your preferences are clearly ranked scenario 2, 1, and 3 in that order and that garden size is more important than you had realized. You also realize that commuting time to downtown is not as important as you had thought. You are able and willing to make a sizable down payment. Cost is relevant in that you don’t want to over-pay, but at the same time you have no problem paying for a house at market value. Based on this general pattern of preferences you decide to assign your points as follows.

Cost – 35 points

Size of garden plot – 50 points

Commuting time from downtown – 15 points

__ __

__Step 3__ – Assign a range of points across the variability of each interest

For each of the three interests create a point spread that represents your preferences across the range possibilities you established in Step 1. Cost is the interest that is used to illustrate this step.

$600,000 – 0 points

$580,000 – 15 points

$560,000 – 25 points

$540,000 – 30 points

$520,000 – 33 points

$500,000 – 35 points

You must complete the same process for the other two interests, garden size and commuting time.

Note that the point spread is uneven, which is a nice subtlety available in this method. A drop from $600,000 to $560,000 ranges from 0 to 25 points, whereas the drop from $560,000 to $500,000 adds only another 10. This means that it is more important to find a home for $560,000, but that a decrease in price below $560,000 is much less of a factor for you.

Once the third step is complete, every house you consider can be plugged into your ranking system, which will yield a total point figure for each house you consider. You now have a systematic means of assessing how well each purchase option satisfies these three confounded interests.

As I wrote above, this method is recommended as an aid to decision-making, not as *the* decision-making process.