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Using Decision Matrices to Resolve Complex Issues ©
By Douglas W. Zeisel, MSF, CTP
When faced with decisions based on several factors that are not all quantitative in nature, a decision matrix can be very helpful.
• A decision matrix provides a means of converting non numeric criteria to a quantified result with the benefits of reduced bias and fuzzy thinking.
• A huge advantage is that alternate decisions can be presented to stakeholders with confidence that the best alternative will be chosen. Using a decision matrix has other benefits. It adds discipline to the decision making process and increases the likelihood that all factors that should be considered, have been considered.
First Step
• The first step in creating a decision matrix is to list all the relevant factors that affect the decision. For example, a decision matrix can be used to choose between proposals from lenders on a line of credit. While one could argue that this is a totally quantifiable decision, consider the case where a company has significant cash on hand but is forecast to have shrinking cash flow three to six months after loan closing. This should be an easy decision since you want the lowest overall cost of capital. But suppose one lender’s covenants are significantly less restrictive than others being considered. Now the situation becomes murkier. Suppose also that the size of the line offered by one of the lenders is considerably higher than the others and the company is worried that it might temporarily need to run its credit line above the levels offered by two of the four lenders being considered. Murkier still. Clearly soft factors other than the lowest overall cost of capital enter the equation.
For this example some of the decision criteria could be listed as:
• Interest rate on the revolver (including monitoring fees, etc.)
• Up Front fees (commitment fees, closing fees, audit fee, etc.)
• Size of the line offered
• Expected Covenant Restrictions
• Advance Rate on Inventory and AR
• Unused line fee
• Default Rate
• Perceived “friendliness” of lender
the next step is to rank the decision criteria as to importance to the situation at hand. In the example given we could rank the decision criteria as follows:
Decision Factor Weight (1-10)
Interest Rate on Revolver 8
Up Front Fees 3
Size of Line 7
Covenant Restrictions 7
Advance Rate 5
Unused Line Fee 3
Default Rate 5
Friendliness of Lender 7
Ranking Decision Criteria
• The interest rate on the revolver is weighted high because cost of funds is obviously important. Up front fees are weighted low because the company has significant cash on hand to pay closing costs. If the company were cash strapped this would be rated much higher. Size of line is important since the hypothetical company expects it may need significant funds a few months after closing. Covenant restrictions are weighted high since the company expects widely fluctuating cash flow; It does not want to trigger covenants if earnings are tight for a quarter. The advance rate on inventory and AR is rated neutral since all lenders are offering the same rates. Unused line fee is rated low since it is anticipated that the amount of unused credit will not be significant and since the fees from each lender are not significantly different. Likewise the default rate is similar with all lenders. Finally, the friendliness of lenders is given a slightly higher than average rating since the consultant knows that some lenders will jack up rates at the drop of a hat and others will bend over backwards to help out if the credit has a bad quarter. He has experience with the lenders involved and knows their tendencies.
The next task is to rank each lender as to how they compare in each category. These rankings should be from highest to lowest. In this case a rating of 4 goes to the winner of each category and 1 to the loser since there are four competitors.
Decision FactorWeight (1-
10) Lender 1 Lender 2 Lender 3 Lender 4
Interest Rate on Revolver 8 1 3 2 4
Up Front Fees 3 2 1 3 4
Size of Line 7 3 2 1 4
Covenant Restrictions 7 4 3 2 1
Advance Rate 5 1 2 2 1
Unused Line Fee 3 2 1 1 2
Default Rate 5 2 1 2 1
Friendliness of Lender 7 1 2 3 4
Note that in some cases tie scores were awarded since the proposals were virtually the same in a category. (see Default Rate for example).
The last step is to multiply the weights of each factor by the ranking to get a score for each factor for each competitor. Then find the
winner by summing the scores of each competitor.
Lender 1 Lender 2 Lender 3 Lender 4
Decision Factor Weight Rank Score Rank Score Rank Score Rank Score
Interest Rate on Revolver 8 4 32 2 16 3 24 1 8
Up Front Fees 3 2 6 4 12 3 9 1 3
Size of Line 7 1 7 3 21 4 28 1 7
Covenant Restrictions 7 1 7 2 14 3 21 4 28
Advance Rate 5 4 20 3 15 3 15 4 20
Unused Line Fee 3 3 9 4 12 4 12 3 9
Default Rate 5 2 10 2 10 3 15 4 20
Friendliness of Lender 7 4 28 3 21 2 14 1 7
Total Score 119 121 138 102
Without a decision matrix all the data given might have made this look like a difficult and confusing selection but the decision matrix gives a clear result. Lender # 3 wins by a wide margin.
• A decision matrix can be used for any decision that is not clearly quantifiable and where a large number of factors affect the outcome. Examples include selection of an auctioneer, selection of an appraiser, and selection of an expert witness.
• Now here is the payoff. As turnaround professionals we are responsible for making decisions that can affect a variety of interests. By using decision criteria to reach appropriate conclusions we reduce our risk of an entity claiming an inappropriate decision was made. Furthermore the decision matrix gives us a tool for communication with stakeholders in a matter. If decisions are clearly justified before they are put in effect, it becomes much more difficult for anyone to cry foul at a later date.
• Copyright Feb 2009
• Douglas W. Zeisel, MSF, CTP
CONTACT INFORMATION
For financial consultation and advisory services contact:
Douglas Zeisel, CTP, MSF
Fulcrum Financial Management, LLC
443-253-5174
