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 Factor
Weight (110)
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
Decision Factor
Weight
Rank
Lender 2
Score
Rank
Lender 3
Score
Rank
Lender 4
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
[email protected]