Figure 1. LCC Evaluation Matrix
Brand
Product
1
2
3
4
5
6
P e rc eiv e d P ro d u ct R elia bility
Brand Engineering Support
A vailability (delivery)
Ease of M aintenance
Brand Sales Support
Ease of A pplication
Docu ment Support
P arts A v aila bility
SCORE POIN TS
Local Stock
W arranty
233332233335
Key
products
333333333338X
333333333337
333333333338
333332333336X
333333332337
Perceived Product Q uality
Perceived Brand Quality
P ric e
332
331
332
331
332
233
Supplier B
1
4
6
2
3
2
2
2
2
3
3
2
2
3
2
2
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
2
3
3
3
3
2
3
3
2
2
2
33
36
34
74
X
X
Supplier C
1
4
2
2
2
2
3
3
3
2
2
2
2
2
2
2
2
2
3
3
2
1
1
1
3
3
2
2
29
27
69
X
X
56
Scoring criteria: Among best= 3 Average= 2 Among worst= 1 Not Known= 2*
*It may be best to avoid criteria for which there’s an unknown for any of the suppliers or products as it can “hide” something that if known could tip the decision.
One of the most daunting parts of the life-cycle cost evaluation process, besides having to gather masses of data, is
organizing and comparing that data in a way that will lead
to meaningful and usable conclusions. Normal LCC data
manipulation can be quite complex and probably exceeds
many professionals’ training levels. Complicating the situation further is the reality that much of the data that needs to
be compared isn’t available as data at all. Instead, many
important factors in LCC conclusions are subjective evaluations resulting from experiences with each potential supplier and product.
Enter the Magic Matrix. Actually, this matrix isn’t magic
at all, but it might feel that way because of its simplicity. For
most of us, the resulting conclusions we can draw are good
enough to provide the basis for making an educated decision.
CONSTRUCTING THE MATRIX
A typical LCC decision matrix will have suppliers and/or
products on one axis, with the various criteria that affect the
cost of ownership on the other matrix. Notice in the example (Figure 1) that many of the latter do not necessarily
translate to a cost that can readily be defined, yet a shortcoming in any of these areas can result in significant expen-
MAGIC MATRIX
ditures of time to rectify or address a problem.
The matrix in Figure 1 is just one example; the criteria
used will vary widely—chosen based on each supplier’s
strengths/weaknesses, as well as the product’s traits that can
be rated. Anything that involves a direct cost or an expenditure of time should be included. In Figure 1, we’ve created
a manageable scale: the scoring criteria are: Among best =
3; Average = 2; Among worst = 1; Not known = 2. A score of
2 is given for an “unknown” because it is neutral and neither
gives an advantage nor penalizes that supplier or product.
Depending on how important the ultimate decision will be, it
might be best in some circumstances to remove criterion if
one of the suppliers or products cannot be given a rating in a
particularly important area.
RATE AND EVALUATE
The last step in this process is to assess the ratings and total
the scores. For those who are buying on price, Supplier B or
C in our example would probably win. But look further.
When all criteria for the key products are totaled and compared, Supplier A might be the better choice.
In the end, it’s still an individual choice. While this
process might seem an oversimplification, it does give the
decision-maker a lot more to go on than simply a low bid.
