Use a decision matrix to compare criteria and identify the choice that best meets your neds.
By Ted Mitchell
Published January 10, 2007
In the pages of Raise the Hammer, any implied approval of cars might go over as blasphemy; but my primary purpose here is to demonstrate the process of using an engineering decision matrix to address a common problem: how to buy a car that best meets your needs.
Several sources will give you their take on car comparisons, but you can do it yourself using only those criteria which matter to you.
In 2002, Toyota revived the hatchback class with the Matrix. Seeing wildly successful sales numbers, other manufacturers quickly jumped in. These cars are small on the outside, large on the inside, offer reasonable price, safety, fuel economy and practicality.
That is, they provide actual sport and utility, unlike the traditional concept of the euphemistically named SUV. Think Meadowlands, you get the idea.
Maybe one of these is for you, but they are all so similar - how does one make sense of it? Like most people, you could buy on price - or reputation, impulse, colour, shape, or (chuckle) how well your desired self-image fits with those people seen in the commercials.
To make an intelligent decision, you should use a decision matrix.
First, compile a list of things relevant to you. For example: power, fuel economy, price, safety, reliability, cargo capacity, and the ability to hold your two teenagers comfortably.
Next, pick specifications that are available and will quantify those qualities.
The first iteration is to refine the criteria. For example, power by itself doesn't do much if the vehicle is heavy. What you really want is a measure of acceleration.
This is actually tested by performance magazines, but you can't find numbers for all the cars you are interested in. Instead, approximate by dividing horsepower by vehicle weight. You now have Criteria 1: Power to Weight Ratio.
Fuel economy ratings are available from Transport Canada. Your use splits city and highway ratings 50:50. This is Criteria 2: Average Fuel Economy.
How well do the teenagers fit? The best measure is rear legroom, an often compromised dimension. Criteria 3: Rear Legroom.
Cargo capacity is a tough one because companies list many incomparable figures. The only statistic available for all is trunk volume with seats up; Criteria 4: Cargo Capacity. Note, however, that total volume with seats folded does not correlate well with this.
Safety ratings can be found from crash testing. NHTSA has a listing of frontal driver, passenger, side front and rear impacts, as well as rollovers, all out of five stars. All numbers are average them for each vehicle. This gives Criteria 5: Safety Rating.
Reliability data is a bit elusive, especially for such a new segment. Consumer Reports uses a five division system for predicted reliability, and where they have no information, use data for the closest similar model. Voila Criteria 6: Predicted Reliability.
Last but not least, delivery and all-taxes-in Criteria 7: Purchase Price.
Next, choose the vehicles. You should include as many as possible, but let us limit them to a certain rough size, deciding on constraints (features that you must have) of four doors, automatic transmission, ABS, air conditioning, and side airbags.
Pick trim packages that have most features in common.
I have chosen the following five: Honda Fit, Mazda 3 Sport, Nissan Versa, VW Rabbit, and a unibody SUV, the Ford Escape (2WD version). Here are the numbers:
|Automobile||Honda Fit LX||Nissan Versa SL CVT||VW Rabbit 5 door||Mazda 3 Sport GS||Ford Escape XLS FWD|
|rear legroom (mm)||856||966||896||922||922|
|cargo up (L)||603||504||400||484||830|
|cargo down (L)||1186||1427||?||884||1877|
Note that our prototype, the Toyota Matrix, fails the constraint requirement of ABS and side airbags. Remember that imposing too many constraints is foolish: you will not consider vehicles that otherwise will meet your criteria nicely.
Now, we need to do two more things.
First, normalize the data for ease of comparison. That is, give the highest rank a value of 1 and everything else is divided by that value to give a fraction between zero and 1.
Second, multiply the quantities by a factor which corrects for the relevance of the quantity.
Most of our factors do not need adjustment, but look at legroom: the smallest and largest differ only by 11 percent. If your kids' legs require something in between, this is the difference between very cramped and lots of room.
To make this figure relevant, let's expand by a factor of three. Mathematically, that equals (Value x 3) ? 2.
Also, we need to invert price, as less expensive is the desired outcome. Similarly, we could have adjusted the relative reliability data to have a less severe rating, or simply adjust for this later in the weighting below.
|Fit LX||Versa 5L CVT||Rabbit 5 door||Mazda 3 GS||Escape XLS FWD|
|avg fuel economy||1.00||0.96||0.76||0.82||0.71|
Finally, weight the relative importance of each criterion. Up to now, the choices have been fairly universal. But this step is entirely your choice. The simplest way is to give equal weight. We will use this:
|Power to Weight ratio||10%|
|Average Fuel Economy||15%|
Now we can multiply each weight by each rating, then add the results to produce a total score and rank.
|Weight %||Fit LX||Versa 5L CVT||Rabbit 5 door||Mazda 3 GS||Escape XLS FWD|
|avg. fuel econ||15||15.0||14.4||11.4||12.3||10.7|
Note that different weightings may produce different rankings. An emphasis on cargo would favour the Ford. Acceleration, the Mazda. Economy, the Honda. Legroom, the Nissan.
There is no weighting which favours the VW. It would take a different set of criteria to get the Rabbit off the ground.
If subjective factors are used such as ride quality and noise, this misses the whole point of using objective, quantifiable criteria.
However, some of these "soft" factors can be significant but are highly prone to marketing suggestion and bias; for example, the good reputation perhaps undeservedly enjoyed by VW in this country.
The next time you need to make an informed, objective decision, have a go at the decision matrix. Or, you can pay the stupid tax.
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