by Mark Little

A very effective way of decision-making is the process of SMART analysis. When having to make comparisons between, several products or designs, it is important to do your research and take this into consideration to ensure you make an informed decision. SMART analysis is a straightforward way of evaluating alternatives with respect to different attributes that can easily be ranked by the user.

SMART Analysis Example

This method can be used for various forms of decision-making and is a way of making calculated decisions within design. For example when we have several concepts that all have valid attributes and we need to choose a final decision to progress with. Another example, which is not just used in design, is the decision a consumer makes when purchasing a product.

Below we have an example of ‘ A user purchasing a portable MP3 music player.’


  1. Identify the decision maker.

                    Decision maker is the consumer.


  1. Identify the alternative courses of action.

                    The alternative courses of action are a selected range of products, i.e. Apple iPod, Apple iPod Nano, Toshiba Gigabeat F20,

                    Creative Labs Zen Touch and Creative Labs Zen Micro


  1. Identify the attributes, which are relevant to the decision problem. Use a value tree to define the key criterion.

tree diagram

  1. For each attribute i.e. the last in the tree for benefits, assign values to measure the performance of the alternatives on that attribute.
                 Size (objective attribute)

                    Smallest size is the most desirable and hence the most attractive.

                    Find the volume for the iPod Nano:          

                    90mm x 40mm x 6.9mm = 24840mm3

                    (24840) = 100                     (159390) = 0


                    The size values will be interpolated between the largest and smallest size, there are no set disproportionate losses, i.e. the smaller the better.

Screen Shot 2017-08-18 at 14.09.05

                 Number of Songs Stored (objective attribute)

                    Largest number of songs is the most desirable and hence the most attractive.

                    The number of tracks values will be interpolated between the largest and smallest size, there are no set disproportionate losses, i.e. the
                     more tracks the better.

Screen Shot 2017-08-18 at 14.09.22

                 Appearance (subjective attribute)

                    The more appealing the form of the product the more desirable it is, hence the most attractive.

                    This attributes rating has been decided by the opinion of the decision maker.

Screen Shot 2017-08-18 at 14.09.32

                 Battery Life (objective attribute)

                    Longest battery life is the most desirable and hence the most attractive. The decision maker wants a midpoint value of 20 hours which will
                    alter the linear method used to determine the values in-between the largest and smallest used in the previous attributes. In effect the
                    midpoint value pulls down the angle of the slope produced on the graph on anything less than 20 hours, denoting lower a lower score.
                    This method shows just one bisection, many more could be added, for example, the decision-maker will accept a utility of 50% at 20 hours,
                    it may be decided that 15 hours doesn’t fall into this same trend and that could be marked with a utility of 10% - penalising any product
                    under 15 hours. Goodwin and Wright’s Figure 2.5 on page 27 along with associated paragraphs demonstrates this well. 

battery life graphScreen Shot 2017-08-18 at 14.09.52

  1. Determine a weight for each attribute. This reflects how important the attribute is to the decision maker.

                    First the decision maker has subjectively ranked the attributes based on his opinion as the following:

  1. Size
  2. Battery Life
  3. Number of Songs Stored
  4. Appearance
                    Swing Weights

swing weights


                     The weights have been normalised to a total of 100 as follows: 

Screen Shot 2017-08-18 at 14.38.17

  1. For each alternative, take a weighted average of the values assigned to that alternative. This will give a measure of how well [the products] perform over all the attributes.


Screen Shot 2017-08-18 at 14.59.53


Screen Shot 2017-08-18 at 15.00.04


Screen Shot 2017-08-18 at 15.00.14


Screen Shot 2017-08-18 at 15.00.23


Screen Shot 2017-08-18 at 15.00.33


                    Summary of Values and Weights for each Portable MP3 Music Player

Screen Shot 2017-08-18 at 15.13.20


Benefits graph


                    The above graph shows the aggregate benefits score of each product plotted against the cost of each product. This visually indicates
                    how each product ranks against each other and its positioning on how suitable it is for the demands of the purchaser. The efficient
                    frontier shows the solutions that are proportionally better than the solutions below in terms of the two criteria, if there are no cost
                    restraints it would be inefficient not to choose one of the products that runs on the frontier. 

  1. Make a provisional decision

                    Moving from the Apple iPod Nano to the Apple iPod would increase the benefit points by 1 for the cost of £60. Clearly the increase in
                    1 benefit point at the cost of £60 appears extremely inefficient when compared using this method.

                    Cost of Apple iPod Nano aggregate points =           135 (cost)

                                                                        / 52 = £2.60 per aggregate point

                    Apple iPod aggregate points =                              195 (cost)

                                                                        / 53 = £3.67 per aggregate point

                    As stated in the problem outline “money is tight” for the purchaser and he doesn’t want limited features, for that reason the iPod Nano’s
                     positioning on the efficient frontier relative to other options, Mark should choose the iPod Nano.

  1. Perform a sensitivity analysis

                    Questions extracted from a teaching source with permission from author for exercise.

                    A sensitivity analysis should help indicate how the iPod Nano’s two top scores, one of which was given the highest weighting compares to
                    the iPod which scored highly in two attributes (which combined ended up only three points shy of the Nano’s highest weighed attribute).

                    The number of songs stored has a relatively low weighting assigned to it, also all except the iPod Nano have a score over 22, three of the
                    four score 100. To see how robust the current choice is the original weighting for ‘Number of Songs Stored’ will be increased from
                    50 to 75. Increasing this attribute’s weighting coincides with the initial brief of chosen a Portable MP3 music player that isn’t limited on
                     features, and number of tracks might have been overlooked in importance.

                     The altered normalised weights become:

Screen Shot 2017-08-18 at 15.40.31

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