Whenever a consequence table is created or modified, a useful first step is to see if there is any information there that isn’t helping a decision about which alternative is best. Suppose we have this consequence table:
You’ll notice that the Biodiversity row has the same value for all the alternatives. Assuming that this really is the case, is having this number visible helping us choose between the alternatives? As important as biodiversity might be to people, it’s not helping us decide – the performance measures are said to be insensitive, or redundant. It can be better to hide this row for now (and reveal it again if ever new alternatives are developed), just to simplify what we are looking at.
An alternative is dominated when it is either outperformed by (or performs no better than) another alternative on every performance measure. Colour-coding the table can help us spot these situations more readily. In the next figure, we’re adding some colours to the cells where:
- Blue = a reference against which something an alternative will be compared
- Green = rows where an Alternative performs better than reference
- Orange = rows where an Alternative performs worse than reference
- White = rows where an Alternative performs the same as the reference
We say “worse” and “better” because sometimes, all else equal, lower numbers are preferred (e.g. for cost) and in other cases, high numbers are preferred.
As we can now see, Alternative 1 either beats or is equal to the Status Quo alternative on every measure. So, unless we’re missing something important (and we might be) it would be logical to simply remove the Status Quo alternative from consideration.
This colour coding can be set up in Excel. Or, try our free interactive consequence table builder here.