Quantifiable factors and solid data are incredibly useful tools for deciding your negotiation priorities and strategies – but they must remain a tool, rather than the master.
Professionals across the world have never had better access to data, or data analysis tools to make use of the information. With almost the entirety of humanity’s knowledge at our fingertips wherever we go, it can be easy to think that the solution to our problems always lies somewhere in the numbers, waiting to be brought out by an expert.
Transforming your priorities into hard numbers (e.g. by rating your priorities from 1-10, then taking a weighted average of the value of each of your available solutions) can be powerful, and good data is worth its weight in gold… but we should remember that solid qualitative input can be just as valuable, and bad data still exists today.
If a friend who has been in the tiling industry for 30 years tells you that Brook’s Tiles are notorious for poor handiwork (and that you probably don’t want them tiling your home, even though they are the cheapest option out!), you might choose to value that opinion over 200 online reviews raving about Brook’s products and rating them 4.5 stars out of 5.
Maybe the friend is just wrong, or biased, of course — but it is also possible that the review link has only been sent to satisfied customers, or that the company has bought fake reviews, or that the data has been manipulated in other ways completely unknown to you. Neither data nor qualitative input are inherently better than the other, and you will always have to make a judgement call as to which is stronger in any particular situation.
Further, don’t let yourself fall into the trap of overvaluing quantifiable factors! You might not have any hard data available to confirm or deny your friend’s hunch that Kim’s Burgers are mildly better than Patty’s Patties, but that doesn’t mean that their price should automatically become the tiebreaker in your decision-making. If food quality is a much more important factor than cost, then at the least you should try to find out more about the quality discrepancy, before you let the numbers or data play into your decision making as a last resort.