Analysis of two data sets ranked by importance

I would like to test a hypotheses based on whether two data sets, ranked by order of impotance, are ranked the same. One will be ranked using secondary data from literature and one by way of a research survey. In other words are the rankings are distributed equally between both groups. Which test would give me the most meaningful result?

Many thanks
I have worked out by the way that a non parametric test may be best. I think the data is categorical as well (it's a list of success factors for a particular activity). Would a Mann-Whitey U test be suitable?

Many thanks. The scenario is this: I am going to do a lit review to identify 10 critical success factors underpinning a particularly business activity. I'm there going to rank them from most to least critical based on my findings. Following this, I'm going to conduct a survey of professionals working in that particular field and I'm going to ask them to independently rank the 10 factors I found in the literature. I then want to compare the two rankings to test the null hypothesis that they are ranked the same by both groups. Will the Wilcoxon test achieve this? Thanks
Would a frequency distribution work as well? For example, total up each of the 10 success factors based on how they have been ranked to find the most the least important. Factor 1 was ranked 1st 12 times, 2nd 6 times, 4th 2 times and 7th 1 time, factor 2 was ranked 1st 2 times, 2nd, 4 times, 5th, 9 times etc etc. So once I have all the totals, I can then place them in order based on the total number of time they were placed 1st, 2nd, 3rd, 4th, 5th, 6th etc.