Last month, in reaction to the “Unreasonable Effectiveness of Data” paper that made the rounds, Stephen Few from the Business Intelligence community wrote an interesting post:
The notion that “we need more data” seems to have always served as a fundamental assumption and driver of the data warehousing and business intelligence industries. It is true that a missing piece of information can at times make the difference between a good or bad decision, but there is another truth that we must take more seriously today: most poor decisions are caused by lack of understanding, not lack of data. The way that data warehousing and business intelligence resources are typically allocated fails to reflect this fact. The more and faster emphasis of these efforts must shift to smarter and more effective. Although current efforts to build bigger and faster data repositories and better production reporting systems should continue, they should take a back seat to efforts to increase the data sense-making skills of workers and to improve the tools that support these skills.
This is a point that I wholely subscribe to, and an aspect of which I encountered the other day when attempting to use web search engines to satisfy my “hidden cafes in prague” information need. It didn’t matter that big data pointed the way to all the popular cafes. And it didn’t matter that the search engine came back with results to each of my [hidden prague cafe] and [prague passage cafe] queries in a blazingly fast 0.7 seconds. The answers weren’t correct. I spent orders of magnitude more time and effort — 20 minutes in fact — trying come up with the right way of instructing the search engine as to my true information need in the first place. In the end I never did find the right query to help me find the U Raka cafe, short of using the name of the cafe itself — which was the whole point.
So I agree; what is needed is not more data and faster answers, but better tools to help us comb and make sense of that data, and ask the right questions in the first place. A one-line text input box is not enough.
See also my commentary on Improving Findability with respect to Government 2.0 Search. The same issue exists there, as well. To rephrase: Although current efforts to build bigger and faster data [Government data] repositories…should continue, they should take a back seat to efforts to increase the data sense-making skills of [citizens] and to improve the [search engine] tools that support these skills.
Few concludes (emphasis mine):
Researchers, especially those who work in the cognitive sciences, have learned a great deal about the way people process information and make decisions, including the flaws in the process that often trip us up. Proper training based on these insights is needed to make us better analysts; good tools are needed to help us work around analytical limitations that are built right into our brains. It is toward these ends that the bulk of our data warehousing and business intelligence investments should be directed. Is this where you’re focusing your efforts? Is this even on your radar?