Why is Business Intelligence Xenophobic?

We were having a discussion at lunch recently about business intelligence and how they’ve started to use maps to visualize data. What fascinated me was not that they were using maps, but the kind of data they were focused on. Specifically, they almost exclusively focus on internal enterprise data. Internal data is no doubt vital to running any business, but got me wondering why these tools do not look at external data in combination with their internal data.

If anything, the past three months should have taught us that external market forces can have massive impacts on businesses. Yet from a business intelligence perspective it seems external data is non-existent or an afterthought. I’ve seen some of the more savvy Fortune 50 enterprises use GDP, unemployment statistics, and survey data etc. to put their sales in context, but seems to be the exception not the rule. These typically take the form of big multivariate regressions to predict sales impacts. That said, it requires a good amount of proficiency in data modeling and statistics – in short not easy or cheap to do.

This really should not be the case. Most of the data needed to have a good pulse on the global and domestic economy are publicly available. As the US Government, other countries and NGO’s further open their data this is only going to get better.

Does current BI leverage this kind of data in their tools, and am I just not aware of it? If it is missing is it because it is hard to do? Is it a data integration issue? My, only slightly informed, take is that these two worlds are largely disconnected. As an enterprise I might have market intelligence data from something like the Economist Intelligence Unit, Lexis Nexis, or even the CIA World Factbook. Then I have all my BI tools and data warehouses to analyze internal data. It would seem that there would be tons of potential in interconnecting these two resources to put your internal data in a global context.

For instance, if I was a global enterprise I’d be interested in what purchasing power looked like across the globe:

Based on that purchasing power I might also be interested in which countries are most susceptible to oil price shocks.

Those countries with a high dependency on foreign oil are going to have their purchasing power most adversely impacted. When another oil price shock occurs I could overlay my sales data and inventory data on the map. Then I would have a good perspective on where sales are likely to decrease and where I could move inventory to less impacted markets. This could work for a variety of scenarios ranging from unemployment impacts, stimulus impacts, demographic impacts, identifying prospects etc. etc. All of which have a large impact on your internal data optimization.