Even if you have great ideas for how to use your Big Data once you have it in place, have you considered where this data will come from?
Where is the ore for your Big Data gold? When most people think about their Big Data strategy, they immediately think about customers--and they should. However, a competitive strategy is not built on customers alone. Even if you have great ideas for how to use your Big Data once you have it in place, have you considered where this data will come from? If not, your Big Data strategy might become a Big Data nightmare. Your Big Data inputs are just as important as your Big Data outputs.
Understanding your Big Data supply
As with the rest of your Big Data strategy, it's important to keep your competitive perspective when addressing your Big Data supply. Whenever I design any process, including the overall process employed by a competitive strategy, I start with a Six Sigma tool called a SIPOC.
SIPOC is an acronym for Suppliers, Inputs, Process, Outputs, Customers. Conceptually, Suppliers provide Inputs to the Process which produces Outputs for Customers. When your Big Data strategy is in motion, your Process may be the fancy algorithms that your data scientists develop, and the Inputs in this case would be the raw data that these fancy algorithms work on.
So, a key question to ask is "Who are the Suppliers of this data?"
To answer this question, we must revisit our competitive definition of Big Data: the massive amount of rapidly moving and freely available data that potentially serves a valuable and unique need in the marketplace, but is extremely expensive and difficult to mine by traditional means. In this definition, we specify that the data must be freely available. This was not arrived at capriciously.
The best competitive position to be in with your suppliers is one where there are no obligations or constraints (actual or potential). The best situation is when your data is yours, public domain, or at least available from a variety of different suppliers that aren't operating as an oligopoly.
To contrast, think about a travel agency selling Disney packages. Disney is one of the strongest brands in the world. It will not be easy for a travel agent to recommend an alternate, if a family has their hearts set on a Disney vacation. Therefore, the travel agency must work with Disney to supply this package to their customer. Disney has all the control, not the travel agency.
Even if the travel agency plans to add value to the vacation by customizing an itinerary with special excursions and arranging for unique transportation, this is a horrible competitive position to be in. Think about this the next time you have a bright idea to integrate data from one of the credit reporting agencies. How much control do you really have on this supply? Do you really want to put your entire competitive strategy in this type of headlock?
Guard your flanks
Freely available data covers your rear, but don't forget about your flanks. For instance, there is a ton of geospatial data freely available at data.gov; however, is this competitive? Well if your plan is to do some simple analysis (or no analysis at all), put a pretty package around it, and sell it to consumers, I think it's time to rethink your strategy. Although this data is freely available to you, it's also freely available to me, your competition, anybody thinking of entering your market, and the rest of the free world.
Think about the last part of our competitive definition of Big Data: extremely expensive and difficult to mine by traditional means. This is the clause that keeps new entrants and substitute offerings out of your market. So, the supply of your data should be freely available to you; however, difficult or impossible for others to procure. So, how can you have exclusive access to your supply of data? There are a couple of ways.
The best way is to supply your data from your own internal--and therefore proprietary--operations. When I consulted for Visa, we were looking at how to best use all the transactional data that was flowing through their network. Visa has a very unique advantage since they process most of the world's credit card transactions. This data is freely available to Visa; however, nobody else in the world has access to it. This is a terrific supply for a Big Data strategy.
Another way to protect your flank is with proprietary analysis. This is where your highly paid data scientists come in. Let's say you sourced this geospatial data from data.gov; then put your data scientists to work to develop a fancy algorithm that could identify where fraud rings are forming in real time.
This might be a valuable service to a select group of customers. So, the idea of free data isn't inherently bad; however, you must think through your entire strategy to make sure it's holistically competitive.
Your supply of Big Data is just as important as its consumers when building your competitive strategy. To avoid an uncompromising situation when your strategy rolls out, make sure the supply for your Big Data strategy is unencumbered.
In most cases, this means mining your own operational data; however, you have other options including the public domain. Be careful, though--public domain data is accessible to everyone, so if this is your plan, make sure you have something special in your analysis.
Oh, and don't forget. Your Big Data strategy needs to produce something valuable and unique for your customers. As nice as they are, the world doesn't need another encyclopedia.