If you believe, as I do, in the wisdom of the crowd, then it’s time for a wholesale shift in how people think about data discovery and analytics. The current working model in the Big Data space typically has companies keeping all of their work within their walls. When they talk with others in their industry there’s little collaboration for fear of destroying the value they have created. Naturally companies need to protect their intellectual property and maintain their value. That being said, even companies concerned about protecting their intellectual property can take advantage of a crowd based model. There are many options when it comes to sharing data and analytics that don’t require exposing privileged information, and not all companies have the same restrictions. What’s right for a Fortune 500 company might not work for a company of 50, or a university researcher, or a not for profit.
Large companies have resources that put them at a competitive advantage. Amazon can hire the best Big Data technologists and data scientists. This means that smaller companies have to find ways to be competitive by doing things more creatively. Just because access to tools and people are limited that doesn’t mean they can’t find other ways to increase the value they receive from data and analytics. It’s important to remember that as great as it is to have financial and technical resources, there’s a reason we see even modest startups change industries. Being small and nimble can often be an advantage. This mindset can turn the tables and applies directly to the value derived from data.
Imagine if smaller entities had a way to work together on data projects. Instead of 10 companies operating individually, what if they combined their resources to expand what any one of them could ever achieve alone. What would the world be like if there was no open source software? The open source software community has dramatically increased the amazing applications we use today, and it’s the community members that drives the innovation. Let’s start using the same community model for data projects. The idea here isn’t to share customer or privileged data. It could be as simple as working together on a cleansing algorithm so everyone can benefit from cleaner data. Let’s all work on a better algorithm to find our top customers and the attributes they tend to share. How about sharing a public dataset or a great data mapping configuration for a particular type of data. The point is, there’s a lot of room for people to work together that won’t compromise any data or impact anyone’s competitive advantage. If I’m a nonprofit in Chicago helping inner city children, would I mind collaborating with other local nonprofits so we can combine our data skills and all be more effective fundraisers? What about data discussions between solar farm operators in different parts of the world on how to learn and optimize their operation? Would a local nonprofit looking to increase contributions mind collaborating with other unrelated nonprofits in another part of the country? There are many ways to be successful working together that don’t compromise data or competitive advantage.
Large companies will outspend and out manpower everyone else. We must find a path so the rest of us can compete. Smaller companies will open up their data and and form communities that will lead to new and exciting learnings that directly contribute to everyone’s success. This will provide new and exciting learnings that directly contribute to everyone’s success.
There’s something especially rewarding about helping not only yourself, but others. The exchange of knowledge is just the start. Data sharing for good allows everyone to benefit and opens up a whole ecosystem to a very real shift in mindset. This shift will change how people think about data. Who really owns it and what it’s true value. Being fast, nimble, and collaborative can be a real plus, and will allow the small fish to cruise right on by the larger ones.
