The rate of data creation today is growing exponentially. This is good news for the fulfillment of the Big Data promise. And a very bad too. About 1.7 megabytes of new information will be created every second for every human being on the planet by 2020. Today, only 0.5 percent of the data created is ever analyzed. The main barriers are not so much technological as organizational.

One principal distinctive trail of the new data potentially available since no more than a couple of decades ago is its origin from very disparate sources. Few years ago, an average consumer product company could barely work with information coming from, for instance, retail POS purchases whereas now it can also gather insights from a great deal of other sources: social channels, online behavior, cell-phone locations and an increasing number of other digital outputs.

According to a study published by Harvard Business Review, two-thirds of organizations are already trying to blend together five to 15 sources of data for analysis. As it happens in some many other fields and activities, operations are becoming too complex for trying to respond to new contexts by oneself. Data analysis is not an exemption. The capability to collect, access, and analyze massive amounts of data has reached the point where no single entity can do all the work. Data collaboration is becoming a necessity for success at any level of business.

In-house data collaboration

Data collaboration will find its potential first within the organizations themselves. And not just by eliminating all inner data silos, a practice whose determining significance few managers would deny today. More importantly, data collaboration will represent a huge opportunity for companies using technologies that enable practically anyone in their organization to be a data analyst and make data-driven business decisions regardless of their technical proficiency.

Some new data analysis systems are moving toward ease-of-use as a main value, using graphical drag-and-drop interfaces and allowing putting business data into the hands of many instead that into the hands of a few, freeing up people throughout the organization to experiment with data.

Of course, some corporate technology managers might see this analytics-for-everyone trend as a threat to governance and security. But as usual, it’s all about trying to avoid or eliminate potential hazards while leveraging the benefits. IT teams should ensure certain data remains private and secure, if necessary learning from mistakes, instead of just shutting down the data pipeline that can empower their organizations to make better and more informed business decisions.

Still an emerging practice

But the true benefits of data collaboration will arrive when this is shared between different companies. If data is the new oil, shared data will become the new gold. External partners can collaborate too on shared data insights, affecting not only the way decisions are made, but also how businesses operate.

Though collaborative analytics is not a new concept, it can be still considered an emerging practice. Progressive companies in Big Data initiatives such as Amazon, Google or IBM have just recently start to talk about the benefits of sharing and collaboration in data analysis. Business cases of companies making better decisions by overcoming the solitary nature of traditional analysis and leveraging collaborative analytical capabilities are still scarce.

Safeware is one of such cases. A leading provider of product protection and extended warranty solutions, the company saw the opportunity to engage in a system of sharing detailed sales data, which does not typically occur in the industry. Its case illustrate how valuable it can be to increase revenue through extended warranty sales if companies are willing to be transparent with their sales information.

By implementing a bilateral sharing data initiative with a top-100 regional retailer, both companies created integrated systems that allowed for seamless information transfer in order to improve the program performance, to properly train associates on best practices of extended warranty sales and to make adjustments as needed.

As predicted, the transparency of this data collaboration allowed the retailer to grow its gross revenue from service contract sales by over 200% in less than two years.