Information Markets

The Objective

Our world is being transformed by the growth of a data economy in which there are suppliers and consumers (demanders), and aspirations for information to become more globally “commoditized” so that it can be leveraged to create value.

As a data consumer, there are questions you are trying to answer, but the data that would be most helpful to combine with your own might be possessed by another organization that will not or cannot share it. This is sometimes the case in a B2B setting where the data that a company collects, its unique “content”, is a core protected asset of the business. If the barriers could be overcome, there might be power in the combined analysis if that data could be integrated.

As a data producer, you possess data you think might be of value to other organizations, and you would like to monetize it and generate new recurring revenue streams, but you are concerned about compromising it, because it is your core protected asset, and undermining its value. On top of that, it might not even be clear how to best reach the customers for your data, or how to establish its value. You are interested to provide your information to the customers for whom it holds the most value, those who will pay the most to obtain it.

The overall goal of an information marketplace is to link data consumers and data producers in a way that provides mutual benefit, and supports an attractive financial model. Consumers pay in proportion to benefit received.

Maybe you are a prominent movie content provider, and if you could just combine your data about customer preferences with data held about the same customers by a prominent social media provider, you could employ vastly more targeted methods, with benefits of high adoption rates (i.e., profitability) and end-customer satisfaction.  But there seems to be no reasonable path to get access to that data. 

Or maybe you are a prominent online retailer, and if you could just combine your customer purchase history and browsing data with the detailed professional histories captured by a prominent professional networking and social media provider, you could do a much better job recommending additional products to consider.  But it seems you could never get access to that data without major changes to strategy. 

The Challenge

Viewing information as a traditional good that is bought and sold for profit is somewhat problematic, particularly in view of the fact that the more sensitive, least known, and most timely information often holds the most value to know. The most significant barriers to trading in information have always been i) establishing its value, and ii) defining control and ownership.

The Collaborative Analytics Solution for Information Marketplace

Collaborative Analytics (CA) provide a mechanism to enable profitable and confident trading in information because the value of adding data to a decision process is readily quantified, and because data can be used while leaving it in place and protecting its content. CA generates prediction networks from an automated “decision-directed design process”, whereby the business questions posed by data consumers initiate on-the-fly construction of the analytics framework, and the value of information in various silos can be quantified in the context of their usefulness to answer the questions which are being posed. This is a very different approach than collecting all the data into a big lake and mining it ex post facto. CA enables a two-sided exchange where the data consumers can test a source by integrating a model (not data), and decide whether the cost-benefit is acceptable. A small increase in decision accuracy (say 0.1 on a probability of correct decision) may not be worth the cost to purchase and include the source.

The right kind of incentives exist for both consumers and producers, and consumers can pay for just what they use in a transactional way. The information is brokered by interconnecting locally-derived analytics into a global analytic network, with only compact privacy-preserving statistics shared. Subscription services are a natural instantiation.  Users can select information sources they want to “socket” into their decision process, evaluate whether they provide sufficient value, then decide whether to subscribe to them, or perhaps even try and negotiate acquisition of the raw content, exclusive rights, etc. A mechanism is provided to share information without ever compromising its raw content, supported by rapid and low cost evaluation of potential impact.

CA provides a means of business partnering to share information and develop new information products, and clears new avenues toward potentially disruptive business models in commoditized information and marketplaces.