Data transactions should look more like Spotify and less like Columbia House or BMG
The promise of data has permeated nearly every sector of industry. While the desired outcomes of a biotech firm and an advertising network vary greatly, both share the excitement of what an ever-growing supply of data can bring. All revolutions have experienced growing pains to enable efficient, widespread adoption. It is in the ease and scalability of the product or service that the dream of mass adoption can be realized.
In today’s data economy growth is slowed by friction created in how data is bought and sold. Rather than focusing on sources of data that produce astounding outcomes, the talk is around contracts, firehoses, deduplication and the slog in the process of transacting on data. Unless the last mile which connects buyers and sellers of data is joined, all industries that use data as their fuel will suffer.
A popular LinkedIn post posits Apple didn’t ruin the record business, having to buy the whole album did. Similarly, those transacting on data in an outdated model will not see the same value as those who view data as elemental. In both cases it is technology that allows for the aggregation and distribution of only the specific elements the end user wants.
Sellers of data, like musicians, are concerned as large data sets are broken apart and scrutinized by potential clients to identify and buy only relevant elements. However, in the long run this creates a distinct advantage for the seller. In setting a value for specific types of data which the seller can license for a higher rate and, as that asset grows, reap more revenue than if its most valuable data was only sold in bulk.
For buyers, a centralized source to discover, evaluate, augment and purchase data is the key to removing the roadblocks which are slowing the growth of the data economy. Lowering the cost of entry for consumers of data in terms of fewer integrations, fewer contracts and being able to de-duplicate, combine and buy data from across multiple data partners will drive exponential growth in data usage across all verticals. This is the “last mile” connecting data buyers and sellers — what it would look like if iTunes sold data.
Observed/raw/unfiltered data is the fuel which feeds the work of data scientist, AI teams and marketers across many verticals. Suppliers and consumers of this data must embrace a new way of discovering and monetizing to realize the full potential data offers. Technology can alleviate the friction which slows or in some cases stops the data economy from growing. If data outcomes were achieved faster and at a lower cost, how much benefit would this provide to your organization? Multiplied out across all data sets and use cases, the shift to technology-driven data monetization could change the data economy forever.