The Six Ds of the Data Economy
I’ve been writing about monetizing data, the Outsell Growth Framework, and other key ways to drive growth by licensing data and analytics solutions. Changing data economy dynamics have driven higher valuations for data-intensive firms. There is now a continued thirst for data to fuel applications and algorithms and high demand for new data sources. Accordingly, it is essential that senior executives understand the business factors driving data value.
Outsell has been analyzing the changing face of data and believes that the structural dynamics of the data economy are likely to change dramatically over the next three to five years, resulting in a significant increase in the quantity and velocity of data bought and sold. This, in turn, will have profound implications for the way that data assets are evaluated, valued, and sold.
Data buyers — particularly those risking meaningful capital in business transactions, such as financial buyers — want data that is relevant, always up to date, and accessible. The current industrial-age processes of sourcing, ingesting, normalizing, and analyzing data from multiple sources takes too long and puts business buyers at a competitive disadvantage. The result is demand for alternative data brokers and data marketplaces, segments that are on a collision course to compete with one another as their categories converge.
The faster that companies can put data to use, the shorter their time to money or time to market, all of which drive value. This is particularly true for large hedge funds and quant shops that are looking for data. They have driven what we’ve come to call “the six Ds” of data providers, whether “alternative data” or otherwise. What starts in financial services often leads to innovation in other industries, and we see the six Ds being de rigueur for data providers to be in lock-step with the needs of data buyers and licensors across all enterprises. Thus, if you are looking to sell data exhaust, or just data, it’s best to make sure you’ve got the six Ds covered:
- Data Provenance: Financial data buyers are increasingly aggressive in demanding that data vendors certify that they have the right to sell data and have anonymized it sufficiently to protect information on individual customers or products. This is necessary to comply with the growing patchwork of state, federal, and global regulations and is particularly important with personally identifiable information (PII). Be able to address where the data comes from, and ensure that you have the rights to license it.
- Data Enhancement: Financial data buyers prefer that vendor data either has been or is prepared to be mapped to business objects such as stocks, virtual assets, or geospatial locations. Be able to make sure data is relatable.
- Data History: Most financial data buyers require a minimum of three years and up to ten years of data to consider purchasing a data set; more is better. Being able to trend data is critical, so in most cases, the longer the time series, the better.
- Data Latency: The old saw that “time is money” holds even more true for the new wave of buyers. In general, the shorter the lead time from when the data is collected to when it is delivered to customers, the more the customer will pay. Just like with farm to table, make sure the data is fresh.
- Data Atomization: Financial data buyers typically only want the fields they need, when they need them, and in the business contexts they need. Many of the fields available in a data feed or data set are not relevant to a capital transaction. Make sure you can deliver specific bits and that data can be broken into them for easy transmission.
- Data Delivery Format: Financial data buyers want data delivered into their low-latency workflows and tools — typically through cloud-based instances such as AWS — not spreadsheet files. Make sure the data is deliverable in ways that speak to the user’s situation.
The days of simply having quality data are over — that’s table stakes for participating in the data economy. Now, it’s about so much more. For some data vendors, the time and cost of preparing their data added to the challenges of finding the right buyers at the right time — inside financial institutions or other enterprise settings — can be quite daunting. Buyers also don’t want to spend a lot of time sourcing, negotiating, purchasing, grooming, and enhancing data, thus the rise of data marketplaces and alternative data brokers.
You must know your data use cases, who will license and why, and because of that, how much they’ll invest. Then determine whom you’ll sell to directly and whom you may use marketplaces or brokers to reach.
Channel comes after the decision about “who,” “why,” and “how,” assuming that your data is the “what.” Channel is part of the “how” of go-to-market and doesn’t come first. Don’t license data through brokers without assessing the important first questions. We’re here to help with that.
Bottom line: Data buyers and licensors must understand the six Ds and make sure that service-level agreements for quality are built-in and enforceable.
Companies that have a clear process and plan to ready their data for the future data economy will be awarded higher prices and, ultimately, higher valuations:
- Begin or accelerate the process of preparing and productizing data for the new data economy.
- Evaluate and prepare to participate in third-party data distribution platforms and data exchanges, but only after you have the initial questions answered.
- Begin an annual measurement and benchmarking process to assess product and data progress readiness since progress improves revenue and valuation.
The price to play in the data economy is increasing, and with it, so are valuations. However, that’s only the case for those who are data-ready and following the six Ds of the data economy.