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Data currency: Five steps to get max value from digital assets

In this tip, learn digital information management strategies to take advantage of the growing data as currency movement.

Conducting business on the Internet has fundamentally changed the nature of commercial transactions in ways that businesses are just now starting to exploit. Companies such as production suppliers, trading networks and transportation firms are moving data continually as information is exchanged during transactions. And now, rather than paying with money, buyers or licensees are using data currency.

You read that correctly: In addition to the routine transfers of data required to complete a transaction, companies are now digging into their vast digital archives and delivering data instead of cash.

For example, consider a home appliance manufacturer selling to a national retail store chain. The manufacturer may be willing to receive 85% of its traditional wholesale prices on washing machines if it can receive retail data that helps better target sales demand for refrigerators and trash compactors among the existing washing machine customers.

In turn, sellers or licensors are using the data they receive to produce larger, faster and more effective analytics that enable both sides to pursue new wealth. This analytical data can better define markets, make customer trends clearer and help determine innovation opportunities. To help make sure your digital information management processes are "as good as gold," here are five strategies your company can embrace to gain momentum and participate in the emerging data as currency movement.

Build rules for inbound data

Nearly all of your company's digital assets will include data acquired externally, whether it's from customers, suppliers or other sources on which the company relies to conduct business. If you cannot certify the inbound data has been governed by rules that determine its veracity and compliance, the data has little downstream value as a substitution for money.

Governance rules must not only address how your internal operations handle the data, the rules also must work to qualify the inbound data. For example, you would not want to acquire personal information from a third party without knowing all of the relevant privacy rules and data subject consents have been satisfied. The same is true for any other compliance or risk management rules; don't ignore the step of vetting the data and thereby introduce risk of it creating legal problems later on.

Create effective performance records

Big data analytics tools can be used to aggressively filter inbound data to qualify how it is governed. Suspect data should be embargoed or rejected. The key is to create effective records of how well your company has applied and executed its own information governance rules. These records allow downstream parties to more rapidly qualify data and in larger volumes, thereby increasing its value and functional utility. Without the records (which also need to be digital to enable automated evaluations), the downstream actors will require further due diligence. That takes time and costs money, which reduces the value of your data as currency.

Comply with official regulations

The largest external "consumer" of a company's internal data assets are public authorities. Regulation SCI, which was recently published by the U.S. Securities & Exchange Commission, is a major step toward official regulations that state how enterprise architecture, information security and information governance must be mapped across a company's internal and distributed cloud assets. Failure to comply with these rules lowers the confidence any third party has when accepting data in exchange for money. After all, what type of value can be derived from digital records that are not acceptable under government compliance regulations?

Evolve toward standards-based governance

When companies use internal rules rather than available public standards to design and operate their information systems, the related digital assets are more cumbersome to offer in substitution for money. Thousands of corporate acquisitions have demonstrated how hard it can be to align and integrate different information systems. These struggles usually stem from disparate, proprietary rules employed by both sides.

The same struggles exist for meeting market demand for valued data assets. Companies that have not evolved toward standards-based governance use their own rules. As a result, the downstream user must conduct additional due diligence. The alignment of your data to widely recognized standards can eliminate added production costs that reduce the value someone is willing to pay for your data.

Standards are shared rules. With standards in place, both sides of a transaction in which data currency is offered as payment know, and share, the same rules. Standards remove friction in the transaction -- and thus speed business dealings. When that is not the case, your data has less value.

Place priority on data that creates new wealth

Event logs, performance logs, compliance logs, identity management logs: All are critical to the ongoing efficiency of your company and its profitable use of technology. The data assets created by these logs, however, may not be the most valued by your data's potential customers. As with all large undertakings, priorities must be established: Which data assets under your control are most valued downstream by your customers, as well as the distributors or retailers of your products? These are the most important external consumers of your corporate data that will help create new wealth.

The beauty of these digital information management examples is that the same data can have more than one customer. If you can succeed in enabling senior management to recognize their corporate digital assets can be exchanged like cash and create new wealth from multiple customers, you will go a long way toward acquiring the support needed to build and achieve effective information governance.

About the author:
Jeffrey Ritter is one of the nation's experts in the converging complexity of information governance, security, the use of digital information as evidence and the emergence of cloud-based services. He advises companies and governments on successful 21st-century strategies for digital information management with legal and business value. He is currently developing and teaching courses on information governance at Johns Hopkins University's Whiting School of Engineering and Georgetown University Law.

Let us know what you think about the data currency story. Email Ben Cole, site editor. For more regulatory compliance news and updates throughout the week, follow us on Twitter @ITCompliance.

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