What It Takes to Make Data a Strategic Asset

Written by Russ Artzt on September 15, 2020

#ArtztOnData​: What It Takes to Make Data a Strategic Asset

This post is part of our exclusive series –”Artzt on Data.” 

By now, it has become commonplace to view data as a corporate asset. What doesn’t get discussed enough, in my experience, is what it takes for a business to realize the full potential value of that data asset. The easy solutions have already been tried, but there is a great deal of room for improvement. What’s required to go further are a commitment to a data-first strategy and the development of a culture of data quality.

Data is a Valuable Corporate Asset

Data has always been a corporate asset, even before it was called data. In the 1950s, for example, heating oil companies in my hometown used to steal garbage cans from their competitors in the hope of getting their hands on carbon copies of typed invoices containing customer names and addresses. (That “cc” in the email interface stands for “carbon copy.” Google it.) The customer list—the data—had immense value. The digital age has simply amplified the importance of the issue.

What’s new, is the law that higher quality data is more valuable than “dirty data.” There are direct, cash flow and earnings reasons for this. High quality data yields the most efficient sales and marketing processes. Used the right way, it enables better operating results. Low quality data does the opposite: people waste time calling dead end leads, marketing to non-existent prospects and shipping goods to out-of-date addresses. This may not seem like a big deal, but in a large organization, the costs and drag on growth can really add up.

One sure sign that data is being taken more seriously as an asset is its increasing presence in merger and acquisition (M&A) due diligence. A recent article on the legal website JD Supra, Data Due Diligence In M&A Transactions: Data Quality and Liability, highlights how acquiring firms now closely examine the data quality of the target business. As time goes on, data quality is starting to affect entity valuation.

Data Quality as a Board-Level Concern

The Board of Directors should take note as data quality shows up in earnings growth and other operational results that drive shareholder value. Just as the Board may focus on protecting the value of the corporate brand as an asset, so too should it pay attention to data quality. This will look different for every Board. In general, though, it’s an emerging best practice to have senior IT and marketing executives with responsibility for data quality report to the Board periodically. The Board should want to know that the company has the highest possible data quality—a fact that can be proven using reporting tools such as the ones built into the RingLead solution.

Adopting a Data-First Strategy

A data-first strategy makes data quality an integral part of business operations and strategic planning. Again, each company will do this a little differently, but overall, adopting a data-first strategy means making data quality part of the management team’s thought process. It involves shifting data from “the data guys handle it” to “It’s my job as an executive to make sure we are working with the best quality.”

Board-level accountability for data quality can and should flow down the day-to-day activities of senior managers. Data quality could be part of executives’ annual plans, with key success metrics identified up front. For instance, can the VP of Marketing commit to a 10% decrease in “wasted dials” by salespeople? Perhaps she should earn a bonus for hitting this target. That’s how a data-first strategy comes to life.

Building a Culture of Data Quality

A culture of data quality is the second major lever for attaining optimal asset value for data. A culture that values data quality is one that embeds data quality into many unofficial areas of operational decision making. For example, a company with a strong data quality culture will have employees that notice data quality problems and take the initiative to solve them. In the same way that FedEx built a culture of “on time,” where virtually every moment of the workday revolved around how to make packages arrive on time, a company can similarly orient itself around data quality.

The RingLead Solution: Building Data Asset Value through Data Orchestration

Our solution enables companies to realize the potential of data as a strategic asset. It makes a data-first strategy and culture of data quality possible. It achieves these goals through data orchestration. This is an approach to data quality that uses automated workflows to control the sequencing of data quality management processes. For example, using our solution, a company can constantly cycle its customer data through corrective enriching processes and de-duplication. The result is data that is perpetually in the right form to serve the business—and contribute to strong cash flow and earnings growth.