February 18, 2016

Four Mandates to Turn Your Underutilized Data Into Revenue

Roman Stanek

(hin255/Shutterstock.com)

Over the past 25 years, enterprises have invested massive amounts of money in tools, people, and infrastructure that create and capture data about their operations and customers. If data is the oil of 21st century business, it’s shocking to see that many organizations still use only a fraction of the valuable data that is available to them. I describe this as being data bankrupt.

In short, underutilized data is a problem – and a big one. A report by Gartner, Inc. states that more than 90 percent of business leaders view information as a strategic asset, yet fewer than 10 percent can quantify its economic worth. While this data has the capability to generate significant business value, many organizations aren’t seizing the opportunity. This can mean improving decision-making, deepening customer relationship, cutting costs, and driving new sources of revenue. In an environment where enterprise investments focus on storing data, many businesses have not yet figured out how to unlock, scale and prioritize their data. Companies are missing out on opportunities to share critical insights across their network of customers and business partners; insights that could enable them to deepen  existing business relationships and create new digital products or services, and drive real revenue for the business.

At the end of this tunnel of missed opportunities is the light of data monetization – the idea that companies can turn their underutilized data into quantifiable returns. While some feel that the term “data monetization” is too aggressive, connoting selling data, the actual process of monetizing data actually involves offering personalized analytics and sharing critical insights to one’s network of customers and business partners to drive retention, relationships, and revenue. Success looks different for different industries, from a new performance-boosting service for franchisees, to a fraud detection analytics service for merchants.

Regardless of the type of deployment, the insights gained give organizations the ability to adjust projects and develop strategies to make businesses perform better. Data monetization is built on delivering true return on investment to ensure that organizations can gain the most value from their data.

Outlined below is a simple blueprint for a recommended approach to monetizing data:

1. Assess Your Available Audiences

Researchers at Booze Allen estimate that $500 billion will be generated from commercializing big data, but currently, 80 percent of that data is not being used to produce or effect revenue. The first step to monetizing data involves analyzing your available business networks. What kind of performance improvement can you imagine if you made analytic information (not raw or personal data) available to these audiences? Where would they see value? If you do business with other businesses, you indeed, have data about those businesses at your fingertips. The challenge then becomes a “what and how” problem. What to give them and how to get there.

2. Outline Value-Based Product Strategy

Once you determine your audience opportunity and focus, it’s time to prioritize applicable use cases, user personas, and desired outcomes. This will help you understand what you build and for whom.  This also helps you identify what data to package for each audience and begin to define KPIs and feature. Think from the audience in. If you need help defining the requirements for your data product, I know a company who has done this hundreds of times.

3. Build ROI Model-Tiered Pricing

After figuring out your value-based product strategy, an organization should develop the key considerations for pricing, packaging and growth of your data products and services. When you compare your competitors’ offerings and prices with your profit margins, you can discover a pricing sweet spot, and develop the right strategy, based on an increasing ROI model. In some cases, you might even decide to make your data products free of charge, in order to drive revenue generation indirectly via other components of your offering or simply extend the lifetime value of your customers.

4. Prepare Internally for Support and Launch

Finally, you need to launch! In order to do this, you must determine the best way to execute your product vision and begin collecting and prioritizing customer feedback. Gathering feedback directly from your users and measuring your audience engagement will help you keep your data offering on the mark. Also, you will help yourself “land and then expand,” at the pace defined by you. This will help your data product or service stick, cementing your monetization strategy.

What has happened to the data enterprises have spent billions collecting and storing? It’s gathering dust, robbing companies of revenue opportunities, and reducing opportunities to gain a competitive advantage. Simply collecting and storing your data is not enough – it’s time to monetize. Luckily, organizations like yours are finally realizing that to differentiate, they need to expand their view of analytics to include the concept of distribution. Analytic solutions targeted at unlocking the value of data will almost always discover previously unrealized opportunities for growth.GD_MgmtTeam_People_Roman_0

About the author: Roman Stanek is the CEO of GoodData, which he founded in 2007 with the mission to disrupt the business intelligence space and monetize big data. Prior to GoodData, Roman was founder and CEO of NetBeans, the leading Java development environment (acquired by Sun Microsystems in 1999) and Systinet, a leading SOA governance platform (acquired by Mercury Interactive, later Hewlett Packard, in 2006).

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