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From Moneyball to Grand Slam Information-Based Business Models

by Doug Laney  |  July 24, 2017  |  Comments Off on From Moneyball to Grand Slam Information-Based Business Models

In 2003, Michael Lewis published the best-seller, Moneyball: The Art of Winning an Unfair Gamefeaturing the nouveau analytics-based approach to evaluating baseball players developed by the Oakland Athletics‘ general manager, Billy Beane. In general the approach dispensed with hindsight-oriented metrics such as batting averages, strikeouts and walks, in developing predictive metrics that could anticipate a player’s contribution to producing runs and winning games. Of course these metrics involved collecting data on players that had not been collected before. Both the compilation of new data sources and creation of forward-looking metrics as a competitive advantage are an obvious lesson for any organization’s leadership, in any industry.

But today we’re seeing a new type of winning via information-based competitive advantage emerge: information monetization. Information has economic value that organizations can “turn into money” in two essential ways:

  • By exchanging it for goods, services, or cash, and
  • By using it to increase revenue, or reduce expenses or risks.

A recent Gartner study found that among the top ten Big Data challenges, respondents cited “how to get value from Big Data” as the #1 challenge three times more often than any other challenge. Value-from-data challenges are cited five times more often than staffing related, leadership, or infrastructure/architecture challenges, and three times more often than risk or governance issues.

The good news is that information is what economists call a non-rivalrous, non-depleting asset. That is you can use it multiple ways simultaneously, and when you do consume it it doesn’t diminish. Moreover, information has relatively low generation/collection, inventory, and transportation (transmission) costs compared to other assets. The bad news: most business executives, chief data officers (CDOs) and enterprise architects don’t fully realize these unique economic properties and are ill-prepared to take advantage of them.

However, some companies, in addition to the well-known digerati, have become laser-focused on broadly levering information capital. Their executives have looked up and down their value chain to identify others who could benefit from their information assets. In effect they have expanded their information ecosystems in a way only possible with this non-rivalrous, non-depleting, cost-efficient asset. These companies have created “grand slam” business models by sharing information throughout their value-chains.

grand slam baseball diamond
Examples of “grand slam” information monetization business models include:

Abe’s Market 

Abe’s Market (now part of Direct Eats) capitalized on the opportunity to provide its multitude of mostly small suppliers with invaluable information from and about buyers. It devised a mechanism for capturing feedback from consumers in return for discounts (i.e., free stuff). This data and comparative insights were made available to suppliers in the form of a custom scorecard. Who bought the products? When and how many? When did they consume them? When do they intend to buy more? How were the product’s taste, value, and nutrition?

Various dietary, demographic, and psychographic information was also gleaned from the transactions and surveys. In return, suppliers didn’t pay cash for this information. Rather they offered free products and deeper discounts just to get their hands on these invaluable insights to help them develop better or different products and optimize inventory levels and shipping.

But Abe’s didn’t stop there. They realized that this information was also valuable to major manufacturers of snacks (e.g., Kraft, Mondelez, and Nabisco) to understand the emerging market for healthy snacks.

Onvia

The U.S. federal government is the largest customer in the world. Its contracts top $1 trillion annually and are bid on by only a small percentage of companies. Why? Determining which of the country’s 80 agencies and hundreds of departments are putting out contracts to bid and when–relevant to the solutions your company offers–is itself a fulltime job. Then add to this the 90,000 state and local agencies offering $1.5 trillion in contracts each year. It’s an impossible maze to traverse, discouraging most companies from even participating. But not impossible for today’s technology.

Onvia is among a small handful of similar companies capitalizing on this problem by monetizing these thousands of annual bid and proposal requests. Since most requests are subject to public disclosure, their technology automatically sources, harvests and intelligently categorizes such content from government websites. This makes it pretty straightforward to create a master directory and set up notifications for RFPs meeting particular criteria (e.g., type of product or service, geography, contract size).

As Onvia’s head of marketing, Alberto Sutton, explained to me, it’s not always a level playing field, as hard as governments try to make it one. Many government agencies and purchasing managers, just as in the commercial sector, are swayed by relationships and the comfort level they have with potential suppliers. Furthermore, incumbent suppliers often are awarded follow-on contracts when the current one expires due to a lack of familiarity with competitors. Providing vendors knowledge of an RFP only after it is issued only offers them “one dimensional value” as Sutton calls it. But how can you know in advance when RFPs are being issued, or when current contracts are expiring? “We harvest publicly available budget documents, capital improvement plans and bid award information to predict what kinds of jobs are going to go out to bid, before they do,” explains Sutton. “This line-of-sight can give a vendor a six month jump on its competitors, whether it’s for a new fire truck, to replace of hundreds of laptop computers, to service a building, or to supply toilet paper.” One such customer, Clarke Power Services, has leveraged this information to grow its public sector sales from $3.5 million to $40 million per year.

But Onvia’s monetization of all this information doesn’t stop there. It also licenses this aggregate data, along with pricing, benchmarks, market analyses and contract efficiency ratings back to government departments themselves–but not for cash, rather in return for enhanced information. And since nobody really wants to write an RFP from scratch when similar proposals have been written by other agencies dozens or hundreds of times before, Onvia also licenses its searchable database of prior proposals. Purchasing managers then can use these as templates. One agency Sutton told me about required cemetery management software, but had no idea how to create an RFP for it. It just so happen to find one in Onvia’s trove of proposals.

Apervita

“The process of valuing data that you talk about,” Apervita founder and CEO, Paul Magelli, tells me as we chat about infonomics, “It doesn’t start with a failure to recognize the value of data. Rather it starts with appreciating the value of a network, usually a network of customers. Then recognizing the value in the information about that network becomes important. This is what’s happening in the healthcare industry right now. The past four to five years, healthcare organizations have begun to recognize that their information is a core asset,” he continued.

Magelli’s startup is poised to take advantage of the increased acknowledgement that one healthcare provider’s information likely has external value to others throughout the industry and beyond. But unlike the hundreds or thousands of data brokers merely compiling and licensing data sets, Apervita has recognized something else: the value of monetizing algorithms. It is providing a marketplace for healthcare and medical metrics, metadata and math, to help all healthcare providers evidence-based analytics and data with intention of improving health outcomes. Apervita estimates there are millions of datasets, and hundreds of thousands of algorithms, protocols, guidelines and metrics in use throughout the industry. Kept in silos, their value is minimal; shared externally they could save lives and money. Not to mention, make money for Apervita.

Early relationships with dozens of healthcare providers, including the Mayo Clinic, are expected to compile and market information to help with readmission reduction, early warning triage, medical device assessments, hospital safety and chronic disease management.

Enologix

On May 24, 1976, at the prestigious Paris wine competition, Stag’s Leap Wine Cellars’ 1973 S.L.V. Cabernet Sauvignon was judged best wine, edging out the offering from renowned Château Mouton-Rothschild. A fledgling California winery started just five years earlier had bested this esteemed 150 year-old estate. Emboldened vintners throughout California rejoiced then never looked back. Rather they looked forward and ultimately started adopting leading edge chemical analyses and analytics to maximize profits, production, aging potential and of course ratings.

Leading the charge has been University California at Santa Cruz PhD in chemical ecology, Leo McCloskey. Once working as a college student applying mildicide primer to wine barrels at a local winery he became intrigued by the chemistry and biology of wine and the possibility of untangling and understanding its gaggle of chemical compounds. After unearthing neglected research on the chemistry of grapes he developed techniques using liquid chromatographs and mass spectrometers to identify and measure the molecular structure of key compounds. Beyond the standard measures of sugar, alcohol and acidity, he gauged terpenes, phenols and anthocyanins and other oils affecting texture, aroma, taste and color–characteristics which separate a $10 bottle of wine from a $100 one.

Following definitive proof his methods could predict consumer preferences, he also realized they could predict Wine Spectator ratings. Today, with a database of chemical analyses, growing conditions, production information and consumer data on over 100,000 wines, his aptly named company Enologix secretly advises hundreds of winemakers throughout their growing and production on how to produce and price the optimal bottle of wine.

Final Thoughts

Creating a “grand slam” information ecosystem model should be part of just about every company’s business strategy. You get win from higher customer satisfaction and increased revenues; your suppliers round the bases faster with information on how to improve their products resulting in increased sales; your partners get RBIs via improved information to help them better sell and deliver on your behalf; and your customers score improved products at lower prices—all from sharing your high-flying information.

For more on infonomics and information monetization, check out these and other Gartner research publications:

Follow me on Twitter @Doug_Laney #infonomics #GartnerDA. Connect with me on LinkedIn

My book, Infonomics: How to Monetize, Manage and Measure Information for Competitive Advantageis now available on Amazon (publication: September 2017).

dual covers

 

Category: algorithm  big-data  cdo  data-broker  infonomics  information-management  information-monetization  iot  social-media  trends-and-predictions  

Tags: analytics  big-data  business-intelligence  business-models  cdo  chief-data-officer  data-mangement  data-monetization  economics  infonomics  information-monetization  monetization  moneyball  

Doug Laney
VP and Distinguished Analyst, Chief Data Officer Research
10 years at Gartner
30 years in IT industry

Doug Laney is a research vice president and distinguished analyst with Gartner. He advises clients on data and analytics strategy, information innovation, and infonomics (measuring, managing and monetizing information as an actual corporate asset). Follow Doug on Twitter @Doug_Laney...Read Full Bio




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