Delivering On Transformational Innovation

R “Ray” Wang

Digital disruption is more than just a technology shift. It’s about transforming business models and changing how people engage with each other. To succeed, we can’t just look at the latest cool set of technologies of the day. Leaders must think more boldly about reinventing business models.

Many of these new business models depend on insights, derived from data analysis and interpretation. These models will create new experiences, broker insights, and deliver new networks to monetize insight. Moreover, a series of network economies will accelerate digital transformation and improve engagement while creating new ways for people to interact.

One of the biggest opportunities for monetizing digital business will come from insight streams derived from Big Data. These insights will come from both the most obvious and the least-likely sources. For example, obvious sources are usually existing transactional systems, data within the data warehouse, and other known structured sources.

Least-likely sources reveal things such as the amount of power consumed, water used, visitors into the building, foot traffic on the sidewalk, and density of the parking lot. These sources may seem mundane and useless to most of us, but large insight brokers will take that data to deliver contextually relevant information and reveal things such as workforce performance , customer satisfaction, and product quality. The goal is to use context signals applied to this information to create market and business differentiation.

New business models are emerging for digital businesses, with three that stand out in adoption and maturity. The first focuses on using data to create differentiated offerings. The second involves brokering this digital information. The third is about building networks to deliver data where it’s needed, when it’s needed.

Here is a look at how each type of business model works:

  1. Differentiation of insight creates new experiences. For the past decade or so, technology and data have brought new levels of personalization and relevance. Google’s AdSense delivers advertising that’s actually related to what users are looking for. Online retailers are able to offer — via FedEx, UPS, and even the U.S. Postal Service — up-to-the-minute tracking of where your packages are. Map services from Google, Microsoft, Yahoo!, and now Apple provide information linked to where you are. Big Data offers opportunities for many more service offerings that will improve customer satisfaction and provide contextual relevance. Imagine package tracking that allows you to change the delivery address as you head from home to office, or map-based services that link information on your fuel supply to data on the availability of gas stations. If you are low on fuel and your car spoke to your maps app, you could not only find the nearest open gas stations within a 10-mile radius, but also learn the price per gallon. I would pay a few dollars a month for a contextual service that delivers the peace of mind of never running out of fuel on the road.
  1. Brokering augments the value of insight. Companies such as Bloomberg, Experian, and Dun & Bradstreet already sell raw information, provide benchmarking services, and deliver analysis and insights with structured data sources. In a Big Data world, though, these propriety systems may struggle to keep up. Opportunities will arise for new forms of information brokering and new types of brokers that handle new unstructured, often open data sources such as social media, chat streams, and video. Organizations will mash up data to create new revenue streams. The permutations of available data will explode, leading to sub-sub- specialized streams that can tell you things like the number of left-handed Toyota drivers who drink four cups of coffee every day but are vegan and seek a car wash during their lunch break. New players will emerge to bring these insights together and repackage them to provide relevancy and context. For example, retailers like Amazon could sell raw information on the hottest categories for purchases. Additional data from business partners on weather patterns and payment volumes could help suppliers pinpoint demand signals more closely. These insight streams could be created and maintained by information brokers who could sort by age, location, interest, and other categories. With endless permutations, brokers’ business models would align by industries, geographies, user roles and other factors.
  1. Delivery networks enable the monetization of insight. To be truly valuable, information must be delivered into the hands of those who can use it, when they can use it. Content creators — the information providers and brokers — will seek placement and distribution in as many ways as possible. This creates ample opportunities for the dealers — the suppliers of the technologies that make all this gathering and exchanging of data possible. It also suggests a role for new marketplaces that facilitate the spot trading of insight and of services that allow for private information brokering.The most intriguing opportunities, though, may be in the creation of delivery networks where information is aggregated, exchanged, and reconstituted into newer, cleaner, and smarter insight streams. Similar to the cable TV model for content delivery, these new delivery networks will be the essential funnel through which information-based offerings will find their markets and be monetized. Few organizations will have the capital to create end-to-end content delivery networks that can go from cloud to devices. Today, Amazon, Apple, Bloomberg, Google, and Microsoft show such potential, as they own the distribution chain from cloud to device as well as some starter content. Telecommunications giants such as AT&T, Verizon, Comcast, and BT have an opportunity to also provide infrastructure; however, we haven’t seen them move significantly beyond voice and data services. Big Data could be their opportunity.Meanwhile, content creators — the information providers and brokers — will likely seek placement and distribution in as many delivery networks as possible. Content relevancy will emerge as a strategic competency in delivering offers in ad networks based on role, relationship, product ownership, location, time, sentiment, and even intent. For example, large wireless carriers can map traffic flows down to the cell tower. Using this data, carriers could work with display advertisers to optimize advertising rates for the most popular routes on football game days based on digital foot traffic.

While insight is one model for delivering content, other sources of content include the mix of products, services, and experiences. In this winner-takes-all digital market, success requires business models that aggregate components of network economies. The three distinct components of the network economy include:

  • Content (value):  Whether it’s a product, service, experience, outcome, or business model, the content is the value. How that content’s value is exchanged is the core tenet of the business model.
  • Network (sourcing and distribution):  How the content is sourced and distributed is the foundation of the network.  The network is only as strong as the content and the participants.
  • Dealers (enablers):  The mission of enablers is to reduce friction between content and network or to improve the experience involving content and network

Most organizations choose one of these components as the primary business model and partner with others to create a network economy. However, over time, organizations realize they need to build business models that include two or even all three of these components.

In fact, successful winners of the digital era have created competitive advantage by taking over all three components.  For example, in the consumer world, four companies have the ability to create this network economy: Apple, Amazon, Google, and Microsoft. These companies have the content, the network, and the dealer capabilities to trade on trust and identity. In the digital world, business networks will provide a foundation where sellers become buyers, buyers become partners, and partners become sellers. Welcome to the business network in a digital world.

Learn more how to drive business innovation.


R “Ray” Wang

About R “Ray” Wang

R “Ray” Wang is the Principal Analyst, Founder, and Chairman of Silicon Valley based Constellation Research, Inc. He’s also the author of the popular business strategy and technology blog “A Software Insider’s Point of View”. With viewership in the 10’s of millions of page views a year, his blog provides insight into how disruptive technologies and new business models such as digital transformation impact brands, enterprises, and organizations. Wang has held executive roles in product, marketing, strategy, and consulting at companies such as Forrester Research, Oracle, PeopleSoft, Deloitte, Ernst & Young, and Johns Hopkins Hospital. His new best selling book Disrupting Digital Business, published by Harvard Business Review Press and globally available in Spring of 2015, provides insights on why 52% of the Fortune 500 have been merged, acquired, gone bankrupt, or fallen off the list since 2000. In fact, this impact of digital disruption is real. However, it’s not the technologies that drive this change. It’s a shift in how new business models are created.