The North American video game market was in a massive recession in 1985. Revenues that had peaked at $3.2 billion in 1983, fell to $100 million by 1985 (a drop of almost 97 percent). The crash almost destroyed the then-fledgling industry and led to the bankruptcy of several companies, including Atari. Many business analysts doubted the long-term viability of the video game console industry[1].
There were several reasons for the crash. The hardware manufacturers had lost exclusive control of their platforms’ supply of games, and consequently lost the ability to ensure that the toy stores were never over-stocked with products. But the main culprit was the saturation of the market with low-quality games. Poor quality games, such as Chase the Chuck Wagon (about dogs eating food, bankrolled by the dog food company Purina), drove customers away from the industry (see Figure 1, with those quality of graphics, how could this game not be a winner??).
The video-game industry was revitalized in 1987 with the success of the Nintendo Entertainment System (NES). To ensure ecosystem success, Nintendo instituted strict measures to ensure high-quality games through licensing restrictions, maintained strict control of industry-wide game inventory, and implemented a security lockout system that only allowed “certified” games to work on the Nintendo platform. In the process, Nintendo ensured that third-party developers had a ready and profitable market.
Transforming Your Business Model With Big Data
As organizations contemplate the potential of big data to transform their business models, they need to start by understanding how they can leverage big data and the resulting analytic insights to transform the organization from a product-centric business model into a platform-centric business model. Much like the Nintendo lesson, you accomplish this by creating a marketplace that enables others – like app developers, partners, VAR’s, and third party solution providers – to make money off of your platform.
In my blog Big Data Business Model Maturation Index, I stated that Phase 5 is where organizations leverage insights from customers’ usage patterns, product performance behaviors, and market trends to create or move into new markets (see chart below).
Let’s drill down into the Business Metamorphosis stage in more details to see what this might mean to your organization, and how you could leverage big data and analytic insights to transform your business model.
From Product To Platform
I have blogged previously about examples of how companies could broaden their charter to provide a more comprehensive solution to their customer base. This process is started by first understanding the broader picture of what your customers are trying to accomplish, versus what they are doing. One example is an energy company leveraging smart meters and intelligent appliances to capture home energy usage insights that they could use to move into the “Home Energy Optimization” business.
- The company could capture home energy and appliance usage patterns that could be turned into insights and recommendations. For example, with the home energy usage information, the company could recommend when consumers should run their high energy appliances, like washers and dryers, to minimize energy costs. The energy company could go one step further and offer a service that automatically manages when the washer, dryer, and other high-energy appliances run (e.g., run the washer and dryer at 3:00 am when energy prices are lower).
- With all of the usage information, the company is also in a good position to predict when certain appliances might need maintenance (e.g., monitoring their usage patterns using Six Sigma control charts). The energy company could make preventive maintenance recommendations to the homeowner, and even include the names of 3 to 4 local service dealers and their respective Yelp ratings.
- But wait, there’s more! With all of the product performance and maintenance data, the energy company is also in an ideal position to recommend which appliances are the best given the customer’s usage patterns and local energy costs. They could become the “Consumer Reports” for appliances (and other home and business equipment) by recommending which brands to buy based on the performance of different appliances as compared to their customers’ usage patterns, local weather, environmental conditions, and energy costs.
- Finally, the energy company could package all of the product performance data, and associated maintenance insights, and sell the data and analytic insights back to the manufacturers who might want to know how their products perform versus key competitors.
In this scenario, there is more application and service opportunities than any single vendor can reasonably supply. That opens the door to transform to a platform-centric business model that creates a platform or ecosystem that enables third party developers to deliver products and services on that platform. And, of course, puts the platform provider in a position to take a small piece of the “action” in the process (e.g., subscription fees, rental fees, transaction fees, referral fees…Man, I’m starting to sound like a bank!!).
Enabling An Ecosystem
Much like the lessons of Nintendo (with their third-party video games) and Apple and Google (with their respective apps store), creating such a platform not only benefits your customers (who are getting access to a wider variety of high-value apps and services in a more timely manner), but it also benefits the platform provider by creating a high-level of customer dependency upon your platform (e.g., increases the switching costs).
Companies that try to do it on their own will eventually falter because they’ll have a hard time keeping up with the speed and innovation of smaller, more hungry organizations who can spot and act on a market opportunity more quickly. Instead of trying to compete with those companies, enable these companies by giving them a platform upon which they can quickly and profitability build, market, and support their apps and solutions.
The platform provider will then need to focus on ensuring that the platform is:
- Easy to develop upon and seamlessly supports app developer marketing, sales, service, and support (e.g., app fixes, new releases)
- Is scalable and reliable
- Provides a delightful and compelling user experience
- Simplifies how qualified third parties make money
A hidden advantage for the platform provider is the ability to instrument and capture all of the activities that are occurring across the platform, and use that information to ensure that developers and customers alike are having a rewarding, effective, and profitable experience. For example, the platform provider can tease out insights across all the platform transactions that can be turned into both app developer and customer benchmarks and recommendations about things like pricing, promotion, and inventory management (think Amazon marketplace).
How Do I Get There?
So how does a company make the Phase 5 business metamorphosis from a product to a platform or ecosystem company?
Step 1 is to invest the time researching and shadowing your customers to understand their desired solutions. Focus on what the customer is trying to accomplish, not what they are doing. Think more broadly about their holistic needs, for example:
- Feeding the family, not just cooking, groceries, and restaurants
- Personal transportation, not just buying or leasing cars, scheduling maintenance, and filling the car with gas
- Personal entertainment, not just going to the theater, buying DVDs, or downloading movies
Step 2 is to brainstorm and prioritize the different data monetization opportunities (discussed in the original “Big Data Business Model Maturity Chart” blog) to 1) clarify, validate, and flush out the customer’s desired solutions, 2) understand what data assets you have or could have, and 3) identify the analytics and data enrichment requirements necessary to turn what you have into the solution that the customer desires.
Step 3 is to create user experience mockups and prototypes so that you can understand exactly what the customer is trying to do with the interface, what’s working and what’s not working (mockups are ideal for web or smartphone-based applications; companies like Facebook have been able to iterate quickly on their user experience this way.) Instrument heavily every aspect of the user experience so that you can see the usage patterns and potential bottlenecks and points of frustration in using the interface.
Summary
Wow, not an easy process. This requires your organization to inventory your data assets and analytic capabilities, and invest the time to understand what your customers are trying to accomplish. But then again, what are your big data business aspirations, and how much effort are you willing to invest in creating and chasing that vision? That’s your call.