IoT Profit & Cost Savings
We’ve all read plenty about the rise of the Internet of Things (IoT), including its exponential growth.
The number of connected devices alone is expected to explode in the next few years, with forecasts for new devices by 2020 ranging from 20 billion to more than 200 billion. Analysts predict that IoT technology will support $273 billion in spending on services alone in 2017, mostly on professional services to design, install, and operate systems.
With all that growth and spending, many companies are struggling to settle on the right IoT application or justify the capital investment that the technology may require. In many cases, this difficulty is due to the fact that, while it may be clear how connected technology can save money—by, for instance, making operations more efficient or allowing workers to do more—it’s often less obvious how IoT applications might generate new revenue.
Indeed, for many executives, the idea of locating value in the combination of physical and digital information is still new. In this issue of CFO Insights, we look specifically at monetizing IoT technology, exploring strategies common in the software world—where information has long generated value—and how those strategies may apply to other industry sectors.
Making the value connection
In the simplest form, IoT technology takes inputs from the physical world, uses digital technologies to derive insights from those inputs, and then makes outputs available for use back in the world. In linking the physical and digital world, the IoT has another impact as well. Traditional physical products create value for customers only by virtue of their performance: A standard lightbulb is valuable based on its brightness, efficiency, and lifespan. With connected objects, information also becomes a key determinant of value: A smart light bulb is valuable not just because it can brighten a room, but because it can enable automation, scheduling, remote controlling, and other abilities.
Yet, due to possible unfamiliarity with the potential market opportunities, many leaders are taking a wait-and-see attitude toward IoT technology. A recent MIT and Deloitte survey of IT executives revealed that most of their companies intend to leverage IoT-generated data to pursue only small-scope applications aimed at efficiency improvement.6 While it is certainly prudent to start small and scale applications as they succeed, thinking big is also a benefit. And for businesses that need to rationalize initial tech investments, using IoT technology to generate revenue may be the key.
Turning IoT data into money is not necessarily a straightforward process, however: It requires knowledge of customers, and the governance capabilities to take advantage of that knowledge, to be able to offer the right item to the right customer in the right way. To develop these data governance capabilities, IoT players can learn from an industry in which information has long been a primary source of value—software—and explore the monetization drivers that leading firms are leveraging.
Selling technology in the software world has evolved from selling packaged software to selling services, building relationships focused on driving value to customers, and meeting customers’ expectations for flexibility in consumption. And from a monetization perspective, this means that new business models are expanding and becoming the norm. For instance, some content management services leverage the “freemium” model: A free service includes a personal account with limited storage and file size, while the premium service allows more storage, bigger file size, more users, enhanced collaboration, etc. Other models in the software sector employ pay-per-use (also known as utility) models, monthly subscription plans, and outcome-based models focused on the business value that the product or service delivers.
All of these techniques can be grouped into three key monetization drivers—usage intelligence, feature-based packaging, and flexible consumption—that form the foundational pillars of top software firms’ monetization strategy. Executives in other industries can look to these pillars in developing strategies of their own. After all, many companies have little direct experience deriving revenue from customer-generated data, and effectively packaging and pricing products and services can prove challenging.
Usage intelligence refers to the capability to collect, analyze, and report data about how the customer uses an intelligent, connected device; this capability helps in generating actionable data-based insights. In the software world, usage intelligence has a specific meaning: It generally refers to the intelligence regarding which product features a customer uses, and how often. In an IoT context, it takes on a broader meaning and includes a range of behavioral information on how a customer uses a product, including structured and unstructured data on the relationship between the customer, the product, and the broader ecosystem.
To software customers, usage intelligence provides greater visibility into their licenses, entitlements, and consumption patterns, enabling them to make informed choices about their usage of a product. For IoT players, intelligence-generated information can help to generate revenue throughout the develop-to-cash life cycle. In the development phase, the data can help improve the next version by prioritizing the features that consumers value most. In the sales-related phases, the data can help uncover potential sell, upsell, and cross-sell leads. In the support phase, this data further provides insights for customer service and support and predictive maintenance, creating numerous opportunities to differentiate the product.
As companies look at the option of deploying usage intelligence, they need to ensure availability of the following supporting capabilities:
Connectivity to send information to devices and back office via networking protocols;
Management of all sources of relevant structured and unstructured usage data;
Reporting and visualization to report on usage to customers and business through user-friendly interfaces;
Advanced analytics to mine data in real time and predict future behavior based on past usage patterns.
Feature-based packaging refers to companies’ ability to provide flexible offerings by allowing customers to configure their products, enabling or disabling features as desired. With IoT applications, this becomes particularly important because companies are no longer locked into selling a single product but, rather, can sell that same product in several different ways based on the combination of features offered. In fact, those product features can even change over time through over-the-air updates or purchases. By offering many different versions at different price points, a company can capture a greater share of the market—and therefore increase revenues.
While feature-based packaging has traditionally been highly popular in the virtual goods market, it has started gaining traction among industrial machinery and durable goods companies as well. For example, one manufacturer of electric vehicles is now able to send over-the-air software updates that add new features to its cars and allows customers to purchase software-based upgrades to unlock some of the functionalities already available. For $8,500 above the purchase price, customers can choose an upgraded version, which can travel about 40 more miles per charge without the need of changing hardware or even taking the car to the service center.
Feature-based packaging offers customers the flexibility to configure and personalize services and enables companies to diversify offerings, helping improve monetization potential. At the heart of feature-based packaging sits entitlement and license capabilities that enforce and adapt the usage policies appropriate to each user. In particular, entitlement management automatically creates and manages electronic records for each user’s entitlements to certain features, while license management locks or unlocks features per entitlements to enforce usage compliance. An additional capability needed to enable feature-based packaging is product configuration that provides the ability to customize offerings by configuring at the lowest level of service or features.
The third driver, flexible consumption, refers to customers’ ability to consume and pay for a service or product based on need and usage. Flexible consumption uses the same data on product usage as usage intelligence, but rather than using that information to improve the next iteration, flexible consumption offers customers the option to pay for only what they have used. Pricing can be strictly usage-based, such as subscriptions or pay-as-you-go, or outcome-based, in which customers pay based on performance. Outcome-based pricing is especially applicable in industrial scenarios, where IoT products are priced based on the operational efficiency improvements that the end user realizes.
Flexible consumption models enable recurring revenue streams and help align business needs with customer preferences. Similarly, when customers desire a new function or capability, they need not go back to the open market to find a new product—they can simply upgrade their existing product. To offer such a model, companies will need to improve some of their core business functions to ensure that they are capable of supporting flexible pricing of software and service to customers:
Order management and customer care functions should be able to manage orders under flexible models throughout the customer life cycle.
Pricing and deal analytics capabilities should be developed to prioritize deal variables and design pricing models.
Billing policies and infrastructure should be upgraded to support invoicing and billing for subscription and pay-per-use consumption.
Revenue allocation function should be able to recognize and allocate revenue based on flexible and recurring schedules.
Driving to monetization
IoT technology is forcing many older companies into unfamiliar places, and one of the least comfortable is the idea that user-generated data—and the software necessary to process it—may be key to future business plans.
But while many new IoT players are adjusting to the world in which information creates value, leading software companies have been living in this world for years. Today, they are leveraging usage intelligence, feature-based packaging, and flexible consumption as part of their monetization strategies to use information to generate more revenue. Given the information-centric nature of connected problems, IoT players can realize the monetization potential of their offerings by investigating these drivers. Whether adopting one, two, or all three of these drivers, an integrated approach to looking at these strategies could help companies maximize their value capture from their IoT offerings and build a sustainable competitive advantage.
So how can companies determine which strategies are right for them?
As a first step, IoT players should develop business use cases for each monetization driver for every stage of the development-to-cash life cycle.
Companies can then evaluate use cases based on their potential revenue impact and investment requirement.
Finally, companies should also analyze the process and policy impact of the identified use cases to uncover potentially hidden costs or risks before beginning implementation.
With these relatively simple steps, IoT players can advance confidently into the previously unfamiliar ground of information-based monetization strategies so far found more typically in the software world. And armed with these strategies, IoT players can begin to use connected technology not just to save money, but to generate new value for customers and new revenue for companies.
Excerpted from Deloitte