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Building a Minimum Viable Smart Product as a Service – Part 1

Updated: Dec 31



Everywhere we look, the technology industry is undergoing a digital paradigm shift that impacts all organizations. With this profound transformation comes an unprecedented opportunity to deliver products offering greater value to customers.


The evolution of products into intelligent, connected services—which are increasingly embedded in broader systems—is radically reshaping companies and competition, and impacting every industry from connected cars to remote healthcare and smart cities.


Organizations are finding innovative ways to integrate internet of things (IoT), artificial intelligence (AI), and digital twin technologies into their products to provide customers with increased value.


These software-enabled smart products, such as connected cars, can stream data about their operation, location, and environment to their makers and receive software upgrades that enhance their performance or head off problems before they occur.


By equipping products with these technologies, organizations can track and optimize the performance of smart products throughout their lifetime, providing quantifiable outcomes.


Customer outcomes are even more impactful when these smart, connected products are transformed from discrete products to product systems. These product systems can “plug into” a system-of-systems coordinated and optimized for an entire environment, such as a smart farm or smart city.


To harness the full potential of smart products and services, organizations must put customer experience and outcomes at the heart of intelligent design and operating models.


Organizations whose products and designs have the greatest impact on total system performance will be in the best position to drive this transformation and capture disproportionate value.


Transitioning to a Product-as-a-Service Model


The relationship a technology vendor has with its smart products—and with its customers—is becoming continuous and open-ended. Smart products can continue to evolve long after entering service and those that can adapt their performance based on customer needs will make the competitive difference.


The data these products generate and collect can enable makers to offer intelligent services, leading to new business and revenue models.


At the heart of this is “servitization”: the shift from traditional business models to a usage-based or outcome-based product-as-a-service (PaaS) model, where smart, connected products are leveraged, together with their on-demand services, as a single solution bundle to meet individual customer needs.


When any product can be found as a service, customer satisfaction and outcomes become essential to securing customer loyalty and, ultimately, are key market differentiators.


With usage-based service models, including subscriptions and pay-per-use, organizations provide customers with access to a product, while maintaining ownership. Outcome-based models take technology service models one step further by delivering actionable business outcomes. Organizations deliver value directly to the customer, and get paid when pre-defined outcomes (e.g., reducing costs) are achieved. In the UK, for example, Hitachi delivers trains-as-a-service and is paid based on reliability KPIs, such as onboard temperature and fleet availability.


More than 80% of companies surveyed by Capgemini Research Institute acknowledge that the shift from product to service-based business models (e.g., as-a-service models) is the key trend impacting their industries today.


However, this shift has product design implications. When a product is delivered as a service, the responsibility and cost of maintenance remain with the maker, and that can alter several design parameters.


Further, products delivered on a pay-per-use model must also capture usage data so that customers are appropriately charged. This requires clear thinking about the type and location of sensors, what data will be gathered, and how often it should be analyzed.


When Xerox evolved from selling copiers to charging by the document, it added sensors on the photoreceptor drum, feeder output tray, and toner cartridge to enable accurate billing and facilitate the sale of consumables like paper and toner.


Applying the Minimum Viable Product (MVP) Process


Transitioning from traditional products to smart products offered as services is complex—it demands customer centricity, new business models, organizational change, new ecosystem partnerships, and digital proficiency. Most organizations are in early stages of this transition with many yet to move beyond pilots and proofs of concept (PoCs). In fact, just 7% of organizations surveyed by Capgemini Research Institute had implemented use cases for smart technologies as services at scale across business units or geographies.


Building smart products as service offerings introduces uncertainties surrounding revenue and margins as they dramatically disrupt marketplaces and existing business models. Many organizations are unsure how to unlock value from them and are stuck in analysis paralysis or pilot purgatory. Like any trend, it’s easy to get caught up in the hype and jump in without specific intent.


At the start, businesses should know the use cases they’re aiming to address and the type of investment returns they can expect.


Applying the principles of a Minimum Viable Product (MVP) can enable organizations to test a new smart product-as-a-service offering at minimal cost and in turn to shape further iterations of the product’s development.


Gartner defines an MVP as the release of a new product (or a major new capability) used to validate customer needs and demands prior to developing a more fully capable product. Unlike a proof of concept or prototype, an MVP is a fully functional product that targets end customers. To reduce development time and effort, an MVP includes only the minimum capabilities required to be a viable customer solution.


The goals of an MVP are to validate the premise of a product, test hypotheses about market needs, adjust the product vision, and prioritize where to invest in future development. As such, MVPs are a powerful approach towards finding product-market fit. In fact, several well-known startups such as Uber, Dropbox, Slack and Zappos started their way to unicorn status with MVPs.


While an MVP is a product release into the market, its purpose is to test and provide information. By releasing an MVP into the market, an organization is seeking to learn about the customer, the market, the channel, and their needs.


How to Gain the Most Value from an MVP


Organizations should consider implementing the following to maximize the ROI of an MVP:


Engage customers at the start of the journey. The initial moves toward smart products require experimenting and engaging with a wider set of players in a product ecosystem. Customer insight will ensure that organizations add features and capabilities that are highly desirable, which will encourage more interaction and thus more data. As customer insights emerge, revenue, pricing and channel models must adapt to large-scale adoption of smart products.


Build or share a digital lab. Making a lab available will help facilitate ideation with stakeholders and showcase the art of the possible. In these spaces, product stakeholders can come together and explore the key business implications of making a product smart. Building powerful customer behavior models will help decode the business possibilities and potential impact on traditional business.


Define metrics. Decide what to track (capabilities, velocity and size) and how it is delivered (defects, performance and spillover). Inspect these metrics regularly and adapt the process to improve outcomes for the customer.


Devise strategies to measure risk and maximize the ROI-to-risk ratio. While there is risk in launching an immature product too early and damaging an organization’s reputation, there is also inherent risk in waiting too long to “perfect” a product since market conditions may move ahead and leave the product behind.


Weight capabilities. Decide which features to introduce based on their revenue potential. The MVP should include the highest weighted capabilities that need to be market tested with this release.


Include necessary core capabilities. Take steps to achieve minimally acceptable safety, security, and performance. For example, you cannot fly anything less than an airworthy aircraft--that platform is an MVP, not its constituent capabilities.


Beware of defining a complex bundle of inter-dependent products as an MVP. Consider complex bundles in a later increment.

Quantify the value of learnings into the ROI calculation. Using the data and information gathered, a more fully capable and valuable product can be released. The product development process is a cycle of learning, and the learning does not stop with the MVP. The continuous cycle means that a product is always being released, with learning generated from the previous release(s).


 

In part 2, we will explore how to leverage no-code development platforms, service orchestration and marketplace platforms, and digital twin models.

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