Iot Analytics

Get Ready For The Product-As-A-Service Revolution

Pinterest LinkedIn Tumblr
PaaS is a great business model for companies that want to extract value from IoT data  

Buying your first car comes with some pretty powerful life lessons. 

Low-code Application Development Company

 When I was 12, I started a lawn mowing business so I could purchase my own set of wheels the moment I turned 16. Some years later, I was the proud owner of a classic Chevrolet Caprice. My plan worked! 

 As part of that process, I learned a few things: New cars lose value instantly, don’t be afraid to walk away from a deal, and leasing is for suckers. I must have internalized that last one—that it’s almost always cheapest to buy your car outright—because I tend to extend the concept to most physical assets.  

 These days I’m not so sure about that last point. It’s not that leasing has suddenly turned into a deal. Instead, it’s due to the rise of a new business model enabled by the Internet of Things (IoT).  

 The rise of product-as-a-service 

 This business model is product-as-a-service (PaaS), and it’s gained traction over the past few years among companies eager to copy the SaaS model of subscription revenue.  

 Initially, PaaS was an add-on to regular products and more akin to service-as-a-service. For example, after buying a car, you’d pay an extra monthly fee for its maintenance, realizing that BMW has access to performance data that enables improved and proactive repair.  

 The game changer is ambient compute, also known as ambient intelligence. As IoT devices and 5G proliferate, ambient compute, which enables compute power and decision-making from the edge to the cloud, will enable PaaS to evolve into exactly what it sounds like. Everything—from washing machines to wind turbines—will be available as a service, with customers (whether consumers, businesses, or governments) paying for what they use on demand. 

 One ServiceNow customer, for example, now sells wind turbine cycles in addition to the turbine itself. That may seem like a bad deal for the purchaser of those cycles; after all, the supplier can sell those cycles indefinitely while the purchaser will eventually walk away with nothing of value. But the reality is, the PaaS model benefits both sides. 

 The competitive advantage hidden within IoT data 

There are already billions of IoT devices deployed. IDC expects that number to rise to 41.6 billion by 2025, generating 79.4 zettabytes of data in that year alone. For context, that’s 80X more stars than exist in the observable universe. 

Yet organizations only analyze about 3% of the data they collect, according to a widely-cited Gartner finding. At most organizations, it sits untouched in large data lakes, because owners lack the manpower or technical know-how to mine insights that could become a sustainable competitive advantage.  

 The good news: PaaS, in which customers pay for outcomes and not products (e.g. wind power, not the wind turbine) is a practical business model for companies that do want to generate value from IoT data.  

  1. Lower operational costs and increased uptime 

 Organizations can use IoT data to lower costs and boost profitable outcomes via  predictive maintenance and workflow-powered productivity gains.  

 Take, for example, TAPCO, a family owned and operated business that provides traffic safety solutions across the U.S. Those blinking “wrong way” signs? There’s a good chance those are TAPCO’s.  

 While you might not associate traffic signage with IoT innovation, TAPCO piloted a new ServiceNow product called Connected Operations to link IoT data from its internet-enabled traffic signs to their customer and field service functions.  

 Now, if a part on a sign fails, it triggers an automated workflow that delivers actionable information to customer service and maintenance teams. The ROI is huge because employees no longer have to manually inspect signs or search through systems to ensure the customer has a service contract in place.  

 Instead, it’s all automated. Over time, the data collected within the system can also be used to predict and address part failures before they occur. 

  1. Design new revenue streams  

 Data from IoT devices allows businesses to better understand their customers and design new revenue streams that fit their needs.  

 For example, a washing machine company may notice that customers of a certain demographic tend to run many small loads as opposed to one big load every week. That finding will allow product development to create a new line of devices or a new subscription model for a previously unaddressed market.  

 At scale, this approach allows organizations to micro-target consumers with personalized bundles and subscription structures. Side benefits include reducing cost by eliminating unused extras that add waste throughout the value chain.  

 Depending on the product, asset owners can also increase asset utilization by adopting a utility-like fee structure that incentivizes usage at different times.  

 More profitable for companies, more flexible for customers 

 If the benefit to service providers is clear, the benefit to customers is no less significant.  

 By avoiding large CapEx costs, customers increase budget flexibility and lower the risk of product failure or obsolescence. Instead, they pay for outcomes as needed, which produces the savings and new revenue streams mentioned above.  

 At the same time, customers will tend to get  improved product performance because of greater alignment between supplier and customer incentives. Rolls Royce’s power by the hour model for aircraft engines shows how this works in practice. As IoT proliferates, similar arrangements will become possible for many more products. 

 Because PaaS is a business model that benefits both service providers and customers, I predict it will continue to grow in popularity. As we roll down the road toward the Internet of Everything, there’s only one big speedbump in our way: smarter use of our most valuable asset—data.

ThinkDataAnalytics is a data science and analytics online portal that provides the latest news and content on AI, Analytics, Big Data, Data Mining, Data Science, and Machine Learning. A team of experts with extensive experience in the field runs