Published on 05/24/2017 | Strategy
1 - How are manufacturers that are used to five-year product lifecycles adapting to agile development methods and radically reduced product lifecycles?
Ayla - When talking to our current and potential customers one of the key challenges we see for IoT is how rapidly the demand from consumers and the choices available to manufacturers changes. Two years ago a company looking to build an IoT device would want to work with IFTTT, eighteen months ago they added Nest, twelve months ago HomeKit became a feature to think about supporting, now its Alexa and next year we see Google Home rising as a integration point. This is just one of many examples of the dynamic market where manufacturers are starting to understand that committing to a two plus year development cycle and all the features and deliverables, without allowing flexibility for change, can make or break the success of their project.
mnubo - Ten or twenty years ago we would only upgrade our thermostats when we bought a new house or when our existing thermostat broke down. Now Nest and Honeywell are challenging that mentality, where they come out with a new thermostat every six months/a year, so already those cycles have become shorter. But it’s important to point out that hardware is not software. Designing, building, manufacturing and deploying hardware will always take time. OEMs need to manufacturer future-proof hardware and make incremental changes through regular software updates. This is already happening in spaces which are great for innovation (think Tesla), but the importance still relies on building modular hardware and using software as a way to bring new features and innovations to the product. Learning from your data and using software as a way to implement a change is the way to address the long product lifecycles that traditional manufacturers have grown accustomed to.
2 - At a high level, emerging regulatory frameworks put the consumer in control of data. Data will become a form of currency that can be exchanged to receive something of value. How will manufacturers convince consumers to share data from smart home solutions?
Ayla - There will be several ways in which consumers will gain perceived value from sharing data with manufacturers. Value added features that were previously unavailable from a non-connected product are the first and most obvious ways to gain value. Allowing consumers to share their device with others in a secure and controlled way or remotely accessing a device to find out the status of their home can be enough to convince a user to share data. Offering connections to other systems that can facilitate control or interoperation between multiple IoT devices will grow as a value add in the coming years. Sharing data in order to use your device with a service like Alexa, or interoperate with your thermostat system will be common. Manufacturer offered services is an underutilized area of IoT currently. Offering extended warranties and post sale support features that rely on monitoring and data will be a more direct trade of perceived value in exchange for access to users data.
mnubo - It’s all about give and take. Consumers willingness to share data is directly correlated to the perceived benefits they will get from it. Taking Facebook as an example, you are willingly sharing personal information because it helps you connect better, communicate better, get more relevant content to you. Similarly, if IoT manufacturers want to ask consumers to share more data, they need to make it very clear what are the benefits they will provide - either better services, better products, updates, warranties, etc. The second part is being absolutely transparent in the use of data. Providers, like mnubo, who don’t deal with the consumers directly have a very strict relationship on data with our customers. Our customer always owns the data. We ensure full privacy, anonymity and encryption of the data. In a smart home environment, it will be hard to have one maker get the data. It will be done in ecosystems, because one of the main benefits of data is seamless use cases. Unless you are a brand that is providing multiple services, it will be hard to enable that. What I foresee are ecosystems coming together, that will have similar data conditions around it.
3 - Data and analytics can create value for manufacturers and service providers by creating operational efficiencies, consumer value and enabling new business models. What is the quickest path to creating value from data? Where is the low hanging fruit?
Ayla - We believe that there is high data value from the minute you connect your device and start pushing data to the cloud. This low hanging fruit begins as part of the development cycle, testing your product for defects and faults in labs, understanding consumer usage behavior in field trials and gaining operational efficiencies in manufacturing. All of these cycles of data generation happen before the device hits the store shelves and can be used to make key decisions about go to market strategies and even to help in deciding about when the device is ready for sale.
mnubo - It all comes down to the data. When looking at product data, there are many low hanging fruits, but I think there are two important and more obvious ones to point out. One is when going to market, manufacturers want to ensure they are deploying the best quality product. Therefore the low hanging fruit, is not necessarily from a services or monetization point of view, but rather for the product manufacturers themselves. Ensuring they are going to market with a product that is going to be sustainable, that the customers are going to purchase, use for a long period of time and not turn off after three or so months. Being able to understand the quality of a product from a firmware and connectivity perspective is one (crucial) low hanging fruit. On the flipside, once deployed, there is the visibility on product usage feedback - how are products being used, which features are used the most, are there patterns in usage that will drive the roadmap for the next product release?
4 - How will data analytics create a better customer experience?
Ayla - One key area that stands out as an opportunity to create a better customer experience with data is in reliability and device uptime. Using the volume of data generated from a connected product a manufacturer can understand where faults may occur with devices and push over the air updates to avoid costly repairs and negative consumer interactions. They can also use predictive analytics to understand when a certain device might need a service and proactively send out a technician to provide maintenance vs complete failure of the device. In both these scenarios the customer experience is increased and the company brand value should grow.
mnubo - There are many strong examples of how data analytics can enhance the customer experience. But we’ve noticed that lifecycle analysis is a very strong driver for connected products. At mnubo we define the ‘pre IoT’ era as the ‘ship and pray’ era. Where the product has been packaged and shipped, but there is no visibility on the behaviour of the product. The only time you hear about how the product is doing is when it is a complaint. Whereas with data insights, you have visibility across the life of the product - from the time it got activated, across the various stages of connectivity. You’re now able to answer questions like:
Where it really makes a difference is the way the data goes back into building better products and features from a product development perspective. Moreover, customer service and operations can now be proactive in the actions they take with their customers - for example, smart replenishment, targeted upselling, reduced downtime, etc.
About the writers
Oliver Cockcroft is Ayla’s product lead for platform level features, managing the development of large scale projects the affect multiple parts of the Ayla Platform. Oliver is also responsible for developing Ayla Networks' relationships with members from cloud partners such as Amazon Alexa, Apple HomeKit. Oliver works closely with Ayla Networks' potential customers and clients to help define their connected product strategy and product development plans and then execute them on aggressive schedules.
Jennifer Sewell is Head of Product Marketing at mnubo, a data-driven leader in the global IoT market with Analytics and Data Science as-a-service experts for equipment manufacturers. Jennifer leads the company's product marketing, as well as branding and go-to-market strategies. She supports the business development and sales team with key insights on market trends and manages the company's worldwide partnership ecosystem.
This article was originally published on LinkedIn.
