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How a culture of invention leads to IoT success

23 January, 2019

Andy Penfold, director of offering management at ADLINK Technology, describes how digital experimentation with the Internet of Things (IoT) leads to innovation and looks at potential solutions for creating a clearer path to innovative IoT.

The Internet of Things (IoT) is the enabler for new types of business model that will increase the bottom line for businesses and improve the range of services they can offer. Edge computing promises near real-time insights and facilitates localised actions that are tuned to the needs of customers. In doing so, businesses can ensure they remain competitive in a rapidly changing world.

According to Markets and Markets, the industrial IoT (IIoT) market alone is expected to grow from $64.0bn to $91.40bn by 2023, a compound annual growth rate of 7.39%. Estimates by Accenture indicate that the IIoT could add $14.2tr to the global economy by 2030.

When the IoT works, the results can be highly effective not just as profit centres but to deliver social benefits through smarter cities and infrastructure. The water utility in Houston, Texas found it was losing as much as 15 billion gallons of water a year through leaking pipes – close to 15% of the total supply. Embedding sensors and smart pipes in the network made it possible to regulate the flow of water and reduce the amount lost where the electronics identified a leak.

IoT concepts have already created novel business models. For example, real-time status updates from an array of sensors mounted around each jet engine have made it possible to change how those systems are sold. Instead of being bought outright, airline operators subscribe to an on-going service that guarantees they can be airborne as much as possible. The sensors and the real-time knowledge they deliver ensure the engine suppliers can organise and adjust maintenance schedules to keep the systems in top condition.

Though the IoT is capable of delivering success, implementing a solution effectively can be difficult and costly. Typically, a fully deployed IoT solution requires significant upfront investment because of the large number of sensors and network gateways that need to be installed and commissioned before services can start running. The solution must not just be functional but also deliver on key metrics such as security and reliability. With such stringent demands, the success rate for early adopters has been comparatively low. A 2016 study conducted by Cisco found the success rate for an IoT project was just 26%.

Research by McKinsey found pilot projects frequently went no further: just 30% of those surveyed were starting to scale to enterprise-wide deployment. The pilots themselves were often lengthy endeavours. Of those organisations surveyed, 84% of companies were stuck in pilot mode for more than a year. For 28%, the pilot was still running after two years.

However, pilot projects do convey important information for the organisation. According to McKinsey, 64% of the decision-makers surveyed agreed they learned even from stalled or failed IoT initiatives and those experiences have helped accelerate their organisations’ subsequent investment in IoT projects. Many of those who have been successful did not try to manage the projects alone: they engaged the IoT partner ecosystem at every stage of the implementation plan. Working with partners is a key factor in IoT success but there are many other contributors.

Continued success in business requires the balancing of a number of factors, some of which can often seem contradictory. Successful organisations want to be able to keep pursuing proven strategies. But to remain competitive, organisations have to embrace change and innovate to maintain market-leading positions. The IoT is now seen to be a leading candidate for advancing innovation. But as with any innovation, working with the IoT involves risk. For every innovation that results in an improvement to the bottom line there are many ideas that fail to deliver. The key is to minimise the costs of failures but learn as much as possible from them to help drive the innovation that will deliver a successful deployment.

The path taken by inventors, such a Thomas Edison, demonstrates how innovation often results not from one bright idea but from the exploration of many different options. There are important lessons in each of them. A failed experiment is as important as one that is successful because it demonstrates what attributes the final implementation should avoid. This spirit of experimentation and invention is required in the new generation of computer-enabled systems that will drive the IoT and IIoT forward. It keeps the cost of failure down without hiding the benefits of what failures can teach us and, in doing so, maximise the return on investment when the final system is deployed.

When a team develops an idea, its members will naturally makes assumptions about why they think it should succeed. It is easy for those initial assumptions to be wrong – if not at a broad level, at least in detail. Experimentation can quickly identify which details need changing or ideas should be fleshed out. In many cases, options that will be expensive to deploy can be ruled out because the data they provide does not provide a significant ROI compared to simpler, more expedient technologies and devices.

Experimentation can answer the many questions that need to be tackled before any mass IoT deployment. But how can the concept be put into practice? What is required is a readymade platform that supports experimentation through plug-and-play substitution of components both at the hardware and software level. The platform needs to offer customers a safe space that makes it possible to get results fast, whether they are successes or failures.

A platform that is offered as a subscription, can provide all the relevant hardware, software and services required for a variety of projects and experiments that are run simultaneously in a manner that minimises risk for the user. It understands the many different protocols and data-access technologies that can form an IoT implementation and lets users connect disparate devices and computers using their native protocols and feed into an IoT backbone. The data flows into a common stream from which back-end services can pull insights and deliver real-time knowledge to users and customers with access to the experiment.

Such an approach is already working in a number of situations. In one case, monitoring systems were incorporated into the air-conditioning systems employed in a factory. The compressors in particular are located in a secured area and are difficult to access, making a traditional inspection regime impractical. Failures in the systems have shut down the factory for days at a time, leading to more than $1m in lost production. The incorporation of real-time asset monitoring and anomaly detection systems able to email service personnel with early warnings of problems proved to be the most cost-effective implementation. Since deployment, the anomaly detection has prevented at least two failures.

When implemented in a manner that satisfies stakeholders and which takes account of the capabilities and limitations of individual technologies, the IoT can deliver cost savings and increased business value. A divide-and-conquer strategy that uses early experimentation to let implementers gain knowledge as quickly as possible provides a way to cut out many of the obstacles to success. Small-scale experiments enabled by a service that provides a wide variety of IoT technologies and devices that are known to work together streamline the learning process. In doing so, they make it much easier for organisations to move from the whiteboard stage to full deployment and not get stuck in development hell.

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