The Internet of Things (IoT) is a fast-emerging ecosystem of IP-connected sensors and devices. It has the potential to deliver significant business benefits and we are already seeing stand-alone sensors and smart devices embedded into our life at an unprecedented rate. But in an industrial setting, “What are some of the useful things we can do with the data being produced and transmitted by smart devices?” or “What are IoT’s economic benefits for my business?”. These seem to be the predominant questions asked by most of the customers that I encounter today. So, I feel it’s about time we discuss how to hone that competitive edge into something that’s really compelling and also look at some challenges that come along the way.
One of the key drivers for organisations to consider IoT is to drive potentially considerable cost savings by improving asset utilisation, enhancing process efficiency and boosting productivity. In general, when we talk about these economic benefits, there are two major paradigms from which business value can be derived, which can be termed as real-world awareness and business process decomposition.
By real-world awareness we imply utilisation of automated identification and data collection technologies like RFID and sensors to better understand what is actually going on, i.e. how the operations are performing and what is the status/whereabouts of assets and products in the supply chain. The increased accuracy and timeliness of information about these within business processes provides competitive advantages in terms of process optimisation. The deeper insights gained into the processes allows for a better understanding at the operational level and for optimisation. A great example is how TfL has discovered some very curious journey patterns on the London tube network by tracking the movements of people by logging the unique Wi-Fi identities of individual devices. It has proved the hidden congestion in stations that has long been anecdotally known, but never proven in actual numbers as tube stations with several lines have a lot of traffic swapping between lines but that would never show up in Oyster card tracking at the ticket gates. Optimised shelf replenishment used by TESCO serves as another great example, which provides optimal product availability for its customers.
These examples show how the use of(near) real-time analytics to analyse, new types of enterprise data based on IoT concepts using Machine Learning & AI can discover patterns and derive more timely and accurate business insight. New strategies and predictions can be generated based on certain pre-configured criteria or based on criteria discovered by the AI itself. When used effectively, this insight can provide real cost savings and also real business advantage.
Business Process Decomposition
Real-world awareness as described above is what basically is done today with RFID and sensing. Data is collected and sent to a central application, where it is processed, analysed and decisions about actions are taken. Business process decomposition takes this a step further. A business process is decomposed into process steps, some of which are executed in a distributed manner, even at the edges of the network and on physical items themselves.
For example, Samsung Electronics has developed the Autonomous Decentralised Peer-to-Peer Telemetry (ADEPT) technology which has implementation in multiple use cases such as a Samsung Washer that can autonomously order parts, detergents and schedule servicing, leveraging this framework to provide better service to customers at the same time as allowing distributers and agents to better plan for and manage maintenance visits, parts needs and consumable stock.
Many current enterprise strategies already operate a few interfaces to smart items, but with the increased computational and communication capabilities of these items, the power shifts towards the edges of the network. The decomposition and decentralisation of existing business processes increases scalability and performance, allows better decision making and could even lead to new revenue streams. This extends the real-world visibility concept with real-world interaction. Smart items become, active participants in the overall business process. This can bring significant benefits, but often at a cost of increased management complexity. This must be understood and managed to ensure that expectations of both shareholders and customers can be met.
Even though IoT offers huge value potential, in order to realise this organisations must understand this complexity and overcome key challenges. These include the lack of interoperable technologies and standards, data and information management issues, privacy and security concerns and finding the skills needed to manage IoT’s growing complexity.
Information technology issues: Routing, capturing, analysing and using the insights generated by huge volumes of IoT data in timely and relevant ways is a huge challenge with traditional infrastructures and systems. The sheer magnitude of the data collected will require sophisticated algorithms that can sift, analyse and deliver value from data, enormous system processing power & capacity to handle such volumes and better network capabilities to cope up with the volume and speed. Another potential for risk in the future is managing the serviceability of these devices - a malfunctioning device could induce catastrophic failures in the IoT ecosystem.
Privacy and security concerns: Deriving value from IoT depends on the ability of organisations to collect, manage and mine data. Securing such data from unauthorised use and attacks is a key concern. Similarly, with many devices used for personal activities, many users might not be aware of the types of personally identifiable data being collected, raising serious privacy concerns. This is particularly relevant given the new GDPR regulations coming in to force next May.
A lack of standards and interoperable technologies: The sheer number of vendors, technologies and protocols used by each class of smart devices inhibits interoperability. The lack of consensus on how to apply emerging standards and protocols to allow smart objects to connect and collaborate makes it difficult for organisations to integrate applications and devices.
Organisational inability to manage IoT complexities: While IoT offers tremendous value, tapping into it will demand a whole new level of systems and capabilities that can harness the ecosystem and unlock value for organisations. For instance, making sense of the flood of data generated by sensors every millisecond will require strong data management, storage and analytics capabilities. Organisations will also need to develop skills to ensure business operations run effectively and efficiently with IoT.
The IoT is enabling companies to transform their operating processes and business models in ways we haven’t seen before. There’s a confluence of innovations that have led us to this point—the reduction in the size and cost of sensors, the ubiquity of mobile devices and connectivity and the availability of cloud platforms to ingest and process data. These factors have enabled IoT solutions that weren’t economically viable or even practical in the past. We are excited about what this means for the future and we are committed to help our clients realise them.