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The Internet of Things (IoT) is both a disruptive and transformative technology concept, with an estimated 8.4 billion devices getting connected by end-2017, according to research firm Gartner Inc. McKinsey Global Institute pegs IoT’s potential economic impact between $3.9 trillion and $11.1 trillion a year by 2025. While manufacturing, transport and logistics, and supply chain industries are already beginning to realize this value, other segments such as public services, retail, consumer products, healthcare and others are expected to follow suit. In this backdrop, Mint recently partnered with SAP India Pvt. Ltd to host a select CXO round table centred around the theme: Harnessing the potential of IoT across industries.
Participants in the discussion—who were divided into three groups to tackle different aspects of IoT—included Vishal Kapil, IT director (emerging markets-India) at Adidas India Marketing Pvt. Ltd; Sumit Sarawgi, partner and director at BCG India; Neeraj Chandra, chief executive officer (CEO) and founder of Arkit Consultants Llc; Jaspreet Bindra, senior vice-president (digital transformation) at Mahindra Group; Rajesh Uppal, executive director (IT) and chief information officer at Maruti Suzuki India Ltd; Farhana Haque, vice-president and business head (IoT) at Vodafone India Ltd; Sagar Aluri, head (technology and innovation) at Adani Enterprises Ltd; Swadeep Bijja, assistant general manager (IoT sales specialist) at Vodafone India; and Prashant Tandon, CEO and co-founder of 1Mg.com. The overall discussion was moderated by Leslie D’Monte, national technology editor of Mint. Here is a summary of the CXO group discussions:
Five essential elements of an IoT strategy
The first element of building a successful IoT strategy is that it should be based on some business value such as percentage increase in revenue or reduction in cost or improvement in productivity/efficiency. The second element is that the commitment should be top-down: What is the leadership’s commitment to the success of the IoT project? Third, it needs to have an ecosystem play, involving all the key ecosystem participants while the strategy is being built. The fourth one is the right set of skills and the capability to consume IoT. And the fifth element is having an end-to-end perspective that touches everyone in the organization for whom the project is relevant.
Five capabilities needed to execute this strategy
The first one is skills—you need to have the right skills. The second capability needed is change management, which involves right culture, communication and the right stakeholder mapping. The third one is building the right business case or the financial model for IoT, as sometimes, even though everything looks good on paper, the numbers don’t add up. The fourth one is about integration, which is a function of technology and process, and the fifth is the services capability. It is not something that is driven only by the application guy or the system integrator; everyone in the value chain—from the device to the connectivity to the middleware to the cloud—has to take ownership of the services required.
Five roadblocks that can derail IoT implementation
The first roadblock is “legacy”: traditional industries such as utilities, energy and manufacturing have technology systems that have been there for a long time. So, how do you bring those systems on the same plane as the new IoT technologies? The second challenge is security, especially given that these IoT devices are unmanned devices. The third roadblock is the lack of skills; sometimes the skills may exist on paper but how many of those skills have been put to practical use? The fourth one is regulatory framework; while regulation can enable growth, quite often, it can actually inhibit growth. And the fifth roadblock is the lack of standards in IoT to tackle interoperability and device-compatibility.
How to efficiently analyse IoT data
Traditionally, industries have relied quite a bit on enterprise resource planning (ERP) but when you look at companies across industries today, the data being generated is increasing day by day. A lot of that data is not captured in the traditional ERP or other similar systems and the more the data, the more is the need to capture and analyse that data—especially with the growing usage of IoT.
An example of IoT analytics in telecom is a proof-of-concept that has been done in Mumbai for simplified traffic management. The utility of IoT in telecom, specifically in disaster management, can be seen by using push notifications and real-time alerts to the people. Another industry where we see a lot of use cases in IoT and machine learning is pharma and healthcare.
Most of us now move around with wearables like Fitbit and have healthcare apps on our smartphones that track our movements. Also, when we visit hospitals, most of the diagnostic machines have sensors built in to capture the information and this huge database of information helps in prescriptive analytics by aiding the doctors diagnose the patients better. And if you look at the likes of IBM Watson and other cognitive techniques, people are able to predict a disease well in advance.
Another thing is that the pattern of consumption of medicines by people can also help doctors to zero in on the medication required by certain patients.
At the same time, there are certain restrictions or regulations in the healthcare sector preventing investments in this sector and some easing of the regulations may be needed for the sector to achieve the IoT potential. In the energy and manufacturing sectors, there are IoT use cases in smart metering, better inventory management and predictive maintenance of assets.
Cognitive is the way to go. And just like we ask intelligent assistants like Alexa and Siri for the weather or for help in our daily needs, the whole world is moving in that direction. Huge data is being generated—on the consumer as well as the industrial side—and the IoT use cases in consumer businesses will also be applicable for industrial enterprises. Going forward, we can easily share data in real time or near real time as it is generated—and the new technology tools will enable us to shorten the lead times for analysing and acting upon that data.
Addressing interoperability, privacy and security concerns
Devices are not purchased by one person or a single service provider. They are bought by a user, and they are of different types spewing out different kinds of data, which makes interoperability a huge challenge. So, there is no one controlling the assets that are aggregated at the end points. That is the first challenge: there are no standards on the hardware side.
The second challenge is about privacy. Even if people want to share data, what is the framework within which they do so? There are petabytes of data going around and we will all benefit if data is shared in a way that privacy is not breached. We need a policy framework to safeguard privacy interests. The third issue is that any security threat in an IoT network starts from the device; the malware first infects the device, and then it floods the network. However, the concern is that the device manufacturers who are the point of attack have the least incentive to do anything about it—because they are not the ones who get harmed by the attack.
IoT trends: way forward
One of the trends in this context is that organizations are moving from just digitization to digital transformation. While digitization is merely a cost concept or an operational efficiency concept, as people move to digital transformation—where the customer value proposition is very strong—IoT will get combined with many other emerging technologies. These include artificial intelligence (AI) and blockchain. IoT combining with AI gives you the power to analyse data in real time, while IoT combined with blockchain gives you increased power to do provenance in terms of tracing where a particular material (or document or data) came from.
Also, from a government perspective, can the government facilitate an ecosystem or a framework within the industry so that different partners in the industry can work together? Imagine, you need to bring together all those device manufacturers in places like China and Taiwan and actually enforce standards across those device makers, the cloud providers, the service providers, etc., to tackle the issue; you also need to incentivize them appropriately.
Things like AI and blockchain may actually enhance the ability to do that. And for the wider success of IoT, this needs to be a global phenomenon rather than just an India-specific one.