The challenges and benefits of data driven IoT, CIOSEA News, ETCIO SEA
The challenges and benefits of data driven IoT

Although the Internet of Things (IoT) has been one of the fundamental tenets in the shift from digitisation to digital optimisation and digital transformation from the late 2000s, it is not a “magic wand” and needs a holistic, multi-pronged and detailed phase wise approach to leverage its benefits. The benefits of IoT are significant, and can unlock a value between USD $5.5 trillion to $12.6 trillion globally by 2030, as per this McKinsey’s research. Major developments and popularity of the cloud, along the IoT ecosystem of the physical, edge computing and the cloud application layer are driving this adoption and growth of IoT in consumer, industrial, government and defence applications. As per this research of IoT Analytics, the number of IOT devices which is 18.4 billion in 2022, shall grow to 27 billion by 2025.

The pandemic with its induced factors of lockdowns, social distancing, and travel curbs also contributed an exponential adoption of IoT and cloud along with 5G and Edge Computing, as well as Artificial Intelligence and Machine Learning (AI/ ML). Right from Automotive, Aerospace, Manufacturing, Healthcare, Oil and Gas to Smart Utilities & Cities, Transportation, Retail, Agriculture, Hospitality, White Goods, Buildings and Government, the use cases of IoT are exploding across the B2C, B2B and Industrial space cutting across operations, manufacturing, supply chain, logistics, HR and other organisational functions.

This co-existence of IoT Industrial Devices, Wearables and Ecosystems with other enterprise systems and technology stacks such as ERP, SaaS solutions, Mobility, AI/ ML, 5G & Edge Computing, BlockChain technologies and others are resulting in an accelerated growth in data generation sources, speed, volume and variety thus resulting in transformation of enterprise and data architecture, and thus to bring about the benefits of data driven IoT. Besides Architecture, there are a whole lot of other data driven parameters that are of paramount importance to the success of IoT initiatives; and these have their challenges and benefits.

So, what are the benefits that data driven IoT is bringing about?

With customer loyalty and stickiness coming under intense pressure especially post the pandemic, IoT and its extension, Internet of Behaviour (IoB) which encompassing ingesting, processing and analysing “digital dust” and data points from a consumer’s online, mobile, e-commerce and other activities to improve customer experience, retention, up and cross sell and referrals. This is even more critical for consumer facing industries such as retail, healthcare, automotive, white goods, hospitality, entertainment, government and others where improved and preemptive customer service, new product launches, recommendation of offers & referrals and citizen indices can be clearly drawn out from data powered IoT. Data Driven IoT is also instrumental in safety and wellbeing of consumers especially considering the Internet of Medical Things (IoMT)and Internet of Packaging (IoP)

From the operations, maintenance and supply chain perspectives, data driven IoT along with other technologies such as additive manufacturing, robotics, digital twins, autonomic systems, smart meters and utilities and others, bring about operational excellence, improvement in quality, lower downtimes on predictive maintenance, improved inventory management, better logistics, equipment and staff surveillance, safety and tracking, employee motivation, energy optimisation, environmental and emission compliance. Thus, resulting in benefits of operational, product and process excellence, high quality, compliance and optimisation of costs.

What are the challenges in implementing data driven IoT?

As mentioned before, there are a plethora of technology and human resources aspects that are challenges, yet opportunities to have a resilient, dynamic and efficient data driven IoT strategy and ecosystem. Let us examine these factors.

What are the considerations from the Business End?

From the business end, it is very important for identification of relevant IoT use cases across business functions and the extended enterprises considering market and competitive dynamics as well as technology roadmap and footprint. IoT use cases must make significant impacts in terms of improving customer, employee or supply chain experience, productivity and satisfaction, reduce costs or improve compliance and fit into the overall organisational technology roadmap and strategy.

Are there challenges from the hardware perspective?

It is expected to have continuing chip shortages amidst the volatile geopolitical world of 2022. In this research of Forrester, it is predicted that the ongoing chip shortage will impede IoT market growth by 10% to 15% in 2022, especially those that power IoT enabled connected devices. In this category of IoT devices, demand shall outstrip supply.

And from the Architecture Perspective?

The importance of Enterprise and Data Architecture in data driven IoT cannot be overstated, especially in these post COVID-19 times of continuing business amidst market uncertainty, decreasing customer loyalty and cost pressures. Enterprise and Composable Architecture, through leveraging reusable components and best practices for Quality Assurance, Storage, and Integration while considering technical debt, emerging technologies and future proofing are critical to organisational resilience and competitiveness, as this article by McKinsey and a research by Gartner highlight.

IoT and digital transformation have made organisations grapple with diversity in data sets across sensor, text, image, Audio-Visual, Voice, E-commerce, social media and others, besides the diverse data sources which reside both on cloud and on-premises, churning out humongous amount of data which is required to be ingested, managed and delivered on real-time and batch mode.

This article by McKinsey summarises the major tenets in data architecture which are Cloud with containerisation and serverless data, hybrid real time and batch data processing, shift from end-to-end Commercially Off the Shelf (COTS) applications to modular best in function/ industry, incorporating APIs and decoupling, shift from centralised Data Warehousing to domain based architecture and lastly from proprietary predefined datasets to data schema that is light and flexible, especially the NoSQL family.

Organisations are implementing ML and API powered Data Fabrics along with Data Lakes, Warehouses and Layers to manage this data lifecycle by creating, maintaining and providing outputs to the consumers of this data, as this Gartner article on technology trends for 2022 highlights. Also, small and wide data initiatives are co-existing with big data drivers and ecosystem

Data Architects and their team need to pay careful consideration in understanding, designing and having an end-to-end business and IT perspective of the Data Sources, Metadata and schema itself, the data lifecycle pipeline of ingestion, cleaning, storage, analysis, delivery and visualisation, Automation, APIs, Cloud computing, container orchestration and storage, Data Streaming, AI/ ML models, Analytics, and Visualisation and Security. They should ensure data consistency and validation, implement ease to use interfaces, minimise data duplicity, movement and irrelevant versions, valid and comprehendible documentation, security and adherence to compliance, access and governance mechanisms and frameworks.

It is also important to consider automated and active data management along with scaling, elasticity and decoupling hence incorporating independence of services, corresponding performance with relation to bursts and shutdowns, high availability, while optimising cost at the same time.

It is also worthwhile to note that while the Investments in the IoT hardware/ physical layer are still the most, the investments in the IoT software and platforms layer are rapidly rising. As per this research by IoT Analytics, spending on IoT software grew by 24% vis-à-vis a corresponding growth of only 5% on IoT hardware in 2021, especially fueled by the popularity of Containerised IoT Platforms.

What about Data Security?

IoT Security especially DDoS attacks and Botnets have been significant challenges, especially throughout the pandemic. The factors are essentially the large number and variety of attack surfaces, access to the humongous IoT points, unsupported and obsolete architecture, inconsistent authorisations, operating systems and firmware, and absence of standard supply chain cybersecurity practices on 1 hand, and the increased importance of compliance to the EU GDPR, NIST and other privacy and security guidelines, and the significant fine and penalties for breaches and leakage of customer sensitive data on the other. Gartner predicts that by 2025, 45% of organisations worldwide will have experienced attacks on their software supply chains, a three-fold increase from 2021.

Governments and Private Enterprises are coming together to address IoT Security concerns in this era of Zero Trust and Cyber Resilience. The European Union Agency for Cybersecurity (ENISA), the NIST in the USA and the President’s May 2021 Executive Order are addressing cybersecurity concerns, guidelines and compliances for the IoT ecosystem. Private enterprises are working on crystallising IoT baseline security standards for consumer and industrial devices, shared security principles, driving basic security certifications, norms, and enforcing cooperation, transparency and conformance across supply chains and customers. Enterprises are gradually relying upon blockchain in securing their edge device data and are also encompassing hardware encryption, zero trust software architecture, and cybersecurity tools and design to also cover supplier compliance and assessment exercises as well.

Is Data Storage a challenge as well?

7 years ago, this article by the World Economic Forum in 2015 predicted the challenges in storing this humongous data from IoT, Cloud and other data sources and that the world could be running out of adequate data storage space. The pandemic accelerated this trend and this IDC Report of 2020 estimated that over 64 Zettabytes of data was created/ replicated across the globe and correspondingly the global storage capacity was just 6.7 Zettabytes. This World Economic Forum report right before the pandemic highlighted the fact that the conventional optical/ magnetic storage systems will be unable to handle this phenomenon for more than a century.

To address this CIOs and Leaders are leveraging automation and cloud, Storage-as-a Service (STaaS), decentralised Blockchain powered data storage as well as storage on the Edge. Researchers are also working on the feasibility of using Human DNA as an alternate to conventional electromagnetic/ optical data storage mechanism

What about cultural and skillset aspects?

The role of Data Architects is critical and companies would do well to have a readily available talent pool as well as consider upskilling of their pool of solution architects, data analysts and engineers.

Having a culture of Data Literacy leveraging business buy-in and alignment, open communication, robust processes and technology, top management focus and strong adherence to security, compliance and governance. This also inculcates a Data Ops culture for ease and quick design, development and deployment of new components in the data architecture.

Data driven IoT can transform organisations from initially achieving customer and operational excellence, to not only gaining significant competitive advantages but also in being resilient, composable and adaptable to evolving new business models, processes and products ahead of the market and trends.

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