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Can data from IOT devices change supply chain analytics?

The supply chain havoc caused by the coronavirus pandemic has left an indelible mark on the minds (and businesses) of manufacturers, wholesalers, dealers and retailers. Lockdowns and restrictions hindered manufacturing and shipping, resulting in shortages in pharmaceuticals, electronics, food items and raw materials in just about every industry. 

A McKinsey study on the impact of this extended disruption found something very interesting: while 75% of companies surveyed faced problems with their supplier base, production and distribution, 85% said they struggled with “insufficient digital technologies” in the supply chain.

The solution? Nine out of 10 leaders in the survey said they planned to focus on digitisation of the supply chain to improve its resilience. Specifically, they’re looking at these areas:

    • Centralised supply chain planning
    • Advanced analytics
    • Reskilling the labour force for digital planning and monitoring

In the never-ending hunt for maximum efficiency and cost savings, supply chain digitisation correlates closely with smart manufacturing processes. And it has quite some catching up to do – the smart manufacturing industry is set to grow from $250 billion in 2021 to $658 billion in 2029

Driving this parallel growth in smart manufacturing and supply chain technology are a handful of technologies:

    • Industrial Internet of Things devices that enable data collection from more interaction points, factory automation, shipment tracking via GPS and machine-to-machine and machine-to-people communications
    • Artificial Intelligence and Machine Learning to automate decisions to produce, store, order and so on
    • Wireless sensor networks to record environmental changes and enable transmission of this data among IoT and the cloud
    • 5G for better network connectivity spread across large geographic regions
    • Big data enables advanced analytics and better outcomes

All this is possible only when companies are able to use the data generated by the monitoring system. Traditional monitoring devices kept their data closed in proprietary databases, locking up companies to their systems in the name of security. Ultimately, businesses didn’t have the ability to analyse this data, gain insights or build apps around the outputs.

Now, however, the IIoT-enabled data logging devices bundled with APIs that help you analyse, repurpose, reformat and channel supply chain data into business intelligence systems such as ERPs and CRMs to optimize operations better. For example, you could integrate dynamic condition data from a logger with QR codes on product labels (which contain pre-set information about the product) and let customer systems process and cross-reference this integrated data using the logger’s API. The result is extensive tracking and planning capability down to a single specific item.

Supply chain data often helps an organization increase transparency and cooperation in multiple, if not all, departments.

The future of the supply chain is IoT-driven

Some industries still smugly operate with the belief that they don’t “need” monitoring along their supply chain. They see it as an additional expense. But they could benefit immensely from logistics tracking and transparency if they’re assured of the payoff (companies selling fragile electronics or brands plagued by fakes and copies come to mind). Digitization of the supply chain – with both hardware and software – is the way forward for them.

Speed and reliability have always been and will continue to be the driving factors of the supply chain for the foreseeable future. The next few months will be critical for companies that bank on data to improve their supply chains. They have a never-before opportunity to build on the momentum and insights gained as a result of COVID-related disruptions by adopting newer technology and systems. The ones that fail to adapt to changing realities will likely be left behind by more agile competitors.



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