How data from IoT devices is changing 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 digitization of the supply chain to improve its resilience. Specifically, they’re looking at these areas:

• Centralized supply chain planning
• Advanced analytics
• Reskilling the labor force for digital planning and monitoring

In the never-ending hunt for maximum efficiency and cost savings, supply chain digitization 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 (IIoT):devices that enable data collection from more interaction points, factory automation, shipment tracking via GPS and machine-to-machine (M2M) and machine-to-people (M2P) communications
• Artificial intelligence (AI) and machine learning (ML): to automate decisions to produce, store, order and so on
• Wireless sensor networks (WSNs): to record environmental changes and enable transmission of this data among IoT devices and between IoT and the cloud
• 5G: for better network connectivity spread across large geographic regions
• Big data: enables advanced analytics and better outcomes

Let’s see how all these technologies come together to fast-track supply chain innovations, improve product distribution and shipping, and help businesses set and meet customer expectations.

Complex infrastructure not needed

Expensive hardware for tracking systems is one of the biggest deterrents to the adoption of supply chain analytics. Further, the tools and devices available on the market are proprietary and prone to vendor lock-in. Setting them up is a byzantine, time-consuming process.

That is changing with the introduction of inexpensive IoT-based data loggers that can be attached to shipments. These instruments measure a variety of environmental factors such as temperature, tilt angle, shock, humidity and so on to ensure quality of goods in transit. Data loggers connect to centralized data management systems and transfer their readings, enabling efficient recording, analysis and decision-making. It also eliminates the need for expensive radio frequency transponders, receivers and signal towers – you don’t need to install any gateways or other special tools to use them.

For instance, data logging company Logmore has come up with data logging devices with QR tags attached to the sensors. This allows you to send updated condition data to a cloud-based server or database from any point along the supply chain simply by scanning a QR code with your smartphone.

Using such devices, you can instantly set up secure, automated logging and monitoring for thousands of products from a centralized ERP or supply chain management system. This also applies to companies that haven’t used supply chain logging before.

“The greatest benefit comes from the quality and volume of data,” said Niko Polvinen, CEO of Logmore. “For example, every shipment of perishable goods is required to have temperature monitoring, but the less expensive the solutions are, the more sensors one shipment can have. This takes the sensors closer to the actual goods and improves the quality and adds to the total amount of data, which ultimately enables everyone in the supply chain to make better decisions, so waste is reduced and processes are optimized.”

That brings us to the value of timely data and analytics.

Democratization of data

Traditional supply chain analytics and decision-making focused on risk avoidance and control. Today, the easy and real-time availability of data from loggers and other devices encourages “opportunity thinking” – manufacturers, suppliers, distributors and retailers can all plan further ahead, capitalize on opportunities in their chunk of the chain and even take calculated risks to increase revenue.

The more data you have, the more costs you save. Some obvious advantages that supply chain analytics brings to the table are:

• Better forecasting of demand, supply and sales
• Shipment and fleet tracking
• Better risk management and fewer disruptions
• Less waste, damage or shrinkage of inventory
• Increased visibility and transparency for all parties involved – data transmission, recording and reporting takes place using readily available cloud-based infrastructure and networks
• Instant decision making and control along the whole process – companies can decide whether to destroy something, proceed with delivery or send it back at any point

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 analyze this data, gain insights or build apps around the outputs.

Now, however, the IIoT-enabled data logging devices bundled with APIs that help you analyze, 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.