Want to know what the world’s most popular supply chain planning method is?
Yes, you read that right.
A McKinsey & Company survey of global supply chain leaders in 2021 revealed that almost 75% of respondents rely on spreadsheets to do their supply chain planning. However, 61% believe technology enhances their competitiveness, according to a recent Gartner survey. Why, then, isn’t there more urgent investment in supply chain technology innovation?
90% of the McKinsey & Company survey respondents indicated that they plan to adopt a new supply chain planning system in the next five years. However, this may not be fast enough – especially when you consider the second most popular supply chain planning method is SAP’s Advanced Planning and Optimisation software, which they’ll no longer support from 2027.
Companies need to invest in supply chain technology now if they’re going to reap first-mover benefits and not be left behind. But, in upgrading digital supply chain technology, the challenge is not to get swayed by the latest shiny thing. Instead, companies need to choose wisely, based on real business needs.
To help your business find the right solution, here’s an overview of the most promising supply chain tech on offer, and what to consider before investing.
Top supply chain tech to streamline processes
But how do you know which technology is right for your business? Let’s explore three types of technology that you can use to create a more efficient supply chain.
The internet of things (IoT)
The Internet of Things (IoT) describes a network of devices that communicate and exchange data wirelessly. IoT can remotely track physical items, such as goods in transit, and monitor environmental conditions, such as the temperature inside a transport vehicle or the moisture content of soil.
When combined with predictive analytics (the use of data, machine learning algorithms and modelling to make predictions), IoT in the supply chain can deliver immense benefits. As just one example, logistics companies can leverage IoT and predictive analytics to deliver real-time route optimisation to their drivers, factoring in goods-on-board, goods-for-pick-up, traffic congestion, distance and weather. This saves time, fuel, vehicle wear and tear and, ultimately, money.
Besides streamlining delivery processes, IoT can:
- increase the visibility of goods and assets
- improve customer experience
- enhance product traceability, transparency and speed of delivery.
If you are considering investing in IoT, make sure that you factor in the security of your IoT devices so that they maintain data privacy requirements and are protected from cybersecurity vulnerabilities. You may also need to consider how you will integrate the data from different devices and sensors to your internal CRM and other systems.
Robots are being put to work across the supply chain, from assembling and inspecting electronics components to picking and heavy lifting in distribution centres.
For example, advanced-technology company Honeywell has found that mobile robots powered by artificial intelligence can dramatically reduce picking times in the warehouse by nearly 50%. And that’s just when they take over the transport tasks of the workflow.
A Deloitte analysis has found that using autonomous robots in the supply chain has the potential to:
- ensure long-term cost savings
- create stability in labour and utilisation
- boost productivity
- decrease errors
- enable fewer inventory checks
- streamline picking, sorting and storing
- improve safety by decreasing access to dangerous areas or performing dangerous tasks on behalf of humans.
To reduce risk and maximise your investment, experts recommend performing smaller-scale tests of robotics before doing a complete rollout. It’s also important to deliver an effective change-management process for existing workers to alleviate fears about potential job losses. Currently, robots are doing the more mundane or dangerous tasks so that people don’t have to.
Data science — AI, machine learning and analytics
As we saw above, data science — which includes AI, machine learning and analytics — can strengthen the effectiveness of other supply chain technologies, such as IoT and robotics.
You can use data science for supply chain forecasting to identify any future problems so that you can take action now to prevent them from occurring. You can even use it to enhance your decision-making. The technology can analyse your data and provide actionable recommendations to streamline and optimise your supply chain.
However, before you invest in data science technologies for your supply chain, you need to consider both your data sources and capture methodology and whether you have enough digital supply chain talent and expertise on your team (to actually interpret, communicate and drive action on any data insights).
Supply Chain Management platforms
The lowest risk, lowest initial investment supply chain tech innovation for most companies would be moving from spreadsheets to a supply chain management platform. Octet’s proprietary supply chain management tool makes tracking, validating and authorising every step of your supplier and customer transactions simple, taking the hassle out of managing your supply chain.
- Save time by centralising supply chain management – get clear visibility across each stage of a transaction and every purchasing document. No more information scattered randomly across email, messaging and paper notes.
- Reduce confusion by eliminating the language barrier – avoid expensive – and potentially relationship-damaging – misunderstandings by easily communicating with your suppliers in their own language using a multilingual supply chain management tool.
- Decrease costs by paying suppliers in up to 15 currencies from multiple funding sources with competitive FX rates. Make payments to 68 countries and close your working capital gap by having up to 120 days to repay us, if you pay using our Trade Finance solution.
Real-world supply chain innovation examples
To get a better understanding of the impact of supply chain technology innovation, let’s take a look at two real-world examples.
Officeworks employing autonomous mobile robots (AMRs)
In their Victorian distribution centre, Officeworks has deployed 86 AMRs and 30 sortation robots. Working with fulfillment team members, the robots are helping with picking from more than 25,000 stock-keeping units (SKUs).
By using robots, the distribution centre’s human employees have been able to spend less time walking around since the robots can take the fastest and most direct route. Previously, the human team walked a startling 10–12 kilometres each shift before employing the robots.
This has enabled Officeworks to have better inventory control and an expanded delivery window for its next-day and express delivery services.
Coca-Cola uses AI and machine learning to enhance supply chain efficiency
To enhance its sourcing and procurement processes, Coca-Cola uses a software platform based on AI and machine learning technology.
The platform allows managers to explore “direct and indirect procurement bid information from suppliers and then analyse multiple awarding scenarios based on those criteria and other constraints”. After analysing the relevant data, including supply chain disruptions and vendor information, the platform provides recommendations.
Coca-Cola has found AI and machine learning instrumental in simplifying its procurement process. For example, at previous procurement events, Coca-Cola staff had to manually cleanse and validate bids from over 200 potential suppliers. Now, they have an automated bid cleansing process.
Unlock your supply chain innovation potential
So, if you’re ready to power innovation in your supply chain, get in touch with the team to find out how we can help.
Disclaimer: The following comments are only our views and should not be construed as advice. You should act using your own information and judgment. Although information has been obtained from and is based upon multiple sources the author believes to be reliable, we do not guarantee its accuracy and it may be incomplete or condensed. All opinions and estimates constitute the author’s own judgment as at the date of publication and are subject to change without notice.