How digital technologies are delivering a competitive edge in the intelligent supply chain

In an age of heightened demand and greater consumer awareness, there is a growing need for brands to use innovative methods to reach targets, adopt sustainable habits and create a safer, more secure environment for workers.

For supply chain managers, the increasing availability of AI and Machine Learning technology has created new opportunities to help optimise the production-to-distribution process.

Read on below to discover some of the ways global brands are revolutionising their operations through new technologies.

A changing landscape

The desire for innovation in supply chain solutions is nothing new. From automation in production to picking and tracking tools, businesses are continuously seeking new ways to streamline and enhance their production to distribution process.

However, increases in consumer demand and the need to economise in order to combat competitors are leading to new, smarter, more efficient methods of optimising the supply chain.

Additionally, the heightened narrative around climate change and ethical practices is playing a key role in new technology and supply chain innovation.

Government regulations – married with an increase in consumer awareness of the environmental impact that brands have – are pushing businesses to accelerate their adoption of sustainable innovations.

For many in the supply chain space, a lack of real-time data is seen as a significant barrier to success.

A recent Capgemini survey cited 83% of supply chain managers as experiencing a range of inefficiencies, from poor end-to-end visibility and slow responses to unforeseen issues, to disorganised data and heightened costs.

Now, a reported 78% of organisations are implementing AI and machine learning tools to their operations to help mitigate these issues.

Digitised methods of easing employees’ workload are set to increase from 2020.

With Information Technology Intelligence Consulting reporting that an hour of unforeseen downtime can cost businesses as much as $100,000, it’s no wonder predictive analytics is expected to become more widespread.

Using IoT technology, predictive analytics helps companies to assess machine failures and inefficiencies as well as identify possible solutions and ways to streamline the process.

The net result would be a reduction in the time employees have to spend on troubleshooting or admin-based tasks.

When it comes to using AI to revolutionise supply chain operations, the development of self-driving vehicles will likely only continue to increase in the coming years.

Some retailers are almost exclusively using autonomous technology in consumer-facing parts of the chain like last-mile delivery, others want to use the technology to connect stores and warehouses.

It’s not just data that’s changing the way people work. Safeguarding workers – in particular factory operators – and providing safe and secure production environments is becoming increasingly important to consumers and company executives alike.

Hyundai Motor Group has recently developed an exoskeletal vest for factory workers in order to improve safety and comfort in factory environments. The vest (Vest EXoskeleton, or VEX) was designed for workers spending long hours in overhead operations, and aims to cut fatigue and enhance performability in the physically demanding role.

A step in the right direction

When it comes to consumers, more and more are making decisions based on the ethical or sustainable policies and practices of a brand.

Consumers have spoken out against the impact of cheap and unsustainable fashion on water use, emissions and air pollution. Now, designer brand Stella McCartney has partnered with Google to help reduce its environmental impact.

Using Cloud-based analytics and Machine Learning, the partnership is developing new supply chain tools.

These will assess current and pre-existing data held on Stella McCartney’s supply chain processes in order to identify areas for improvement, and help develop a strategy to minimise the negative effects of production.

If successful, Google aims to roll out these tools for use with other clothing and consumer-centric brands.

With 66% of consumers saying they’d consider paying more for products from sustainable companies, the brand value of sustainability is only set to increase.

Whether its Machine Learning tools to analyse and help reduce negative effects of production, or sourcing recyclable or renewable materials, the call to revolutionise operations has never been greater.

Unipart is currently working with a wide range of customers to explore new ways in which digital technologies can provide detailed analytics and automate processes and physical environments to make operations easier for employees and more efficient for customers. To learn more contact, email katy.farrington@unipart.com