High data quality key to reducing supply chain disruption | 7wData

• Read original article here

Those in the Supply chain discipline have always known how much is at stake in logistics management, but the problem has really entered the public consciousness over the last few years. Especially in the UK, where uncertainty has gone from bad to worse because of the triple whammy from Brexit, the pandemic, and political and economic crises. In 2021, a Gartner survey found that 76% of supply chain executives thought they faced more disruptions to the supply chain than three years ago. 

Big data has sprung up as a possible solution to many of the problems the supply chain faces, and a way to make the process more efficient. However, although the potential is there, the answer isn’t necessarily as simple as “using big data” – companies using software also need to be conscious of how big data works and how to use it properly.

It is fair to say the UK supply chain has faced challenge after challenge in recent years. The first came with the 2016 decision to leave the European Union, which had the government scrambling to find a new way to trade with the European market – and companies scrambling to pick up the pieces.

Then came the Covid-19 pandemic, which caused all kinds of material shortages – for instance, the construction industry saw its stock levels change by up to 5% each quarter. Semiconductors and motors were also affected. These problems were compounded further by geopolitical issues, which resulted in energy shortages and uncertainty.

“Supply chains have risen to a top three position on board agendas,” says Iain Prince, a partner and UK supply chain lead at KPMG. 

This comes on top of the usual challenges of the UK landscape. “UK companies rely more heavily than other countries on items produced abroad,” says Doug Laney, an innovation fellow in data and analytics strategy at West Monroe. “This means supply chain visibility, and predictability is ever more critical.”

With so many obstacles to overcome, the supply chain needs a saviour – and many experts are pointing to big data to fill the role. Prince believes data will become more important in this new era. He says that after Brexit, “there is uniquely new importance placed on master data, given the customs and other regulatory impacts of moving goods between the two markets”. Also, the greater risks posed in global trade and the need to be resilient mean that the predictive capabilities of data could be crucial. So, what exactly are the problems that big data can solve? According to a special report from Thomson Reuters, the biggest factors are traceability (knowing where goods are), predicting potential problems, having plans in place to address these issues, and carrying out customer service.  Big data can also tackle tasks such as: Big data can become even more powerful when combined with other new technologies, such as artificial intelligence (AI) and the internet of things (IoT). AI can crunch data to manage operations or make predictions about how the supply chain will react to different scenarios, while IoT makes it possible to access high-quality, real-time data using sensors – for instance, to oversee inventory. A 2020 study from Oxford Economics found that 49% of supply chain leaders can capture real-time insights from data, and the other 51% use AI and predictive analytics to do the task. Combined, these innovations are sometimes known as “Supply Chain 4.0” – and they are already having a huge impact on many organisations.

One Fortune 500 company partnered with software and analytics company N-iX to help manage data related to its supply chains, especially regarding inventory costs. The business wanted to extend its existing system to collect data from departments undergoing expansion, while migrating everything to the cloud for more scalability. It also integrated more than 100 different sources of data into one platform, including historical and future information.