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How to collect enough data to improve supply chain visibility

Posted by Peter Needle

28-Sep-2015 11:00:00

Complex How to collect enough data to improve supply chain visibilitysourcing patterns often mean that a single supplier can affect a whole range of companies. This is particularly true in the case of the garment industry, as complex production lines can create various supply chain visibility challenges.

Here’s how data collection and analysis is transforming manufacturing processes and the retail world more broadly. 

Supply chain visibility can help to protect your brand 

Undeclared allergens can commonly result from errors in product packaging, putting millions of people with known allergies at risk of illness or even death. This was the reason for 95% of all food recalls in the first quarter of 2015. 

SupplyChainBrain recently examined the recall of common ingredient cumin earlier this year. The spice was found to contain undeclared peanut proteins which could trigger serious allergic reactions. Cumin features on the ingredients list of many food products, and this meant that the recall had huge repercussions. This single ingredient quickly spread to 14 companies, 100 brands, 153 products and 769 different sets of packaging. 

So can we learn from this retail disaster? Ultimately, if a single component of a complex supply chain fails to meet set quality standards, it can potentially have a domino effect across multiple tiers. 

The same can be said for products which fail to meet ethical standards. Following the Rana Plaza collapse, investigations by the Clean Clothes Campaign revealed that over 20 retailers were linked to the factory. Many of these companies claimed to be unaware of their connection, or cited unauthorised subcontracting practices. 

Supply chain visibility can help retailers adapt to changing demand 

Retail is a continuously evolving industry, and agility is more important than ever. Shoppers are becoming increasingly expectant of fast, reliable and convenient service, and supply chain visibility benefits any brand trying to achieve this. 

We commonly see supermarkets stocking up on seasonal products, arranging storefront displays of barbeques, ice lollies and sun loungers when a summer heatwave hits the UK. However, retail demand can change suddenly across various sectors without any predictable pattern. Thanks to the rise of fast fashion, garment retailers are expected to respond to changing consumer demands on a daily basis, and this requires them to strike a fine balance. 

If too many fast fashion items are produced, it’s likely many will fail to sell or will have their sale price reduced, cutting into the retailer’s profits. However, retailers can also lose out on revenue if a popular design instantly sells out. In order to place the perfect amount of orders, retailers must continually monitor and manage their inventory. This requires a high level of visibility in the supply chain, as companies must keep track of current stock levels and incoming purchase orders. 

However, the potential rewards are huge for any retailer which achieves this. If a brand can accurately predict the demand for certain products, consumers will become loyal fans. 

Segura supports the process revolution 

Accenture argue that we are due to see “a process revolution” within the next five to seven years, as digital platforms and technologies totally transform the procurement process. Procurement will soon operate at radically lower cost, involve far lower levels of risk and drive significantly more strategic value. In short, technology may radically change the layout of many supply chains. 

Segura’s cloud-based software makes it simple to take control of complex secondary supply chains. Orders are placed within a framework of approved suppliers, and an online audit trail is built to reveal the entire sourcing process, step by step. If any orders are fulfilled by unauthorised parties, real time alerts give users an opportunity to address the issue before a disaster arises.

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Topics: supply chain transparency