Building Trust in Your Manufacturing Ecosystem

Building Trust in Your Manufacturing Ecosystem

Gibu Mathew, Zoho Corporation’s VP and GM for Asia Pacific, discusses how digitisation is enabling manufacturing companies to evolve their traditional linear supply chains.

Credit: Mixabest / CC BY-SA

Global manufacturing supply chains today are designed to save costs by moving the manufacturing process to the most efficient locations and minimising the inventory held at final assembly or distribution points.

As the manufacturing process becomes increasingly complex, digitisation is enabling organisations to evolve traditional linear supply chains into interconnected digital supply networks (DSNs) that are responsive, adaptive, and driven by data flowing through the ecosystem.


This level of complexity requires organisations to become more agile, analysing the data aggregated at multiple points across the supply chain to create more accurate models that will better predict and respond to demand. 

Without this level of visibility into supply and production, organisations will find it difficult to meet demands for more individualised products and services.

To successfully handle these demands, manufacturers should consider deploying an inventory management solution that serves as a central repository for all relevant data exchanged between headquarters and all manufacturing units.

When all the data the business needs to manage its supply chain is centralised, each department is able to access the same source of information. 

When all parties trust the accuracy of the data, collaboration becomes second nature and the organisation can make decisions with confidence, in real time.

The global asset tracking and inventory management solutions market is expected to grow almost 13 percent between 2018 and 2026, largely driven by industries present in the Asia-Pacific market. 

Such systems automate tasks that are too complex to be handled manually, and provide tracking to reduce the risks of over- or under-stocking, unmet customer expectations, and losses from theft and spoilage. 

These systems also derive insights from the aggregated data that will help drive down cost, improve efficiency and anticipate market trends.

Inventory management solutions should include modules for areas such as product bundling, RFID and barcode scanning, multi-warehouse management, packaging and shipment and tracking. 

Each module aggregates data, which must be shared and integrated to be of value. The real-time availability of critical information helps address multiple inventory management issues, such as:

  • Demand forecasting: Access to point of sale (POS) data through a shared documentation system can address a potential out-of-stock situation before it happens.
  • Order batching: Different stages along the supply chain can contribute to larger, less frequent orders to reduce costs. A centralised documentation system, in which each supply chain member can update order quantity periodically and notify upstream members, solves this problem.
  • Lead time: Longer lead times mean retailers and wholesalers order a greater quantity than required to maintain a safety stock while waiting for orders to arrive. A seamless system for information exchange between all departments drastically reduces lead time.


Why does it matter?

A proper system for the timely exchange of information enables organisations to provide real-time updates, which can build trust and transparency in customer relationships. 

These systems also help organisations to track and trace suppliers, improving overall relations with this important stakeholder group. 

Suppliers should also be provided with dedicated portals, so they can stay updated on the demand-supply gap and plan for future requirements. 

The single, master database will allow the easy management of supplier onboarding details, spending, and contracts.


Artificial Intelligence In Inventory Management

It is worth noting that the increasing use of AI in various aspects of doing business is also seen in inventory management and in the overall manufacturing process. 

As an example, artificial intelligence can help workers make faster decisions on identifying the right package to use based on the dimensions of the shipment. 

This in turn can ensure optimum use of resources and materials and increase the trust quotient in the manufacturing and inventory management ecosystem.

Additionally, capturing data at the source and tracking throughout a product’s journey creates a verifiable audit trail – increasingly seen by consumers as an important factor in their purchase decisions. 

Organisations that lack such a system risk losing business and market share if preferred products are not available, as customers are not as loyal to products as in previous decades.

An inventory management system that integrates data from every node on the supply chain will ensure the reliability of the manufacturing ecosystem, creating efficiency, saving cost and meeting – or exceeding – customers’ expectations.








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