Agile Supply Chain VS Efficient Supply Chain

Agile Supply Chain Advanced Analytics QAD DynaSys


The ideal strategy to survive and prosper in a dynamic environment is to have an agile behavior that is conducive to change. This is true for everyone, and supply chains are no exception. An agile supply chain requires the ability to rapidly identify, evaluate and execute alternative supply chains scenarios. However, being agile contradicts what many practitioners have been taught over the past decades. Supply chain experts have traditionally focused on efficiency and consequently pursued the lowest unit cost dream. By utilizing optimization techniques, we have sought to minimize procurement costs absorbing larger order quantities and longer lead-times; we plan for longer manufacturing runs to drive a higher return on assets and full-container load land and marine freight to reduce transportation unit costs.

Agile supply chains exist almost as the antithesis of efficient supply chains. Agility implies the ability to detect, analyze and execute the best possible business decision regardless of traditional sources of supply and demand. An agile supply chain requires an end-to-end visibility, actionable insights, analytical decision support, and of course, the decision execution.


Today’s businesses are experiencing exponential growth in volumes of available data, way more than a human being can actually process. However, the challenges of today’s data are greater; not all of the data is structured and a large amount is unstructured, not all of the data is relevant, and not all of the data is decision grade quality. Data is changing in real-time and the volume keeps increasing. 

In addition, there are unprecedented expectations of the problems the data can help solve; there are insightful sales trends to identify, predictions to make, outliers to examine, exceptions to initiate action, and no end to these types of critical questions in supply chain planning. 

A key challenge in supply chain practice is how to provide supply chain visibility while not omitting a decision influencing data point. When adopting a supply chain visibility strategy, it is important not to “save the world;” do not take on everything that is possible. A good litmus test for data inclusion is the customer service criterion, “Can this data help serve my customer better?” This enables the company to leverage its data assets to the value of the customer. 

However, even if sufficient data visibility can be provided across the supply chain, how does this support rapid insightful decision making? Numbers are not enough; it is the meaning of the numbers that must be understood. It is critical to ask the right questions of the data; only then can intelligent analytics identify trends and correlation to drive prescriptive actions.

Modern analytical technology is capable of digesting millions of data points capturing outliers, trends, and step-changes; only some of this will result in actionable insights. 

Actionable insights must be profiled and triaged. If everything is important, then nothing is important. Actionable insights may be operational (expedite replenishment as a stockout is predicted within the frozen horizon), tactical (adjust supply parameters as average actual lead-time is excessive), or strategic in nature (expedite product launch to cover demand shortfall).

Strong advanced analytics and end-to-end stakeholder collaboration are the basis of modern supply chain planning technology. As digitalization continues to disrupt, supply chain technology must be hyper-connected, highly automated, and produce actionable business insights that promote the value of the enterprise and ensure business continuity.

Advanced analytics technologies help companies to evolve from the theoretical “Efficient Supply Chain” strategy and reach the agility they will need to face their future challenges.

To learn more about Advanced Analytics for Supply Chain, please read our complete white paper.