Timing is everything. Yes, it is so cliché to say such a thing.
However, the ability to control every detail of timing – particularly in the world of international supply chain logistics – truly defines the difference between success and failure. As Woody Allen famously said, “Ninety percent of life is showing up.” In the dynamic, fast-moving logistics industry, one might add “…showing up on time.”
Engineering control of risk through the dynamic, unpredictable supply chain challenges from producer or manufacturer to consumer is not rocket science. Unpredictability is not an unresolvable problem and twists and turns in the dynamics of getting product to market can be anticipated. What is required is risk prediction, not just risk analysis. Not so long ago, this would have been a daunting task. Goods were packed into a container, locked and sealed, and dispatched on a ship or airplane with hundreds of other containers. Email updates kept one abreast of status but this hardly had any predictive value. If there was an unavoidable delay, knowledge of it was received well after the fact.
Advances in so-called “big data” [also called the “internet of things”] are changing this situation. Threats to the supply chain such as natural disasters or extreme weather conditions, labor slowdowns or strikes, political unrest, equipment or capacity breakdown, may still be inevitable but they do not have to be unavoidable. There are tools available to supply chain professionals that can keep their companies ahead of the risk curve, for whatever contingency man or nature might throw their way.
For companies that seek to re-engineer their logistics chain, an intelligence-driven, risk based proposition – it is important to first establish an operations risk baseline. This entails an assessment that clearly defines the supply chain’s current state, its vulnerabilities, its strengths, and existing linkages. Every element of the process is exhaustively examined to determine what kinds of threats might exist or arise, what weakness exist, and current procedures or measures to address those vulnerabilities. Once a risk baseline is established, then – and only then – are relevant data streams identified, classified, contextualized, and meshed with existing logistical processes. These data streams generally include items regarding the shipment itself, the logistic elements, routes, and contextual elements such as weather data, geopolitical developments, and other factors. Without a clearly defined baseline, these otherwise valuable data streams lead to confusion, conflicting priorities, and muddled outputs.
While harnessing the power of data itself is good, it is not enough. It is crucial to have a tool that filters the “noise” and distills the raw data streams into timely, actionable information. Developing a risk baseline allows the further design of rule-sets and scenario-based threat and vulnerability models from which data can be associated with the vulnerable links in the supply chain. For instance, this can be the route itself, inter-modal transfer, transportation or port of call. As potential threats to the supply chain’s continuity or “resiliency” increase, alerts are generated to provide advance notification to logistics planners. Route plans can be diverted, alternative suppliers selected, shipments transferred, sped up or expedited to mitigate the risks along the way. Insuring risk is certainly one way of transferring it, should an act of God put your containers at the bottom of the sea. However, anticipating and thwarting the risk through advance notification puts control back into the hands of logistics professionals and just might keep your container above water and on-time.