Riskpulse: Optimize the Supply Chain

Optimize The Supply Chain, Gain a Competitive Advantage

We are always hearing about various risks to the supply chain and how risk can cause so much damage if not appropriately addressed. That “if,” however, introduces hope: the opportunity to actually do something about that risk. While not all risks are completely preventable, emerging technology is enabling organizations to at least predict them with greater accuracy and much earlier in the planning process. Instead of looking at the glass half empty, companies are recognizing they have more control than they think. They can optimize the supply chain to not only lessen many of their risk factors but actually improve their competitive advantage.

Moving from Traditional Planning to Dynamic Planning

The problem with many traditional supply chain risk solutions is they can only identify risks when the shipments are already in transit. If they can see risks earlier in the workflow, before the shipment leaves the dock, they can make wiser decisions that can save costs, shipments, and reputations. For instance, if a significant freeze is expected along a planned rail shipment, the shipper or carrier can decide to modify the mode of transportation from rail to truck, avoiding freezing rails for the more reliable trucking mode.

On the opposite end of the spectrum, companies can protect cargo from expected heat waves. Knowing the temperature may rise above safe levels for sensitive cargo, they can opt for a reefer truck instead. Without this reliable, predictive data, companies would not know of these temperature fluctuations until the unrefrigerated truck is already enroute. Conversely, why go the the expense of a reefer, if the temperatures are going to be cooler than the seasonal norm and within the tolerance of the load?

In order to optimize the supply chain, companies must shift from traditional planning to dynamic planning. They must be agile and responsive to change. They should be able to make quick but confident decisions that are backed by timely, accurate data. They need the flexibility to alter schedules, routes and modes at any point to ensure more on-time, in-full deliveries, a top priority for supply chains, according to Supply Chain Dive. They must also be able to protect facilities and provide an overall better awareness of risk.

Related: OTIF Programs: What You Need to Know to Nail On-Time In-Full Performance Metrics

Advanced Technology for an Optimized Supply Chain

The supply chain involves manufacturing and distribution facilities as much as it does the shipping and delivery links on the supply chain. There are so many things that can go wrong anywhere along the supply chain and many of those disruptions are still unknowns for many organizations.

The most basic requirement to reduce supply chain risk is to make the supply chain more predictable. Unpredictability increases uncertainty, costs, risks and repercussions. Organizations can greatly reduce costs by optimizing their operational planning and performance. When there is true insight into the at-risk shipments, companies can make proactive decisions faster. This capability begs for technology. Many organizations are investing in an actionable, predictive analytics solution for the whole supply chain using advanced machine learning techniques.

Manually searching through data to find the status of individual shipments is unreliable and dependent on external parties providing much of that data. It is difficult to get the status from all of the carriers and modes at one time. With risk factors constantly changing, it’s nearly impossible to see the entire picture of what is really going on now, let alone what risks may be a threat somewhere down the line. By then, it’s too late to make changes to avoid those risks.

Companies must be able to look at all of their shipments simultaneously across all modes, lanes and facilities at once. With Riskpulse, they can. Riskpulse continually assesses risks across multiple factors, then predictive analytics provide dependable insight into what is likely to happen up to 15 days in advance. Because change happens so rapidly, companies have to be able to make changes on the fly. With a technology-enabled solution that optimizes the entire supply chain, organizations can do that quickly and with confidence.

Going Beyond Risk Identification to Risk Mitigation

The easier the risks are to see and understand, the faster decisions can be made. It’s not enough to just identify the risks. Yes, knowing the risks is a valuable and necessary step, but it is but one step in the journey. Organizations must be able to then decipher which risks present the most immediate dangers so those risks can be prioritized and avoided. The other risks don’t necessarily fall off of the radar, rather, they are duly noted and continually monitored while the higher-risk issues are addressed. This lightens the load on thinly-stretched resources and ensures the right risks are the main focus at the right time.

Because each risk factor has its own level of importance, there needs to be a way to communicate those differences in a way that is easily understood. Companies shouldn’t have to spend time figuring out the data. The data should be operationalized for them so they can rapidly make those decisions. Gartner agrees, saying organizations “must move data science out of the ivory tower and into the real world.”

Related: Leveraging Intelligent Automation in Logistics

How does this play out for a company with logistics concerns? An established common language, one that anyone can understand and use to inform decisions, takes complicated data and boils it down to describe the severity of risk in context to other locations, shipments, or facilities. Converting disparate risks into scores is an effective solution. For instance, a forecast of snow in Minneapolis will have a different risk score than a forecast of snow in a southern city like Houston. Decision makers can see those scores and instantly know where to direct their efforts.

Optimizing the supply chain means making the data usable while also ensuring the right people have that data. A comprehensive supply chain risk management solution may offer risk alerts that notify specific stakeholders of predicted, measurable threats well enough in advance as to enable swift reaction. When risk scores hit a certain threshold, for instance, organizations should receive automatic risk alerts so they can make changes, call other supply chain stakeholders to notify them of the risks, or contact their customer to inform them of the issue.

For the most efficient and effective remediation, the risk management solution should easily integrate with an existing Transportation Management System (TMS). This integration will enable organizations to combine risk data with their existing planning system for faster, more automated responses.

How to Tell If Your Supply Chain Is Optimized

Assessing whether your supply chain is optimized, isn’t as simple as knowing whether your organization is meeting delivery windows and avoiding the emerging penalties that are tied to on-time, in-full delivery performance. It involves understanding how well you are addressing all of the risks that impact the entire supply chain. One recent study concluded there are seven individual indicators that should be considered as acceptable metrics:

  • Cost
  • Product quality
  • Flexibility to fill customers’ demands
  • Customer satisfaction
  • Order fill capacity
  • Delivery speed
  • Delivery dependability and consistency

Investing in an automated, intelligent supply chain risk management solution is the only way to keep pace with the rapidly changing logistics ecosystem. If your current technology and techniques don’t allow for dynamic planning and don’t enable comprehensive, automated risk identification and analysis, you’re operating with one hand against your back. Predictive machine learning is quickly becoming the standard. As more companies transition to solutions that utilize this capability to optimize the supply chain, those who fall behind will likely find themselves at a competitive disadvantage.

These metrics include financial and non-financial, operational, tactical and strategic level and other members of the supply chain. Every one of these metrics can be impacted by weather, temperature fluctuations, environmental events, infrastructure issues, and even social unrest. Therefore, it is critical to have real-time data that brings all of those risks to light, early enough in the planning process to make decisions that can reduce costs, ensure product quality, fulfill customers’ changing demands, maintain or improve customer satisfaction, maintain facility operations to fill orders, deliver products on time and in full.

Investing in an automated, intelligent supply chain risk management solution is the only way to keep pace with the rapidly changing logistics ecosystem. If your current technology and techniques don’t allow for dynamic planning and don’t enable comprehensive, automated risk identification and analysis, you’re operating with one hand against your back. Predictive machine learning is quickly becoming the standard. As more companies transition to solutions that utilize this capability to optimize the supply chain, those who fall behind will likely find themselves at a competitive disadvantage.

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