Digital transformation is inevitable, and digital transformation within the supply chain has the potential to streamline operations, reduce costs, and offer a better work environment for employees. The result is improved customer service, but the real implications of supply chain analytics go much further. The proper use of supply chain analytics is crucial to digital transformation and ensuring the ability to compete with Amazon, especially as new services and capabilities make interacting with Amazon more lifelike. Those interested in putting the power of supply chain analytics to work need to understand how they affect the digital transformation of your organization.
The difficulties of implementing supply chain analytics reflect many of the challenges of digital transformation in any industry. People may not want to make the changes necessary to use analytics, and for supply chain leaders, the cost of inaction can be steep. To overcome the challenges, your organization needs to understand the top obstacles that you will face in digital transformation. These include:
The defining factor between traditional supply chains and those focused on a digital future is data. The ability to collect, use, and apply data sets supply chain leaders apart from followers, and it is the process for empowering supply chain leaders with the insights and information necessary to make informed decisions. Moreover, the use of supply chain analytics can help workers improve productivity, reduce nervousness, find new ways to add value to your supply chain, optimize warehouse layout, and much more, explains Kevin McGirl of Supply Chain Management Review.
Implementing supply chain analytics in your warehouse and throughout your supply chain network represents a significant challenge. Poor planning in the process could result in lost opportunities to connect systems and assets to the overarching analytics system, and an opportunity for data loss will naturally increase risks to your organization. Instead of putting your business at risk, follow these best practices to implement supply chain analytics successfully:
Digital transformation is inevitable, and supply chain leaders that understand the digital transformation of supply chain management can successfully leverage new systems and take advantage of innovative technologies. As the power of data analytics increases, integration will play a more significant role in ensuring data accuracy and valuable insights.
The digital business landscape for a shipper, such as the use of an ERP, TMS, and other digital aspects, such as The Internet of Things, provides unparalleled insight into how an organization in the supply chain can improve efficiency, visibility, and productivity. Through the use of connected devices and greater abilities to capture data in real time, the concept of end-to-end visibility and improvement thru the use of supply chain analytics has changed.
As explained by Bruce Tompkins, improving the supply chain includes improving service levels through better inventory management, reducing operating costs, reducing order-cycle time, achieving 100-percent accuracy, improving supply chain security and control, and improving flexibility. As the supply chain grows increasingly focused on meeting the demands of an increasingly data-driven and customizable world for consumers and business to business partners, the need for continual improvement and better visibility will continue to drive analysis of available supply chain analytics.
The availability of supply chain analytics of a given organization is defined by how well the organization is able to monitor and control processes and make changes to such processes with an informed decision-making process. This is a critical component of seeking improvement in the supply chain, and benchmarking enables a supply chain entity to assess the current condition of such technologies and applications to improve the overall supply chain. Consequently, more data equates to more analysis and insight, which can then be used to create and implement new solutions to existing problems and issues in visibility and capability, explains McKinsey and Company.
Certain parts of the cold supply chain, such as those involved in processing and shipping poultry, fruits, vegetables, or other meat products, have an inherent duty in ensuring the safety and timely delivery of these goods to the appropriate retailer or party. Failure to do so could result in the assessment of fines and penalties against the organization by the Food and Drug Administration.
Currently, up to 33 percent of all perishable products are thrown away before reaching the consumer due to spoilage, explains Lora Cecere. For retailers and grocery stores alike, the spoilage represents an increased cost to the company. The affected store then it has to receive a refund on previously purchased goods or replacement goods and products from the existing supplier or supply chain.
Ultimately, this represents an added cost to the supply chain for failing to maintain the freshness and quality of the goods. As explained by Supply and Demand Chain Executive magazine, one of the primary ways an organization can meet this demand is by setting a performance review for suppliers. Such reviews rely on key performance indicators and metrics to determine what step of the distribution center-to-retailer route experienced an unnecessary delay, causing the given item to perish. In other words, was the temperature in the shipping container too high, were products left on a loading dock for extended periods or did the supplier accidentally contaminate the given product with another product in the same shipment without realizing it?
For example, a shipment of fresh, not thawed chicken should not be shipped at the same time, in the same container as a shipment of fresh fruits and vegetables, due to potential Salmonella cross-contamination.
Manufacturers must look at trends found in supply chain analytics over time as well as “aggregate and average related issues, non-conformance, late deliveries, and quality problems.” This information can then be used during the periodic supplier review to determine if the supplier is underperforming. In the past, the use of this table would have been applied in a backward-looking approach. After all, a given distributor cannot evaluate a supplier without being able to see how that supplier has performed in terms of the specific metrics. However, the Internet of Things and big data supply chain analytics are allowing manufacturers to monitor performance in near real-time. In other words, this real-time data allows for the manufacturer to immediately identify when a supplier encounters multiple issues within a given time frame as they occur.
For example, a shipment of potentially perishable or time-sensitive goods is delayed for 2.5 hours at Port A, which triggers an automatic performance alert on an interactive performance dashboard for the given distribution, enabling the distribution center to reach back to the supplier and determine if the product can still be safely moved. As a result, the supplier can either delay the shipment of the product, cancel the transaction, or replace the product with an appropriate product before incurring the cost of shipping an inappropriate, potentially hazardous product to the consumer.
The driver shortage, albeit potentially corrected in coming years through autonomous vehicles (driverless cars and trucks) is continuing to grow worse. Furthermore, FedEx and UPS are planning on increasing the general rate by 4.9%, and fuel surcharges are expected to rise, even though gas prices have reached a 10-year low, explains PLS Logistics. Since these issues are occurring today, the need to address the potential problems is right now, not several months down the road when a performance review takes place. Essentially, manufacturers need to work harder on improving real-time inventory management, making data from across an organization available to all parties in the organization, improving collaborative relationships, and working towards sustainability measures, especially since the EPA is set to become more stringent on pollution standards within the transportation industry in 2016, explains Salient Management Company.
Data analysis of supply chain analytics is a buzzword in the supply chain, but it has been around for a few years. Suppliers have grown tired of hearing this word, and many believe existing data analytic capabilities are meeting their demands. However, the overwhelming majority of supply chain executives, 64 percent, are actively seeking and view data analysis as a top priority for their respective organizations. Ultimately, the supply chain must work with a finite amount of resources, and a renewed, if not new, focus on data analysis will allow the supply chain to meet the demands of a modern economy and customer base.
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