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Analytics in Modern Supply CHain Taking Center Stage

Supply Chain Analytics


This is a guest blog from our friend Adam Robinson at Cerasis. In this post, Adam outlines a few important things that need to be understood about analytics in the modern supply chain in order to ensure business success.


Analytics has been a buzzword in recent years. Everyone seems to be clamoring to get on the big data and analytics train. Part of this drive toward more interest in analytics in distribution and manufacturing comes from the ability of analytics to reduce inefficiencies dramatically and increase productivity in both physical and virtual sales environments.

Furthermore, analytics are becoming more widely available through the cloud, and manufacturers and distributors of any size can reap significant benefits from implementing analytics in their operation, explains Eric Smith of Modern Distribution Management. To guarantee your business’s success in the modern supply chain, you need to understand a few things about analytics in distribution and manufacturing.


How Are Analytics in Distribution and Manufacturing Being Used?

Analytics can improve upon any process in distribution and manufacturing. According to McKinsey & Company, analytics fill the gap between efficiency improvements from lean systems and the next stage in the future supply chain. For example, operations managers may use advanced analytics to analyze historical data of prices for raw materials, identify trends in raw material availability and accommodate changes to make the most efficient use of these resources.

Imagine the scenario mentioned above applied to the forecasting process. Manufacturers could increase or decrease production to meet trends within varying markets and customer bases. Meanwhile, distributors could reorganize and optimize their fleets, picking processes and billing capabilities to adjust to fluctuations within the forecast. As a result, the entire supply chain becomes more efficient and capable of predicting the future with near-clairvoyant accuracy.


How Are Analytics Evolving Within the Supply Chain?

Analytics in manufacturing and distribution are also evolving both dependently and independently of analytics in other industries. Within the logistics and manufacturing industry, more data collection points are being created on a daily basis than ever before. In fact, the final product may collect some of this data.

For example, Samsung’s revolutionary Family Hub Refrigerator can communicate to the manufacturer if it is working correctly, what its temperature is and how it can be improved in real time. As a result, the research and design process is becoming simpler and more driven by the use of analytics and cloud-computing technologies.

But, this refrigerator is not merely just providing the manufacturers with information; it’s giving families a new way to manage their personal inventory of groceries and creating automated shopping lists within Samsung-affiliated apps, which can then be accessed by the Internet of Things (IoT) to define further trends and correlations that are used in calculating and creating accurate forecasts. Ultimately, this example of a typical household appliance exemplifies how analytics in distribution and manufacturing are evolving beyond the constraints of imagination and impacting the global supply chain.


How Do Analytics in Distribution and Manufacturing Benefit and Augment Supply Chain Processes?

Analytics are not necessarily exclusive to efficiency improvements in the supply chain. Advanced, predictive systems are being used to enact cultural changes within the supply chain as well, explains Thomas P. Gale of Modern Distribution Management. Predictive analytics are being used across social media and millions of connected devices through granted user permissions, and the findings from these analyses are being used to ensure companies’ goals align with the expectations and needs of their consumers. As a result, the modern supply chain is benefiting by reducing the divide between corporate and consumer values. More importantly, this goes back to inventory management and making wise decisions for the use of all resources involved in the supply chain, which ranges from truckers to auditors and beyond.

E-commerce is another major benefactor of the “Analytics Revolution.” Analytics systems practically govern e-commerce. For example, a given retailer needs to understand where traffic to the company’s site derives from, which can position the company to generate leads and close sales better. Meanwhile, e-commerce allows retailers to go beyond the physical boundaries between isolated and connected markets, enhancing the overall flow of goods in both directions, and this not just sales and returns being moved. It represents a flow of materials and ideas from consumers toward the company, which can be used to create new products and define the competitive value of their goods or services.

E-commerce will go further as it becomes agiler and capable of handling complex changes within the online retail environment. As the website accepts and processes orders, order fulfillment requests are automatically generated at the appropriate centralized or regionalized distribution center. In other cases, the order may be processed at the nearest local store, eliminating shipping costs and reducing delays to the Amazonesque delivery capabilities.


Wrapping It All Up.

Analytics are radicalizing the manufacturing and distribution landscape. Truckers are faced with more constraints on their schedules, and electronic logging devices are tracking their movements to ensure adherence to government standards. In many ways, analytics and modern technologies are taking control of the whole supply chain to create a more prosperous future. Of course, some human input is necessary, but with cloud computing and other technologies doing the thinking and analyzing, the only real decision left is selecting the best solution derived from the careful analysis of endless streams of data.

If that doesn’t seem like enough for analytics in distribution and manufacturing to take center stage, consider this: 56 KPBS was the standard Internet speed of 2000. After 16 years, Internet speeds have soared beyond 4 GPS, representing an increase in data processing capacity of nearly 80,000 percent, so within the two decades, data collection and processing capacity for analytics could realistically surpass an Exabyte (1 billion gigabytes) per second.


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