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5 Ways Analytics Are Disrupting Supply Chain Management

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5 Ways Analytics Are Disrupting Supply Chain Management

5 Ways Analytics Are Disrupting Supply Chain Management

Harmonizing supply chain management analytics will put organizations on a path to automating their operations.

The evolution of infotech increased customer expectations, economic behavior, and other competitive priorities have caused firms to modify themselves in the current business landscape. Supply chains globally are becoming more complex, thanks to globalization and the consistently changing dynamics of demand and supply. As per a forecast by Gartner, the global supply chain management market was valued at USD 15.85 billion in 2020 and is expected to reach almost USD 31 billion by 2026.

Businesses are channeling the power of big data analytics to disrupt transformations at all levels of supply chain management. Data started as a fundamental component of digital transformation and is now a revolutionary concept. It is the key to achieving breakthroughs in supply chain management systems, and more organizations are integrating data analytics to mine data for proactive insights and accelerate intelligent decision-making.

Big data implementation in supply chain management addresses several issues, from strategic to operational to tactical. It includes everything from building efficient communication between suppliers and manufacturers to boosting delivery times. Decision-makers can utilize analytics reports to increase operational efficiency and boost productivity by closely monitoring the system’s performance at each level.

What is Big Supply Chain Analytics, and How Does it Work?

Integrating big data analytics with the supply chain makes big supply chain analytics enable business executives to compute better growth decisions for all possible maneuvers by combining data and quantitative methodologies. Notably, it adds two features.

First, it broadens the dataset for analysis beyond internal data stored in existing SCM and ERP systems. Second, it uses advanced statistical techniques to analyze the new and existing data. This generates new insights that help make better decisions for improving front-line operations and strategic decisions like implementing the best supply chain models.

Here are five ways big data and analytics are disrupting supply chain management:

1) Improved demand forecasting

Demand forecasting is one of the crucial steps in building a successful supply chain strategy. With data science and analytics in play, businesses experience automated demand forecasting. This assists them in quickly responding to fluctuations in the market and streamlining the optimal stock levels every time.

2) Enhanced production efficiency

Data science and analytics play a significant role in gauging organizational performance. Accurate application of big data analytics can help organizations track, analyze, and share employee performance metrics in real time. You can identify excellent employees who are struggling to maintain a consistent performance. This could be quickly done with IoT-enabled work badges, which exchange information with sensors installed in production line units.

3) Better sourcing and supplier management

Supply chain management systems have empowered organizations to collate data on multiple suppliers. Using data science solutions, you can leverage this data to gain insights into the historical record of any supplier. With this, you can gauge based on crucial metrics such as compliance, location, reviews, feedback, services, etc.

4) Better warehouse management

Warehouses are acquiring modern technology and have started installing sensors to collect data on the inventory flow. This helps you build an extensive database containing information based on the weight and dimensions of the packages. With sensors installed in your warehouse, you can identify bottlenecks that obstruct the flow and can be easily resolved at the earliest with the big data-fueled systems.

5) Improved distribution and logistics

Order fulfillment and traceability are essential for business productivity and customer satisfaction. Logistics have traditionally been cost-focused and effectively look for ways that provide them competitive advantages. Data science solutions enable logistic providers to leverage data analytics to improve their operations. For instance, they use fuel consumption analytics to improve driving efficiency. With GPS technology, they can track real-time routing of deliveries and reduce long waiting times by allocating nearby warehouses.

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What’s the Next Phase of Supply Chain Evolution?

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What’s the Next Phase of Supply Chain Evolution?

What’s the Next Phase of Supply Chain Evolution?

The reworking of supply chains has a simple purpose of fitting the new world economy’s needs and demands. And freight data sharing platforms had already started before the mess of 2020 began. Additionally, the shift towards digital media and reinvented processes of global supply chains continues still today. Supply chain evolution is highly focused on market sub-segments, especially on those within the middle class. According to Supply Chain Management Review, “this matters a lot in a world where the population of middle-class consumers will reach 5.5 billion or over 60% of world population by 2030—a phenomenal growth from 1 billion middle-class people comprising 20% of world population in 1985. Middle-class consumption will soon comprise one-third of global GDP. Five-and-a-half times as many middle-class consumers means far too many consumers to be efficiently served by a global factory.” These figures hint at why supply chain evolution is essential. It ensures shippers can meet consumers’ needs and demands to keep up with the global market shift.

The Driving Forces of Digital Transformation

The move towards digital processes and platforms is essential for supply chain evolution, and behind the movement are four driving forces that necessitate such a transformation. They include the following:

  1. Competition. Competition drives innovation and keeps businesses on their toes, especially within the supply chain network.
  2. E-commerce. There has long been a steady push towards virtual processes for supply chains, and recent world events make it all the more necessary to embrace e-commerce.
  3. Visibility. Another critical part of supply chain evolution and growth in the modern age relies heavily on improving the network’s visibility.
  4. Speed of delivery. For most supply chains and transportation management teams, accurate and timely delivery is the ultimate way to keep customers satisfied.

The Digital Twin Is Getting Smarter and Adaptive

There is a digital side for every aspect of life, which is often unseen and largely ignored. It is the digital twin, the virtual symbiote, that exists for just about everything in existence. The digital twin is a large part of the supply chain evolution process. Think about it. Shopping and purchases have a face-to-face component as well as a virtual component. Deliveries and shipments can be managed with a physical paper trail or with a digital and automated platform. The digital twin can no longer be ignored and will no longer be relegated to the corner as it is becoming more and more essential for the success of supply chain evolution.

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Technology’s Role in Managing the Evolution of the Customer Centric Supply Chain

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Having an effective supply chain has always been key to retail success. Whether you call it micro-merchandising or the customer-centric supply chain, the challenge has traditionally been to quickly identify trends or activity in a store that is outperforming the norm, and rapidly roll this out to all stores with similar attributes and customer behaviours. Indeed, much of the ‘flair’ that separated well- from poorly performing retail operators was down to the ability of some key individuals to spot trends, clusters and patterns that drove better understanding of customer behaviour, and act upon these insights to deliver to customers’ demands.

This macro-level insight is, however, no longer good enough. Today, retailers need to be able to understand not only how items are performing across the entire retail estate as well as within individual stores and spot trends and patterns accordingly; they also need to be able to marry this micro-level performance to geographic and demographic information to reflect the demand from a particular store’s customers. And, they need to be able to forecast how those same items will be performing in weeks and months to come.

This is the capability that is required to truly deliver today’s customer-centric supply chain. But it demands a level of detail simply too difficult for humans to manage. Software solutions are designed to raise the average performance level by helping the poor or below average operators benefit from the expertise of the higher performers and placing this supporting technology in the hands of those key individuals who would act as district or regional manager.

But the needs of today’s customer-centric supply chain have outpaced even the majority of these solutions.

Read more Technology’s Role in Managing the Evolution of the Customer Centric Supply Chain

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