“Increasing globalization and complexity have put supply chains in the spotlight like never before.”
Economies around the world are stepping back from the financial brink and have begun adjusting to a new normal, however, at the height of the downturn companies face a different set of supply chain challenges than they did. Some of these supply chain challenges include rising pressure from global competition, increasingly complex patterns of customer demand, and consumer expectations. In this blog discuss some of the biggest supply chain management challenges. The experts from Quantzig have curated some of the key benefits of supply chain analytics in overcoming these challenges.
What are the Key Supply Chain Challenges?
Supply chain management primarily revolves around ensuring that the right product in the right quantity reaches the right place and the right time. As much as this might sound simple, this can indeed prove to be a complex task.
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The rising energy/fuel and freight costs are putting supply chain managers under extreme pressure to manage their operating costs. The greater number of global customers, technology, labor rates, and rising commodity prices tend to become more expensive.
Planning and Risk Management
Staying efficient and effective in today’s highly competitive marketplace is no easy task. It requires periodic assessments and redesigns to stay in the game. These adjustments are in response to changes in the market including new product launches, global sourcing, credit availability, and the need to protect intellectual property. These risks must be identified and quantified in order to control and mitigate.
Supplier/Partner Relationship Management
It is important to create, understand, and follow standards that are mutually agreed upon in order to better understand current performance and opportunities for improvement. Having two different methods for measuring and communicating performance and results in the wastage of time and effort.
It is becoming increasingly difficult to find talent that is qualified and interested. Supply chain managers need an extensive understanding of the key competencies and duties that are quintessential for effective supply chain management roles and the ability to efficiently source specific skill sets and methods for developing future leaders.
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The use of supply chain analytics is resolving several fundamental pain points in supply chain management at the operational, strategic, and tactical levels.
What is Supply Chain Analytics?
Supply chain analytics is the application of statistics, predictive modeling, mathematics, and machine-learning techniques to find meaningful patterns and knowledge in order to analyze the shipment, transactional, and sensor data. Supply chain analytics primarily aims to improve forecasting and efficiency and prepare companies to be more responsive to customer needs. For instance, supply chain analytics on point-of-sale terminal data can prove to be helpful for businesses to anticipate consumer demand, which in turn can lead to cost-saving adjustments to inventory and faster delivery.
End-to-end supply chain analytics starts with the procurement of raw materials and extends through production, distribution, and aftermarket services. Effective supply chain analytics depends on effective integration between the many SCM execution platforms that make up a typical company’s supply chain. The primary goal of such an integration is supply chain visibility: the ability to view and analyze data on goods at every step in the supply chain process.
Why Supply Chain Analytics?
Factors including commodity volatility, changing demand forecasts, and supplier-specific challenges have affected nearly every organization. This includes companies that have a well- managed supply chain. In recent years, even top supply chain performers have faced embarrassing stock-outs during periods of unanticipated demand. This underperformance occurs from the fact that supply chain visibility and analytical models are typically grounded in hindsight. Competitive advantage is no longer gained by making decisions based only on what happened in the past.
Benefits of Supply Chain Analytics
Reduced Inventory Costs
Supply chain analytics can help companies to add value by gaining a clearer and more efficient picture of their entire operation. This can be achieved with supply chain analytics for forecasting future demand. In the past, companies relied on past orders as their only guideposts for estimating future demand levels, often leading to decisions that don’t account for likely future changes. Supply chain analytics combines all of your previous order data with real-time market analyses to create dynamic demand forecasts. This proves much more successful at predicting changes in the demand landscape than human supply chain planners. There are several areas in which this can drive increased value, but one of the most critical is inventory management. A company without a robust supply chain analytics workflow might expect a customer to place a large parts order in the near future and stock their warehouse accordingly only to find that the order size had declined when compared to the previous year. This means that the parts would just continue to take up valuable space. With better demand sensing via advanced supply chain analytics, the company could have anticipated these demand changes by reducing their production of the part in question, thereby freeing up valuable storage space.
Optimization of Production Plans
Supply chain analytics helps companies identify specific processes in order to understand the potential areas of waste or inefficiency. Supply chain analytics feeds the existing processes schedule into the analytics workflows. This optimizes and presents back-up plans in response to real or hypothetical disruptions, thereby keeping your production plans on track even in the face of unexpected or unforeseen contingencies.
More Responsive Transport Logistics
By using advanced supply chain analytics processes, companies can improve the functioning of their transport logistics processes. Not only can supply chain analytics analyze their existing freight network usage to find potential areas for improvement, but also improved demand predictions can help companies to plan their transports in advance with added certainty.
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Advanced supply chain analytics can also have operational benefits that are slightly harder to quantify. Supply chain analytics can help to promote cross-functional collaboration by creating highly-visible, shareable forecasts that can help disparate teams across a given organization to get on the same page and rally around a common future vision. Currently, it is easy for future expectations to create areas of disconnect between different teams. For instance, inventory planners are expecting higher demand levels than the transport planners, this could put organizations in a position where there isn’t enough freight capacity to move existing inventory or unnecessary usage of costly inventory space. In case both teams are working from the same forecasts, such instances are less likely to happen.
New Sales and Operation Execution Workflows
Apart from offering predictions and process optimizations, supply chain analytics can help add real-time information into a company’s value stream by giving more structure to data and data feeds. In this way, supply chain analytics powers sales & operations execution processes that can help keep longer-term operational plans on track. Sales & operations execution processes accomplish this by offering planners a real-time demand snapshot that enables them to make small daily and weekly adjustments to transport plans and inventory levels. That may sound simple on its face, but, just like them modern baseball statistics we discussed above, it’s actually the result of years of process improvements, analytical insights, and technological improvements. Also, like modern baseball statistics, and like many of the other bullets on this list, it helps businesses to visualize and understand their entire operation in new, potentially game-changing ways.