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In follow-up qualitative interviews, one of the largest issues with organizational alignment was metric definition and a clear definition of supply chain excellence. In my post Mea Culpa, I reference my work with the Gartner Supply Chain Hierarchy of Metrics. Error is error, but is it the most important metric? My answer is no.
The issue is that when companies optimize functional metrics, they throw the supply chain out of balance and sub-optimize value. Traditional approaches built optimization on top of relational databases. This shift improves modeling options and the use of disparate data. Today, the bright and shiny object is AI.
Meanwhile, advances in AI-driven route optimization reduce unnecessary mileage, cutting emissions and costs. Smart energy management systems further enhance efficiency by tracking and optimizing energy use in real-time. Reducing carbon emissions is a cornerstone of this effort.
By harnessing the power of data science and analytics, you can gain end-to-end visibility across your entire network, breaking down information silos and optimizing every stage of your operations. Data analytics also offers actionable insights for: Inventory Management: See stock levels across multiple locations in real-time.
Green Logistics: Optimizing transportation routes, consolidating shipments, and employing energy-efficient vehicles to reduce emissions. Advanced route optimization tools further support these goals. AI-powered warehouse management improves inventory flow and reduces waste.
Reason #4 Making key decisions by modelling the supply chain in Excel. Reason #6 Not effectively managing inventory. Reason #9 Relentless pursuit of one supply chain metric at the expense of other metrics. Reason #9 Relentless pursuit of one supply chain metric at the expense of other metrics. Don’t care.
But between rising costs, complex logistics, and the constant struggle to optimize space and labor, staying ahead can feel like an uphill battle. That’s where warehouse optimization comes in. Here’s what you can expect: A clear definition of warehouse optimization and its core components. Ready to get started?
trillion distortion inventory problem. Trillion Inventory Distortion Problem In this podcast, Karl Swensen, CEO and Co-founder of Pull Logic, discusses how their AI-enabled technology helps retailers, brands, and manufacturers reduce lost sales by addressing supply chain and selling process failure points. Summary: Solving the $1.8
Picture this: You’re a warehouse manager, and with a few taps on your smartphone, you instantly know the exact location and quantity of every item in your inventory. That’s not science fiction—it’s the power of mobile inventory management. Ready to turn your inventory from a headache into a strategic asset?
Supply chain optimization has also improved in significant ways that can address these trade-offs better than before. Analytical techniques like linear programming can create the mathematically “optimal” plan, but these methods must be implemented well to avoid creating other challenges. Supply chain optimization for today’s realities.
Continuous network optimization recognizes that supply chains are complex organisms. Continuous network optimization creates an environment where supply chain planning operates at the next level. World class organizations can sustain living models of their networks and keep them tuned to small, frequent changes.
Three months into 2025, we have seen a barrage of on-again, off-again tariffs that have supply chain and logistics teams reeling, as they must rethink everything from next weeks shipping route to their foundational network models. The Ukraine-Russia conflict is ongoing. Tensions flare in the Middle East without warning. billion to $23.07
As companies across industries have discovered, a well-optimized supply chain can drive significant improvements throughout their operations. In the automotive sector, manufacturers are simultaneously reducing inventory costs and delivery times. This post delves into the core drivers of supply chain efficiency.
Returns Management and Integration With 35% of online purchases being returned, predominantly to physical stores, retailers are grappling with the ripple effects on inventory management. Early adopters of these integrated platforms report significant improvements in inventory turnover and reduction in stockouts.
Continuous network optimization recognizes that supply chains are complex organisms. Continuous network optimization creates an environment where supply chain planning operates at the next level. World class organizations can sustain living models of their networks and keep them tuned to small, frequent changes.
The primary payback for demand and supply solutions comes in the form of reducing the amount of raw material, work-in-process, and finished goods inventory a company needs to carry. A network design model figures out where factories and warehouses should be located. Each time horizon usually has its own model associated with it.
Supply chain resilience refers to planning for things that could go wrong and then creating inventory buffers or contingency plans. SCP solutions provide a solid ROI based on hitting targeted service levels with less raw material, work-in-process, or finished goods inventory. Supply planning engines “optimize” the schedule.
In traditional advanced planning applications (APS) for a manufacturing company, the forecasting model’s role is to generate a time-series forecast in the tactical horizon (outside of lead time). (An In traditional planning taxonomies, the tactical forecast is modeled, and the operational signal is calculated using consumption logic.
There are supply chain and demand analytics models that describe the type of analytics being deployed (e.g., Now Gartner has created a different look at the issue by creating a five-stage maturity model for assessing the overall maturity level of your organization in using supply chain analytics. descriptive, prescriptive, etc.).
A new report from Nucleus Research, Value Drivers of Single Model S&OP , concludes that the historical disconnect between planning and execution in S&OP is best bridged by a single unified data model that allows companies to continuously synchronize their strategic, tactical and execution plans.
The problem lies in effectively balancing inventory across the supply chain. This critical aspect of optimization is often overshadowed by flashier supply chain trends. When demand surges, inventory needs to rise, and vice-versa. Mastering Inventory in 2025: Key Trends Watch Webinar Now WATCH WEBINAR What is Stock Balancing?
What is the Perfect Delivery Metric? Improving on this metric will always involve a focus on people and processes, but often also includes implementing new, more robust, supply chain applications. The wrong metrics drive suboptimal behaviors and metrics can often be manipulated.
To keep customers like my dad satisfied, RGD and Quick-commerce companies need to invest in new technologies to optimize the supply chain and logistics operations. InventoryOptimization. InventoryOptimization involves decisions about the inventory level, the location, and the mix of products.
The world of NoSQL unified data models is inconceivable to most. Software built on graph technology can model flow, but the transactional paradigms of historic practices hold development team’s hostage. The larger the global corporation, the more that the use of functional goals sub-optimizes growth, margin and inventory levels.
How are companies rethinking their liquidity management strategies in response to the recent degradation across major working capital metrics? In the wake of economic uncertainty, many companies have experienced a degradation in key working capital metrics.
Without sufficient data, AI models can’t uncover meaningful patterns, make accurate predictions, or provide valuable insights for informed decision-making in complex and dynamic environments. At the same time, feeding your AI models too much data can also be a problem. Data is the lifeblood of AI in the supply chain.
” As I write, I think about the ironies: We talk about the bullwhip, but we do not measure it or use it in driving optimization. We talk about the move from functional metrics to a balanced scorecard, but we don’t use a balanced scorecard as an objective function. My question is “Will the work make a difference?”
The promise was the delivery of a decision support system that would allow the organization to optimize the relationships between cash, cost and customer service against the strategy. It was also the preference of the consulting partners because the projects were longer, more costly and better aligned with the consulting model.
This means routinely bringing together the C-suite, finance, supply chain, manufacturing, sales and marketing teams so everyone is seeing, working from and agreeing to an aligned plan that achieves optimal business outcomes. Inventory-based KPIs probably make sense for you, but how will you benchmark results?
Using ourA-B-C of Route to Market model, the Catalyst Phase is when we execute or as we sometime call it ‘How to Win’. Ensure they have the necessary inventory, marketing materials, and training to effectively introduce your products to the market. Utilize inventory management tools and techniques to optimize stock levels.
The impact of complexity on inventory is not quick. To help, today I want to share some of the insights from our recent InventoryOptimization study. Inventory management is a hot issue. Companies invest in project after project, yet inventory levels remain the same. The Business Problem.
Use tools like network design optimization and simulation modeling to help people model trade-offs. Force finance and sales teams off of spreadsheets that cannot model the complex relationships of trade-offs. Advance their thinking to use more advanced supply chain modeling tools. The value proposition still holds.
This is because most classical planning solutions lack the modeling capability and computing power to accommodate different data sources, large SKU count, and detailed constraints and contingencies to build an immediately executable plan. each with discrete plans generated typically in sequential batch runs.
For instance, a student struggling with inventory management concepts can receive supplementary materials, interactive simulations, and one-on-one tutoring sessions tailored to their needs. Conversely, a student who quickly grasps procurement strategies can be challenged with advanced case studies and leadership projects.
Can you describe the outside-in model? Based on the work with Georgia Tech, we are getting clear on which metrics matter by industry. As companies adopt a balanced scorecard, the functional metrics shift to a focus on reliability. Based on market conditions, the meat packer will shift to optimize the demand opportunity.
It could no longer be just about inventory levels. This analysis needed to be completed monthly and fed to newer forms of inventoryoptimization technologies. The advanced Llamasoft user has a model on a computer tablet (Sherpa product) that enables the visualization of S&OP trade-offs within the S&OP meeting.
However, AI’s inability to solve the very limited problem of ensuring that inventory is located in the right place in a warehouse suggests that planners don’t have to worry too much about job security. For fulfillment to be efficient, a warehouse needs the right inventory located in the right slots in a warehouse.
Closing the gaps happens when there are aligned metrics, clarity of vision and aligned planning processes. This includes optimization and discrete event simulation. Metrics Alignment. Most companies operate well within functions, but struggle to build strong horizontal processes. They lack cohesion.
Optimization engines to improve functional metric performance resulted in an exploding number of planners. Rolling up a perpetual inventory signal takes eleven hours. days to get a perpetual inventory signal and 2.2 What is the impact of the amplification and distortion on inventory and cost? When did you know it?
1) Apples Supply Chain Model. Supply Chain Model of Apple Inc. Inventories can become obsolete or exceed the anticipated demand. So this section will explain some characteristics of Apple Supply Chain through various metrics and compare them with Amazon Supply Chain. Inventory Turnover. Number of Key Suppliers.
That’s where manufacturing inventory management software comes in. The right software can streamline your production, optimize stock levels, and even help you save money. In this ultimate guide, we’ll break down everything you need to know about manufacturing inventory management software.
Interview with Lora Cecere, Founder and CEO of Supply Chain Insights and Author of Supply Chain Metrics that Matter ( published December 2014 ). Metrics that Matter became a three year research project. I realized that many organizations are very confused about metrics. So I started this book as a summary of this research.
We were discussing the results of the planning benchmarking work that we have just finished, and I was sharing some insights on inventory management when one of the panelists emphatically stated, “Inventory is a waste to manage. We feel so strongly about this that we do not have an inventory planning role.”
The answer is to increase modeling, evaluate sourcing strategies, and build the right push/pull decoupling points. Due to the lack of design of work processes, the output from the technology is sub-optimal. As a supply chain pioneer in the 1990s, I was vested in the concept of using optimization to make better decisions.
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