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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.
From balancing cost-efficiency with ethical sourcing to enhancing transparency and integrating corporate social responsibility (CSR), businesses face mounting pressure to align their operations with sustainability, technology, and energy practices. The energy sector provides a compelling example of CSR-driven compliance.
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.
Proactively adopting cleaner energy sources ensures alignment with these evolving regulations. The industry’s dependency on traditional energy sources necessitates an urgent shift toward cleaner alternatives. Advanced route optimization tools further support these goals.
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. Ethical sourcing is a fundamental aspect of social sustainability.
During his tenure in the industry, he built innovative pricing and forecasting models, leveraging internal and external data sources to improve internal decision-making and increase profitability. Prior to joining DAT, Adamo led the pricing and decision science teams at FedEx.
It’s the key to transforming your supply chain from a source of frustration into a well-oiled, profit-generating machine. 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.
Strategic sourcing and innovative solutions are often viewed as two distinct procurement tools, but they should not be seen in isolation. Strategic Sourcing: The Foundation of Effective Procurement Strategic sourcing is far more than simply choosing suppliers. Done well, it can become a key driver of competitive advantage.
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?
Instead of relying solely on a single, monolithic AI model (based on a massive large language model), a company can orchestrate a team of specialized agents, each leveraging the best AI or mathematical technique for its specific task. We needed to model the data in a way that we can do simple searching. Celanese has 2.5
For organizations layered in functional metrics and driving a cost agenda, this is a tough nut to crack. During the pandemic, companies struggled with planning systems turning off the optimizers, and using the technology as a system of record. Steps to Take Here are three steps to take: Adaptive Modeling. Higher variability.
As companies across industries have discovered, a well-optimized supply chain can drive significant improvements throughout their operations. We’ll examine the key components of efficient supply chains, explore essential performance metrics, and uncover the fundamental drivers that influence efficiency.
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
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.
In this final blog on agility and why you should consider becoming an agilist to survive the new completion (of the continuous mention) of the application of enterprise decision management systems (EDMS) from Taylor and Raden cited in the first blog, I turn to the metric of agility and a new ROI metric of decision yield. The Takeaway.
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. ERP, CRM, SCM), external sources (e.g.,
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.
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.
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.
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. The SCOR model contains more than 150 key indicators that measure the performance of supply chain operations.
With its ability to derive insights from vast amounts of data and derive insights, generative AI has emerged as a valuable tool to optimize supply chain operations. AI models have grown tenfold, representing a step-change in AI capabilities, creating new use cases across the supply chain. Generative AI is all about scale.
” Corporations serve international markets, and the source of rare minerals (so critical for the evolution of the green supply chain) is primarily Asia. Others argue the demise of global sourcing; might I add caution? Yet, transportation optimization products focus on managing price, not constraints.
Supply Chain Insights recently published a Metrics That Matter report covering both the Semiconductor and Hard Disk Drive (HDD) industries. Semiconductor is poised to consolidate, which will have huge impact on the metrics. by CJ Wehlage. Success, provided they monitor the 7 “elephants” in the room. Global pressure.
This critical aspect of optimization is often overshadowed by flashier supply chain trends. By ensuring optimal stock levels where demand exists, businesses can minimize holding costs, prevent lost sales due to stockouts, and ultimately, keep customers happy. The problem lies in effectively balancing inventory across the supply chain.
Before boarding the plane, I watched a traveler pull a diet Coke from the bin and thought about the struggle to source sweetener with the rise of COV-19. As I poured the dog food into the bowl for my pups, I wondered if I was going to have to switch kibble due to the looming issues of sourcing taurine—a health additive in many pet foods.
Digital commerce efficiently requires the digitalization of many customer-facing operations and sourcing and procurement. Supply chain planning involves interaction with different types of information based on internal and external data sources. These data sources are often spread across multiple platforms and come in various formats.
MTSS platforms facilitate hands-on projects where learners can apply statistical methods to identify trends, forecast demand, and optimize inventory levels. For instance, a student interested in sustainable supply chain practices might choose courses focused on green logistics, ethical sourcing, and environmental impact assessment.
As product flows rapidly shifted and hard baked assumptions about lead times and sourcing locations were put to test, users across many organizations bypassed their planning systems and turned to excel sheets, internal data science teams or non-traditional supply chain vendors who could deliver AI based solutions at a faster turn.
Supply chain executives must evolve from cost and service as the key objectives for optimal demand-supply balancing towards the “quadfecta” of cost, service, resiliency, and sustainability. Metrics such as lead-times, forecast accuracy, inventory levels, and service are used to measure operational risks. are most exposed to risk?
Supply chain optimization is a widespread term, but did you know that an optimized supply chain is not necessarily a resilient one? There are four steps businesses can apply to understand and improve the resiliency of their supply chain network: Assess: Use all modeling and analytics to identify areas of risk.
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.
Without baseline metrics on what you want to improve on and why, how can you be confident your strategy is working? And because machine learning systems get smarter over time, having a consistent method of measurement is even more important to ensure you can accurately track how outcomes and ROI are improving against established metrics.
Demand forecasting should be tightly integrated to an inventory optimization application. It is important to benchmark forecast accuracy and similar supply chain metrics against your peers. Demand models need to be continuously updated. The model can be updated to reflect a demand spike for that city during the relevant period.
Year after year, well intentioned people toiled against improving metrics that reduced, not improved, the effectiveness of the supply chain. I like Amazon and Apple, and I admire the leadership within each of these companies that had the courage to redefine business models. Metrics comparison of Kellogg Co. You got it!
During this time, the same AI tools that underwrite new technologies have been key in improving efficiency and optimizing all areas of logistics and supply chain processes including forecasting, supply planning, inventory management, manufacturing, network optimization, and more. trillion parameters.
1) Apples Supply Chain Model. Supply Chain Model of Apple Inc. Apple Inc purchases raw materials from various sources then get them shipped to an assembling plant in China. . Some components are currently obtained from the single or limited sources. But, is Apples Supply Chain really the number 1? Inventory Turnover.
Not all data is forecastable, and not all demand optimization engines are equal. The more forecastable the data set, the easier it is to find an optimizer. In addition, there is often a seasonal, new product launch and service supply chain logical model. To be successful, each logical supply chain model needs different tactics.
Closing the gaps happens when there are aligned metrics, clarity of vision and aligned planning processes. It combines decisions across sell, deliver, make and source processes to drive value based outcomes. This includes optimization and discrete event simulation. Metrics Alignment. They lack cohesion.
According to the UN Environment Program’s Food Waste Index, 923 million metric tons of food is wasted globally every year. Source: [link]. By creating greater transparency throughout food supply chains, manufacturers can identify where the wastage happens and solve the problem at the source.
Their metrics are often misaligned as well – supply chain focuses on service and procurement focuses on the cost of acquiring materials and services. Optimizesourcing: Focus on optimizingsourcing spend across all categories of products. Conduct this resiliency test for all categories of products and suppliers.
The quality of supply chain operations is critical to evolve business models, deliver new products and services, seize new opportunities, respond to market dynamics, and mitigate risks across strategic operations. Comparing a supply chain planning platform against an ERP system that offers supply chain management capabilities is a challenge.
But companies often have diverging incentives and interests from their supply chain partners, so when they independently strive to optimize their individual objectives, the expected result can be compromised. ”. I think about this discussion with Keith often as I work on the Supply Chain Index and edit the chapters of Metrics That Matter.
If you (or your boss) are measured by your company's Return on Invested Capital (ROIC) or a similar metric, then you want to turn assets into cash. Inventory optimization is one proven way to do it. That's where inventory optimization comes in. Inventory optimization software bolts onto your existing management solutions.
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