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Each supply chain planning technology at the end of 2024, went through disruption–change in CEO, business model shift, layoffs, re-platforming and acquisitions. To build an outside-in model, and use new forms of analytics, we must start the discussion with the question of, “what drives value?” My advice?
AI in supply chain automation is gradually reshaping how core functions operate, particularly in procurement, warehousing, and logistics. Key Insight: The use of AI in supply chain automation is producing tangible benefits across procurement, warehousing, and logistics.
As supply chains become more interconnected and risks more dynamic, traditional procurement tools fall short. AI agents offer a smarter, faster way to manage sourcing, risk, and spend across the entire procurement lifecycle. What’s the technology behind autonomous procurement agents? You may also have heard of Agentic AI.
Enterprise procurement teams face growing pressure to deliver strategic value – managing supplier risk, ensuring compliance, and supporting sustainability – all without sacrificing speed or control. This blog explores the most common challenges in digital procurement and the capabilities that matter most.
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.
Venture capitalists are high on Artificial Intelligence (AI), and over-exuberant professors with shiny new models are jockeying into position to get rich. Most of the business networks were hollowed out by venture capitalists or purchased by opportunists. Building a software company is hard work. Ask for use cases.
Green Logistics: Optimizing transportation routes, consolidating shipments, and employing energy-efficient vehicles to reduce emissions. These initiatives also lead to cost savings by maximizing load capacity and reducing fuel consumption. Advanced route optimization tools further support these goals.
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. With the global e-commerce market predicted to reach $8.1 The Ukraine-Russia conflict is ongoing.
Strategic sourcing and innovative solutions are often viewed as two distinct procurement tools, but they should not be seen in isolation. Think of them as apples and gearseach essential and effective on its own, yet when combined; they create a formidable mechanism for achieving procurement excellence.
Advanced supply chain planning is being transformed by probabilistic forecasting , which revolutionizes demand forecasting, supply planning, and inventory optimization. However, this approach ignores real purchasing behavior, such as customers buying complete sets of four tires.
Traditionally, procurement has been a process weighed down by manual tasks, fragmented systems, and endless paperwork. Today, procurement is undergoing a transformation. While procurement teams have long worked to add strategic value, Artificial Intelligence (AI) amplifies their impact.
Probabilistic forecasting is revolutionizing demand forecasting, supply planning, and inventory optimization by significantly improving forecast accuracy and decision-making across distribution networks. However, this approach ignores real purchasing behavior, such as customers buying complete sets of four tires.
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.
The trade with Asia we take for granted today was only possible by mitigating a significant supply chain trade-off – reducing costs without appreciable impacts to quality and service. Supply chain optimization has also improved in significant ways that can address these trade-offs better than before.
In a previous post , I made a case for how the Chief Supply Chain Officer (CSCO) and Chief Procurement Officer (CPO) are smarter together. Accordingly Supply Chain and Procurement will need continuous collaboration. By aligning supply chain and procurement, spend can be considered more holistically.
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?
The onus is on ecommerce retailers to control the controllables, and focusing on eliminating uncertainty from the consumer fulfillment process and optimizing the last mile is a smart approach. Embedding predictability Retailers can influence buyer behaviour—during the online purchasing process—by offering achievable delivery options (e.g.,
This advanced analysis allows businesses to predict promotional lift with unprecedented accuracy, ensuring optimized production schedules and inventory positioning through sophisticated supply planning.
But supporting the process with advanced analytics goes even further, contributing to higher levels of productivity and profitability. Like many organizations, Tereos recognizes the use of advanced analytics as an imperative. Advanced analytics as enabling technology. The use of predictiveanalytics is fairly common nowadays.
AI and machine learning tools identify patterns, predict issues, and suggest ways to optimize operations. Having a well-documented DPP also makes it easier to report to regulators and stakeholders. Why DPPs Matter Consumers today expect transparency about the products they purchase.
Here’s your two-minute guide to understanding and selecting the right descriptive, predictive and prescriptive analytics for use across your supply chain. Companies that are attempting to optimize their S&OP efforts need capabilities to analyze historical data, and forecast what might happen in the future.
following the reporting of fourth-quarter results. The Salesforce.com model is primarily a pipeline management tool suitable for discrete markets but not process manufacturers. The models are just too different.) Customers will migrate off of the Logility platform onto newer flow-based outside-in models. Kinaxis and o9.
Supply chain efficiency is the cornerstone of success and involves the effective management of processes, resources, and technologies from procurement to production, transportation to warehousing. As companies across industries have discovered, a well-optimized supply chain can drive significant improvements throughout their operations.
Procurement and Supply Chain Management are essential functions that can help companies navigate these challenges, but they are often siloed and operate in separate departments. Their metrics are often misaligned as well – supply chain focuses on service and procurement focuses on the cost of acquiring materials and services.
Analytics and business intelligence (BI) are no longer optionaltheyre essential. They integrate, align, and activate data across the business to drive better, faster decisions unlike legacy reporting tools that can’t. Flexible Delivery Options Interactive dashboards, scheduled reports, alerts, mobile access, and more.
” As I dipped my spoon into some scrumptious chestnut soup at a great restaurant, my companion asked, “With the advancements in optimization and self-learning, aren’t we close to having self-driving supply chains?” There is no magic ball on design: the organization’s reporting structures vary by culture and size.
The basic frame of supply chain planning–functional taxonomies for optimization on a relational database–must be redesigned before supply chain leaders can reap the benefit of deep learning, neural networks, and evolving forms of Artificial Intelligence (AI). Or a unified data model across source, make, and deliver for planning?
I know that your primary focus is procurement. The distribution models were never tested when implemented. As a result, after four years of the initial go-live, the team blindly used planning models, distorting the plan. Or planned orders to purchase orders?) I encourage all to backcast to test and improve their models.
By embedding analytics across logistics, sourcing, and fulfillment, businesses gain the visibility and foresight needed to stay competitive.Analytics-driven leadership is no longer a luxury; it’s the foundation of operational survival in todays volatile business environment. Analytics allows organizations to move beyond intuition.
BOSTON, February 16, 2022 : ToolsGroup , a global leader in supply chain planning and optimization software, has partnered with Planalytics to integrate their weather-driven demand (WDD) analytics with ToolsGroup’s retail planning solutions, enabling customers to isolate, measure, and manage the influence of weather on their businesses.
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.
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. Data does not move.
I see a preponderance of reports and white papers that have lots of pages but say little. Optimization engines to improve functional metric performance resulted in an exploding number of planners. days to receive a purchase order confirmation. The average purchased order changes 3.5 Back to John.
One of my favorite supply chain leaders has a stack of Palantir reports in black binders on his desk. Kinaxis Purchase of Rubikloud. The purchase of Rubikloud by Kinaxis shows just how little the Kinaxis team knows about demand management. Kinaxis Purchase of Rubikloud. The Rubikloud acquisition was a $60M cash purchase.
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. Inventory Optimization. Inventory Optimization involves decisions about the inventory level, the location, and the mix of products.
(I never republished the report, because not enough has changed to warrant it.) The report centers on the concept of moving from inside-out to outside-in technologies. Why is there a discontinuous line on the model?” This model reminds me of a snail. Here I write about what I hope that he learns.
How the digital twin concept drives benefit By using advanced analytics and machine learning algorithms, digital twins can provide real-time insights and recommendations to optimize operations, reduce costs, and increase productivity. Physical change (i.e., changing the structure of the warehouse, modifying processes, etc.)
The consulting team pitches a theme–vision of supply chain best practices, big data analytics, or demand-driven value networks– to the executive team, and a new project is initiated. It was also the preference of the consulting partners because the projects were longer, more costly and better aligned with the consulting model.
Improve visibility across the networks that operate in self-serving business models. For example, change the business models so that Ariba must interoperate with GT Nexus, E2Open with Elemica, MPO (Kinaxis) with Nulogy, etc. Maximize the value of the purchase order flow data already in the existing networks. (A
In companies, there is no standard model for demand processes. New forms of analytics make new capabilities possible. Let’s start with these: Demand Sensing: The reduction of time to sense purchase and channel takeaway. For the purchase of Tide at Walmart to translate to an order at P&G, the time is 5-7 days.
Last week in the middle of a presentation, a supply chain leader made the statement, “We have solved the issues in supply through better optimization and use of data. The data models are wrong. Which supply chain metrics correlate to market capitalization by Morningstar sector? Experiment with these new forms of analytics.
Part 2 in the series explores the “analytical scenario exercise” and how decisions based on certain scenarios heavily impact each aspect of the value chain. Ultimately, what KPIs, as metrics and indicators derived from the set of plans are taken into account and prepared for each scenario. Technology for Effective Planning.
Digital commerce efficiently requires the digitalization of many customer-facing operations and sourcing and procurement. The First Step: Bring all the data together and ensure analytics and planning can happen on the same platform. . Accurate and timely reconciliation of purchase orders with receipts.
Shoppers coping with inflation have shifted buying habits , purchasing fewer goods and cutting back on big name brands in favor of cheaper alternatives. Behind the scenes, CPG brands are strategically balancing cost cutting measures with supply chain investments to ensure preparedness for continuing market shifts.
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