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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.
In today’s architectures and functional metrics, value optimization does not exist. And, when procurement and tactical planning operate in isolation, there is no decision support framework to guide the trade-offs especially when the functions are tethered to different and conflicting metrics. You are right.
When it comes to running a company, when things break down executives have traditionally said “we need to improve our forecasting!” Would better forecasting accuracy be a good thing? Unfortunately, most companies cannot, and will never be able to, consistently rely on highly accurate forecasts. Absolutely!
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.
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. Transparent sourcing practices build trust among consumers and investors.
The waste included: Negative Forecast Value Added (FVA) in demand planning. In 85% of organizations that I work with, conventional demand planning processes increase forecast error. Inventory is both our most important buffer and greatest source of waste.) Muda comes from many sources. It was never measured or managed.
Reducing cost was the primary objective, and most operational decisionsfrom sourcing to fulfillmentreflected that mindset. Leading organizations are building supply chains that are less exposed to single points of failure, more informed by real-time data, and more able to adjust sourcing, inventory, and routing based on current conditions.
Optimizing fulfillment requires a series of steps to get a shipment from its source to the end customer. These steps include sourcing and receiving inventory, storing inventory, order processing, picking and packing an order, shipping the order, and returns management. The ability to meet fulfillment goals is impeded by several issues.
Clear operating strategy and definition of supply chain excellence across plan, source, make and deliver. A shift from functional metrics to a balanced scorecard. I like the use of growth, margin, inventory turns, Return on Invested Capital, customer service and ESG metrics. Improved Forecast Value Added (FVA).
I’ve always maintained that improving demand forecast accuracy, as helpful as it can be, shouldn’t be the end goal itself, but simply a means to the end. A recent report from Gartner agrees, focusing specifically on the challenge of building a better business case for improved forecast accuracy.
We’ve seen AI take over everyday tools and search engines; AI in Sourcing and Procurement is becoming a strategic tool in our kit, At Ivalua, we are helping global procurement teams integrate AI across the Source-to-Pay process, bringing automation, insight, and agility to every step. This is where AI can make a huge difference.
Samuel Parker and Joe Lynch discuss DAT iQ: the metrics that matter. Key Takeaways: DAT iQ: The Metrics that Matter In the podcast interview, Samuel Parker gave a freight market overview based on DAT’s database of $150 billion in annual market transactions.
beef from 1,000 to 13,000 metric tons , removing the 20% tariff within that limit. Cost Forecasting : The 10% tariff baseline increases landed costs and may affect margin forecasts across multiple sectors. Companies should incorporate these provisions into their sourcing, pricing, and compliance strategies.
Do Set Clear KPIs and Governance Structures : Establish transparent metrics for sales, coverage, and service levels. Do Embrace Technology and Data : Use real-time data for demand forecasting, inventory management, and route optimization. A well-equipped distributor is an extension of your brand and a key to market penetration.
Over my 25+ year supply chain career I have worked for several distribution-intensive companies and every single one of them had a focus on improving forecast accuracy. Achieving a high SKU level forecast accuracy is a top goal for supply chain planning teams regardless of industry, size, location, etc.
It’s the key to transforming your supply chain from a source of frustration into a well-oiled, profit-generating machine. Demand Forecasting: Analyze past data to predict future needs. Integration of Data Sources Data integration connects different information streams to create a single view of your supply chain.
At a high level, procurement focuses on sourcing the goods and services an organization needs, while supply chain management oversees the broader flow of those goods, from raw materials to end customers. Supply Chain Management (SCM) involves orchestrating a product’s or service’s entire lifecycle, from sourcing and production to delivery.
So, the promise of using statistical algorithms, forecasting and predictive analytics is now added to the list of a company’s number one priorities. Here are a few steps that you will need to take to deploy your forecasts successfully. Phone * Company * Job Title * Zip Code * Source Asset Source Download ID.
We’ll examine the key components of efficient supply chains, explore essential performance metrics, and uncover the fundamental drivers that influence efficiency. Efficient supply chains strengthen collaborative relationships through automated communication systems and shared performance metrics.
It is useful to analyze demand data to understand “forecastability” and randomness. 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. When I delve into the data, I find: Forecasting Solution Signal Efficacy.
AI is reshaping the way organizations source, manage suppliers, and drive value today. AI agents offer a smarter, faster way to manage sourcing, risk, and spend across the entire procurement lifecycle. For example, agentic AI can analyze supplier data, evaluate contracts, manage purchase orders, or recommend sourcing strategies.
AI is reshaping the way organizations source, manage suppliers, and drive value today. AI agents offer a smarter, faster way to manage sourcing, risk, and spend across the entire procurement lifecycle. For example, agentic AI can analyze supplier data, evaluate contracts, manage purchase orders, or recommend sourcing strategies.
Procurement professionals can contribute significantly to the S&OP process by providing valuable insights into supply chain dynamics, identifying potential risks, and optimizing sourcing strategies. Help Forecast Upstream Supply Constraints Early Warning Signs: S&OP can identify potential demand increases.
Top 3 Demand Forecasting Mistakes —How To Avoid Them with Demand planning software Demand forecasting is a critical facet of successful business operations, acting as the helm guiding companies through the rocks hiding beneath the water of market demands. What is Demand Forecasting?
Digital procurement streamlines workflows and unifies data, enabling faster sourcing, better collaboration, and improved accuracy. AI and automation boost procurement’s strategic impact, helping teams reduce risk, ensure compliance, and forecast spend.
Definition: Financial forecasting is a projection of the company's future financial performance based on historical data, market research, and business needs. The forecasts act as a guide, which you can use to make strategic decisions on resource allocation and define clear, attainable goals.
MTSS platforms facilitate hands-on projects where learners can apply statistical methods to identify trends, forecast demand, and optimize inventory levels. Through interactive tutorials and practical exercises, learners can become adept at using software for inventory management, transportation planning, and demand forecasting.
Our preliminary findings suggest that supply chain resilience has been increasing in importance over time, but still remains secondary to the end goal embedded in the perfect order metric – the right product, to the right place, at the right time. However, I am surprised at the degree that localized sourcing is being considered.
I would like for us to move past the conventional view of sourcing strategies and globalization to drive improvements to the supply chain in a variable world. The populist narrative of sourcing globalization is only part of the story. Forecastability. In 2015, the forecastable volumes were over 50%. Let me explain.
Gartner says that the most common outsourced SCP processes are inventory management, statistical forecasting and service parts planning. Companies moving to BPO in these practice areas are experiencing supply chain improvements in metrics such as inventory turnover and customer service. Driven by improvements in performance and cost.
Koganti said this is the fastest-growing use of AI in supply chain, especially when it comes to forecasting, procurement and fulfillment. He sees a near future in which there are multiple agents, each with their own realm of responsibility, such as shipping, pricing and forecasting.
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.
Digital twins bring enterprise-level visibility to network planning, allowing organizations to simulate new fulfillment strategies, evaluate sourcing risks, and prepare contingency plans that support both customer experience and bottom-line resilience. Scope Creep: Avoid trying to simulate the entire enterprise at once.
Collaborative discussions can help identify relevant data sources and metrics that capture the end-to-end supply chain process and align with overall business goals. Data inventory and assessment: Conduct a comprehensive inventory of available data sources within the organization, including internal systems (e.g.,
PO Collaboration focuses on maintaining accurate demand forecasts, timely communication with suppliers, and efficient replenishment processes to ensure optimal stock levels and minimize stockouts. Configure to Order: This strategy involves customizing standard products based on customer specifications.
While the terminology evolved, the underlying thesis of S&OP has stayed the same, i.e., bridge the divide between sales forecasts and operational plans while respecting the budget. For example, forecasts are generated using the past three years of history, implicitly assuming history repeats.
This blog offers a clear, practical overview of what spend analysis is, how it supports strategic sourcing, and why it matters for both direct and indirect procurement. We’ll walk through key benefits, types of spend analysis, steps to get started, and metrics to track—backed by lessons learned from real-world implementations.
Anyone who has done demand planning knows it is extremely complex, with forecasting challenges and rapidly shifting consumer demand, often exacerbated by seasonality, new product introductions, promotions, and myriad causal factors (e.g. Data Variety The more different types of data sources you factor in (e.g. weather, social media).
If you’ve been in supply chain for any length time, you might be wondering what caused demand forecasting to develop so many different ‘personalities’ over the years. Demand forecasting, planning, sensing, shaping…what’s going on? Demand Forecasting. Demand forecasting describes the decades-old science of predicting demand.
The traditional metrics of excellence cost efficiency, on-time delivery while still important, are no longer sufficient in an era defined by volatility, complexity and political changes. Gone are the days of monthly forecasts based solely on historical data. The first is living demand intelligence.
Aside from mitigating risk and saving organizations money, Procurement teams have an opportunity to add value by working closely with suppliers to reduce carbon emissions while ensuring supply chain continuity through diversity and proper forecasting. Tracking the Metrics that Matter. Inflation Metrics. Risk Metrics.
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. Start by analyzing your Forecast Value Added by demand stream. Most of the models are supply-centric with no place to put channel data.
They source from approximately 15,000 suppliers with a sourcing spend of over €7 billion. But even multi-sourcing is not enough. A supply chain is mapped, where components are source from, how they flow through a supply chain to factories and out to customers. Their revenues exceed €25 billion.
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