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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. The reason?
In follow-up qualitative interviews, one of the largest issues with organizational alignment was metric definition and a clear definition of supply chain excellence. To manage continuous improvement, companies need a clear definition of excellence and organizational alignment to that goal. What Drives Value?
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!
Clear operating strategy and definition of supply chain excellence across plan, source, make and deliver. Most companies buy decision support technology, but do not redefine work to improve decisions. A shift from functional metrics to a balanced scorecard. The focus on functional metrics sub-optimizes balance sheet results.
In my first classes, I taught the group how to speak the language of demand—forecastability, Forecast Value Added (FVA), backcasting, demand and market latency, and market drivers. 40-50% of items are not forecastable at an item/location level. Lack of aligned metrics. Lack of executive buy-in. The So What?
Forecasting projections is one of the toughest things to get right. Whether your brand is experiencing gradual sales or is in high-growth mode , we’ll walk you through some tips to improve your ability to forecast demand. Jump to section: What is demand forecasting? Jump to section: What is demand forecasting? Conclusion.
Initially, the output was published to procurement to design strategic buying strategies. Watermelon Metrics Don’t Drive The Right Results. I love the metaphor of watermelon metrics. The issue is that traditional functional metrics drive underperformance—the greater the variability, the larger the gap.
The classical approach involves functional silos, sequential decisions, and Excel and people to render a plan executable. Big data is used to understand a customer’s propensity to buy, the tendency to return, conversion of clicks to orders, demand sensing signals, individualized promotions, etc.
Introduction Gardner, (1954) and Huntzinger, (2007) define Purchase price variance (PPV) as a metric used to measure the effectiveness of cost-saving efforts by calculating the difference between the planned cost (standard pricing) allocated for purchasing activities and the actual cost incurred.
Millions of shoppers, like my Dad, are not going back to their old habits because there are now faster and more convenient ways for buying daily household needs. It excels on a union of E-Commerce mobile apps and last-mile delivery innovations. I have to forecast my avocado sales, including seasonal patterns and promotional effects.
Nick Lynch is the Global Excellence Manager at Shell Lubricants, a division of Shell Global. Completed in 2012, the ERP project forced the company to standardize organizational design, roles, and metrics. What can often look like compliance in APO could actually be numbers calculated in Excel and posted into the SAP system.
We’ll examine the key components of efficient supply chains, explore essential performance metrics, and uncover the fundamental drivers that influence efficiency. An efficient procurement process optimizes vendor selection and purchasing decisions to maintain cost-effective inventory levels.
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.
Manufactures are continuously faced with the challenge of forecasting how much (raw material) to purchase and how much (finished goods) to produce. To manage this delicate balance of demand and supply, manufacturers often use statistical forecasting techniques to predict future demand by looking at historical sales data.
I have heard a number of supply chain professionals proclaim that their companies should stop forecasting product demand due to poor forecast accuracy. However, what is often overlooked is that moving to a pull strategy does not eliminate the need for a forecast. It’s the old Push – Pull argument. Financial Impact.
Today, their functionality has increased, and businesses are leveraging CRM systems for demand forecasting, buyer behavior analysis, and more intelligent inventory management. This real-time visibility translates into faster issue resolution, enhanced forecasting, and vendor coordination. Check out this course by Vera Rozanova!
They can adjust quantities and generate supplier replenishment orders in PDF or Excel as needed. In this version, there’s no automation around managing promotions, so demand planners need to get involved in adjusting the forecasts for promotions. The platform serves the needs of different levels of resource availability.
Running procurement and supply chain without metrics is like driving blindfolded. Identify Bottlenecks & Opportunities: Quickly spot areas that are underperforming and need attention or areas where you’re excelling. Control Costs: Track value beyond just the purchase price and manage inventory effectively.
The focus is on the role of supply chain finance in driving supply chain excellence. The design of the conference includes tours of several modern warehouses and centers of excellence. The budget is not sufficient and is often a detrimental input for supply chain forecasting. The supply chain forecast is a rolling forecast.
Forecastability. Today, due to the increase in the long tail of the supply chain and changing customer dynamics, less than 50% of items are forecastable at an item level. The only products that can be efficiently outsourced with long lead times are in the “forecastable” column. Let me explain. Not so today.
If you are going to be excellent at ecommerce fulfillment, you need to have great perpetual inventory capabilities. Aggressively design and test products online and then bring the data into your forecasting tools to predict sales of new products by channel. Don’t fool yourself. 2) Endless Aisles Need Boundless Fulfillment.
Users are accustomed to building everything in Excel and manipulating the data as needed for their own particular use, typically using static reports or spreadsheets that are siloed in specific departmental needs. A key first step is to have buy-in at the highest level of the organization. Starting at the Top. Other Suggestions.
Or agreement on the definition of supply chain excellence. As a result, functional excellence anchors action. The focus is on digitization—automating today’s processes—versus rethinking process excellence based on the art of the possible. An orbit chart is a plotting of data at the intersection of two metrics.
At a time that marketplace offerings were super-hyped, I forecasted the doom of ten e-marketplace providers. While there is work within SAP to rethink SNC and use the assets purchased with Ariba to build multi-tier capabilities, the progress is not encouraging. At the time, I was a junior Gartner analyst. was controversial.
As an analyst in the supply chain market for 15 years, I have written many articles on best-of-breed technology companies purchased by a larger company. The initial software product release name was Real-Time Forecasting. DS replaced rules-based forecast consumption with better math (statistics and pattern recognition).
It was a story where people believed that functional excellence leads to supply chain superiority. Year after year, well intentioned people toiled against improving metrics that reduced, not improved, the effectiveness of the supply chain. Metrics comparison of Kellogg Co. You got it! vs. General Mills, Inc. A Case Study.
By purchasing planning and transactional systems for a common vendor, they had one throat to choke and they were familiar with the architectural elements. In addition, I am now done with the page proofs for my new book, Metrics that Matter. Instead, he wants to drive supply chain excellence and build the metrics that matter.
Ask yourself, “Are your supply chain metrics bogging you down?” ” To manage a supply chain containing complex dependencies between teams, departments and partner companies across international boundaries requires a rich set of metrics. Functionally isolated metrics lead to sub-optimized supply chain performance.
The network senses, translates, and orchestrates market changes (buy- and sell-side markets) bidirectionally with near real-time data to align sell, deliver, make and sourcing organizations outside-in. It is about much, much more than Vendor Managed Inventory (VMI ) or Collaborative Forecasting and Replenishment. The Building Blocks.
These procurement technologies empower teams to move beyond traditional methods, using data-driven insights for smarter sourcing, demand forecasting, and risk management. Predictive AI, on the other hand, uses historical data to forecast potential disruptions, price changes, and supply chain risks.
Using POS Data for Improved Sales & Demand Planning By leveraging POS data, companies can additionally (and accurately) forecast future sales, which is crucial for demand planning. Improved Forecast Accuracy Since POS data reflects real consumer purchases, forecasts based on this data are more accurate.
Tight coupling of the supply chain forecast to the financial forecast will improve value. Demand latency is two-eight weeks delayed from consumption purchase to translate to an order. Organizations can align to drive value despite the allegiance to functional metrics. If you want to know future sales ask sales.
Keep in mind that a WMS may not be enough and you might need to add an Inventory Management System (IMS) , which focuses specifically on optimizing inventory levels, forecasting demand, and preventing stockouts or overstocking. Data-driven forecasting improves purchasing and cuts storage expenses.
When making discretionary purchases, I could look at my projection to make sure that if I made that purchase, I would have enough money in the bank, not only now, but at the end of the month when my mortgage and car loan came out. Then could I buy it? For me, this was game changing! What if I save my money this month?
Driving an excellent supply chain depends on how people are recruited and managed, processes, and the technology used. In the annual report where they report on their key performance indicators (KPIs), they don’t just report on core financial metrics and the NPS, they also have people metrics. Getting the Most out of People.
Available to Promise (ATP) Available to Promise (ATP) is a real-time inventory management metric that tells you how much of a product you can promise to customers without overcommitting. Supply chain managers use ATP to trigger reorders or adjust forecasts. Sales teams use ATP to give accurate delivery dates. Why is GMROI important?
On one extreme, there is an argument that forecasts are always wrong, “Why do them at all?” ” At the other end of the continuum is the argument that “ Forecast error is the most important metric to improve.” I do believe in demand planning, but most companies overstate forecast improvements.
Modern platforms pull data from a wide array of sources: ERPs, relational databases, Excel files, cloud apps, third-party providers, and beyond. Packaged Analytics, KPIs & Reports Ready-to-use reports, metrics, and dashboards that accelerate time-to-insight. They served a purpose but lacked flexibility and real-time relevance.
As the markets plummet, it is time to remind ourselves that demand is not a forecast. Traditional forecasting approaches are not adequate in a time of market volatility. In the real world, companies operate with a Mean Absolute Forecast Error of 24-60%, and have a bias of 9-40%. Markets drive supply chains.
The choices that must be made by the end of each round (where each round represents one month of play) include how much of each finished good to produce and how much of each raw materials to purchase at the various manufacturing sites. Screenshot of SCI IMPACT! Results Example. the importance of making decisions based on a strategy.
To drive global scale, companies need to design the supply chain to buy globally and execute locally. The company leverages globally sourcing strategies to buy products at a lower cost and then deploys some unique process logic to drive mass customization for retailers. Performance on the Supply Chain Metrics That Matter.
I was an avid student of supply chain excellence; and in this role, I watched as best-of-breed solution after best-of-breed solution replaced with more complicated technology. As a result, we can push and push on forecasting processes and not drive improvement. I worked first at Gartner Group and then at AMR Research. I was a skeptic.
By infusing intelligence into every supply chain touchpoint—from sourcing to shelf—AI is driving operational excellence, customer satisfaction, and exponential growth. Smart In-Transit Inventory Redistribution: Redirects shipments mid-route based on updated demand forecasts. ThroughPut.AI Here’s how ThroughPut.AI
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