Logistics Viewpoints
MARCH 27, 2023
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!
ToolsGroup
MARCH 3, 2022
Despite knowing all this, too many retailers ignore the impact of weather and this adds error to plans and demand forecasts. And even though meteorology has come a long way, weather is a notoriously fickle and uncontrollable factor, and no forecaster can reliably predict it beyond the next few weeks. It all evens out in the end.
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SCMDOJO
SEPTEMBER 8, 2023
This blog explains The Key MRP Metrics in Supply Chain whcih every supply chain professional in Manufacturing or Distribution Businesses. The metrics that underpin MRP could be described as the balls in this juggling act. This article takes an in-depth look at the crucial metrics every supply chain professional needs to know.
SYSPRO Smarter ERP
MARCH 15, 2023
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.
Logistics Viewpoints
JUNE 29, 2023
It is crucial for organizations to understand the importance of Purchase Order collaboration to effectively manage their direct spend, optimize operations, and mitigate risks. From natural disasters to geopolitical tensions and the ongoing COVID-19 pandemic, supply chains have been significantly impacted.
Precoro
NOVEMBER 13, 2023
However, only 30% of CPOs claim they have achieved their cost-saving targets in 2023. One of the ways that procurement teams improve this figure is by tracking and improving the purchase price variance (PPV) metric. Why Is Purchase Price Variance Important?
Logility
MARCH 6, 2020
Machine Learning for demand forecasting has matured to a level of accuracy, transparency and replicability that translates into transformative results, including in these five areas: Accuracy, transparency, thoroughness of analytical options and results. Let’s take a closer look at each one. Accuracy and transparency.
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