Data Events Examples Replenishment 
Logistics Viewpoints
MARCH 27, 2024
MODEX 2024, held in Atlanta, Georgia, from March 11 to 14, attracted more than 35,000 attendees and featured over 150 educational sessions, keynote speakers, and networking events. Here are some of the examples that caught our attention. They can also work alongside humans or independently, depending on the task and the environment.
FreightWaves SONAR
SEPTEMBER 29, 2023
The COVID-19 crisis unveiled major issues within global supply chains and, as we have seen with SONAR freight data, volatility in the market. For those that make the right applications of freight data, the massive problems created by the pandemic could have been more easily mitigated.
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FreightWaves SONAR
MARCH 9, 2021
Data for data’s sake lacks value, especially in the view of the supply chain. And across the market, submitted data becomes rapidly outdated. And in some industries, outdated data can have disastrous consequences. For instance, take the value added by more accurate data in the health industry.
Logistics Viewpoints
APRIL 4, 2024
Data Normalization & Removing Bias Data normalization in the context of forecasting is the process of going from actualized sales, which may be biased by various factors such as weather or inventory availability, to an understanding of baseline demand that is stripped of the impacts of these demand drivers.
Logistics Viewpoints
JUNE 7, 2021
When companies implement a demand management or replenishment system, the goal is usually to improve customer satisfaction while holding less inventory. The implementation also involves leveraging weather data to improve forecasting. For example, a warehouse might have a big propane tank they use with forklifts that run on propane.
EazyStock
APRIL 20, 2020
Planned Events for Managing Forward Orders. A planned event is when your customer has a planned event where the future demand is known; for example scheduled repairs and maintenance. This gives you a number of benefits: Planned events, such as scheduled repairs and maintenance, can take place as planned.
EazyStock
OCTOBER 20, 2020
This keeps the data clean and easier to use for forecasting going forward. Look out for such trends in your historical demand data and adjust your forecasts accordingly. Qualitative factors: Add any qualitative forecasting factors into your data, such as sales promotions, competitor activity or external market events.
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