Rapid demand response forecasting techniques are forecasting processes that can incorporate key information quickly enough to act upon in real time by agile supply chains. Retailers and consumer goods suppliers are urgently trying to determine how changes in consumer behavior will affect their regions, channels, categories, brands and products during
Many of us are currently working from home and getting adjusted to this new way of working. If you’re an employee working on the shop floor of a manufacturing facility, however, working from home is not an option. Among the many hard decisions manufacturing leaders have had to make during
Today, many assets across multiple industries are becoming more instrumented and connected to enterprise platforms to provide additional insight into their health and operation. IDC estimates that Internet of Things (IoT) investment will reach $1.12 trillion in 2023. One important area for many industrial organizations that are focused in using
Is it getting harder and harder to find empty Excel spreadsheets cells, as you run out of columns and rows? Do your spreadsheet cell labels have more letters than the license plate on your car? Do you find yourself waking up in the middle of the night in cold
Almost everyone enjoys a good glass of wine after a long day, but did you ever stop to wonder how the exact bottle you're looking for makes its way to the grocery store shelf? Analytics has a lot to do with it, as SAS demonstrated to attendees at the National
According to the Price Waterhouse Cooper 2018 Global Economic Crime and Fraud Survey, the reported rate of economic crime is on the rise, up to 49% in 2018. That makes the use case I want to share particularly relevant, no matter what industry or sector you're in. This use case
As you will have read in my last blog, businesses are demanding better outcomes, and through IoT initiatives big data is only getting bigger. This presents a clear opportunity for organisations to start thinking seriously about how to leverage analytics with their other investments. Demands on supply chains have also
How do you explain flat-line forecasts to senior management? Or, do you just make manual overrides to adjust the forecast? When there is no detectable trend or seasonality associated with your demand history, or something has disrupted the trend and/or seasonality, simple time series methods (i.e. naïve and simple
There's been a lot of hype regarding using machine learning (ML) for demand forecasting, and rightfully so, given the advancements in data collection, storage, and processing along with improvements in technology. There's no reason why machine learning can't be utilized as another forecasting method among the collection of forecasting methods
When it comes to forecasting new product launches, executives say that it's a frustrating, almost futile, effort. The reason? Minimal data, limited analytic capabilities and a general uncertainty surrounding a new product launch. Not to mention the ever-changing marketplace. Nevertheless, companies cannot disregard the need for a new product forecast
