Forecast Errors
Volume 2, Issue 17, April 27, 2015
A forecast error is the difference between the actual and predicted value. The consequences are expensive inefficiencies that can be resolved with lean manufacturing technology.
Forecast Errors as Wrong as the Forecast
The Economic Detective blog recently shared some important data. James Montier claimed that in the US analyst community, the forecasting error was 47% over 12 months and 93% over 24 months. To have forecasting errors almost as big the forecast itself, begs the questions as to why we have them at all. Granted, predicting the direction of a specific security price might be difficult, given the multiplicity of variables and innate complexity of expectations, but even broader market predictions have turned out to be mostly incorrect. Read more.
Electricity Reserves Similar to Manufacturing Inventory Reserves
The Union of Concerned Scientists recently noted that while a variety of facilities generate electricity, the location of these electricity generators – and their distance from end users – varies widely. Certain types of power plants, such as coal and nuclear power plants, have little short-term flexibility in adjusting their electricity output; it takes a long time to ramp up or down their electricity output. Other plants, such as natural-gas fired plants, can be ramped up very quickly, and are often used to meet peaks in demand. At any given time, there is also always a “reserve margin,” a specified amount of backup electricity generating capacity that is available to compensate for potential forecasting errors or unexpected power plant shutdowns. Electricity demand, supply, reserve margins, and the mix of electricity generating technologies is constantly monitored and managed by grid operators to ensure that everything runs smoothly. Manufacturers play a similar game with inventory. Read more.
Manufacturers Can Predict Inventory Unlike the Wind
The wind is unreliable according to Smart Energy. To reduce forecasting errors there are new grid codes enforced. Unscheduled-interchange charges (charges for under-generation based on the frequency at the time) and penalties are applicable for output above +/- 30% of the scheduled. Wind forecasting is inherently unreliable. Manufacturers are not subject to force de jour in most cases. View here.
Data-Driven Analysis to Mitigate Forecast Errors
The Operations & Supply Chain Club reported that companies like Union Pacific Railroad use thermometers and ultrasound to capture data about their engines and send it for analysis to identify equipment at-risk for failure if any. The world’s largest multi-carrier network for the ocean shipping industry-INTTRA uses its OceanMetrics application to allow shippers and carriers to measure their own performance. Companies are also using telematics and big data to streamline trucking fleets. GE believes these types new capabilities can contribute $15 trillion to the global GDP by 2030 by using systematic and data-driven analysis. Ultriva supports real-time supply chain visibility. Read more.
Move from forecast errors to demand driven accuracy:
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