Keep Cribbing or Find Solutions
There was an interesting technical issue at a client using SAP SCM with substantial investment in demand planning using SCM tools. After some googling, I landed on this blog … Read More
Forecast Error Benchmarking Across Various Industry – Survey Results
we started conducting the survey across supply chain and demand planning professionals from various industries. This survey was meant to compile information about their pain points, forecast error metrics they use, industry they work for, and who owns the demand planning function. We are publishing the first installment of the results from this survey in this newsletter.
As expected one of the metrics used by 52% of the respondents is WMAPE or volume weighted MAPE, calculated as Sum of Absolute errors divided by sum of actual demand.
Demand Planning = Unlocking Stat Models + Engaging your Sales Force!
Demand Planning Net offers a service called Usability consulting where we improve the usability of your statistical tool by performing model tuning, setting the right tool parameters and finally training the planners in statistical modeling. Demand Planning Net has worked with clients helping them leverage the statistical features in their software applications.
• Most applications inherently have the analytical power to develop effective baseline forecasts.
• Most software tools allow you to create exception thresholds so you can streamline the forecasting process by exception.
How Good Are Your Stat Models In APO DP?
Find out and bench mark with your peers from companies such as Michael Foods, Chemtura, Newell Rubbermaid, Johnsonville Sausage at our upcoming workshops. With very strong response for our September … Read More
Demand Segmentation and Forecastability Analysis
We segment you…………
Forecast Reconciliation and Proportional Forecasting – My e-book On Amazon.com
First e-book on forecast reconciliation and proportional forecasting released through Amazon.com.
Silver Bullets To Tackle The Intermittent Demand Problem
The first step to handle intermittent demand should not be looking for a magical statistical model to solve our problems. We should question the reasons for intermittent demand and come up with a business angle to formulate solutions. These may include integrated demand-supply strategies as well as sales intelligence on customer ordering patterns. Applying Croston’s models and discrete distribution models should be the last resort to address intermittent demand problems.
The Use of The NORMSINV Function In Safety Stock Calculations
There was a question on Linked in about the use of the NORMSINV function in Excel. Initially the poster mentioned the NORMSDIST function. But for safety stock purposes, you … Read More
Is Statistical Modeling an After thought?
I have been preaching Usability for the past few years.
Put together fine tools – But help the users in making the transition to the tool – give them better understanding – Make the new tool more usable!
Give them the reports they need. Provide them an exception based workflow!
APO has good statistical models. They will help you move the peanut forward but only if they are understood and leveraged.
We just re-launched the marketing campaign for our Usability Consulting. Model tuning and model matching to product profiles are important elements of the Usability training.
Once implemented the Usability project will harmonize the use of models across planners from various geographies for the same business/product family. There will be streamlined work flow.
Slow Moving, Short History and Intermittently Demanded Products – How To Forecast?
Every time we come across a slow moving item, we have to spend quite a bit of time analyzing the different factors to come up with a forecasting strategy that … Read More