Sales and Operations Planning (S&OP) is typically a monthly process. Through a series of detailed planning steps, and usually three meetings, companies define a plan to deal with what they think they can do to meet the demand given their supply and other constraints.
Key Point: A Sales and Operation Planning (S&OP) meeting is a meeting to design the future course of a business. Yet, too many companies spend too much time talking about the past or the current period. I recommend using about 60-70% of the time discussing the future. The (S&OP) process consists of a lot of
Key Point: Coefficient of Variation is not a perfect measure of forecastability. However, if used properly, it can add value to a business’s forecasting process. In the world of forecasting, one of the key questions to consider is the forecastability of a particular set of data. For example, a salesman might consistently be better at
You have a favorite forecast accuracy metric(s) you’ve been practicing within the organization for a while, and now you think you are ready to bring it to the Sales and Operations Planning (S&OP) meeting as a Key Performance Indicator (KPI) of your demand planning process. But you are not sure exactly how to go about
I saw this news article on CNN (here) about our planet’s earth bigger, older cousin. Quite an interesting discovery if you ask me. However, it got me thinking about the family tree of Mean Absolute Forecast Error (MAPE), a subject that I am a little bit familiar with. A few weeks ago, I wrote about
I spent some time discussing MAPE and WMAPE in prior posts. In this post, I will discuss Forecast BIAS. Forecast BIAS can be loosely described as a tendency to either Forecast BIAS is described as a tendency to either over-forecast (meaning, more often than not, the forecast is more than the actual), or under-forecast (meaning, more often
A few weeks ago, I talked about the Supply Chain of Belgian Beer (click here to read that) and shared some trivia. Some folks suggested a follow up on frites or french fries. I will share a few more interesting things I learned about Belgium during my trips there. And just to be upfront, unlike
In our line of work at Arkieva, when we ask this question of business folks: What is your forecast accuracy? Depending on who we ask in the same business, we can get a full range of answers from 50% (or lower) to 95% (or higher). How is this possible? Imagine a management team being given
Key Points on MAPE: Mean Absolute Percent Error (MAPE) is a useful measure of forecast accuracy and should be used appropriately. Because of its limitations, one should use it in conjunction with other metrics. While a point value of the metric is good, the focus should be on the trend line to ensure that the
Research shows that a majority of mergers fail. A recent study put the percentage as high as 83%. As one would imagine, there are various reasons for this high rate of failure. However, the reasons can be divided into two main groups: