Arkieva Supply Chain Link Blog.
Creating the link between better supply chain planning and decisions.
RECENT POSTS
What-if Wednesday: Seasonal Model Forecasting with Seasonal Methods
Seasonal method is a regression method that fits a linear trend along with sine and cosine curves. These sine and cosine portions of the regression can fit any seasonal deviations from the linear trend. Robust seasonal method also fits a trend along with sine and cosine curves, however this method uses linear programming to fit a seasonal series in a way that compared to the regular seasonal method is less likely to be thrown off by noisy values that depart from the trend or seasonality.
Only the Shadow Knows – Identifying the Unobvious with Supply Chain Modeling
While reading a wonderful article titled “Linear Thinking in a Non-Linear World – the obvious choice is often wrong” in the May-June 2017 issue of Harvard Business Review, I was immediately transferred back to the early 1980’s and theme of the IBM Advanced Industrial Engineering department – “only the model knows.”
5 Reasons Why the Amazon-Whole Foods Merger Will Reshape the Supply Chain World
What does the Amazon-Whole Foods Merger mean for the Supply Chain world? Amazon, in a revolutionary move, has acquired Whole Foods Market and its 436 stores nationwide for a cool $13.7 billion. The news has rocked the world of retail with several competitors such as Walmart, Target, and Costco losing shares by 4% - 9% in the aftermath
Key Steps for Measuring, Monitoring, and Improving S&OP Performance
You cannot improve the performance of something that is unpredictable. S&OP processes allow businesses to create a predictable approach to managing the supply chain. In this week’s ‘Supply Chain Talk,’ Arkieva CEO Harpal Singh discusses some of the key steps for measuring, monitoring, and improving S&OP performance.
Establishing a Proactive Supply Chain Using Early Warning Indicators
While major supply chain consequences aren’t usually life threatening, you can bet they have a huge impact on you, your organization, and your customers. Your goal is to prevent problems early but it doesn’t always happen.
How Does a Demand Forecast of Zero Impact Your Forecast Accuracy?
For most businesses that rely on demand forecasts for supply and capacity planning, improving demand forecast accuracy is critical. There are many methods to measure forecast bias and the accuracy of supply chain forecasts including using statistical methods like the Mean Absolute Percent Error or MAPE that we’ve discussed in our previous blogs.
The S&OP Process Improvement Illusion – Are We There Yet?
Almost three decades ago Sales and Operational Planning (S&OP) became the innovation in manufacturing and supply chain. When S&OP came about in 1987 as a concept, we did not yet have the internet much less the “internet of things.”
What-if Wednesday: Holt-Winters Multiplicative Forecast Damping Factor Simulation
In the previous What-if Wednesday posts, we experimented with the three parameters of the Holt-Winters Multiplicative method, namely; alpha, beta, and gamma. This time we are going to run similar tests by adjusting damping factor for the Winters Multiplicative method.
How to Predict Sales Using Markov Chain
The Supply chain is driven by demand, supply, and inventory planning. Under demand planning, the importance of sales forecasting is undeniable. It provides a basis for the production process regulating quantities, inventory and maximizes the efficiency of the resources available.
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