Forecasting | Arkieva Supply Chain Blog - Page 2

Category: Forecasting

Automated Forecasting: Finding the Handshake Between Demand and Supply

Having a good forecast is essential to demand planning. It ensures the right goods are produced at the right time and reach the right customers. What’s more is that demand planning is situated at the start of your supply chain, playing an integral part in a streamlined supply chain.

How “Forecastable” is Your Data? It’s Complex Anyway You Look at It

These “key tools” balance a need for simple with a need to handle the complexity of SCM – following the IBM adage – complexity exists whether you ignore it or not, best not to ignore it.

Going Beyond Historical Data for Forecast Accuracy

Our focus in this blog series has been to establish forecast accuracy targets. In very general terms, the goal should be to add value to the business through the forecasting process. We have however focused on the forecast value add and using that to create a minimum acceptable forecast accuracy target in the previous blog. Now we will take that a step further and talk of ways of improving it.

3 Aggregation Mistakes When Reporting Forecast Accuracy

It is important to measure and improve the forecast accuracy at the right level of aggregation. If you measure at too high a level, your accuracy picture will look better than what it needs to be as the data at high (aggregated) levels is more forecastable. By contrast, at too low a level...

How Forecastable is Your Data?

Having access to an accurate forecast is very beneficial for businesses. If used correctly, it can provide better margins, increase market shares, and many other positive results. At a more tactical level, it can help reduce the costs associated with meeting the customer demand and make the supply chain more efficient.

Using Coefficient of Variation to Drive Safety Stock Related Decisions

In a previous blog post, we discussed how a high or low value of Coefficient of Variation (CV) impacts the first or second term of safety stock. Today we decided to put this to the test using real customer data - here we will discuss our findings.

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