We are excited to announce that we are rebranding Arkieva to fuel growth, strengthen our position in the market, and continue to be a recognized leader in the supply chain industry. Over the past few years, we have been relentlessly focused on solving the most complex planning challenges through simple, intuitive, end-to-end solutions leveraging our best-in-class data scientists, software developers, and supply chain optimization consultants.
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.
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.
We have all seen it in the news. Covid-19 outbreaks, labor shortages at the port as well as in trucking, and port delays coupled with high demand from consumers are causing major supply chain issues. Shipping containers are in short supply, or perhaps a better way to say it is that they are waiting to be unloaded or loaded resulting in a shortage. In this blog, let us try to enlist some possible future impacts of this situation. Let us look at it from the perspectives of the different players in the supply chain.
Everyone is talking about supply chains these days. Ever worsening weather, a global pandemic, and a labor shortage have generated a perfect storm that has pushed global supply chains to their breaking point. I propose that the problem has been building for some time and this perfect storm may just be the reset we need.
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...
In today’s blog, we will share some examples to help Inventory Planners explore different methods available to calculate Demand Variance and decide which method is best suited for their products and businesses.
When many companies produce products, they also produce by-products. Often, they have no use for these by-products and so they are discarded or sold off as scrap. But companies that embrace sustainability do not accept this fate. Some companies have found a way to turn their waste streams into revenue streams...
Learn the best approach to setting forecast accuracy targets and how to set expectations for your management team.
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.