Why forecast sales?
Humans have the magical ability to plan for future events, for future gain. It’s not quite a uniquely human trait. Because apparently ravens can match a 4-year-old.
An abundance of data, and some very nice R packages, make our ability to plan all the more powerful.
A couple of months ago we looked at sales from an historical perspective in Digital Marketplace. Six months later. In this post, we’ll use the sales data to March 31st to model a time-series forecast for the next two years. The techniques apply to any time series with characteristics of trend, seasonality or longer-term cycles. Continue reading “But can ravens forecast?”
With tensions heightened recently at the United Nations, one might wonder whether we’ve drawn closer, or farther apart, over the decades since the UN was established in 1945.
We’ll see if we can garner a clue by performing cluster analysis on the General Assembly voting of five of the founding members. We’ll focus on the five permanent members of the Security Council. Then later on we can look at whether Security Council vetoes corroborate our findings. Continue reading “An East-West less divided?”
Revisiting an old post
Last September I wrote a post entitled Is the Government realising its ambition for SMEs on G-Cloud? Six months on, I wanted to revisit and update this article, fold in a second Digital Marketplace framework, and share the R code here. Revisiting an old post also provides an opportunity to see if one can simplify and improve older code. Continue reading “Digital Marketplace. Six months later.”