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PATTERNS IN NATURE, MATHEMATICS (AND RE:SOURCE)

By Andrew Leighton | 22 October 2018

Charles Darwin encouraged us to find reasons for the natural patterns that occur in nature. The wonderfully named Sir D'Arcy Wentworth Thompson followed this by pioneering mathematical biology, paving the way for the scientific explanation of ‘morphogenesis’ - the process by which patterns and body structures are formed in plants and animals.

Some 60 years ago, Second World War code breaker Alan Turing used nothing but numbers and logic to explain how those patterns are formed. He proposed that two chemicals - an “activator” and an “inhibitor” - work together, like a pencil and eraser. The activator makes a stripe and the inhibitor shuts off the activator. This repeats, stripe after stripe after stripe.

Numbers can explain so much of nature, but it’s nature that brings those numbers visually to life.

I can’t claim this drove us to developing our charting tools in re:source, but, re:source does contain millions of rows of data and it’s this breadth and granularity that ensured we had to deliver simple visual representation of the data.

Annual chart patterns

We’ve been charting annual trade flow trends since we launched re:source and browsing through the apparel category dashboards brings out some fascinating visual patterns of apparel trade. (Note, all data represented in this blog post is trade value in US$.)

Below, we can see the gradual decline of exports from China for many of re:source’s apparel categories. 2011 appears to be the tipping point from growth to decline, which has been generally consistent across most categories:

Unclicking China from the charts reveals the growth in China’s wake from the likes of Bangladesh and Vietnam:

Delving into a couple of specific export countries also reveals some interesting trends. Take Ethiopia, for example:

Here we see the country rising from very little casualwear and formalwear trade in 2009 (US$4m) to US$33.5m in 2016.

Myanmar’s seen a similar success story, but viewed from re:source charts, it’s clear to see the ramp-up. Here’s pullovers and t-shirts, for example:

Monthly data charting reveals new patterns

With the launch of monthly trade data in re:source, we can now reveal some fascinating new patterns, largely unseen before at the broad category level we’re tracking. 

Here’s all apparel imports to EU, US, Canada and Japan. We can clearly see the seasonal patterns, generally ramping up in early summer and dropping back down in fall/autumn. Then rising again from late winter:

These seasonal ups and downs remind me of those “activators” and “inhibitors” that make up a zebra’s stripes!

By inverting the data from imports to exports we can see a similar pattern for example, exports from China:

But here we see the two ramp-up patterns naturally beginning earlier, from late winter/early spring and from fall/autumn. Clearly, we can see the shipping lag from export to import. We’ll be analysing these lags in detail, and we’ll be able to feed this data into our shipping lead times' methodology.

Hunting through re:source’s data dashboards has enabled me to step back and look at the patterns that apparel trade data flows create, rather than always being buried at the deep end, looking at specific data. Whether it’s seeing points in time when countries’ trade values, volumes or prices increase/decrease - and by how much, or identifying regular trade flow trends to help with planning strategy, re:source’s charts can help users see the wood for the trees - or the animal from its camouflage, so to speak!

We’re aiming to begin delivering the latest-available monthly trade data from US, EU, Canada and Japan as soon as it’s released. The next exciting phase thereafter will be for us to begin tracking monthly price trends by garment. We’ll have more news on that soon...


Tagged in this post: Sourcing Countries, Trade Data

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