3. Comparison to Plan

Industry 4.0 Blah Blah Blah

One of our biggest bugbears as a company is the over-complicated terminology surrounding Industry 4.0, an unnecessary term in itself considering most technologies under the I4.0 umbrella have existed for decades anyway (for a longer gripe, you can read the blog post here). But if you can't beat them, join them...kind of.


In Spring 2020, before the world turned upside down, we developed a series of features that used the data captured in our software to make predictions about how long orders would take. If you like jargon, our software takes big data captured from Internet of Things devices, stores it on the cloud, and uses artificial intelligence and machine learning to process data through advanced algorithms in real-time to create analytical insights for your workforce. And if you don't like jargon, we’re able to tell you how long a planned order is likely to take, and whether each of your ongoing orders is likely to be on time, or not. Useful, eh.

Comparison to Plan

Whilst planning the specific direction and features of the To Me, To You project, we had a catch-up with one of our friends at a major aerospace company. They spoke about a current blind spot in their supply chain operations being an inability to identify whether their orders were still on time. If orders are late from suppliers, this can result in a chain of delays which can ultimately delay multi-million pound projects, making a system whereby orders can be kept on time vital to the efficiency of a supply chain. So, we spoke to several other manufacturers about this, who all identified this 'Comparison to Plan' value as something of great need. So. we started to turn it into a larger part of the To Me, To You project.


New Features, More Usable Outputs

In the current version of our intelligence, we can identify how long an order will take to an accuracy of a day, making it suitable for longer processes taking multiple weeks. Unfortunately though, this makes it less suitable for shorter processes. So, the first step will be to add features to Elements Docket to increase the detail and accuracy of the predictions, making it useful and usable for manufacturers with orders long and short. The first of these features, which is due to be released in June, is a pausing functionality allowing users to pause orders, allowing users to omit time spent going for lunch and finishing for the day. We will then go one step further and automate the more predictable pauses, by adding shift patterns and working days as part of a larger company details section. This will mean that orders that start at 2pm on a Friday (with a 5pm shift end) and finish at 11am on the Monday (with shift starting at 9am) will recorded as taking 5 hours rather than 64 hours. This level of data will allow us to provide more accurate predictions of how long an order will take before it is started, and it will allow us to create accurate comparison to plan values, meaning that as a supplier you will be able to quickly identify orders that are slipping behind, and as a customer you will be able to view whether you're likely to receive your items on time and in the expected condition.


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To keep up to date with the To Me, To You project, find out about our latest blog posts by following us on Twitter and LinkedIn. To see our current intelligence in action today, sign up for a free Elements Docket account or book your own personalised demo with one of our team.