How much data is in your cup of tea?

What’s the link between making a cup of tea and your manufacturing process? Data. We look at how data management is vital to manufacturing (and tea making)

You can’t get a simpler manufacturing process than making a cup of tea.

Boil kettle. Put a teabag in a cup. Pour over hot water. Add milk. Stir.

It’s simple, yes. But if you really think about it, there’s a significant amount of information needed to make that tea look and taste the way it should. Water temperature, tea leaves, sugar or no sugar, type of milk (and – controversially – whether it goes in first*) ...

Get part of that information wrong and the end result won’t be what you expected.

The same is true of any manufacturing process. The data surrounding your methods, your components, your suppliers and raw materials effect the product you end up with.

Add cold water? Your tea won’t brew.

Buy budget teabags? The quality will be affected.

Use milk that’s past its use by date? It’s going to taste bad.

Whether you’re making a cup of tea or building a monster truck, it’s the same principle. Data can give you the information you need to make the right decisions, follow the correct procedures and get the results you want.

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The data you need, the data you don’t

But the data available and the data you need are not always the same. There’s data that’s useful to you, data that’s legally needed, and data that is superfluous. A successful data strategy knows the difference. It concentrates on collating data that ticks the right boxes and enables your data goals – whether that’s improving a product , making your manufacturing process more efficient or conforming to a new set of regulations – and works on making sure that data is fit for purpose throughout the supply chain, through initiatives like data quality and data governance.

In the tea making example, your goal is to make a perfect cup of tea. The use-by date of the milk is pretty vital data to make that tea drinkable. The brand name of the kettle probably isn’t. In manufacturing, collating data you don’t need won’t help you – but guaranteeing the accuracy of the data you do need is vital.

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Speaking the same data language

To benefit from that data, you need to be speaking the same data language as your supply chain. Units of measurement, material composition, component codes – whatever the data, you, your suppliers and, to some extent, your customers all need to understand precisely what that data means.

Say it’s the 3rd April, and you’re making a cup of tea. You check the date on the milk: 3/4/20 – good to use. Except, the date used on the carton is in a month/date/year format, not date/month/year – making that milk not so good to use.

The rise of specific data languages are helping manufacturers (and distributors) across every sector to address these issues. The likes of ETIM, aCl@ss and GS1 provide a master data standard for businesses to follow. Transferring all of your existing data to a new classification standard can be a lengthy process, but it is worth it as a data quality exercise – and it’s becoming an increasingly important step in any digital transformation.


Making data work for you

So what are you doing with the data at your disposal? Are you using it to create better products? Improve efficiency? Reduce costs? Streamline your supply chain?

Or are data management problems causing issues before you’ve even looked to the next set of possibilities?

With Comma, managing your data as a manufacturer or distributor – whatever systems and software you use – can be as simple as making a cup of tea. We’ve worked with manufacturers at every stage of their digital journey, driving them to achieve their data goals through data quality, data governance, technology implementation and data migration services. We connect data and people to create sustainable, long-lasting data strategies that make manufacturer’s ambitions a reality. 

If you want to talk about your data targets (or data troubles) you can contact us on +44 1926 911820.

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