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Data Strategy

Data Strategy for Metals Manufacturers

Your factory produces data constantly. Shift reports, inspection results, order histories, material certifications, supplier records. Most of it is scattered across spreadsheets, email inboxes, and filing cabinets.

A data strategy is the plan for changing that. It covers what data you collect, where you store it, who can access it, and how you use it to make better decisions.

For metals manufacturers, the priorities are clear:

  • Data governance: who owns each data type, and who is allowed to change it
  • Data quality: are your material records accurate, complete, and traceable?
  • Data security and privacy: protecting customer order data and supplier certifications
  • Business intelligence: turning production records into dashboards that help you manage
  • DataOps: keeping your data pipelines working when systems change

You do not need a data science team to start. You need a clear picture of what data you already have and what decisions you wish you could make faster. Start there.

For metals manufacturers considering new software: your data stays yours. GoSmarter is EU-hosted and compliant with the General Data Protection Regulation (GDPR), your records are exportable as CSV at any time, and there are no exit fees. The data-strategy questions worth asking before any new system: where does my data live, what happens to it when I leave, and does the vendor make it easy to find out? Those should have clear, written answers before you sign anything.

Posts in this section cover governance frameworks, data platform choices, and the practical steps that turn scattered records into a working system.

Microsoft Build 2021 announcements for manufacturers

Microsoft Build 2021 is kicking off and whilst it tends not to be as announcement heavy as Microsoft Ignite, it’s still got some great things for manufacturers to pay attention to. This post gives a quick run down of the most important stuff you need to read about. Enjoy!

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Smart Manufacturing is all about Real-Time Data Analytics

Manufacturers are spending far too much time on data entry or looking at stale data which is hindering growth. Here are seven ways real-time data can turn things around.

Read More: Smart Manufacturing is all about Real-Time Data Analytics

Announcing GoSmarter In A Day

Our GoSmarter In A Day workshops solve one problem like processing Accounts Payable incoming invoices to demonstrate the value such automation can bring.

Read More: Announcing GoSmarter In A Day

European AI Act

The European Commission proposes new rules and actions aiming to turn Europe into the global hub for trustworthy Artificial Intelligence (AI).

Read More: European AI Act

Data Champions are critical to your success in digitally transforming

Manufacturers need Data Champions to help them succeed in today’s digital world. To learn more about how you can find your Data Champion for your team or company, read on!

Read More: Data Champions are critical to your success in digitally transforming

Reports supported by AI & automation

Data compilation for reports created by experts is usually more time consuming than writing the valuable content. Using AI and no-code automation techniques, data collation and visualisation can be greatly streamlined, letting staff focus on the value.

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Checklists make everything better - including responsible AI!

Building a checklist to cover the six key areas of responsible AI can drive better outcomes and returns for your business. Start with the list of areas as a discussion aid and grow your checklist with use.

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Using AI to make your warehouse operations smarter

You can benefit from lower overheads by using AI to manage stock levels, whilst building a more scalable warehouse operation that is safer for employees, using AI.

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Detecting defects with AI - a computer vision challenge

With the pace of output on machines ever increasing, quality control becomes a lot tougher. Using AI to detect defective products sooner can help scale your quality processes and avoid significant stops.

Read More: Detecting defects with AI - a computer vision challenge

How can Digital Innovation Hubs support SMEs to adopt AI?

A workshop on “AI-standardisation landscape & the role of Digital Innovation Hubs (DHIs)” discussed the role hubs can play in supporting the uptake of AI among SMEs and how they can help technology frontrunners.

Read More: How can Digital Innovation Hubs support SMEs to adopt AI?