Revisited: how to get started with industrial data collection (free white paper)

Jolan De Cock on

Factory chimneys through a picture frame

Are data silos, paper processes and manual data collection putting the brakes on optimising your operations? Due to popular demand, we’re making our white paper ‘How to get started with industrial data collection’ available to anyone. Download your free copy here - no email adress required.

Your free guide to get started with industrial data collection

So you want to eradicate paper, disparate data sources and manual data collection? Automated industrial data collection is the backbone of any IIoT initiative. It involves gathering data from machines, equipment, and IT systems to improve plant operations, reduce downtime, and optimise asset usage. The primary goal: leverage this data to produce smarter and drive business value.

Three years ago, we released our comprehensive white paper, ‘How to Get Started with Industrial Data Collection’, providing an eight-step checklist for launching your IIoT journey. As the process industry continues to evolve, the insights and strategies outlined in this white paper remain not only relevant but crucial for companies looking to harness the power of their industrial data.

Grab your free copy now!

And get started with industrial data collection

What you’ll read

Download our free white paper and follow this 8-step checklist to successfully kick off your industrial data collection project. Here’s what you can expect:

1. Assessing equipment and IT systems

This foundational step of evaluating your current equipment and IT systems ensures that you understand the capabilities and limitations of your existing setup. This knowledge is crucial for integrating new technologies effectively.

2. Mapping pains, challenges, and goals

Clearly defining your objectives and identifying pain points will help you in aligning IIoT initiatives with business goals. It ensures that projects deliver tangible benefits, such as improved efficiency and reduced downtime.

3. Setting out a Proof of Concept (PoC)

Starting with a small, manageable project allows you to test your IIoT solution and demonstrate value quickly. This approach not only minimises risks, but also builds confidence within your organisation when moving the project forward.

4. Forming a dedicated project team

A small, cross-functional team with a clear mandate can drive your data collection project more effectively than a large, unwieldy group. It ensures focused effort and quick decision-making. Discover best practices and roles.

5. Choosing the right software vendor

What is the best technological solution for your needs? Find out why opting for generic, versatile and open tools over industry-specific solutions ensures scalability and long-term flexibility, and is key to avoiding vendor lock-in​.

6. Deciding on cloud or on-prem storage

Your decision between cloud and on-premises storage impacts scalability, security, and cost. Therefore, when implementing industrial data collection strategies you must carefully assess your options. Read actionable advice.

7. Involving your machine suppliers early

Engaging with machine suppliers early provides access to essential technical details and speeds up the integration of older equipment. Find out how to ensure compatibility with IIoT standards and avoid costly project delays.

8. Choosing your software integrator wisely

Selecting an experienced integrator is crucial for project success. But how do you tell which integrator is the best fit? Get actionable advice on what to look out for in a vendor, on top of a proven track record and deep industry knowledge.

Data collection white paper

Get actionable insights to ensure project success

As the process industry continues to evolve, our white paper remains a critical guide for successfully launching and managing your IIoT project. By revisiting these timeless strategies, you can ensure that your project efforts are aligned with current best practices and positioned to deliver significant business value.

Not convinced yet?

Find out how we tackle data collection using Factry Historian

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