In the increasingly high-tech, high-touch realm of manufacturing, actionable data is an ever-growing factor in business and technical decision making. It’s tempting to think that data collection can be a fully automated process, especially in the age of IoT and AI.
Five Steps to More Effective Operational Data Collection
Alex Brown, Technical Editor | Form.com
Access to accurate, timely data regarding safety, quality, maintenance and performance metrics has never been more important. Manufacturers need up-to-the-minute information from the factory floor to operate with the agility today’s volatile environment requires. Foreknowledge of surfacing trends, critical issues, and operational efficiency can make or break a manufacturing organization.
However, many organizations struggle to get their data collection balance right. Often the challenge is not a lack of access to data but rather the ability to collect the right data and to put it to work in the right way. Below, we’ve gathered steps to help you identify vulnerable areas in your inspection processes and increase the structure and efficiency of your data collection operations.
1. Consider the kind of data you need to collect
Most manufacturers already gather massive quantities of data on a regular basis. Prioritizing information is the first step in better data collection. Begin by classifying what kind of data you’re collecting. This will help you define the most significant data. For example, if you’re collecting safety inspections, your key data will involve the number of violations per quarter, the number of accidents in a year, and so on.
2. Set goals for your data
Establish goals for your data. In the above example, the goal of collecting safety data would be to prevent accidents. The purpose of collecting customer surveys would be to improve satisfaction and enhance sales. Likewise, gathering performance metrics would strive to improve your manufacturing processes. Once you’ve defined your goals, determine how you will measure your success.
A great way to do this is to outline your top-level organizational goal, such as “improve overall workplace safety,” and allow each division or team to set their own OKRs (Objectives and Key Results). Each team can then prepare a numerical stretch goal and compare their outcomes against it, like reducing the number of safety incidents or accident-related downtime by a set amount. Setting clear objectives ensures that you’re collecting the right data and sets you up to get the most out of analyzing it.
3. Standardize your process
In manufacturing, consistent processes are at the core of most operations, and data collection should be no different. Define a consistent, reliable process for collecting data. Your data collectors should all do the job in the same way. Variance in practice can lead to erroneous numbers, and volatility makes data unreliable or unactionable. It’s critical to ensure that everyone collecting data on your behalf knows the procedure and is familiar with the organization’s standards.
4. Optimize your tools
Better manufacturing data collection begins with using the right tools and tuning them for peak performance. Highly customizable, mobile-first electronic forms are key for collecting timely and actionable data. And, as with any tools, optimizing your forms will drive better results. Here are a few tips for designing forms that will help your data collectors make better, smarter choices:
Simpler is better. Whenever possible, keep forms short and to the point. Save reference information for other sections. Don’t cram dozens of questions on a single page. Single-column layouts are best because they show a clear, unmistakable trajectory to the finish line.
Make forms self-explanatory. For an experienced worker in the field, the content of your forms should provide all the information they need to get the job done. Try to refrain from referencing external sources. When in doubt, include examples of the standard within the form. If you’re using a mobile forms app, be sure to clearly label where help sections can be accessed.
Break up complex questions. If you have conditional questions, or questions that should only be answered based on a previous question’s response, keep them separate and clear. If you’re working with digital forms, this is a great place to exercise conditional logic.
The cleaner and easier-to-understand your forms are, the higher quality your data will be. If your employees are finding forms hard to understand or feel that they’re inefficient, talk to them about potential changes. Better yet, perform user testing to determine how long it takes to fill out a form and which sections prove to be problem areas. Often, it’s the people closest to your data collection processes who know where the weak points lie.
5. Make data actionable
One of the most significant parts of data collection is also one of the most overlooked—where data goes once it’s gathered. Workflows help you ensure that data is actionable right away. When you route data directly into the next logical step, you can dramatically improve productivity.
If a regular inspection uncovers a maintenance issue, that should trigger an automated chain of events. Built-in workflows can initiate a repair order, send an email to the relevant supervisor, and assign a task to the right person, all without any added human-to-computer interaction.
Instead of sending countless emails to get everyone on the same page, a workflow will automatically engage stakeholders. Automated workflows get straight to the point and forgo any unnecessary clarifications. Approvals, escalations, and follow-up tasks automatically trigger based on predefined conditions.
Bringing it all together
In the post-COVID-19 world, you can’t afford to miss critical inspection data, especially with so many new guidelines in effect. Data collection in manufacturing is vital to your success and crucial for your employees’ health and safety. Getting accurate data from the front lines will allow you to quickly pivot when necessary and make adjustments based on the circumstances. The best way to stay ahead is to shape your data collection processes based on what works for your organization. Make sure to use the right tools, define your processes, and put your data to work.
About Alex Brown
Alex Brown is the technical editor for Form.com. He writes regularly about digital transformation, data collection and mobile technology developments and adoption.
The content & opinions in this article are the author’s and do not necessarily represent the views of ManufacturingTomorrow
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