With the increase in accessibility to production and quality data from the use of automation, the Internet of Things, and handheld devices manufacturers are finally able to gather and analyze data to improve their processes at a level hereto unseen before. However, with this seemingly limitless access data comes a new problem: having too much data. More and more companies are falling into the trap of collecting data for the sake of collecting data just because they can and this can actually be harmful to a business. As Douglas Fair states in his article “Drowning in Quality Data: How to Rise Above”, “the insight gleaned from data that is what actually benefits the business”. This means that along with optimizing their processes and machines on the manufacturing floor, manufacturers now also have to think about optimizing how they collect their data so that they are getting the most benefit from it.
When optimization the data collection process, it is important to ask these five simple questions when assessing whether or not they need to be collecting certain pieces of data.
- Why do we need to gather this data? What is the improvement we are trying to make with this data we are collecting?
- How will we use the data after collection? What are we going to do with it after we have collated it?
- Who will evaluate the data? Will it be automated or will we be dedicating personnel to it? Do we have the labor available right now to handle it?
- What is a reasonable amount of data to collect? Can we defend why we need as much as we do or could we do the same thing with less?
- How frequently do we need to collect the data? How often are we analyzing and using the data to make decisions? Do these coincide with each other well?
At the end of the day, the only sure fire way to make sure you don’t fall into “data gluttony” is to check yourself and ensure that you are collecting data for specific purposes, using all the data you collect, and acting on the insights gained from the data to improve your bottom-line.
- With data becoming so centric to operations now-a-days, are we going to start seeing roles dedicated to data analysis on site at plants? How will this affect the way plants are run?
- What are the costs associated with “data gluttony”? Is it really as big a problem as Fair makes it out to be?
- How long does the process of optimizing data collection take? How often should companies review their data collection process to ensure they aren’t collecting useless data?