Tracking and understanding data in today’s economy, especially for heavily regulated industries that might be subject to an audit, is incredibly important. Every business in every industry generates data. If you are tracking this data and using it to help understand your situation and drive decision-making about your future, that’s good.
If you are not collecting the data, not analyzing the data properly, not basing decisions on the data or, worst of all, ignoring it completely, that’s bad. In 2021 and beyond, companies that use data well will separate themselves from companies that don’t. Data driven decisions will be a big factor in who rises to the top of competitive industries.
In regulated industries, such as food and beverage, pharmaceutical, hospitals and healthcare, medical devices, aerospace, manufacturing, and more, additional considerations come with data collection and use. In these industries, companies need to use data in a way that complies and marries well with the complex regulations they deal with every day. Here are four data best practices for regulated industries.
1. Regularly evaluate your data tracking processes
The point to collecting data is to use that data to constantly improve your processes to be the best company you can be. This process improvement should include the processes you use for the data collection as well. You can use several metrics to evaluate your data tracking process to assess its efficiency and determine if you are getting the best and most relevant data you can to help you make decisions.
These data tracking metrics include looking at things like the ratio of data to errors to find out what percentage of your data contains errors. Data transformation error rates track data that becomes problematic when transferred to a different format. You can also look at data time-to-value, which analyzes how long it takes you to get real value from the information you collect. In addition, data storage costs can fluctuate as well, so you should periodically reevaluate that number.
2. Follow IQ OQ PQ processes
Any company in a highly-regulated industry should be familiar with IQ OQ PQ as a quality assurance process, but many may not think of it in terms of a data collection process. That is exactly what it is though. The process of qualifying all new equipment and systems involves accurate record-keeping for accountability and is the basis for a successful data collection program. Dickson’s IQ OQ PQ guide explains how proper collection and storage of data is foundational to quality assurance.
IQ OQ PQ is a three-step process of qualifying any new equipment or systems before they are integrated into your overall process. The first step, installation qualification (IQ) is all about ensuring the product meets the specs and is installed correctly at the beginning of the process. This step is followed by operational qualification (OQ) where the machine’s capabilities are tested and appropriate parameters are established.
In the third step, performance qualification (PQ), the boundaries of the equipment are tested and it is integrated into the real-world process it will be a part of in your company. Along the entire path of IQ OQ PQ, data is collected, recorded, and analyzed both about the function the equipment performs and the equipment or system itself.
3. Prioritize Data Security
It should not be news to any company that data security is of the utmost importance in 2021. In regulated industries, data security is more than just important, it is a mandated part of what they do. Data security in 2021 should be a top priority, especially with the rise of cyberattacks during the pandemic. These cyberattacks have targeted work-from-home employees as well as many of the regulated industries we are talking about here such as healthcare and pharma companies.
Prioritizing data security means putting together a comprehensive plan for security and making sure it is executed at all levels of your organization. It includes using the proper, most up to date data management software and anti-virus programs. It also means training employees on data best practices and warning them about social engineering attacks like phishing scams. All this cannot guarantee that an attack won’t compromise your data, but it will put the company in the best position to prevent an attack.
4. Make Sure Data is Easily Accessible
While you want to make sure that people outside your organization do not gain access to your data, making sure that it is available to everyone (or as many people as possible that it makes sense for) in your organization is important. The whole point behind collecting data and using data analytics is to enable your organization to make the best data-driven decisions possible. If parts of your organization do not have access to the data, they will be frozen out of the process. This means your organization can miss out on exciting new ideas at best and at worst will have parts of the company making decisions without consulting the relevant data.
You can create easy access to data without compromising security. Giving everyone a unique username and password to access relevant data allows you to track who is accessing data if a problem arises. You can also set up restrictions on regulated data, such as personally identifiable information about patients in healthcare. Once everyone has access, there should be a top-down culture created where everyone is encouraged to use data-driven decisions to generate the best outcomes possible.
Regulated industries face challenges that other industries don’t. This is because in these industries, following the regulations is key to keeping consumers safe as well as not running afoul of regulating bodies and facing costly fines or shutdowns. These regulations do not have to prevent companies in these industries from properly using data to become more successful. By following a few best practices in 2021, such as reviewing your data tracking processes, using IQ OQ PQ, prioritizing data security, and allowing appropriate access throughout your organization, you can turn this year into a data filled and data driven success.