Date: August, 2019 | Category: quality | Author: Ryan Szporer

“Just” backing up data isn’t enough to keep data intact anymore. While it’s a necessary step and a good start at that, a backup means little if there aren’t adequate safeguards in place to protect the integrity of the data that might have to be recovered. Even if back-ups themselves are a safeguard, they must be seen as an asset in their own right. After all, it’s estimated 100 mb of company data is worth $1 million on average. Half the firms that cannot recover lost data in 10 days cannot recover themselves.

It just makes good strategic sense to have a backup plan in the most literal sense as a result. Here are the top five strategies to keep data intact, for the sake of keeping your data integrity intact:

1. Know What to Back Up

It’s not only files that must be backed up but programs, including Operating System software as well. After all, if a newer version of a program has been released, it may not be able to read your data.

The fix simply requires that an image, or a carbon copy of all critical information including programs and their data saved into a single file, be backed up. That way no synchronization issues arise, preventing you from using the data even if you may have successfully recovered it. It would be like having the keys to the wrong car. Only this car can’t be hot-wired to run.

There is an admitted caveat: If you upgrade your hardware, the image may no longer be compatible itself. So, an alternative solution would be to just stay up to date with your program versions and continue to back up data as you normally would (i.e., thoroughly).

2. Encrypt Your Back-Ups

It almost goes without saying in this day and age, information must be kept secure for its data integrity to stay intact. One way to avoid confidential information from being compromised is to encrypt it into code, which is of course standard practice. It’s a standard practice for a reason though, namely its effectiveness. As a result, it’s significant enough in importance to rank on this list.

3. Make Regular Back-Ups

You can’t simply back up data before an upgrade. Ideally scheduled for when there is low network activity to prevent slowdown, back-ups should be made every day, with daily snapshots taken as well to monitor performance. Furthermore, at least two weeks of daily backups should be kept at any one time, as it represents a manageable time frame in case a file does get lost or corrupted.

Meanwhile, once-a-month back-ups should be preserved for one year, while annual back-ups should be kept for seven years in case a governmental request is made. In each case, consideration should also be made with regard to how much space is available, with old backups deleted to make room for new ones.

4. Store Your Back-Ups Properly

It goes beyond storing your backups in environmentally controlled facilities, even if that’s admittedly a good practice. You would also want to store your backups off-site, separately from the original data. Every good plan has redundancies built in and a backup/ data recovery plan is no different.

The reasoning is simple, as they represent contingencies in case of disaster. Imagine a worst-case scenario in which a literal natural disaster strikes. You would want as large of a chance as being able to pick up right where you left off as soon as possible. You don’t want to lose your backups and the original data all in one fell swoop. That would truly be a disaster.

5. Validate the Recovery Procedure

Validation can take many forms. With regard to the GlobalVision Quality Control Platform, for example, Installation, Operational, and Performance Qualification procedures serve to verify the application works as it should.

As the definition of validation suggests, it “provides a high degree of assurance that a specific process will consistently produce a product meeting its pre-determined specifications and quality attributes.” In the case of backups, the process in question is the recovery procedure. The back-ups themselves are the product.

Verifying the viability of the backup data is critical. Test runs ensure that, in a worst-case scenario like the one outlined in Point No. 4, the data and operations can be picked up in a reasonable amount of time, even if off-site. Restoring back-ups on a regular basis helps validate the recovery procedure. Restoring back-ups to an alternative server before so doing is actually the best practice as it validates the ability of the data to be recovered. Seeing as the data would have just been validated in a new environment, it also provides you with a backup you can be sure is viable, should you ever need to use it. Knock on wood.

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Date: June, 2019 | Category: Quality | Author: Ryan Szporer

Consistency is a trademark of both validation and data integrity. In fact, without validation and the consistency for which it strives, forget data integrity. It’s like there is no data at all.

What Is Validation?

To be clear, validation is defined as, “evidence that provides a high degree of assurance that a specific process will consistently produce a product meeting its pre-determined specifications and quality attributes.” The “consistently” is key. There is no good use for a system that cannot do what it promises every single time.

Think along the lines of a phone that only dials the right number four out of five times. Eighty percent is a good mark on a test, but not so much in case of an emergency when you need to call 9-1-1 and you get the local pizza place instead. That’s in large part why system validation is so thorough, with Installation, Operational, and Performance Qualification processes entering into the equation.

For its part, data must be consistent throughout its entire lifecycle for it to have integrity. It plays into the need for data to also be accurate, which is one of the Food and Drug Administration’s expectations for Good Manufacturing Practices. Altogether, data is expected to be “Attributable,” “Legible,” “Contemporaneous,” “Original,” and, of course, “Accurate,” or “ALCOA” for short.

Data itself can be validated too. For example, to achieve compliance with the FDA (21 CFR Part 11, specifically) in pharma and life sciences, companies must ensure integrity is maintained with regard to drug safety data as it is collected, stored, and transmitted. This is done through preliminary planning, risk identification, and testing. After the fact, everything is regularly verified as working as expected, while regular audits and reports are made to improve processes after the fact.

What Must Be Validated?

In essence, while validation is an admittedly and justifiably complex process, it boils down to that same simple premise: It all has to be verified as working as expected. Anything less and the resulting data can’t be trusted. It would be useless and just as good as if it were non-existent.

Now, confusion may admittedly arise over what exactly is being validated. In a word almost “everything.” For example, in pharma, every piece of equipment that touches or impacts the development of a drug during the manufacturing process must be validated.

While equipment validation is nothing specific to pharma and is important in other industries, IT systems and processes also qualify as requiring validation here. Even proofreading software like GlobalVision, which helps to verify packaging as being accurate but may not actually come into physical contact with the product itself, would fall into this category.

Audit trails and the like within applications are generally designed to keep excellent records. And, if they are validated as being reliable without fail, it’s safe to operate under the assumption the data they keep is as well. And, as mentioned earlier, the data must be validated too.

Data Integrity vs. Data Validation

Data integrity and data validation are two separate concepts, but they effectively have the same end goal. Data validation covers the testing and processes that lead to data complying with regulations put in place by the FDA (for example). Data integrity is what you get once it has been deemed to be secure as a result, along with several other qualifications.

In other words, much like data security is a basic tenet of data integrity and not vice versa, the same goes for data validation. If your data has been validated and/or you have proper security precautions in place, the threat of a breach or malicious attack has been mitigated. There has been no such breach with regard to data that has integrity. It has to be kept that way.

It’s similar to how a ship’s hull has integrity until it hits an iceberg. Steps are taken to avoid contact or keep water from breaching. Since there are measures in place and the ship is afloat, to begin with, it means the ship is secure. Meanwhile, validation determines how effective those measures are. If they aren’t any consistency, the ship shouldn’t have even made it out of the shipyard.

In that sense, the ship is like any other manufactured product. Only its best possible, viable version should be made available. Validation helps ensure that is the case. Consistently.

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Date: April, 2019 | Category: Quality | Author: Mike Malz

Regardless of the industry, all companies have the same goal in mind: to provide high-quality products to keep customers loyal and attract new ones. To accomplish this, each product must go through a strict proofreading process to ensure the accuracy of all labeling and packaging.

This can be time-consuming. As a result, some early adopters have switched to proofreading software due to time constraints. In fact, sticking with human proofreaders has proven to be a potentially costly mistake, one that may even lead to expensive recalls.

Avoid Manual Errors

Although they do their best, human proofreaders are not able to catch all errors that can be found on a label. In a North Carolina State University article about errors in food manufacturing, 25% to 50% of recalls were due to human error. There are many reasons why these errors were missed; For one, a proofreader could have been tired or simply unfocused.

With new technologies continuously introduced into every aspect of our lives, people can be distracted by an email alert or text message. When an error is detected in packaging, companies must issue a recall on their product, costing them thousands of dollars and leaving them with a ton of unsellable inventory. Fortunately, there are measures to ensure each packaging component is error-free. These measures can be combined into a single solution: an automated proofreading platform.

Proofreading That Checks Every Word

Human brains are trained to skip words. So, no matter how fluent they are in a language, they can overlook one that’s misspelled. Most people use spell-checking software such as the spellcheck feature in Microsoft Word or maybe even an online solution like Grammarly. These tools help catch those mistakes, but they do have flaws. For example, some English words are spelled differently, such as “color” and “colour.” One solution would be proofreading software that automatically detects errors in a loaded file.

Catch Discrepancies in Color

Despite evidence to the contrary, some may argue human proofreaders do catch misspelled words. Nevertheless, color differences are a different kind of animal. It’s important that the labels of packaging have a consistent color pattern. This helps promote brand awareness and identity. If the color has faded or the hue is slightly different, the product will come off as rushed. Color-detection software is one way to identify any issues before the file gets sent to the printing press.

A+ Barcode Grading

Every company wants to send out Grade “A” barcodes and nothing less, as recalls can be issued if they will not scan. And, yet, despite the very real need, human proofreaders are unable to tell if a barcode will scan properly when it reaches the customer. Leveraging technology is the only option here, and it makes sense to opt for the best solution possible. Having a process in place to digitally check barcodes saves you time and money. This is especially true when it comes to consumer goods.

Checking Labels Even After Printing

There is still a chance some errors or color differences will slip through the cracks even after the job is done and the labels are printed. The best way to review your printed files is by reverifying them, using proofreading software. This way the user can find any differences and decide to reprint if necessary.

It’s important to make sure that, even when the final label is produced, it remains error-free. It would be infinitely preferable to find errors in labels immediately after they’ve been printed instead of having a customer find them while in line at a store.

Making sure your products are high-quality extends to the packaging. Errors are not only costly but embarrassing. People are far from infallible, and companies that rely on human proofreaders risk having their products recalled and losing customers.

Making the switch to automated proofreading, like with GlobalVision, can save you time and money by sparing your firm from having to issue recalls. Businesses should consider spending a little more money now on solutions that help maintain their reputation and brand integrity. It’s not about short-term gains, but rather the long game, in which everyone is a winner.

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Date: January, 2019 | Category: Quality | Author: Ryan Szporer

It’s easier to think of an audit trail as a collection of breadcrumbs leading out of the woods.

The Bright Side of Being Audited

Admittedly, the word “audit” gets a bad reputation. It’s usually associated with the unpleasant process of the same name that can be initiated by the U.S. Internal Revenue Service. In actuality, audits are an unavoidable part of life for many corporations in the sense that they can take place not once but multiple times a year. With an audit trail, they don’t have to be nearly as grueling as people have come to expect, though.

For the uninitiated, trails are the lists of transactions or events kept track of to help auditors and, in many ways, those being audited too. Of course, at its most fundamental level, a company’s audit trail does contain financial transactions. However, they can be chronological catalogs of so many more types of events. An audit is simply an investigation of accounts and records in general. They aren’t limited to those of the financial variety.

For example, audits can be key to achieving and maintaining regulatory compliance, which is in turn critical to operating in sectors like pharma. For a company that develops software intended to meet ISO compliance, perhaps for use within that same pharmaceutical industry, regular internal and external audits are to be expected.

External vs. Internal Audits

External audits can either be initiated by the relevant regulatory body (for certification purposes) or even a client that relies on the given software. Take a digital proofreading application for example.

Continuing within pharma, each piece of equipment that enters into a drug’s chain of custody has to be “validated” as meeting pre-determined specifications and attributes. Obviously, software qualifies as equipment in that context. It makes sense that a firm with as much at stake from a quality perspective as a pharmaceutical company would want to get assurances that a piece of equipment on which they rely comes as advertised as being compliant. It’s theoretically similar to how consumers depend on medication and accurate information on its packaging.

In contrast, an internal audit serves as an evaluation of the company’s effectiveness, from risk-management, governance, and process standpoints. As data integrity arguably touches on all three areas, its importance in a corporate environment cannot be understated. In fact, audits specifically aimed at examining data integrity are a real thing.

Benefiting from an Audit Trail

Regardless of the focus of an audit, trials are undeniably critical to their success. And success is what all parties should strive for, whether they’re doing the auditing or being audited. No one wins however unnecessarily hard one becomes to complete.

That’s one of the misconceptions regarding audit trails that is generally associated with the earlier IRS example. Obviously, an audit isn’t exactly something to look forward to, but it can be made less of a headache if all required records have been kept and are easily accessible to the auditors. Automated trails that are easily searchable make smooth audits more of a reality.

Trails are theoretically included in the software as one of many required technical controls that enable users to achieve compliance with 21 CFR Part 11 with the Food and Drug Administration (in the United States; equivalent to Annex 11 in the European Union). Compliance here ensures companies implement good business practices through reliable electronic records, which must be able to be accurately displayed and exported. Here, the audit trail serves to log what changes to application data were made, when, and by whom and be available for review.

Whoever ends up conducting that review, whether it’s an agency or the company itself, the auditor will no doubt thank you as the bigger picture begins to take shape. Identifying the individual trees is key to seeing the forest as a whole, though. Finding your way through can be hard, but an audit trail can clearly reveal the right path to take.

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