May the Data Be With You


2021-bl-analytics-trends-brief_715x320Today is May the fourth, a day when Star Wars fans the world over celebrate the franchise. The date is a pun of the oft-quoted phrase “May the Force be with you.” In the Star Wars universe, the Force is the energy holding the universe together. It’s also the power that lets Luke Skywalker make decisions based on feeling as opposed to logic. It’s how he knows when to fire the proton torpedo that finally destroys the Death Star. It’s how he learns that Han and Leia are in trouble in Cloud City. And how he realizes that there’s a bit of good left in his father.

Using the Force to make decisions in Star Wars works well. Tragically, since most of us don’t have that ability in the real world, we’d probably be better served if we listened to C-3PO more. While we’re short on protocol droids, we do have the tools to let you make decisions using advanced analytics and artificial intelligence (AI). And the odds of those paying off are considerably better than navigating an asteroid field.

“I’ve Got a Bad Feeling About This”

There’s a reason we’ve been pushing data-driven decisions instead of instinct-driven ones. Experience and intuition aren’t reliable ways to conduct business — especially when it comes to quality. To be fair, quality managers do try to make decisions using data. The problem is getting that data together and doing something useful with it. Quarterly reports contain old data that, depending on human error, might never have been accurate. Even if you could gather all that data together, there’s definitely a limit to what you can do in Excel.

Advanced analytics and AI are key to getting the most out of your data. At their best, they can tell you what’s happening, why it’s happening, and what you should do about it. Unlike Han Solo, quality professionals are very interested in the odds. For example, advanced analytics can tell you the likelihood of a certain outcome after a corrective or preventive action. They can also suggest actions you could take and tell you the results (e.g., putting specific employees to work on a manufacturing line will increase efficiency by a certain percent).

Fortunately, there’s no need to design these technologies yourself. What once would’ve been built in house can now be purchased and used out of the box. A recent Deloitte report explains, “With AI capabilities increasingly embedded in enterprise software, and an abundance of cloud-based offerings and tools that accelerate AI development, a company no longer needs as many heavy-duty specialists to get started.”(1) Software companies have already done the heavy lifting. That said, there’s still plenty that life sciences companies need to do to prepare for analytics.

“This Isn’t the Panacea You’re Looking For”

It is important that life sciences companies use these tools, but they are just that — tools. Digitization, analytics, AI, etc. are the means to an end. In 2019, more than 60% of life sciences companies spent over $20 million on AI initiatives. (2) Making that a wise investment means doing some planning beforehand.

  • Align With Business Strategy: Data analysis can help in all areas of business. Start by identifying the areas your company intends to focus on. Then define which metrics will show success in that area. From there you can determine which technologies are best suited to improve those metrics.
  • “I Find Your Lack of Data Integrity Disturbing”: Data is the foundation of analytics. If you don’t have good data integrity practices in place, no solution, no matter how advanced, will give you reliable insights. And since AI is trained using data, cleaning up your company’s data is essential.
  • Check on Vendors and Suppliers: The Force might tie the universe together, but data ties your supply chain together. To get the most out of analytics, you need complete data from your vendors and suppliers. If they still run on antiquated systems, it will be hard to achieve the connectivity you need to use advanced analytics.

Conclusion

Headlines about data and AI are common. But it can be hard to know how it applies specifically to your job in your industry. In our new trend brief, we discuss how quality management will be changed by analytics and what you can do right now to take advantage of it. The U.S. Food and Drug Administration (FDA) is in the process of deciding what AI should look like in regulated industries, but life sciences companies will be responsible for using their data wisely. Taking steps to properly handle your company’s data now will save time when it comes to using this technology in the future.

Advanced analytics are no longer the future of quality — they’re the present. We’ve gone from discussing what data theoretically could do to what it currently can do now. Before you binge-watch what happened a long time ago in a galaxy far, far away, familiarize yourself with what’s happening right now in the life sciences. That way you can ensure everything in your company proceeds exactly as you’ve foreseen.


Sources:

  1. The window for AI competitive advantage is narrowing,” Susanne Hupfer, Deloitte, September 11, 2020.
  2. Scaling up AI across the life sciences value chain,” Aditya Kudumala et al, Deloitte, Nov. 4, 2020

2019-bl-author-sarah-beale

Sarah Beale is a content marketing specialist at MasterControl in Salt Lake City, where she writes white papers, web pages, and is a frequent contributor to the company’s blog, GxP Lifeline. Beale has been writing about the life sciences and health care for over five years. Prior to joining MasterControl she worked for a nutraceutical company in Salt Lake City and before that she worked for a third-party health care administrator in Chicago. She has a bachelor’s degree in English from Brigham Young University and a master’s degree in business administration from DeVry University.


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