How my human condition became very real when I discovered APERIO

How my human condition became very real when I discovered APERIO

How my human condition became very real when I discovered APERIO 1800 1000 APERIO

My name is Livia Wiley and I’m the Vice President of Marketing at APERIO. As a marketer, I am challenged with taking technically challenging details and crafting a story that appeals to the buyer persona we seek. Sometimes this can be difficult; while other times, it’s quite obvious. This story is the latter. What you can’t tell by looking at me is that I’m a Type 1 diabetic. Two months before my 5th birthday, I ended up in the hospital and was diagnosed with insulin-dependent diabetes. It was the day that changed my life, and my family’s, forever. Why do I tell you this? Let me explain by sharing my medical journey.

Back in the early 80s, the only way to test your sugar levels was a ketone urine test. I’m no doctor but typically it takes about 24 hours for your body to enter ketoacidosis as a result of high sugars and another 1 to 3 days to see ketones in your urine. That means by the time you get a ‘positive’ test, the ‘time to act’ has passed. It’s already too late to stop it from happening; four days in, all you can do is try to improve the current situation and return to some sort of normal. There’s no data to trust because the reality is, you’ve already damaged your organs by waiting that long. And over years, because you only tested when you felt bad, say once a week, it’s an extremely dangerous way to live.

A decade later, after a near-death experience from ketoacidosis, I got a glucose monitor that could measure sugar level by blood. It was revolutionary because I could know my sugars on the spot, and know when to take insulin or when to get food. For more than 30 years, I would prick my fingers up to 10 times a day before and after I ate, and any other time I need some clarity. It worked, for the most part. But you couldn’t always trust data, which was especially inaccurate at high numbers. And, sometimes there was a noticeable mismatch between how I felt versus what the tester was telling me. Plus, the same drawback of a random spot check remained. True, I didn’t have to wait days to know I was in trouble, but I still didn’t know for how long my sugars were high. (It’s a constant chasing of high and lows; back and forth.) I was still contributing to the long term effects of diabetes for X number of hours per day, multiplied by 30+ years. It’s not insignificant. But it was certainly better than a urine test.

This year, after four decades as a diabetic, I finally got a DexCom Continuous Glucose Monitoring (CGM) system. WHAT A LIFE CHANGER! It automatically takes a reading every 5 minutes, that’s 288 sugar level readings a day. At any time, I can see my current level, plus if I’m trending up or down. It alerts for sugars that are too high or too low, even when I’m sleeping. It calculates if my sugars are rising or falling too quickly to tell me I should take action and how quickly. You can log events, like insulin and carb intake, against the data to identify patterns. For example, I found out that caffeine first thing in the morning instantly raises my blood sugar level by 200 mg/dL. Mind blowing. My body treats a Diet Coke (my fav!) like a carb. I never knew that. How could I? I can now look at my day in real time and learn how to better match insulin and food to keep tighter control. It’s not perfect, but with numbers and context (trends), there’s no more guessing. With enough data, it’ll even give me a 14-, 30-, and 90-day average to mimic my A1C and can correlate patterns automatically. I cannot tell you how excited I am as a diabetic, and as an engineer, to have so much data at my fingertips. It has afforded me a way of life I’ve never imagined! Fewer highs, fewer lows, tighter control, lower A1C; better overall health. I’ll never go back to tester strips.

So why do I share all of this? Well, if it hasn’t already been made obvious, this is a story about data and data integrity. My journey went from using a “tool” that was very inaccurate that I used bimonthly, to one that was more accurate that I used up to 10 times a day but still lacked context, to one that is automated, accurate, and streamed, with some fancy AI.

The same evolution is taking place in processing plants around the world. More than a century ago, we looked at plant data historically only when necessary—safety or regulatory events—analogous to the ketones in the urine test. Then in the 1920s, we started to monitor data in control room HMIs, a spot check, to tell us when certain boundaries were breached and make improvements; a lot like the blood test. But we still had no context. Today, it’s possible to monitor hundreds of thousands of real time data streams to automatically determine when ‘undetectable to the naked eye’ anomalies occur, like my CGM, and take immediate action. But most plants are still in the tester strips stage—not taking full advantage of the technology that exists to make life so much easier!

If you want to revolutionize the way you use data, ensuring it’s accurate and reliable for your operators and data scientists alike to make data-driven decisions with confidence, you need APERIO. APERIO DataWise is the CGM equivalent for your operational data. Powered by AI machine learning, APERIO DataWise automatically validates operational data at scale to improve data accuracy, security, and value, allowing for better, smarter business decisions based on real-time, trusted, superior data. (Forgive me, but I wouldn’t be a good marketer if I didn’t have a CTA at the end!)

About Livia

Livia Wiley has over 25 years of professional experience focusing on strategic planning, industry growth, and process innovation. This is underpinned by broad industry expertise and applications of industrial automation software, having worked for AVEVA, Schneider Electric, Honeywell, and Aspen Technology. Livia holds a B.Sc. in Chemical Engineering from Queen’s University, and a M.Eng in Chemical Engineering from the University of Houston.

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