Data-driven parenting: Tracking baby sleep, eating, and pooping on spreadsheets

I Measure Everything My Kid Does, and Track It on Spreadsheets. It Makes Me a Better Parent.

I Measure Everything My Kid Does, and Track It on Spreadsheets. It Makes Me a Better Parent.

How to understand your data
July 9 2013 11:38 AM

I Measure Every Single Thing My Child Does

And I track it on spreadsheets. Really—every single thing. Even every poop. And it makes me a better parent.

Parents with baby on couch.
Let's add this to the spreadsheet

Photo by Pixland/Thinkstock

My obsession with quantifying my kid started while I was still pregnant. I was giving birth for the first time at age 35, and modern medicine had invented a new category for women like me: “advanced maternal age.” At the doctor’s office, I received a yellow pamphlet with a list of instructions for women in my condition. Exercise, but not too much, else I could wind up with placental problems. Watch my sugar intake, or I might contract gestational diabetes, and give birth to a gigantic baby. Consume enough DHA in my prenatal vitamins, or my baby’s brain might not develop properly.

So at 16 weeks, I gave birth to a pregnancy tracker. I made a spreadsheet with every piece of data I could wrangle out of my doctor, along with all of the personal notes I’d been keeping on myself. I weighed in daily, ensuring that during my entire pregnancy I didn’t gain more than the recommended 26 pounds. I counted DHA milligrams in order to reach my daily target of 300. I bought a special thermos with a lid that clicked around to designate my progress drinking my required 10 daily cups of water. At the end of the day, that number got transferred to my computer.

And so it went for the remaining five months. I brought home copies of my medical records and tests, noting my blood pressure and sugar levels, sonograms and ultrasounds, along with the baby’s heartbeat, fetal positioning, and the like.


The logical part of me knew that all the healthy habits and precautions wouldn’t necessarily prevent autism or cystic fibrosis. But mapping all of my data to an area chart made me feel less anxious.

Though we exhaustively researched newborn development and first-time parenthood as much as we could, little could prepare us for what happened next. Our daughter lost a little weight in the day after her birth, which we were told is normal after a C-section. The following day, another test showed that she’d lost more than 10 percent of her birth weight. I was visited by three lactation consultants, each offering different advice on what to do to ensure she ate enough. Another nurse suggested I was holding my baby incorrectly, and that I should instead cradle her like a football. (As if I even knew what that meant.)

We were teetering on a dangerous situation, so our pediatrician asked us to supplement her feedings with formula and to start measuring exactly how much she was eating. Quantifying our baby’s feeding habits? That was the one instruction that finally made us both relax.

I built the first spreadsheet to track up to 10 daily feedings. Columns displayed the amount of formula and breast milk she consumed, along with the time of day, number and description of wet diapers, number and description of dirty diapers, and a special category I labeled “dessert.” Since our goal was to get our daughter’s weight up, we hoped that she’d be interested in just a bit more after each main course.

We loaded the spreadsheet to our home network so that both my husband and I could access it for real-time updating from any computer in our house. Because of the amount of weight our daughter had lost, I was told to use a breast pump and measure out my milk for her. (I was supposed to continue allowing her to nurse, but our primary objective was making sure she had adequate nourishment.) During the first feeding at home, I put my laptop on the nightstand beside my bed and filled out the chart as I tried to burp my daughter:

Time: 11:15 a.m.
Breast Milk: 75 milliliters
Formula Supplement: none
Wet Diaper: 1
Yellow Scale (1 = clear, 10 = call the hospital): 3
Dirty Diaper: 1
Poop Scale (1 = Dijon mustard, 5 = pâté, 10 = tar): 5
Dessert: 0

At 2 a.m. the next morning, I attempted the same routine. Laptop on left nightstand, baby attached to right boob. Either the harsh white light or my keyboard tapping, I’m not sure which, proved too distracting for the baby and my sleeping husband, so we opted instead for a giant binder with the spreadsheet in paper form. Later, we’d transfer the data back to our network.

As long as we were already tracking her intake and output, we thought it would be interesting to also track her sleep habits. We’d already decided to sleep train her, and we were curious about whether certain times of day correlated to more restful sleep. If we read to her during feeding, would that impact her sense of calm? Did the sound of the air conditioner make her tense and more awake? Were there other triggers, like the church bells across the street, or a mobile phone ringing? So we added another column.

Time: 6:30 p.m.
Breast Milk: 60 milliliters
Formula: 30 milliliters
Wet Diaper: 1
Yellow Scale (1 = clear, 10 = call the hospital): 3
Dirty Diaper: 2
Poop Scale (1 = Dijon mustard, 5 = pâté, 10 = tar): 3 and then another 3
Dessert: 10 milliliters
Sleep: 2:30 p.m.–6:30 p.m. 4 hours. We woke her up to feed; she was groggy the whole time.

After the second week, our daughter’s weight was exactly on target. Our pediatrician told us we could relax our rigid feeding schedule, and that we no longer needed to fill out the spreadsheets.

But why would we stop now? We’d already noticed a few patterns, and we had allowed the data to dictate our parenting style. Singing her the exact same song during her 6:30 p.m. feeding seemed to encourage longer, more restful sleep. Swaddling guaranteed 90 percent more quiet sleep than nonswaddling. She seemed to eat most around 11 a.m., 4:30 p.m., and 8 p.m., so we kept at the strict feeding schedule.

It occurred to us that while our baby daughter couldn’t communicate directly beyond crying, we could have a deeply intimate, beneficial conversation with her through data. We realized that we could quantify and study her in an attempt to optimize all of her development.