What delayed detection is really costing your dairy.

It’s time to take guesswork out of dairy management.

In the dairy business, timing is vital to the bottom line. Every hour a cow is sick without intervention could mean lost milk, missed breeding windows, higher treatment costs and a greater chance she leaves the herd. In a thin-margin market, early detection of illness is more than just helpful — it's essential.

The real cost of waiting

Health and reproduction don't operate in isolation. A cow that develops subclinical ketosis is significantly more likely to also develop metritis, a displaced abomasum or compromised reproductive performance in the same lactation.¹ A lame cow detected late breeds later, produces less and is far more likely to be culled prematurely.² Delayed detection doesn't just create a single cost event. It cascades, and each condition along the way adds its own price tag.

• Mastitis alone can run up to $444 per cow.³

• Metritis cases average $513 lost.⁴

• Lameness can cost around $177.⁵

• Milk lost during the antibiotic withholding period that follows treatment can add another $352 per head.⁶

Research from Cornell University shows producers using SenseHub® Dairy monitoring reports can successfully identify cows with a potential illness up to three days earlier than traditional detection methods. These 24/7 insights help producers identify cows showing abnormal behavior days before clinical symptoms become visible, allowing them to be proactive instead of reactive with herd health.

The science behind the system

As herd animals, many cows instinctually hide problems. Some may show clear symptoms when they're sick, but many may not show any symptoms until we see a drop in milk and money flying out the door. Traditional detection methods of sick cows rely heavily on visual observation or changes in milk characteristics, which can delay intervention or lead to early culling.

Monitoring reports change that.

By continuously tracking rumination and activity levels, the system produces a Health Index Score for each cow. A drop in this score — particularly below the threshold of 86 — prompts employees to take a closer look at the cow to see what is going on.

Across three Cornell research studies tracking over 1,100 Holstein cows, researchers found that SenseHub Dairy monitoring could:

• Identify cows with metabolic and digestive disorders at a 93% accuracy rate.⁷

• Detect cows experiencing E. coli-related mastitis with 81% sensitivity, which significantly outperformed traditional observation alone.⁸

Flag cows with other concurrent disorders (like metritis or lameness) 89% of the time.⁹

Early detection in action

When cows get sick, their behavior changes — but not always in ways we can see immediately. Drops in rumination and activity are all subtle signs that a cow may be getting sick, but they are hard to catch without constant observation.

With monitoring reports, these data points are captured in real time every day. Instead of using a one-size-fits-all metric, SenseHub Dairy allows producers to see what's going on with each cow based on deviations from their own normal behaviors. This individual approach makes it possible to catch changes earlier and with greater precision.

In the Cornell studies, using SenseHub Dairy monitoring to flag cows demonstrating abnormal behavior resulted in:

• Illness detection up to three days earlier than traditional methods.⁷

• Detection of metabolic or digestive disorders an average of two days earlier than clinical diagnosis by farm personnel.⁷,⁹

• Finding cows with lower rumination, activity and milk yields at the time of diagnosis compared to baseline.⁷,⁸,⁹

Doing more with the data

Data-driven insights like these help producers do more with less. Dairy monitoring technology helps detect key behavior changes for every cow, which empowers producers and veterinarians to make faster, more informed decisions with cow health. Most importantly, it helps keep dairies profitable by avoiding late treatments.

With SenseHub Dairy, producers can better monitor cows from calf hutches and group housing to the maternity pen and in the milking herd. By embracing this targeted, individual approach, dairy producers can spot cows needing attention earlier and support better overall cow health and well-being. It removes the guesswork from daily management by enabling proactive, data-driven decisions instead of costly, reactive care.

Want to gain the power to never guess again if a cow is getting sick? Click here to get started.

1 Raboisson D, Mounié M, Maigné E. Diseases, reproductive performance, and changes in milk production associated with subclinical ketosis in dairy cows: a meta-analysis and review. J Dairy Sci. 2014 Dec;97(12):7547-63.

2 Booth CJ, Warnick LD, Gröhn YT, Maizon DO, Guard CL, Janssen D. Effect of lameness on culling in dairy cows. J Dairy Sci. 2004 Dec;87(12):4115-22.

3 Rollin E, Dhuyvetter KC,Overton MW. The cost of clinical mastitis in the first 30 days of lactation: An economic modeling tool. Prev Vet Med. 2015;122(3):257-264.

4 Pérez-Báez J, Silva TV, Risco CA, Chebel RC, Cunha F, De Vries A, Santos JEP, Lima FS, Pinedo P, Schuenemann GM, Bicalho RC, Gilbert RO, Rodrigez-Zas S, Seabury CM, Rosa G, Thatcher WW, Galvão KN. The economic cost of metritis in dairy herds. J Dairy Sci. 2021 Mar;104(3):3158-3168. doi: 10.3168/jds.2020-19125. Epub 2021 Jan 15. PMID: 33455790.

5 Booth CJ, Warnick LD, Gröhn YT, Maizon DO, Guard CL, Janssen D. Effect of lameness on culling in dairy cows. J Dairy Sci. 2004 Dec;87(12):4115-22. doi: 10.3168/jds.S0022-0302(04)73554-7. PMID: 15545373.

6 Merck Pinkeye Quantitative Survey, 2021, FarmJournal, Lenexa, KS.

7 Stangaferro ML, Wijma R, Caixeta LS, Al-Abri MA, Giordano JO. Use of rumination and activity monitoring for the identification of dairy cows with health disorders: Part I. Metabolic and digestive disorders J. Dairy Sci. 99:7395–7410.

8 Stangaferro ML, Wijma R, Caixeta LS, Al-Abri MA, Giordano JO. Use of rumination and activity monitoring for the identification of dairy cows with health disorders: Part II. Mastitis. J. Dairy Sci. 99:7411–7421.

9 Stangaferro ML, Wijma R, Caixeta LS, Al-Abri MA, Giordano JO. Use of rumination and activity monitoring for the identification of dairy cows with health disorders: Part III. Metritis J. Dairy Sci. 99:7422–7433.

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