Dairy Herds: When to Cull and When to Keep Using Lifetime Data
You check production records every month. Feed costs, vet bills, milk checks, all accounted for. But here’s what most farmers miss: the cows draining profits aren’t always the obvious ones. A cow producing 70 pounds daily might look solid in today’s numbers, yet cost you thousands over her lifetime. Meanwhile, another animal you’re considering culling could be one of your most profitable performers when you look at the complete picture.
The difference? Lifetime data tells the real story that snapshot records hide.
Why Snapshot Data Misleads Dairy Herd Culling Decisions
Most culling decisions rely on current lactation numbers, test day results, recent breeding records, last month’s SCC. This approach misses critical patterns that only appear when analyzing a cow’s entire productive life.
Research from Swedish dairy farms analyzing over 1,900 operations found that farms with longer average cow lifespans showed better technical efficiency and profitability, though the relationship followed an inverted U-shape pattern (Adamie et al., 2023). This means keeping cows longer improves profitability, but only to a point. The key is identifying which cows to keep and which to cull, and you can’t make that call from current lactation data alone.
Think about it this way. A cow in third lactation producing 75 pounds daily looks average. Your test day report shows nothing remarkable. But lifetime analysis reveals she’s produced 25,000 pounds above herd average over three lactations, had zero health events, and bred back quickly every time. Another cow producing 80 pounds daily appears better, until lifetime data shows chronic mastitis costing 2,000 pounds per lactation, late breeding adding 60 days to calving intervals, and cumulative losses exceeding $4,000.
Current data showed one thing. Lifetime data revealed the opposite.
Three Lifetime Patterns That Change Culling Decisions
When you analyze cow performance across complete lactations, three distinct patterns emerge. Each requires different management, and current records rarely reveal which category your cows fall into.
Pattern 1: Consistent Top Performers
These cows exceed herd average in every lactation. They might not break records in any single test, but they deliver steady production year after year. Lifetime analysis from Dutch herds showed that cows with consistently high lifetime production could be identified early using machine learning models combining genetics, environment, and management data (Perneel et al., 2024).
These are your breeding candidates. Keep them, breed them with sexed semen, and build your next generation from their daughters. Many farmers cull these cows because they’re not flashy in current numbers, a costly mistake that removes the most reliably profitable animals from your herd.
Pattern 2: Chronic Underperformers
These cows consistently fall below herd average. They might have occasional good months that keep them off your cull list, but lifetime data reveals persistent patterns: slower milk letdown, recurring health issues, delayed breeding. Canadian research analyzing over 22,000 cows found that focusing only on current lactation costs and revenues without considering lifetime cumulative costs led to retaining low-profit cows much longer than economically justified (Warner et al., 2022).
Here’s the opportunity many farms miss: these underperformers often still have sale value as dairy animals. Cull them early, while they’re productive enough to sell to operations with lower production targets. Waiting until they’re obvious culls means shipping them for beef prices, leaving money on the table.
Pattern 3: Declining Performers
The trickiest group. These cows started strong but show consistent decline across lactations. First lactation: 23,000 pounds. Second: 21,500. Third: 19,000. They’re not terrible in current numbers, but the trend is clear when you look at lifetime patterns.
Swiss research examining real farm culling decisions found that many farmers kept declining cows too long, resulting in average losses of 161 CHF per farm per month compared to optimal economic culling timing (Schlebusch et al., 2025). Current data doesn’t reveal this decline clearly, it looks like normal lactation variation. Lifetime analysis makes the pattern obvious.
The Hidden Costs of Wrong Culling Timing
Culling too early wastes the investment in raising that animal. Culling too late drains profits through extended underperformance. But most farms focus only on the first risk while ignoring the second, and the second costs more.
Consider this scenario. A 100-cow herd keeps 10 chronic underperformers an extra year because current lactation data doesn’t clearly flag them. Those cows produce 5 pounds below herd average daily. Over 305 days, that’s 1,525 pounds per cow, 15,250 pounds total. At $0.40 per pound, that’s $6,100 in unrealized milk revenue. Add feed costs for animals producing less than they consume, and the annual loss exceeds $8,000.
Now compound that over multiple years. Research on Dutch dairy operations found that herds with optimized culling timing showed improved gross margins, though the study revealed complex interactions between longevity and profitability depending on specific farm characteristics (Vredenberg et al., 2021).
The math is clear. Early identification of underperformers through lifetime analysis could recover $500-1,000 per cow over their remaining productive life. For a 100-cow herd with 10 chronic underperformers, that’s $5,000-10,000 annually, money currently invisible because you’re looking at the wrong data.
When Current Numbers Lie About Profitability
Here’s where lifetime data becomes crucial: a cow can look profitable in current lactation while costing you money overall. Or she can appear mediocre while being one of your most valuable animals.
The key factors current data misses:
Cumulative health costs: A cow with three mastitis cases over her lifetime has treatment costs in your books. What you don’t see: the extended milk loss across entire lactations. Research quantifying hidden disease costs found that mastitis reduced cumulative milk value by $228 to $470 per case when accounting for production losses throughout the lactation (Puerto et al., 2021). Current test day results won’t show this, you need lifetime tracking.
Breeding efficiency patterns: Days open accumulate faster than you realize. A cow taking 45 extra days to breed compared to herd average costs $2.00-3.00 per day in extended calving interval. Over three lactations, that’s $270-405 per cow. Multiple cows with this pattern cost thousands, but monthly breeding reports won’t reveal it because they show current status, not cumulative impact.
Production consistency: Two cows might average 75 pounds daily over a lactation. One maintains steady 73-77 pound production. The other swings from 85 to 65 pounds with health events. The volatile cow creates management challenges, unpredictable milk flow, and hidden costs. Lifetime analysis reveals these patterns; test day reports don’t.
Building Your Lifetime Data Culling Strategy
Implementing lifetime analysis doesn’t mean abandoning current metrics. It means adding critical context that snapshot data can’t provide. Here’s how to integrate both approaches.
Step 1: Establish Baseline Lifetime Metrics
Start tracking cumulative production relative to herd average for each cow. When she’s at 50,000 lifetime pounds, is she 5,000 above or below average for cows at that stage? This single metric reveals more than any monthly test day.
Add cumulative health costs per cow. Not just treatment expenses, include estimated milk losses from disease. Research on global dairy disease burden found that comorbidity-adjusted economic analysis revealed substantially higher total costs than simple disease-by-disease accounting (Rasmussen et al., 2024). Track these combined impacts over each cow’s productive life.
Monitor cumulative days open. A cow might breed fine one lactation and struggle the next. Lifetime totals reveal which animals consistently breed efficiently versus those accumulating extended intervals.
Step 2: Segment Your Herd by Lifetime Performance
Divide your herd into thirds based on lifetime profitability: top performers, middle tier, and bottom third. Current lactation numbers place cows differently than lifetime analysis, and the difference matters for culling decisions.
Top third: These are breeding candidates. Keep them longer, breed with sexed semen, retain their daughters. Many farms don’t recognize these animals because they’re not flashy in current numbers. Lifetime data identifies them clearly.
Bottom third: Early cull candidates. Don’t wait until they’re salvage-only. Sell them as productive dairy animals to operations with lower targets. This strategy could add $500-800 per cow compared to waiting until they’re obvious culls.
Middle third: Monitor closely with monthly updates. Some will trend toward top performers and earn longer retention. Others decline toward bottom tier and need timely culling before they become money losers.
Step 3: Set Lifetime-Based Culling Triggers
Current triggers focus on single lactation: “Below X pounds for Y days” or “Failed to breed after Z attempts.” Add lifetime triggers: “Cumulative production 10,000 pounds below average” or “Lifetime health costs exceed $3,000 with declining production trend.”
These triggers catch chronic underperformers that slip through traditional metrics. Research on culling decision optimization found that economic models accounting for lifetime expected performance, replacement costs, and future cow value significantly outperformed intuition-based culling timing (Lehenbauer and Oltjen, 1998).
Step 4: Review Decisions Quarterly
Monthly reviews focus on current status. Quarterly reviews should analyze lifetime trends. Which cows moved between performance tiers? Are declining performers accelerating downward or stabilizing? Did cows flagged for culling last quarter validate or contradict that decision?
This quarterly cadence catches patterns before they cost serious money. A cow trending downward for three months needs attention. Waiting six months means another lactation of underperformance.
Common Pitfalls When Implementing Lifetime Analysis
Farmers new to lifetime data make predictable mistakes. Avoid these to maximize the benefits of this approach.
Pitfall 1: Overvaluing genetic potential. A cow with excellent pedigree and high genomic predictions might still underperform in your specific environment. Lifetime data shows what she actually produces in your herd, your management system, your feed program. Genetic potential matters, but realized performance matters more for culling decisions.
Pitfall 2: Ignoring opportunity cost. Keeping a bottom-tier cow means not having space for a potentially better animal. Research analyzing replacement decisions found that the opportunity cost of retained cows depends on available replacement quality and herd expansion plans (Han et al., 2022). If you’re raising quality heifers, early culling of underperformers becomes more valuable.
Pitfall 3: Analyzing in isolation. Lifetime data for one cow means little without herd context. A cow producing 18,000 pounds per lactation might be excellent in one herd and mediocre in another. Always compare to your herd average, not industry benchmarks.
Pitfall 4: Paralysis by analysis. Lifetime data provides clarity, not certainty. You’ll still make judgment calls. The goal isn’t perfect decisions, it’s better decisions than you’d make with current data alone.
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The ROI of Lifetime-Based Culling
Let’s quantify what lifetime data analysis could mean for your operation. These numbers come from research on real dairy herds implementing optimized culling strategies.
A 100-cow herd with average 35% annual replacement rate culls 35 cows yearly. Research suggests optimal rates range from 20-25% for herds with good health management (Penn State Extension, 2024). But the key isn’t just the rate, it’s culling the right cows at the right time.
Here’s what optimization might look like:
Scenario 1: Earlier identification of chronic underperformers. Lifetime analysis flags 8 bottom-tier cows one lactation earlier than traditional methods. Selling them as productive dairy animals instead of waiting until salvage-only adds $600 per cow. Total gain: $4,800.
Scenario 2: Retained top performers. Lifetime data identifies 6 consistent high producers you would have culled based on current lactation numbers alone. Keeping them one extra lactation adds 15,000 pounds per cow at $0.40/pound. Additional revenue: $36,000.
Scenario 3: Reduced involuntary culling. Better identification of declining performers before they become health problems could reduce involuntary culls by just 2 cows annually. Avoiding emergency culling saves $800-1,200 per cow in lost revenue and replacement timing. Annual savings: $1,600-2,400.
Combined potential benefit for this 100-cow herd: $42,400-43,200 annually. That’s $424-432 per cow in improved profitability from better culling decisions, without changing production levels or adding costs.
Making the Transition to Lifetime Analysis
You don’t need sophisticated software to start. Most herds already collect the necessary data through DHIA testing and herd management systems. The challenge is organizing and analyzing it differently.
Start simple. For your next 10 cull candidates identified by current metrics, run a lifetime analysis. Calculate cumulative production versus herd average. Add up health costs across all lactations. Total breeding days across all services. Does this change your culling order? For most herds, it rearranges 3-4 animals on that list, and those changes matter financially.
Track results. When you cull based on lifetime data, note what that cow sold for and what her replacement produces. Compare to previous years’ culling outcomes. Most farms find lifetime-guided decisions improve both cull cow revenue and replacement performance.
Expand gradually. Once you’re comfortable analyzing cull candidates, extend lifetime review to breeding decisions. Which cows deserve sexed semen based on lifetime performance? The answers differ from genetic rankings alone, and breeding your proven performers builds a stronger next generation.
From Our Family to Yours: The Real Value of Lifetime Data
We’re a family of scientists, a veterinarian and a data analyst, raising a child who’s learning to respect the farmers who feed us all. We built DairyCommand because we’ve seen too many good farming families leave money on the table through culling decisions based on incomplete information.
Current lactation data tells part of the story. Lifetime analysis reveals the complete picture. The cows you think are average might be your most profitable. The animals you’re keeping longest might be draining thousands annually. You can’t know which is which from snapshot records alone.
Lifetime data doesn’t make decisions for you. It gives you the information to make better decisions yourself. You know your herd, your goals, your constraints. Adding lifetime context to that knowledge creates culling strategies that improve profitability while building a stronger operation to pass to the next generation.
That’s what matters: not just this year’s production, but building herds that thrive for decades. Lifetime data makes that possible.
References
Warner, D., Dallago, G.M., Dovoedo, O.W., Lacroix, R., Delgado, H.A., Cue, R.I., Wade, K.M., Dubuc, J., Pellerin, D., and Vasseur, E. (2022). Keeping profitable cows in the herd: A lifetime cost-benefit assessment to support culling decisions. Animal, 16(10), 100628. https://www.sciencedirect.com/science/article/pii/S1751731122001859
Han, R., Kok, A., Mourits, M., and Hogeveen, H. (2022). The association of dairy cattle longevity with farm level technical inefficiency. Frontiers in Veterinary Science, 9, 1001015. https://www.frontiersin.org/journals/veterinary-science/articles/10.3389/fvets.2022.1001015/full
Schlebusch, S., Eppenstein, R., Hoop, D., and von Rohr, P. (2025). Are dairy cow replacement decisions economically justified? Evidence from Swiss farms. Animals, 15(16), 2442. https://doi.org/10.3390/ani15162442
Lehenbauer, T.W., and Oltjen, J.W. (1998). Dairy cow culling strategies: making economical culling decisions. Journal of Dairy Science, 81(1), 264-271. https://pubmed.ncbi.nlm.nih.gov/9493103/
Adamie, B.A., Owusu-Sekyere, E., Hansson, H., and Telezhenko, E. (2023). Dairy cow longevity and farm economic performance: Evidence from Swedish dairy farms. Journal of Dairy Science, 106(9), 6387-6403. https://www.journalofdairyscience.org/article/S0022-0302(23)00598-2/fulltext
Penn State Extension. (2024). Cull Rates: How is Your Farm Doing? https://extension.psu.edu/cull-rates-how-is-your-farm-doing
Perneel, M., De Smet, S., and Verwaeren, J. (2024). Data-driven prediction of dairy cattle lifetime production and its use as a guideline to select surplus youngstock. Journal of Dairy Science, 107(11), 9390-9403. https://www.journalofdairyscience.org/article/S0022-0302(24)00069-9/fulltext
Puerto, M.A., Shepley, E., Cue, R.I., Warner, D., Dubuc, J., and Vasseur, E. (2021). The hidden cost of disease: I. Impact of the first incidence of mastitis on production and economic indicators of primiparous dairy cows. Journal of Dairy Science, 104(7), 7932-7943. https://www.journalofdairyscience.org/article/S0022-0302(21)00510-5/fulltext
Rasmussen, P., Barkema, H.W., Osei, P.P., Taylor, J., Shaw, A.P., Conrady, B., Chaters, G., Muñoz, V., Hall, D.C., Apenteng, O.O., Rushton, J., and Torgerson, P.R. (2024). Global losses due to dairy cattle diseases: A comorbidity-adjusted economic analysis. Journal of Dairy Science, 107(9), 6945-6970. https://www.journalofdairyscience.org/article/S0022-0302(24)00821-X/fulltext
Vredenberg, I., Han, R., Mourits, M., Hogeveen, H., and Steeneveld, W. (2021). An empirical analysis on the longevity of dairy cows in relation to economic herd performance. Frontiers in Veterinary Science, 8, 646672. https://www.frontiersin.org/journals/veterinary-science/articles/10.3389/fvets.2021.646672/full
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About DairyCommand
From our family to yours: we’re dairy people who understand that every cow represents an investment and every decision matters. DairyCommand combines veterinary science, data analytics, and practical farm experience to help you build a more profitable, sustainable operation. Our Cow Performance Ranking System analyzes lifetime data across your entire herd, identifying top performers to keep and breed, chronic underperformers to cull early, and declining animals requiring close monitoring. Learn more about transforming your culling decisions with lifetime data at signal2action.com
