{"id":1062,"date":"2026-06-04T21:10:45","date_gmt":"2026-06-04T21:10:45","guid":{"rendered":"https:\/\/drms.org\/?page_id=1062"},"modified":"2026-09-17T13:05:27","modified_gmt":"2026-09-17T17:05:27","slug":"too-much-data-no-clear-signal","status":"publish","type":"page","link":"https:\/\/drms.org\/index.php\/products-and-services\/herd-hq\/too-much-data-no-clear-signal\/","title":{"rendered":"Too Much Data, No Clear Signal"},"content":{"rendered":"\n\n\n\n\n<p class=\"wp-block-paragraph\"><em>This case study is based on real DRMS testing data and herd-level outcomes from a large Midwest herd. While the farm is not identified, the scenario reflects actual analysis and results, showing how HerdHQ tools like MilkMetrics and DairyDepot can surface key improvement areas and support confident, data-driven decisions.<\/em><\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Background<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">A 3,300-cow herd in the Midwest was trying to understand why performance gains had stalled. The cows looked good, facilities were solid, and the nutrition program was strong. But overall herd performance wasn\u2019t improving \u2014 and they weren\u2019t sure how they stacked up against their peers. The team had plenty of data \u2014 they just didn\u2019t have a clear view of what was working and what wasn\u2019t.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">The Problem<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">The herd&#8217;s data was not integrated. It took too much time to sift through different sources to find answers, and it wasn\u2019t clear which metrics actually needed attention. Without a unified view, it was tough to know where to focus or how to measure progress.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">The Solution<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">With HerdHQ\u00ae, the team could quickly and easily identify the areas that needed the most attention.<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>They used&nbsp;<strong>MilkMetrics<\/strong>&nbsp;to compare their herd to other Midwest herds over 1,000 cows.\n<ul class=\"wp-block-list\">\n<li>Although the herd had an older age profile (top 75%), milk production ranked in the bottom half, and fat was in the bottom 20%.<\/li>\n\n\n\n<li>Somatic Cell Count (SCC) was also a concern \u2014 higher than 75% of peer herds.<\/li>\n\n\n\n<li>A high percentage of their cows, nearly 15%, had dry periods under 40 days, while peer average was below 2%.<\/li>\n\n\n\n<li>Reproduction was strong: pregnancy rate was over 30% (top 80th percentile), and 1st service success was in the top quartile.<\/li>\n\n\n\n<li>Genetics were excellent, well above peer averages.<\/li>\n<\/ul>\n<\/li>\n\n\n\n<li>After identifying production, components, and short dry periods as key issues, they used&nbsp;<strong>DairyDepot<\/strong>&nbsp;to dig deeper.\n<ul class=\"wp-block-list\">\n<li>Despite an increase in average milk, peak milk had been steadily dropping, and Energy Corrected Milk (ECM) was flat.<\/li>\n\n\n\n<li>Mature Equivalent (ME) values were declining across all lactation groups, while average days in milk continued to rise.<\/li>\n\n\n\n<li>First-lactation cows were calving in with much lower production than older cows \u2014 averaging just 60% when they should be at 75\u201380%. Peak milk values were also considerably lower for lactation 1 cows, indicating a need to dig into fresh cow performance.<\/li>\n\n\n\n<li>SCC issues were concentrated in third-lactation cows, averaging a linear score of 3.5, while lactation 1 and 2 cows were below 1.5.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n\n\n\n<h3 class=\"wp-block-heading\">The Results<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li><strong>$445,500 projected annual herd gain<\/strong>\n<ul class=\"wp-block-list\">\n<li>Overall herd peak milk rose from 104 to 107 lbs.<\/li>\n\n\n\n<li>This 3 lb. increase equates to 675 lbs. more milk per cow annually.<\/li>\n\n\n\n<li>At $20\/cwt, that\u2019s a gain of $135 per cow, or $445,500 across 3,300 cows.<\/li>\n<\/ul>\n<\/li>\n\n\n\n<li><strong>ME Milk averages went from 24,712 with 172 days in milk to 26,346 and 167 days in milk<\/strong>\n<ul class=\"wp-block-list\">\n<li>Late lactation cows were managed better and improved turn over.<\/li>\n<\/ul>\n<\/li>\n\n\n\n<li><strong>$350 gain per lactation 2 cow<\/strong>\n<ul class=\"wp-block-list\">\n<li>In just 6 months, peak milk for lactation 2 cows increased from 109 to 116 lbs.<\/li>\n\n\n\n<li>That 7 lb. increase in peak milk equates to roughly 1,750 additional pounds over the lactation \u2014 or $350 in added income per cow at $20\/cwt.<\/li>\n<\/ul>\n<\/li>\n\n\n\n<li><strong>First test production on lactation 1 cows increased 8%<\/strong>\n<ul class=\"wp-block-list\">\n<li>First test production on lactation 1 cows went from 75 to 81 lbs. of milk.<\/li>\n<\/ul>\n<\/li>\n\n\n\n<li><strong>Additional $143 income on lactation 3 cows<\/strong>\n<ul class=\"wp-block-list\">\n<li>Lactation 3 cows went from 3.5 to 2.2 linear score, resulting in 715 lbs. more milk in the lactation or $143 per cow at $20\/cwt.<\/li>\n<\/ul>\n<\/li>\n\n\n\n<li><strong>Herd has continued to target shorter dry periods for cows going into their 3rd or greater lactation<\/strong>\n<ul class=\"wp-block-list\">\n<li>Herd is using a 45-day dry period for incoming lactation 3+ cows and a 55-day dry period for incoming lactation 2.<\/li>\n\n\n\n<li>Suggest that this approach be changed driven by first-test results showing that lactation 2 cows continue to outperform lactation 3+ cows \u2013 highlighting the need for more recovery time for the older cows.<\/li>\n<\/ul>\n<\/li>\n\n\n\n<li><strong>All data pulled together for quick review<\/strong>\n<ul class=\"wp-block-list\">\n<li>Once key issues were identified, the team set alerts in&nbsp;<strong>MilkMetrics<\/strong>&nbsp;to flag dips or highlight major improvements \u2014 making it easier to recognize problems or celebrate wins.<\/li>\n\n\n\n<li>A custom dashboard in&nbsp;<strong>DairyDepot<\/strong>&nbsp;now allows for fast follow-up analysis \u2014 saving time and helping the team track previously flagged concerns while staying focused on progress.<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n\n\n<div class=\"is-text wp-block-ncst-buttons\">\n    \n<div class=\"wp-block-ncst-button\">\n      <a\n        class=\"ncst-block__button-link btn\"\n        href=\"https:\/\/drms.org\/wp-content\/uploads\/2026\/06\/HerdHQ-Case-Study-Too-Much-Data.pdf\"\n        data-ncst-lightbox=\"false\"\n         target=\"_blank\"          rel=\"noreferrer noopener\"       >\n                  <span class=\"text\">Download Printable PDF<\/span><span class=\"arrow-indicator\"><svg class=\"wolficon wolficon-arrow-right-bold\" role=\"img\"  aria-hidden=\"true\">\n\t\t\t\n\t\t\t<use xlink:href=\"#wolficon-arrow-right-bold\">\n\t\t<\/svg><\/span>\n              <\/a>\n    <\/div>\n  \n\n  <\/div>\n\n\n<div class=\"layout-one-column is-text wp-block-ncst-link-list\">\n          <h2 class=\"link-list-section__heading\">\n        explore more\n      <\/h2>\n        <ul class=\"link-list__container\">\n      \n<li class=\"ncst-component__bold-link-container wp-block-ncst-bold-link\">\n      <a \n      href=\"https:\/\/drms.org\/index.php\/products-and-services\/herd-hq\/\"\n      class=\"ncst-component__bold-link text-link\"\n                >\n    <span class=\"text\">Back to HerdHQ Overview <\/span><span class=\"arrow-indicator\"><svg class=\"wolficon wolficon-arrow-right-bold\" role=\"img\"  aria-hidden=\"true\">\n\t\t\t\n\t\t\t<use xlink:href=\"#wolficon-arrow-right-bold\">\n\t\t<\/svg><\/span>\n    <\/a>\n      <\/li>\n  \n\n    <\/ul>\n  <\/div>\n","protected":false},"excerpt":{"rendered":"<p>This case study is based on real DRMS testing data and herd-level outcomes from a large Midwest herd. While the farm is not identified, the scenario reflects actual analysis and results, showing how HerdHQ tools like MilkMetrics and DairyDepot can surface key improvement areas and support confident, data-driven decisions. Background A 3,300-cow herd in the&hellip;<\/p>\n","protected":false},"author":3,"featured_media":0,"parent":46,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"ncst_custom_author":"","ncst_show_custom_author":false,"ncst_dynamicHeaderBlockName":"ncst\/split-header","ncst_dynamicHeaderData":"{\"backgroundColor\":\"custombg_one\",\"imageID\":2122,\"imageURL\":\"https:\/\/drms.org\/wp-content\/uploads\/2026\/07\/Too-much-data-video-thumbnail-web.jpg\",\"pageIntro\":\"HerdHQ Case Study\",\"imageAlt\":\"Link to Too Much Data video\"}","ncst_content_audit_freq":"","ncst_content_audit_date":"","ncst_content_audit_display":false,"ncst_backToTopFlag":"","footnotes":""},"class_list":["post-1062","page","type-page","status-publish","hentry"],"acf":[],"_links":{"self":[{"href":"https:\/\/drms.org\/index.php\/wp-json\/wp\/v2\/pages\/1062","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/drms.org\/index.php\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/drms.org\/index.php\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/drms.org\/index.php\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/drms.org\/index.php\/wp-json\/wp\/v2\/comments?post=1062"}],"version-history":[{"count":7,"href":"https:\/\/drms.org\/index.php\/wp-json\/wp\/v2\/pages\/1062\/revisions"}],"predecessor-version":[{"id":3568,"href":"https:\/\/drms.org\/index.php\/wp-json\/wp\/v2\/pages\/1062\/revisions\/3568"}],"up":[{"embeddable":true,"href":"https:\/\/drms.org\/index.php\/wp-json\/wp\/v2\/pages\/46"}],"wp:attachment":[{"href":"https:\/\/drms.org\/index.php\/wp-json\/wp\/v2\/media?parent=1062"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}