{"id":7950,"date":"2026-09-17T09:50:40","date_gmt":"2026-09-17T07:50:40","guid":{"rendered":"https:\/\/getnave.com\/blog\/?p=7950"},"modified":"2026-09-17T09:50:40","modified_gmt":"2026-09-17T07:50:40","slug":"chat-with-your-delivery-data","status":"publish","type":"post","link":"https:\/\/getnave.com\/blog\/chat-with-your-delivery-data\/","title":{"rendered":"Want to Chat with Your Delivery Data? Decide Who Owns the Math First (Build the Engine, or Use One That&#8217;s Ready)"},"content":{"rendered":"<div class=\"cf-14869-area-150045\"><\/div>\n<p>Sooner or later, every org points an LLM at its raw delivery data and arrives at the same decision. It usually takes a few months to show up.<\/p>\n<p>The experiment starts the same way everywhere. An engineer wires the tracker&#8217;s API to a model in a sprint, the demo answers every question leadership throws at it, and for a while, chatting with your delivery data feels solved. Then a team renames two workflow states. Another starts routing defects through a separate board. Someone asks last quarter&#8217;s question again, gets a different number, and nobody can say which of the two was right.<\/p>\n<p>That&#8217;s the moment the decision surfaces. The numbers your org plans around need an engine underneath them: calculation rules written down, tested, and applied the same way to every question, every time. And there are exactly two ways to get one. You build one and commit to maintaining it, or you use one that&#8217;s ready.<\/p>\n<p>Most organizations make this choice without noticing they&#8217;re making it. The prototype just keeps running. Today, let&#8217;s make it on purpose, on paper, with a name next to it.<\/p>\n<h2>What the Demo Didn&#8217;t Sign You Up For<\/h2>\n<p>And I can guess the objection: our engineers already built the prototype, and it works. I believe you! The demo probably earned the reaction it got, and your engineers did nothing wrong.<\/p>\n<p>And that&#8217;s the trap: the prototype settled the calculation rules once, for one board, for the workflow as it looked that month. And that workflow is already gone. Boards change every quarter: a state gets added, a team splits, defects start taking a different path. Every one of those changes reopens a rule somebody thought was settled.<\/p>\n<p>So walk it forward with me. Does the prototype produce a cycle time today? It does. Will it produce the same cycle time after the next board change? Only if someone notices the change, re-decides the rules, and retests them. Is that someone&#8217;s name written down anywhere? In most organizations, no.<\/p>\n<h2>Two Ways to Get an Engine<\/h2>\n<p>Building is still a legitimate choice. If delivery analytics sits close to your core business and you&#8217;ll fund a named owner for the definitions, it can be the right call. Just size it correctly. The wiring is a sprint of work. The rules are a standing job that starts the day the demo ends and has no last day.<\/p>\n<p>Using one that&#8217;s ready is the other way, and we&#8217;ll look at what ready means in a moment. Either way, the decision deserves a sentence on paper, because an unmade decision here doesn&#8217;t stay neutral. It defaults to the prototype, with nobody&#8217;s name on it.<\/p>\n<h2>Six Questions, Whichever Way You Go<\/h2>\n<p>There&#8217;s a check that settles where you stand, and it works on anything: a prototype, a vendor tool, the spreadsheet a project manager keeps alive. Sit down with the source your org relies on today and ask it six questions. Which workflow states count as the start of work, and which count as the end? What happens to an item that moves backward? To one that skips straight to done? To one that gets reopened after it was closed? Does the time work spends waiting count toward the number? And is the number you get back an average, or a percentile you could commit to?<\/p>\n<p>A source you can build commitments on answers all six, applies the same rules to every question, and can walk you through the math when you ask. If yours can&#8217;t, your build-or-ready decision is already overdue.<\/p>\n<h2>What Ready Looks Like<\/h2>\n<p>Ready means the rules were settled and tested long before your question arrived. That&#8217;s what we&#8217;ve spent eight years building Nave to be, edge case by edge case, so the definitions still hold when the boards underneath them change.<\/p>\n<p>Here&#8217;s a ready engine answering the biggest question in delivery: when will it all be done? The Monte Carlo simulation in Nave runs a large number of random trials using your past throughput data to predict your throughput for a future time frame. On the chart below, the question was 40 backlog items starting March 1st, and the engine ran 10,000 trials on the team&#8217;s own throughput history. Follow the dotted 85% line, the point where 85 of every 100 trials had all the work finished, and it hands you the sentence for the planning meeting: there is an 85% probability that we can finish all the backlog items by July 5th. Run the simulation again tomorrow, and the answer moves only if the data moved.<\/p>\n<p><a href=\"https:\/\/getnave.com\/blog\/wp-content\/uploads\/monte-carlo-simulation-results-nave.png\" target=\"_blank\" rel=\"noopener\"><img loading=\"lazy\" decoding=\"async\" class=\"alignnone size-full wp-image-7951\" src=\"https:\/\/getnave.com\/blog\/wp-content\/uploads\/monte-carlo-simulation-results-nave.png\" alt=\"Monte Carlo: Delivery Date simulation in Nave, a histogram of 10,000 trials on the team's own throughput data, with percentile lines and an 85% probability of finishing 40 items by July 5th\" width=\"1710\" height=\"877\" srcset=\"https:\/\/getnave.com\/blog\/wp-content\/uploads\/monte-carlo-simulation-results-nave.png 1710w, https:\/\/getnave.com\/blog\/wp-content\/uploads\/monte-carlo-simulation-results-nave-768x394.png 768w, https:\/\/getnave.com\/blog\/wp-content\/uploads\/monte-carlo-simulation-results-nave-1536x788.png 1536w, https:\/\/getnave.com\/blog\/wp-content\/uploads\/monte-carlo-simulation-results-nave-700x359.png 700w\" sizes=\"auto, (max-width: 1710px) 100vw, 1710px\" \/><\/a><br \/>\n<em>The Monte Carlo simulation in Nave. 10,000 trials on the team&#8217;s own throughput history, an 85% probability of finishing all 40 backlog items by July 5th. The same rules, every run. Learn more at <a href=\"https:\/\/getnave.com\" target=\"_blank\" rel=\"noopener\">getnave.com<\/a>.<\/em><\/p>\n<p>And you keep the chat! Nave&#8217;s MCP server lets your own AI tools ask their questions against validated metrics instead of against raw tracker records, so the interface everyone wants sits on top of math that doesn&#8217;t change between questions.<\/p>\n<div class=\"cf-14869-area-125960\"><\/div>\n<h2>Tomorrow Morning: One Sentence, With a Name in It<\/h2>\n<p>Here&#8217;s what to do, in two steps.<\/p>\n<p>First, run the six questions on whatever produces your numbers today. One team&#8217;s board is enough.<\/p>\n<p>Then write the decision down, one sentence, with a name in it. Either: we build and maintain our own engine, and this person owns the definitions. Or: we use one that&#8217;s ready. If nobody will put their name in the first sentence, the decision has made itself; the paper just makes it official. Book the half hour on your calendar now; if you don&#8217;t schedule it, you won&#8217;t get to it.<\/p>\n<p>Your org is going to chat with its delivery data. That part is settled, and it should be. What the answers are worth is decided by the engine underneath them, and an engine nobody owns produces numbers nobody should plan around.<\/p>\n<p>Thanks for tuning in! I&#8217;ll see you next week, same time and place for more managerial goodness. Bye for now!<\/p>\n<div class=\"cf-14869-area-150046\"><\/div>\n<div style='text-align:left' class='yasr-auto-insert-visitor'><\/div>","protected":false},"excerpt":{"rendered":"<p>Sooner or later, every org points an LLM at its raw delivery data and arrives at the same decision. It usually takes a few months to show up. The experiment starts the same way everywhere. An engineer wires the tracker&#8217;s API to a model in a sprint, the demo answers every question leadership throws at [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":7953,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"yasr_overall_rating":0,"yasr_post_is_review":"","yasr_auto_insert_disabled":"","yasr_review_type":"","footnotes":""},"categories":[69,7],"tags":[1949,1952,1951,1948,1813,1838,1955,1950,1954,1953],"class_list":["post-7950","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-process-improvement","category-project-management","tag-ai-delivery-analytics","tag-build-or-buy","tag-calculation-engine","tag-chat-with-your-data","tag-cycle-time","tag-data-driven-decisions","tag-delivery-metrics","tag-llm","tag-mcp-server","tag-monte-carlo-simulation"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v24.7 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Chat with Your Delivery Data? 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