diff --git a/bytesofpurpose-blog/blog/2026-08-04-deciding-what-to-buy.md b/bytesofpurpose-blog/blog/2026-08-04-deciding-what-to-buy.md new file mode 100644 index 000000000..2ce316795 --- /dev/null +++ b/bytesofpurpose-blog/blog/2026-08-04-deciding-what-to-buy.md @@ -0,0 +1,176 @@ +--- +slug: deciding-what-to-buy +title: "Deciding What to Buy" +kind: framework +sidebar_label: "Deciding What to Buy" +description: "A framework for making a purchase decision on evidence instead of spec sheets: rule things out before you score them, grade every claim by how you learned it, and never quote an asking price as a market price." +authors: [oeid] +tags: [decision-making, evaluation, best-practices, research] +date: 2026-08-04T10:00 +draft: true +--- + +The listing said the printer could run PEEK-CF. I looked up the machine's own spec sheet: the +nozzle tops out at 280 °C. PEEK needs somewhere around 400 °C and a heated chamber. Not a stretch, +not a "your mileage may vary" — physically impossible on that hardware. + +That one line took ninety seconds to check and told me more than the rest of the listing combined. +Not because the material mattered to me — it didn't — but because the seller had just demonstrated +they'd never run the machine. + + + +I set out to answer one question — *is this used printer worth it?* — and ended up building a +framework, because the reasoning kept being the same reasoning and I kept rebuilding it by hand. +This is that framework. The printer is just the worked example; the method is what transfers. + +## Why the normal approach fails + +The normal approach is: open four tabs, compare spec sheets, pick the one with the best numbers. + +It fails because **spec sheets are marketing**, and the things that actually determine whether you +get what you wanted appear on none of them: + +- What the replacement part costs when the common failure happens — and whether it's a $30 part or a + $180 sealed assembly that contains the $30 part +- How long spares will exist, which almost nobody publishes and which is therefore itself a signal +- What it actually sells for used, as opposed to what people are asking +- Which axis is slightly off, which the manufacturer will never tell you and the owners will + +Meanwhile the specs that *are* published are chosen to be flattering, quoted "up to," and measured +under conditions nobody names. + +## What I actually did + +Six steps. The order matters more than any individual step. + +**1. Pin the requirements before looking at any product.** Not specs — the *job*. What's the biggest +thing you need to make? Where will it live? Who's going to run it? A person knows what they want to +do. They don't know what build volume, tolerance, or duty cycle that implies, and asking them to +translate is asking them to do the hard part themselves. + +Write these down and stop. Everything downstream is built on them, and adding one later is expensive +— more on that below. + +**2. Rule things out loudly, before scoring anything.** Some failures aren't low scores, they're +disqualifications: it doesn't fit, it can't cut that material, there's no ventilation path in that +room, the electrical service doesn't exist, it's end-of-life inside your ownership window. + +The temptation is to score those candidates anyway and let them lose on points. Don't. A +disqualification buried inside a weighted average reads as *merely weak* rather than *impossible*, +and a table is very good at making impossible look like 2.4. + +**3. Score the survivors against written anchors.** Not "5 = excellent accuracy," which says nothing. +`5 = ±0.05 mm held across a batch, under load.` Anchors written as observable outcomes mean the same +thing across candidates and across years. Anchors written as adjectives mean whatever you felt like +that afternoon. + +**4. Grade every score by how you learned it.** This turned out to be the most valuable single idea, +and it came from a frustration: **nobody publishes comparable test data.** No reviewer had run all +three candidate machines on the same file. Every comparison I could find was assembled from +different materials, different profiles, different rooms, different operators. + +So each cell carries a grade: + +| Grade | Means | +|---|---| +| **A** | Independently measured — somebody put calipers on it | +| **B** | Reviewed but not measured — described, no figure | +| **C** | Owner report — a forum post, a seller claim, one anecdote | +| **D** | Inference — reasoned from specs or a sibling model | + +And it goes **inline, in the cell**, not in a footnote. A footnote is a place where honesty goes to +be skipped. Inline, a table full of Ds looks like a table full of Ds, which is exactly what it is. + +The rule that makes this work: **a criterion you couldn't verify gets a D with a note saying what you +checked — never a blank, never a quiet guess.** A recorded gap stays visible. A skipped one silently +narrows the comparison down to whatever happened to be easy to find. + +**5. Weight by use case, not in the abstract.** The same eleven criteria produce different winners +depending on whether you're selling parts, prototyping, or doing this on weekends. Set the weights +from what the person told you in step 1. If two weighting profiles never change the ranking, they're +the same profile and one of them is decoration. + +**6. Compute cost over three years, separately from the score.** Purchase price plus consumables plus +the wear part plus the thing nobody budgets for — in this category, ventilation and the electrical +work — minus realistic resale. If the winner on points is also the most expensive to run, one of your +inputs is wrong. Go find out which. + +## What the research turned up + +Three findings that changed how I'd do this in any category. + +**The vendor's own support forum beat every review.** The single most decision-relevant fact in the +whole comparison came from a manufacturer's support forum, not from a review: owners reporting a +nominal 150 mm feature coming out at about 149 mm on stock profiles. The reviews described the +machine as accurate. The forum said *which axis was off*. + +This is now near the top of my evidence hierarchy — above spec sheets, above independent reviews. +Search the model name plus failure words: `accuracy`, `fails`, `warranty`, `won't`, `broke`. Then +read the *replies*. How fast and how well the vendor answers **is** the support-quality score, +observed instead of claimed. It's the highest-value search available and it's the one everybody +skips. + +**Asking prices ran about 87% above sold prices.** On the sample I collected — small, and I'll say so +rather than dress it up — the median asking price sat roughly 87% above the median confirmed sale. +The forum "comps" I found for the machine I was looking at ($5,250 in 2022, $3,500 in 2023) were +*never confirmed as sales at all*. Someone asked. That's all we know. + +This is why browsing a marketplace gives you a badly inflated sense of what something is worth: the +listings that never sell stay up forever, so what you're actually browsing is a museum of prices +nobody paid. Sold and asking are two different quantities and they must never be averaged together, +drawn with the same mark, or quoted in the same sentence without saying which is which. + +**One check killed more candidates than price did: the ceiling.** A used item cannot rationally be +worth more than the cheapest *new* item that meets all the same requirements — minus the warranty, +the remaining support horizon, and a healthier parts supply. Work out that new number first. It's the +anchor; everything else is a discount off it. Original MSRP is irrelevant, and a listing that leads +with "originally $X" is anchoring you on purpose. + +## What changed my mind + +The recommendation reversed twice, and both reversals came from *searching* rather than reasoning +from what I already knew. + +I started confident: buy the cheaper, better-supported current-generation machine; the used one has a +dying consumable format. Then I found a competitor I hadn't considered that cleared the size +requirement outright. Then I found a machine from the first manufacturer that inverted their own +naming — the cheapest model in the line had the *largest* build volume and the *highest* speed. +Nobody would guess that from the product names, and I certainly didn't. + +Related: one of the products I was comparing had a "+" in its name that I read as an upgrade tier. It +isn't. It replaced the original and there is no cheaper base version. **Verify what a product name +actually denotes before you put it in a table.** + +The lesson isn't "I was wrong twice." It's that **recalled knowledge about a product lineup is +routinely a generation stale**, and a recommendation built on it can reverse completely on a single +search. If your answer never changes during research, that's not confidence — it's a sign you were +confirming rather than checking. + +The other reversal was self-inflicted. Late in the process I added a criterion — programmatic API +control — and it reordered the entire ranking. One manufacturer's firmware verifies that commands +come from authorized software, and the escape hatch requires going LAN-only, which kills the cloud +features and the phone app. The other publishes an OpenAPI spec and runs local and cloud as one +service. + +Adding that criterion at the end meant re-researching candidates I'd already finished. **Pin the +requirements before you research, and build the matrix so it can be re-weighted rather than +re-derived.** + +## What I'd tell someone starting from scratch + +- **Check one claimed capability against the vendor's own stated maximum.** Ninety seconds. If the + listing claims something the hardware can't do, every other claim in it is unverified — the seller + either never used the machine or copied a spec sheet. +- **Find the cheapest new thing that meets all your requirements before you look at a single used + listing.** That's the ceiling, and it ends most "great deals" on its own. +- **Read the manufacturer's support forum**, not the reviews. Search failure words and read the + replies. +- **Write down what you don't know**, in the table, next to what you do. A comparison that only shows + the confident findings misrepresents itself, and the gaps are usually the more useful half. +- **Say your sample size out loud**, in the same sentence as the number. Three listings is an + anecdote. I don't quote a range under eight. + +A polished decision matrix is a persuasive object, and it is very easy to build one that overstates +what it knows. Most of the rules above exist for no other reason than to stop that — including when +the person being persuaded is me.