Comment of the Day: A Quick and Easy Way To Decide What To Keep and What To Give Away

COMMENT OF THE DAY: A QUICK AND EASY WAY TO DECIDE WHAT TO KEEP AND WHAT TO GIVE AWAY “I can create a cost model for any particular item based on the cubic feet of space it requires for storage vs. the price per cubic foot of space in the house.* (Actual monthly cost, NOT “sale price per foot,” because taxes and interest are real things.) Measure the cost of keeping it for X period of time, vs. replacing it at an expected point in the future combined with the fuzzy application of inconvenience factors (can it only be purchased via a 1-hour drive, or week-long wait for delivery?) and criticality (would I have a broken pipe for days if I don’t have this pipe wrench?) and I have a good, solid grasp on any individual item and whether its worth keeping based on the expected frequency of its utility. If the cost of keeping it during the periods of uselessness exceeds the weighted replacement cost by more than 10%, it’s gone. Unfortunately, this model -can not- be applied to items with a sentimental factor value of greater than 0.3. Sure recipe for a very long argument with the SO. * – in a more functionally perfect model, the overall value of a particular sq. ft. of space would be [weighted] on many factors such as its visibility, ease of access, specialized design, etc. However, these factors complicate the model to such a degree that I’d then have to write some software to handle it, and then I’d have the further conjoining restraint of cost of permanent storage for the data as well as the physical items. I usually determine that the feedback cycle that rears its head in the process isn’t worth the effort, and the generalized model works well enough.” [drone, commenting on Comment of the Day: How Houston’s East Enders Have Rid Themselves of Clutter]

11 Comment

  • And how long did you attend college to learn this?

  • Just kidding, that was really funny.

  • If you have to think about it…just chunk it!

  • haha, above posters.
    I thought, “Well get on it! We need an Ap for this.”

  • Asset Management 101 – It’s true.

  • Did this raise the bar high enough?

  • My husband used to threaten to call the “Jettison Brothers” every time we moved, because I had more than 2 shelves of books. He managed to make several collections just “disappear” or “fall off the truck” when I wasn’t looking. Im guessing that “drone” is a left-brained man, and I applaud his minimalist attitude. But as someone who once moved from a 2200 sq. ft. house to an 850 sq. ft. apartment, believe me, I’ve “downsized” as far as I can go.

  • I admire your linear optimization, decision tree model and appreciate the reality of your simple life!

    Your core model assumption is based on no price risk exposure and a 2 sigma or 95% probability of operational risk exposure; however it appears you have isolated the random variable, statistical fat tail event of 99.9999% probability or 4 sigma event (fuzzy factor) which is adequate.

    As we all know in Houston, a critical event never happens in a singular observation but in clusters.

    For example, Hurricane strikes Houston, your home is damage by the floods, your insurance deemed damage to house by wind which you have no coverage, your car gets repo due to non-performance on a contractual obligation which was caused by loss wages due to the local, public company outsourcing your position to the Canada instead of India. Oh, did I fail to mention, all your associates and friends have left Houston based under defined disaster recovery protocols of their companies.

    How are we going to model the non-linear optimization problem based on the 4 sigma events? For me, a bottle of tequila from the downtown Specs, a nice hot shower from a a natural gas water heater instead of those tankless water heaters and a fabulous 20 minute reading of inspires me through that narrow path in metro city life!

  • Depreciation rate per square foot. The actual cost of the item is irrelevant.