Template:M intro design System redundancy: Difference between revisions

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 {{Quote|“I think the people in this country have had enough of experts from organisations with acronyms saying that they know what is best and getting it consistently wrong.”
 :—Michael Gove}}
-===On pet management theories===
 [[System redundancy|The]] JC likes his pet management theories as you know, readers, and none are dearer to his heart than the idea that the [[High modernism|high-modernist]]s have, for forty years, held western management orthodoxy hostage.
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 In any case, just in time rationalisers take a cycle and code for that.  What is the process, start to finish, what are the dependencies, what are the plausible unknowns, and how do we optimise for efficiency of movement, components and materials, to manage
+=== It’s the long run, stupid===
+The usual approach for system optimisation is to take a snapshot of the process as it is over its lifecycle, and map that against a hypothetical critical path. Kinks and duplications in the process are usually obvious, and we can iron them out to reconfigure the system to be as efficient and responsive as possible. Mapping best case and worst case scenarios for each phase in that life cycle can give good insights into which parts of the process are in need of re-engineering: it is often [[What will it look like?|not the ones we expect]].
+But how long should that life cycle be? We should judge it by the frequency of the worst possible negative event that could happen. Given that we are contemplating the [[infinite]] future, this is hard to say, but it is longer than we think: not just a single manufacturing cycle or reporting period. The efficiency of a process must take in ''all'' parts of the cycle — the whole gamut of the four seasons — not just that nice day in July when all seems fabulous with the world. There will be other days; difficult ones, on which where multiple unrelated components fail at the same moment, or where the market drops, clients blow up, or tastes gradually change. There will be almost imperceptible, secular changes in the market which will demand products be refreshed, replaced, updated, reconfigured; opportunities and challenges will arise which must be met: your window for measuring who and what is ''truly'' redundant in your organisation must be long enough to capture all of those slow-burning, infrequent things.
+Take our old, now dearly departed, friends at [[Credit Suisse]]. Like all banks, over the last decade they were heavily focused on the ''cost'' of their prime brokerage operation. Prime brokerage is a simple enough business, but it’s also easy to lose your shirt doing it.
+In peace-time, things looked easy for [[Credit Suisse]], so they juniorised their risk teams. This, no doubt, marginally improved their net peacetime return on their relationship with [[Archegos]]. But those wage savings — even if $10m annually, were out of all proportion to the incremental risk that they assumed as a result.
+(We are, of course, assuming that better human risk management might have averted that loss. If it would not have, then the firm should not have been in business at all)
+The skills and operations you need for these phases are different, more expensive, but likely far more determinative of the success of your organisation over the long run.
+The [[Simpson’s paradox]] effect: over a short period the efficiency curve may seem to go one way; over a longer period it may run perpendicular.
+The perils, therefore, of data: it is necessarily a snapshot, and in our impatient times we imagine time horizons that are far too short. A sensible time horizon should be determined not by reference to  your expected regular income, but to your worst possible day. Take our old friend [[Archegos]]: it hardly matters that you can earn $20m from a client in a year, consistently, every year for twenty years ''if you stand to lose  five billion dollars in the twenty-first''.
+Then, your time horizon for redundancy is not one year, or twenty years, but ''two-hundred and fifty years''. Quarter of a millennium: that is how long it would take to earn back $5 billion in twenty million dollar clips.