Playbook: Difference between revisions
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And are we even going to talk about the fact that the big shock risks that hit the systems are never ones that have previously been recognised, analysed and subjected to constant monitoring? [[Black swan]]s gonna be [[black swan]]s, yo. | And are we even going to talk about the fact that the big shock risks that hit the systems are never ones that have previously been recognised, analysed and subjected to constant monitoring? [[Black swan]]s gonna be [[black swan]]s, yo. | ||
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Revision as of 11:36, 18 January 2020
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Negotiation Anatomy™
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A playbook is a comprehensive set of guidelines, policies, rules and fall-backs for the legal and credit terms of a contract that you can hand to the school-leaver in Bucharest to whom you have off-shored your master agreement negotiations. She will need it because, being a school-leaver from Bucharest, she won’t have the first clue about the subject matter of the negotiation, and will need to consult it to decide what do to should her counterparty object[1] to any of the preposterous terms your risk team has insisted go in the first draft of the contract.
Playbooks derive from a couple of mistaken beliefs: One, that a valuable business can be “solved” and run as an algorithm, not a heuristic;[2] and two, that, having been solved, it is a sensible allocation of resources to have a cheap and stupid human being run that process rather than a machine.[3]
In Thomas Kuhn’s argot[4] playbooks are “normal science”: They map out the discovered world. They contain no mysteries or conundrums. They represent tilled, tended, bounded, fenced, arable land. Boundaries have been set, tolerances limited, parameters fixed, risks codified and processes fully understood.
Playbooks are algorithms for the meatware: they maximise efficiency when operating within a fully understood environment. They are inhabited exclusively by known knowns. No playbook will ever say, “if the counterparty will not agree this, make a judgment about what you think is best.” All will say, “any deviations from this requirement must be approved by Litigation and at least one Credit officer of at least C3 rank.”
As far as they go, playbooks speak to the belief that, as normal science, the only material risk lies in not complying with established rules: They are of a piece with the doctrine of precedent: when they run out of road, one must appeal to the help of a higher authority, by means of escalation to a control function, the idea being (in theory, if not in practice) that the control function will further develop the algorithm to deal with the new situation — stare decisis — and it will become part of the corpus and be fed back down into the playbook of established processes.[5] The algorithm operates entirely inside the organisation’s real risk tolerance boundaries. This is a good thing from a risk monitoring perspective, and is inevitable as a matter of organisational psychology — if in doubt, stick it in — but it all comes at the cost of efficiency. The escalations it guarantees are a profoundly wasteful use of scarce resources.
In theory the control function will have its own playbook, and the “court of first instance” is as bound by that as the baseline process is by the basic playbook. There is an algorithm, a recipe, and the main ill that comes about is by not following it. Hence the existence of an internal audit function.
And are we even going to talk about the fact that the big shock risks that hit the systems are never ones that have previously been recognised, analysed and subjected to constant monitoring? Black swans gonna be black swans, yo.
See also
References
- ↑ As it will certainly do, to all of them.
- ↑ This is a bad idea. See Roger Martin’s The Design of Business: Why Design Thinking is the Next Competitive Advantage.
- ↑ Assumption two in fact falsifies assumption one. If it really is entirely mechanistic, there is absolutely no reason to have a human operating the process.
- ↑ The Structure of Scientific Revolutions. Brilliant book. Read it.
- ↑ This rarely happens in practice. Control functions make ad hoc exceptions to the process, do not build them into the playbook as standard rules, meaning that the playbook has a natural sogginess (and therefore inefficiency).