Observe
Darshana (seeing)Look at the situation as it is before forming a view: data, people, events, in their own terms.
In practice: Before a major decision, the CEO asks for the raw facts first and the recommendation second.
The 27 models
WCRC-GLC-01 — The Classical Acharyas
Adi Shankaracharya
The WCRC SeeClear Model
See the rope before you fight the snake.
THE MODEL
The WCRC SeeClear Model
The SeeClear Model treats most leadership failure as a failure of perception: leaders react to what they have projected onto a situation instead of what is there. It asks a leader to observe, separate fact from projection, enquire to the root, act on what is real, and then build the insight into the institution so it outlasts the person.
Anchor teaching: Adhyasa (superimposition): mistaking a rope for a snake
This is a selection of teachers linked with the Hindu tradition, not a ranking. The models offer management reflection, not religious instruction.
WCRC is not affiliated with or endorsed by any teacher or organisation discussed.
MODEL STRUCTURE
How it works
Separate fact from projection
Adhyasa auditName the fears, hopes, past wounds and status assumptions the team has laid over the facts, the snake drawn on the rope.
In practice: In each strategy review, the CEO lists which claims are observed and which are assumed, and labels them openly.
Enquire to the root
Vichara (enquiry)Keep asking what lies beneath a symptom until the cause is clear, with a trusted teacher, adviser or dissenting voice in the room.
In practice: The CEO assigns one person to argue the opposite case before any irreversible commitment.
Act on what is real
Decide and move once projection has been cleared; clear sight exists to serve action, and endless analysis is its own projection.
In practice: The CEO records the decision, the facts it rests on and the date it will be checked.
Institutionalise the insight
Matha (seat of teaching)Shankara's tradition is carried by the mathas, not by one life of about 32 years. A leader builds the habit of clear sight into structures that outlive any one person.
In practice: The CEO turns the review questions into a standing decision checklist used across business units.
TEACHING AND CONTEXT
The thinking behind it
Devotees recount that at Kashi, Shankara asked a chandala, a man that society treated as an outcaste, to step out of his way. The man asked whether the body should move from the body, or the self from the self, since both are the same in all. Shankara saw that his own command rested on a projection of status, bowed, and composed the Manisha Panchakam. The story shows a teacher of rank changing course the moment he saw what was real.
Superimposition (adhyasa): suffering comes from mistaking the body-mind for the self, like seeing a snake in a rope.
Stanford Encyclopedia of Philosophy, as given in briefKnowledge liberates: direct knowledge, gained through scripture, a teacher and reflection, removes ignorance; it is realised, not manufactured.
Stanford Encyclopedia of Philosophy, as given in briefThe same Self is present in every person, whatever their status (the chandala episode and Manisha Panchakam).
Sringeri Sharada Peetham, Madhaviya Shankara Digvijayam (abridged), as given in briefThe amnaya mathas that tradition credits to him carried the teaching beyond his short life (the exact number is disputed between institutions).
Sringeri Sharada Peetham; Kanchi Kamakoti Peetham, as given in briefOPERATING MODEL
From principle to practice
Inputs
- Raw data and front-line reports
- Dissenting views on record
- Leaders willing to question themselves
Practices
- Fact-versus-assumption labelling in reviews
- Root-cause enquiry before major commitments
- Pre-decision bias checklist
- Post-decision review against original facts
Outputs
- Fewer decisions built on untested assumptions
- Shorter, clearer board papers
- A written record of decision logic
Outcomes
- Better capital allocation
- Earlier detection of strategic errors
- Judgement that survives leadership change
BENEFIT MODEL
Who it is for
leader
The leader carries fewer avoidable mistakes and can explain every major decision by the facts it stood on.
employees
People see that evidence counts more than rank, so they bring bad news and unpopular data earlier.
customers
Products and services respond to what customers actually do and say, not to what the company assumes they want.
investors
Investors get decisions with traceable reasoning and a management team that admits and corrects errors quickly.
society
Institutions that check their own projections are less likely to harm people through careless assumptions about them.
WCRC MODEL PARAMETERS
Model emphasis
The scores describe this model's emphasis on each parameter. They are not scores for a person or organisation.
Vision Quotient5 / 5
Impact Index3 / 5
Innovation Score5 / 5
People Leadership2 / 5
Stakeholder Trust4 / 5
Resilience Factor3 / 5
Global Mindset2 / 5
THE AI AGE
Why it matters now
Dashboards, forecasts and AI outputs now arrive with a confidence that can hide error, and AI adoption has reached 88% of surveyed organisations [4]. A model's output is a rope that can look like a snake, or the reverse. Kahneman's account of fast and slow thinking [1] and the work on noise in judgement [2] show how easily people project onto data. The SeeClear discipline gives a CEO a simple test before acting on any machine output: what is observed, what is assumed, and who has checked the root?
EXECUTION
Put the model to work
On Monday, ask for the raw facts behind your next major decision before anyone sends you a recommendation.
Founder and CEO
- Ask for facts first: In the first week, require every decision paper that reaches you to open with observed facts and put the recommendation after them. Founders of small firms can ask for this in person; CEOs of large ones should write it into the paper template.
- Label your own assumptions: In each strategy review, say aloud which of your own claims are observed and which are assumed before you label anyone else's. This keeps the adhyasa audit from becoming a weapon in internal politics.
- Appoint a standing dissenter: Before each irreversible commitment, name one person to argue the opposite case and hear them out in full in the meeting. Rotate the role every quarter so dissent does not become one person's identity.
- Record and date decisions: For every major decision, write down the decision, the facts it rests on and the date it will be checked, and keep the log yourself. Revisit each entry on its date and say openly if the facts have changed.
- Set a limit on enquiry: Agree a decision date at the start of each enquiry so vichara serves action and does not become paralysis. Each month, check which decisions you are delaying in the name of more analysis.
Company
- Audit recent decision papers (CEO office with the company secretary): Review the last quarter's board and executive papers and mark which claims were observed and which were assumed. This sets the starting point for the assumption labelling rate.
- Pilot in one review forum (CEO and one business head): Run fact-versus-assumption labelling and a documented opposing case in one unit's strategy reviews for a quarter. Small companies can pilot this in the weekly leadership meeting.
- Embed the decision checklist (CEO office and board): Turn the review questions into a standing pre-decision checklist attached to every capital request and board paper, followed by a post-decision review against the original facts. Make assumption labelling a condition for a paper to be tabled.
- Train managers in root-cause enquiry (CHRO with business heads): Teach all people managers to separate fact from projection, run root-cause enquiry and argue the opposite case without personal attack. Include how to check AI-assisted recommendations against source data.
- Track the clear-sight KPIs (Company secretary and CFO): Report assumption labelling rate, decision reversal lead time, dissent on record and AI output verification to the board every quarter. Treat a fall in dissent on record as a warning sign.
- Scale and refresh the checklist (Board): Extend the checklist to every business unit once the pilot shows clearer papers, and review it every year so it does not harden into a form to fill. Retire questions that no longer prompt real enquiry.
Readiness check
Before starting
- Will the leadership team accept having its own assumptions labelled in front of colleagues?
- Is someone willing to argue the opposite case before major commitments without fear of penalty?
- Do we keep a written record of why major decisions were made?
Phase 1 · Diagnose and commit
Establish how far current decisions rest on projection instead of observed fact.
- Audit last quarter's board and executive papers, marking each material claim as observed or assumed (the adhyasa audit).
- In the next strategy review, the CEO labels their own claims as observed or assumed before labelling anyone else's.
- Open a decision log recording each major decision, the facts it rests on and the date it will be checked (Act on what is real).
- Choose one business unit's strategy review as the pilot forum and name its first standing dissenter for the Enquire to the root step.
Deliverable: An assumption baseline drawn from last quarter's papers, and an open decision log.
Gate: Baseline recorded for every KPI (or a written note of why one cannot yet be measured), the decision log is open, and the pilot unit head has agreed to run labelled reviews.
Phase 2 · Pilot and prove
Show in one review forum that labelled facts and a documented opposing case give clearer decisions without slowing them.
- Apply fact-versus-assumption labelling to every paper tabled in the pilot unit's reviews.
- Require a documented opposing case before any irreversible commitment, argued in full in the meeting.
- Agree a decision date at the start of each enquiry so vichara ends in action.
- Log every AI-assisted recommendation and check it against source data before it reaches a decision.
Deliverable: A pilot review pack: labelled papers, opposing cases on file and a first post-decision review against the original facts.
Gate: Every irreversible commitment in the pilot unit has a documented opposing case on file, AI output verification is logged for each AI-assisted recommendation, and no pilot decision ran past its agreed decision date for want of more analysis.
Phase 3 · Embed and scale
Make the clear-sight checklist a condition for tabling any capital request or board paper.
- Turn the pilot review questions into a standing pre-decision checklist (Institutionalise the insight).
- Train people managers in root-cause enquiry, arguing the opposite case without personal attack, and checking AI output against source data.
- Extend assumption labelling and documented opposing cases to every business unit's reviews.
- Start quarterly post-decision reviews that compare outcomes with the facts each decision was approved on.
Deliverable: A board-approved decision checklist and the first quarterly clear-sight KPI report to the board.
Gate: The company secretary confirms assumption labelling on every board paper tabled in the quarter, and the board has received its first report on all four clear-sight KPIs.
Phase 4 · Sustain and renew
Keep the enquiry alive so the checklist does not harden into a form to fill.
- Review the checklist every year and retire or rewrite questions that no longer prompt real enquiry.
- Rotate the standing dissenter role every quarter across senior people.
- The CEO reopens their own logged decisions when the facts change and says so openly.
- Track decision reversal lead time from post-decision reviews as the main sign that clear sight is working.
Deliverable: An annually refreshed checklist and a decision log covering every major decision since launch.
Gate: Decision reversal lead time is stable or shortening in post-decision reviews, and the annual checklist review has rewritten or retired questions that had stopped prompting enquiry.
Governance
sponsor: The CEO, because projection starts at the top and only the CEO can have their own assumptions labelled in public without the exercise turning into internal politics.
lead: The company secretary, who already controls what reaches the board and can check labelling and opposing cases on every paper.
forum: Monthly in the executive committee for the pilot and the decision log; quarterly at the board's audit or risk committee for the clear-sight KPIs.
decision_rights: The lead can send back any paper that lacks assumption labelling or a documented opposing case; changes to the checklist itself and any exemption for an urgent decision go to the CEO.
Cadence
Daily: Decision owners log each AI-assisted recommendation with the source data they checked it against.
Weekly: The CEO reviews decision log entries that have reached their check date and reopens any whose facts have changed.
Monthly: The executive committee opens with one past decision examined against its original facts, observed and assumed claims marked.
Quarterly: The standing dissenter role rotates, and the board receives the assumption labelling, reversal lead time, dissent and AI verification figures.
Annually: The checklist is reviewed and questions that no longer prompt real enquiry are retired.
By company stage
startup
The founder asks for facts first in person and keeps the decision log in a shared document, with the weekly team meeting as the review forum. A co-founder or early hire argues the opposite case on every irreversible bet, such as a key hire, a fundraise or a change of market.
scaleup
The decision paper template carries an observed and an assumed section, checked by the CFO or chief of staff before leadership meetings. Labelling and opposing cases spread unit by unit after one pilot, with managers trained in root-cause enquiry.
enterprise
The company secretary makes labelling a condition for tabling board papers and capital requests, and the audit or risk committee reviews the clear-sight KPIs each quarter. The board asks for post-decision reviews of major investments against the facts on which they were approved.
Success looks like
- Board papers open with observed facts, and directors ask 'observed or assumed?' without being prompted.
- Leaders reverse a decision openly when its facts change, and the decision log shows the reasoning.
- AI-assisted recommendations reach the executive committee together with the source data they were checked against.
MEASUREMENT AND LIMITS
What to watch
Assumption labelling rate
Share of board and executive papers that separate observed facts from assumptions, checked by the company secretary each quarter.
Decision reversal lead time
Average time between a decision going wrong and the leadership formally acknowledging it, taken from post-decision reviews.
Dissent on record
Share of major decisions with a documented opposing case before approval.
AI output verification
Share of AI-assisted recommendations in material decisions that were independently checked against source data, logged by the decision owner.
Failure modes
- Clear sight turns into paralysis: endless enquiry used as a reason never to act.
- The leader audits everyone's projections except their own, and the model becomes a weapon in internal politics.
- The checklist is institutionalised as a form to fill, and the actual enquiry stops.
Execution risks
- Enquiry turns into paralysis, and more analysis becomes the reason never to commit.: Decisions are pushed past their agreed decision dates with the note 'pending more data'. Mitigation: Fix the decision date when the enquiry opens, and have the CEO decide on the available facts any item that misses its date.
- The audit is used on others but not on the top, so it becomes a weapon in internal politics.: Junior authors' papers arrive heavily labelled while the CEO's and senior leaders' proposals come through unlabelled. Mitigation: Put the CEO's own papers through the check first, and have the company secretary report labelling by author seniority.
- Authors game the labelling rate by marking every claim as observed.: The labelling rate looks healthy, yet post-decision reviews keep finding untested assumptions behind approved decisions. Mitigation: Sample papers each quarter and trace a set of 'observed' claims back to their source data.
- Dissent becomes a ritual, especially where contradicting a senior person is culturally hard.: Opposing cases are always written by the most junior person present and never change or shape a decision. Mitigation: Rotate the dissenter role among senior people, allow written dissent before the meeting, and record where dissent altered a decision.
RESEARCH SOURCES
Sources and notes
- Kahneman, D. (2011). Thinking, Fast and Slow. New York: Farrar, Straus and Giroux.
- Kahneman, D., Sibony, O., & Sunstein, C. R. (2021). Noise: A Flaw in Human Judgment. New York: Little, Brown Spark.
- Kahneman, D., Lovallo, D., & Sibony, O. (2011). Before you make that big decision… Harvard Business Review, 89(6), 50–60.
- Stanford Institute for Human-Centered Artificial Intelligence (HAI). (2026). The 2026 AI Index Report, Chapter 4: Economy. Stanford University.
The WCRC Guru Management Codex and its 27 models are proprietary WCRC models. © WCRC. All rights reserved.