“PULSE-X™: From Potential to Performance — A New Coaching Architecture for the Future of Work”
- Dr Amrit Karmarkar
- 13 hours ago
- 9 min read
Copyright: Dr Amrit Karmarkar (2026). All Rights reserved
“PULSE-X™ is an original coaching architecture that integrates established coaching and experiential-learning principles around an explicit behavioural experimentation, evidence and adaptation loop.”
Executive Summary
PULSE-X™ is designed for organizations seeking a practical way to move development beyond conversation and intention into observable workplace learning. Its central premise is that a coaching conversation should produce more than insight: it should generate a testable hypothesis, a small behavioural experiment, evidence from the real work environment, and a deliberate learning-and-adaptation cycle.
The six-stage architecture is:
Stage | Core question | Primary output |
P — Perceive | What is happening? | Reality snapshot |
U — Unpack | What is underneath? | Assumption map |
L — Locate | What matters to me? | Identity & growth map |
S — Speculate | What might work? | Growth hypothesis |
E — Experiment | What can I test? | Micro-experiment |
X — X-Ray | What did reality teach me? | Learning & adaptation decision |
The defining mechanism is the Growth Evidence Loop: Assumption → Hypothesis → Experiment → Evidence → Learning → Adaptation. This extends the coaching process into the workplace and makes the employee's experience between sessions part of the development system.
1.1 Purpose
PULSE-X is intended for workplace coaching, manager-as-coach conversations, early-career development, career exploration, leadership development, internal mobility, capability building and other developmental contexts where the employee can safely test behaviours in real work.
1.2 Design principles
Agency before advice: the coachee owns decisions and experiments.
Reality before interpretation: observations are separated from stories and assumptions.
Identity plus behaviour: development addresses both who the person is becoming and what they do.
Small experiments before large commitments: reduce the cost of learning.
Evidence over certainty: treat assumptions as hypotheses rather than facts.
Learning over failure: an unsuccessful experiment is useful when it produces credible learning.
Adaptation over completion: the cycle continues until a useful behaviour is established or a hypothesis is discarded.
Boundaries matter: coaching is not therapy, clinical care, legal advice or performance adjudication.
1.3 Intended users
User | Primary use |
Internal coaches | Structured developmental coaching |
People managers | Short-cycle coaching in 1:1s |
L&D teams | Development programmes and coaching academies |
HRBPs | Career and capability conversations |
Employees | Self-coaching and reflection |
Leadership programmes | Application and transfer to workplace |
2. Theoretical Foundations & Positioning
PULSE-X does not claim to replace established coaching models. GROW, for example, structures coaching around Goal, Reality, Options and Will and is designed to be flexible rather than mechanical. PULSE-X builds a different emphasis: it makes the post-conversation experiment and evidence cycle explicit.
Experiential learning provides a second foundation. Kolb's model describes learning as a cycle involving concrete experience, reflective observation, abstract conceptualization and active experimentation. PULSE-X translates that logic into a coaching workflow in which workplace behaviour becomes the site of experimentation and subsequent evidence becomes the basis for adaptation.
2.1 Positioning against established models
Model | Primary contribution | PULSE-X relationship |
GROW | Goal, Reality, Options, Will | Extends the action stage into explicit hypothesis testing and evidence review. |
OSKAR | Outcome, scaling, know-how, affirmation, review | Adds a more explicit behavioural-experiment and evidence mechanism. |
CLEAR | Contract, listen, explore, action, review | Retains reflective/action logic but makes the experiment the central transfer mechanism. |
Co-Active | Whole person, values, fulfilment, balance, transformation | Uses identity/values as inputs to observable workplace experimentation. |
Experiential Learning | Experience, reflection, conceptualization, experimentation | Operationalizes the cycle as a coaching-to-workplace loop. |
The defensible originality claim is therefore one of synthesis and operationalization: PULSE-X makes the movement from coaching insight to workplace experiment, evidence, learning and adaptation a first-class component of the coaching architecture.
3. PULSE-X Theory of Change
The theory of change proposes that coaching produces stronger transfer when insight is converted into a bounded behavioural experiment, the experiment generates observable evidence, and that evidence is deliberately reviewed and used to modify subsequent behaviour.
Level | Mechanism | Expected change |
Input | Coach capability + safe coaching relationship | Psychological space for exploration |
Process | Perceive → Unpack → Locate | Greater clarity and assumption awareness |
Hypothesis | Speculate | Alternative explanations and possible actions |
Transfer | Experiment | Observable behaviour in real work |
Feedback | X-Ray | Evidence-based reflection |
Adaptation | Keep / Modify / Drop / Scale | Improved behavioural fit |
Outcome | Repeated learning cycles | Self-efficacy, capability, career clarity and work outcomes |
3.1 Core propositions to test
P1: PULSE-X increases developmental clarity relative to baseline.
P2: PULSE-X increases the frequency and quality of behavioural experimentation.
P3: Experimentation followed by structured reflection increases learning from experience.
P4: Learning and successful adaptation are associated with increased self-efficacy.
P5: Repeated behavioural adaptation is associated with relevant workplace outcomes.
P6: The Growth Evidence Loop mediates the relationship between coaching exposure and behavioural change.
4. The PULSE-X™ Model
P — PERCEIVE
What is happening?
Capture facts, events, emotions, context and observable behaviour. The coach slows down premature problem solving.
U — UNPACK
What is underneath?
Separate FACT → INTERPRETATION → ASSUMPTION → EMOTION → NEED. The objective is not to prove the employee wrong, but to make the thinking visible.
L — LOCATE
What matters to me?
Explore identity, values, strengths, motivation and friction. Translate desired identity into observable behaviours.
S — SPECULATE
What might work?
Generate alternative explanations and growth hypotheses. A hypothesis is a testable proposition, not a promise.
E — EXPERIMENT
What can I test?
Design the smallest useful behavioural experiment with a defined context, timeframe, evidence source and learning question.
X — X-RAY
What did reality teach me?
Compare expectation with observation, extract learning and choose KEEP, MODIFY, DROP or SCALE.
4.1 Signature mechanism
ASSUMPTION → HYPOTHESIS → EXPERIMENT → EVIDENCE → LEARNING → ADAPTATION
This mechanism is intentionally compatible with experiential-learning theory while giving workplace coaching a practical transfer architecture. Kolb's model explicitly positions active experimentation as a route back into experience.
5. Coach Manual
5.1 Coach stance
Coach competency | Observable behaviour |
Presence | Creates psychological safety and listens without rushing. |
Precision | Distinguishes observation, interpretation and assumption. |
Provocation | Challenges thinking respectfully and with permission where appropriate. |
Experiment design | Helps convert vague intentions into observable tests. |
Evidence facilitation | Helps the coachee examine what happened rather than defend a story. |
Adaptive questioning | Changes questions based on what emerges rather than forcing the sequence. |
5.2 Intervention ladder
Level | Coach move | Example |
1. Reflect | Mirror | “I hear autonomy is important here.” |
2. Clarify | Explore meaning | “What makes you interpret it that way?” |
3. Challenge | Test assumptions | “What evidence might contradict that?” |
4. Reframe | Offer a different lens | “Could this be an expectation problem rather than a confidence problem?” |
5. Experiment | Design a test | “How could we test that this week?” |
6. Offer | Advice only with permission | “Would you like an observation or suggestion?” |
5.4 Coach questions
· What do we know for certain?
· What part is fact and what part is your story about the fact?
· What else could be true?
· Why does this matter to you now?
· Who are you trying to become in this situation?
· What are three possible explanations?
· Which assumption is most useful to test?
· What is the smallest experiment that could teach you something?
· What evidence would change your mind?
· What happened compared with what you expected?
· What will you keep, modify, drop or scale?
6. PULSE-X™ Experiment Canvas
Fill in the blanks
P — PERCEIVE | U — UNPACK |
Situation: __________________________ Observed:__________________________ Feeling: __________________________ | FACT:________________________ INTERPRETATION: __________________ ASSUMPTION: ______________________ EMOTION: _________________________ NEED: ____________________________ |
L — LOCATE | S — SPECULATE |
Identity: __________________________ Value: _____________________________ Strength: __________________________ Friction: __________________________ Why now: __________________________ | H1: If ______ then ______ H2: If ______ then ______ H3: If ______ then ______ Selected: H____ |
E — EXPERIMENT | X — X-RAY |
Behaviour: ________________________ Context: ___________________________ Frequency: ________________________ Timeframe: _________________________ Evidence: _________________________ Learning question: ________________ | Expected: _________________________ Actual: ____________________________ Surprise: __________________________ Evidence: _________________________ Learning: _________________________ KEEP / MODIFY / DROP / SCALE |
7. Twenty Worked Workplace Cases
1. Manager trust
· Assumption: frequent review means low trust.
· Hypothesis: proactive updates may increase confidence and reduce follow-ups.
· Experiment: two structured updates per week for two weeks.
· Evidence: follow-up frequency and manager feedback.
· Decision: Modify or Scale.
2. Meeting confidence
· Assumption: low confidence prevents participation.
· Hypothesis: repeated low-risk exposure increases confidence.
· Experiment: make one contribution in three meetings.
· Evidence: participation and self-rated confidence.
· Decision: Scale if useful.
3. Career uncertainty
· Assumption: career clarity should come from thinking harder.
· Hypothesis: exposure to real roles will improve clarity.
· Experiment: three informational conversations.
· Evidence: post-conversation interest ratings.
· Decision: pursue highest-fit path.
4. Low visibility
· Assumption: good work should speak for itself.
· Hypothesis: concise impact communication increases visibility.
· Experiment: monthly impact summary.
· Evidence: stakeholder response and opportunities.
· Decision: Scale useful communication.
5. Procrastination
· Assumption: lack of motivation is the cause.
· Hypothesis: task ambiguity is the bottleneck.
· Experiment: 15-minute first-action breakdown.
· Evidence: time to start.
· Decision: Modify workflow.
6. Team connection
· Assumption: team belonging will happen automatically.
· Hypothesis: intentional interaction increases connection.
· Experiment: three short non-task conversations.
· Evidence: connection rating.
· Decision: Continue or redesign.
7. Saying no
· Assumption: declining requests damages relationships.
· Hypothesis: alternatives preserve relationships while protecting priorities.
· Experiment: decline one low-priority request with an alternative.
· Evidence: reaction and workload impact.
· Decision: Scale.
8. Senior influence
· Assumption: influence requires more technical detail.
· Hypothesis: business framing improves engagement.
· Experiment: lead with business metrics.
· Evidence: questions, objections, decisions.
· Decision: Scale best framing.
9. Interruptions
· Assumption: interruptions mean others don't respect me.
· Hypothesis: clearer openings improve conversational authority.
· Experiment: recommendation-first openings.
· Evidence: interruptions and outcomes.
· Decision: Modify.
10. Leadership
· Assumption: leadership is a personality trait.
· Hypothesis: leadership can be practised through clear delegation.
· Experiment: delegate one meaningful responsibility.
· Evidence: quality, ownership, feedback.
· Decision: Scale.
11. Feedback
· Assumption: manager should initiate feedback.
· Hypothesis: specific requests increase feedback quality.
· Experiment: ask for one targeted feedback point after a task.
· Evidence: feedback quality and frequency.
· Decision: Continue.
12. Defensiveness
· Assumption: feedback threatens competence.
· Hypothesis: clarification before response reduces defensiveness.
· Experiment: ask two questions before defending.
· Evidence: emotional response and outcome.
· Decision: Scale.
13. Promotion
· Assumption: promotion requires simply working harder.
· Hypothesis: visible next-level behaviour creates stronger readiness evidence.
· Experiment: own one next-level responsibility.
· Evidence: outcomes and stakeholder feedback.
· Decision: Scale or choose another gap.
14. Overwhelm
· Assumption: more effort will solve overload.
· Hypothesis: prioritisation and removal will help more than acceleration.
· Experiment: STOP / DELEGATE / DO / DEFER for one week.
· Evidence: hours and stress rating.
· Decision: institutionalise where useful.
15. Disengagement
· Assumption: the organization is the entire problem.
· Hypothesis: task mix drives part of the energy loss.
· Experiment: track energy by task for two weeks.
· Evidence: energy patterns.
· Decision: redesign role or task mix.
16. HR-to-business move
· Assumption: wanting business exposure means a career switch is right.
· Hypothesis: actual exposure will clarify fit.
· Experiment: join a cross-functional business project.
· Evidence: interest, energy, capability.
· Decision: explore further or stop.
17. Fear of mistakes
· Assumption: mistakes must be avoided.
· Hypothesis: bounded-risk decisions build confidence.
· Experiment: make one low-risk decision without excessive escalation.
· Evidence: decision time and outcome.
· Decision: scale autonomy.
18. Team ownership
· Assumption: people lack accountability.
· Hypothesis: unclear decision rights create escalation.
· Experiment: clarify decision authority for three recurring activities.
· Evidence: escalations and delays.
· Decision: formalise decision rights.
19. Conflict avoidance
· Assumption: delaying conflict keeps peace.
· Hypothesis: early fact-impact-request conversations reduce escalation.
· Experiment: address one minor issue within 24 hours.
· Evidence: resolution time and relationship outcome.
· Decision: scale.
20. Skill choice
· Assumption: development means choosing a popular competency.
· Hypothesis: future-role evidence identifies better priorities.
· Experiment: interview two people in target roles and map recurring capabilities.
· Evidence: capability frequency and personal fit.
· Decision: choose one capability for deliberate practice.
Selected References & Evidence Base
Kolb, D. A. (1984). Experiential Learning: Experience as the Source of Learning and Development. Prentice-Hall.
Whitmore, J. (1992). Coaching for Performance. Nicholas Brealey.
Grant, A. M. (2013). The efficacy of executive coaching in times of organisational change. Journal of Change Management.
Theeboom, T., Beersma, B., & van Vianen, A. E. M. (2014). Does coaching work? A meta-analysis on the effects of coaching on individual level outcomes in an organizational context. The Journal of Positive Psychology, 9(1), 1–18.
Jones, R. J., Woods, S. A., & Guillaume, Y. R. F. (2016). The effectiveness of workplace coaching: A meta-analysis of learning and performance outcomes from coaching. Journal of Occupational and Organizational Psychology, 89(3), 249–277.
Kolb, A. Y., & Kolb, D. A. (2017). Experiential learning theory as a guide for experiential educators in higher education. ELT Hub.
Mokkink, L. B., et al. (2010). The COSMIN checklist for assessing the methodological quality of studies on measurement properties of health status measurement instruments. Quality of Life Research.
Prinsen, C. A. C., et al. (2018). COSMIN guideline for systematic reviews of patient-reported outcome measures. Quality of Life Research.
Evidence links consulted for this framework include the COSMIN measurement-property guidance, descriptions of GROW, and authoritative educational resources on Kolb's experiential-learning cycle.
Copyright: Dr Amrit Karmarkar (2026). All Rights reserved. Use without permission of author is prohibited.
Kindly write email to me on abkarmarkar@gmail.com before you want to use this model.
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