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Leadership Vision
Presented By Gaurang Rottela
Role AR Lead (Proposed)
Date May 2026
Data As Of 15-May-2026
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₹27.08 Cr
Total pending dues
across 1,822 trails
₹11.62 Cr
Actionable overdue
due today, no excuse
70%
YOY revenue growth
expected — ₹500 Cr → ₹850 Cr
18–27×
ROI on team investment
payback under 6 weeks

Where we are.
Where we need to be.

AR at PYT today is reactive, fragmented, and unscaled. The opportunity to fix it — and turn it into a competitive advantage — has never been more urgent.

⚠ Where We Are

High overdue aging. No collections process. No dashboard. Team attrition. Backlog growing daily.

◈ The Opportunity

Every rupee in aging is recoverable. Collections is an untapped cash engine — not a back-office function.

✦ My Commitment

Process-first. Metric-driven. Commercially aligned. I will turn AR into a function PYT can benchmark against the best.

"Transform AR from a reactive ledger function into PYT's most disciplined cash engine — driven by process rigour, daily metrics, and zero tolerance for untracked overdue."

Five pillars.
One direction.

Every pillar directly addresses a current-state failure. Nothing theoretical — each is a concrete build with a defined outcome.

1
Process & Governance
Collections cadence (T+30/60/90), escalation matrix, dispute SOP, CN trail protocol.
Zero AR disputes without an open case
M1
2
📊
Metrics & Visibility
Daily input KPI tracking, live AR aging dashboard, DSO by owner.
Leadership sees AR health in < 2 min
M2
3
👥
Team & Incentives
Backlog squad vs. current dues squad, FT hiring (1 per ₹10 Cr revenue), performance-linked incentives.
Attrition drops; team is motivated & accountable
M1–2
4
🔒
Controls & Reconciliation
Daily 3-way recon: Bank vs. Plato vs. Zoho Books, automated mismatch alerts.
Zero undetected posting errors daily
M1–2
5
🤖
AI & Automation
AI calling (Q2–Q3), automated dunning, reconciliation automation, refund TAT: 15 → 2–3 days.
Human dependency in routine collections eliminated
Q2–Q3

10 problems.
10 solutions. All owned.

No ambiguity about what is broken or how it will be fixed. Each problem is documented with a specific solution and a committed timeframe.

#01 Attrition & Team Building People
Problem

No process, no single data source, no dashboard. Cross-functional chaos (Visa, Vouchers) leaves team directionless. Monotony drives attrition.

Solution Immediate

Define the process end-to-end. Single source of truth in Plato. Structured follow-up mechanism. Clear SLA owners for cross-functional blockers.

#02 Incentive Structure People / Commercial
Problem

Collections drives cash but has no performance-linked incentives. No individual metrics = no motivation to outperform.

Solution Month 1–2

Variable pay linked to calls made, ₹ collected, DSO by owner, and aging movement. Daily KPI tracking, weekly team review.

#03 Clearing the Backlog Operations
Problem

Backlog is growing, not shrinking. Same team can't chase history and current dues simultaneously — backlog always loses.

Solution Month 1

Split team: Backlog Squad (100% on historical overdue) + Current Squad (current cycle dues only). Reviewed and rebalanced quarterly.

#04 Payment Structure Optimisation Commercial
Problem

No region-level float analysis. Unknown if we're cash-flow positive by region. Payment terms not benchmarked vs. industry standards.

Solution Month 2–3

Region-level float analysis. Benchmark vs. tour operator competitors. Redesign payment milestones for cash-flow positive positioning in every region.

#05 Right Hiring — Short-Term Fix Capacity
Problem

A cash-flow-critical function is being run on interns. This is unsustainable and is directly causing backlog growth.

Solution Immediate

Hire FT collections agents immediately. Norm: 1 agent per ₹10 Cr revenue until process is fully operational.

#06 AI-Based Calling — Long-Term Fix Technology
Problem

Human dependency in outbound calling is expensive and inconsistent. Unrecorded use cases make automation hard.

Solution Q2–Q3

Enable AI calling by Q2–Q3. Record all use cases before go-live. Humans handle escalations only; AI handles routine follow-ups. Successfully adopted by Zomato, Flipkart & HDFC.

#07 Metricing Collections Analytics
Problem

Collections is unmeasured. DSO is being used as both input and output — it is only an outcome. No inputs tracked = no lever to pull.

Solution Month 1

Track daily inputs: calls, promises, ₹ committed vs. collected, follow-up TAT. DSO is the output — manage inputs and DSO follows.

#08 Refund Workflow & TAT Process / CX
Problem

Refund process is internally-oriented, not customer-oriented. Heavy CX dependency. Current TAT ~15 days from cancellation.

Solution Month 2–3

Redesign workflow with customer at centre. Reduce CX dependency with self-serve + controls. Target: 2–3 day TAT using existing cancellation data in product.

#09 3-Way Reconciliation Controls
Problem

No daily recon between Bank, Plato, and Zoho Books. Mispostings go undetected. Product payment adoption is untracked.

Solution Month 1–2

Daily 3-way recon: Bank → Plato → Zoho Books. Automated mismatch alerts within 24 hrs. Drive full product payment adoption.

#10 AI Adoption Across Collections Technology
Problem

Every monotonous task — dunning, follow-up logging, recon matching — is done by humans. Burnout and error risk are high.

Solution Q3 Target

Mandate AI for every manual/repetitive task. Full AI adoption across the collections workflow by Q3 end.

Real numbers.
Right now.

The data below is from PYT's own AR tracker as of 15-May-2026. These are not estimates — they are live, actionable numbers.

Exposure Amount Why It Matters
Total Pending Dues (1,822 trails) ₹27.08 Cr Entire due universe as of 15-May-2026
Actionable Overdue
Actual due now
₹11.62 Cr Money owed today with no valid excuse for non-payment
(Includes Events, Plato errors & HNI)
Already Departed — Overdue ₹2.36 Cr Customer has travelled; no reason for any balance to exist
180+ Day Bucket — Departed ₹1.02 Cr 43% of departed overdue; write-off risk rising daily
(May include HNI and erroneous dues as well)
'Returned' Status with Pending Dues ₹1.96 Cr Trip done, customer returned — these should be ₹0
90+ Day Overdue (across all) ₹1.88 Cr High probability of becoming irrecoverable without immediate action
⚡ The 70% growth problem — without fixing AR now

At ₹500 Cr current revenue, PYT is already under-resourced in collections. At 70% YOY growth (→ ~₹850 Cr), the overdue problem will scale proportionally — unless process, team, and systems are locked in today. A company can survive without being EBITDA positive. It cannot survive without cash. Every month of delay compounds the backlog and dilutes recovery ability.

This is not a cost ask.
It's a cash decision.

Collections headcount is a revenue recovery function with measurable, short payback. Here is the unit economics.

Collections Agent
CTC / Month ₹30,000
Coverage ₹10 Cr revenue
Target Recovery ₹50–80 L / month
Senior Agent
CTC / Month ₹35,000
Coverage ₹10 Cr + escalations
Target Recovery ₹1–1.5 Cr / month
AR Analyst (Dashboard & Recon)
CTC / Month ₹35,000
Coverage All regions + reporting
Value Created Prevents 0.5% GM dilution / month

"A team of 5 FT collections agents at ₹1.5 L/month total cost can realistically recover ₹2–3 Cr per month from the current backlog alone — an 18–27× return on investment, with payback in under 6 weeks. This is not a cost ask. It is a cash-generation decision."

The case for
giving me this role.

I am putting myself forward for the AR Lead mandate. Here is why my background makes me the strongest fit — and why the timing matters.

🏢
4.5 Years at PYT
The learning curve is near-zero. I understand the product, the customer journey, Plato CRM, booking lifecycle, and payment milestones better than any external hire.
🔄
Multiple Finance Roles at PYT
Generalist finance background — FP&A, AR review, month-end, refunds, credit notes, margin governance. I have seen every part of the cash cycle from multiple angles.
📋
Process & Workflow Builder
Built multiple SOPs, dashboards, and governance frameworks at PYT. I know how to design process from scratch and get cross-functional buy-in.
🎓
Strong Analytical Foundation
Can build the business case, the KPI framework, and the team structure with institutional-grade rigour. Background in finance, audit, and applied analytics.
🚀
The 70% Growth Context
PYT needs someone who can build the AR function correctly the first time — not someone who needs 6 months to understand the business before starting. Speed of context = speed of execution.
Days 1–30
Build the team first
Assess current team structure. Hire the right FT collections agents (1 per ₹10 Cr revenue). Assign portfolio ownership. Audit the full AR — every overdue gets a named owner and a follow-up date. Establish baseline metrics. No process improvement is possible without the right people in place first.
30
Days 31–60
Build the process
Design and implement the collections cadence (T+30 / T+60 / T+90). Set up follow-up mechanisms and escalation matrix. Start clearing the backlog — squad split deployed. Begin DSO reduction. Target: 30–40% DSO reduction from baseline by Day 60. First live dashboard published.
60
Days 61–90
Start the AI journey
Initiate AI-led calling setup. Record and cover all use cases. Reduce human dependency on routine outbound collections. Target: AI pilot live on at least one market segment with minimal escalation. Human team focuses only on escalation and relationship-sensitive cases.
90

Three phases.
One outcome.

Horizon
0–90 DaysStabilise
90 Days–6 MonthsSystematise
6–12 Months+Scale & Automate
Focus
AR audit · ownership map · FT hiring · team split · SOP v1 · baseline metrics · daily 3-way recon
Live AR dashboard · automated dunning · joint Sales review · credit policy · refund TAT < 3 days · individual KPI scorecard
AI calling live · DSO < 35 days · full recon automation · zero manual dunning · AR data feeds pricing & PLB strategy

Clear asks.
Clear accountability.

Delivering this vision requires alignment and support from leadership. These are the five critical enablers.

⚖️
Mandate & Authority
Formal AR ownership; ability to escalate overdue to Sales leadership
Critical · M1
🤝
CXO Backing
Support for collections escalations and credit policy enforcement
Critical · M1
🔗
Sales Alignment
Joint monthly AR review; shared overdue accountability with Sales Head
High · Month 1
💻
Tech Support
Dashboard build support for live AR reporting & revamping the process and workflows with scale in mind
High · Month 2
👥
Team Build
1 FT AR analyst + hiring budget for 1 agent per ₹10 Cr revenue. This is the single highest-leverage investment PYT can make in cash flow recovery today.
High · Month 1
"AR is the final mile of revenue realisation. Every rupee that ages past 90 days is margin we earned but haven't collected. I will fix that — with urgency, with data, and with no room for ambiguity."
Gaurang Rottela AR Lead (Proposed) · Finance · PickYourTrail · May 2026