Kargo HiringEmail sending LIVE
Dashboard / Candidate

Ananya Rajan

Applied for Product Manager · pm_05_ananya_rajan.pdf
Private: squad_5@pg27.mesaschool.co · +91 96293 47850
Applied-role score
69/100
#6 of 34 PM applicants
PM score
69/100
SPM score
53/100
Current status
Analysed
Borderline (AI suggestion)
Your decision
1

Why they fit

  • Problem -> Change -> Result 25%

    The candidate provides multiple concrete examples of noticing friction, taking direct action to change tools or processes, and achieving measurable results across both PM and operational roles. Results include a 22% reduction in SLA breaches, reduced back-and-forth communication, and significant annual cost savings.

  • Evidence-Led Decisions 20%

    The CV shows explicit examples of decisions being stopped or revised based on data rather than assumptions, specifically killing two championed features after behavioural and customer-segment data proved the hypotheses wrong. A carrier rate renegotiation was also driven by an objective performance data model.

  • Builds Repeatable Ways of Working 20%

    The candidate has created tools and formats that others adopted, such as rebuilding the daily exception report format used by the ops team and creating the company's first user manual and documentation from scratch. However, deeper detail on ongoing organizational adoption and evolution of these systems is limited.

2

Where they fall short

  • Carries Ambiguous Problems Through to Closure −16 pts

    The CV notes managing delivery exceptions and multi-account logistics, but does not provide a specific narrative of taking a messy, ambiguous problem across multiple functions through to post-resolution closure. Evidence of cross-functional escalation handling and subsequent follow-up is largely absent.

3

Rubric breakdown: PM

CriterionWeightScoreWeightedAI reasoningEvidence from CV
Problem -> Change -> Result25% 5/525.0/25The candidate provides multiple concrete examples of noticing friction, taking direct action to change tools or processes, and achieving measurable results across both PM and operational roles. Results include a 22% reduction in SLA breaches, reduced back-and-forth communication, and significant annual cost savings.
  • “Built a delivery SLA monitoring dashboard in Tableau; moved from reactive to proactive exception handling — reduced SLA breaches by 22% over 2 quarters”
  • “Rebuilt the daily exception report format that the ops team sent to clients — reduced back-and-forth by removing ambiguity from the status descriptions”
  • “Renegotiated rates with 3 underperforming carriers using a performance data model I built; saved n18L annually on one account”
Evidence-Led Decisions20% 4/516.0/20The CV shows explicit examples of decisions being stopped or revised based on data rather than assumptions, specifically killing two championed features after behavioural and customer-segment data proved the hypotheses wrong. A carrier rate renegotiation was also driven by an objective performance data model.
  • “Shipped 5 features in 12 months; killed 2 — one after a week (data showed the behaviour we assumed didn't exist), one after a month (adoption was strong but the right customers weren't using it)”
  • “Renegotiated rates with 3 underperforming carriers using a performance data model I built; saved n18L annually on one account”
Builds Repeatable Ways of Working20% 3/512.0/20The candidate has created tools and formats that others adopted, such as rebuilding the daily exception report format used by the ops team and creating the company's first user manual and documentation from scratch. However, deeper detail on ongoing organizational adoption and evolution of these systems is limited.
  • “Rebuilt the daily exception report format that the ops team sent to clients — reduced back-and-forth by removing ambiguity from the status descriptions”
  • “Built product documentation from scratch; created the first user manual that didn't exist when I joined”
Carries Ambiguous Problems Through to Closure20% 1/54.0/20The CV notes managing delivery exceptions and multi-account logistics, but does not provide a specific narrative of taking a messy, ambiguous problem across multiple functions through to post-resolution closure. Evidence of cross-functional escalation handling and subsequent follow-up is largely absent.
  • “Managed carrier planning and exception management for 4 FMCG client accounts across South India — 600+ shipments monthly”
Gets to the Source Before Designing the Fix15% 4/512.0/15The candidate demonstrates firsthand discovery through direct interviews and regular operating touchpoints before designing solutions. This directly led to the creation of the carrier rate benchmarking feature, which became the primary sales demo hook, and directly shaped product decisions to match carrier realities.
  • “Designed carrier rate benchmarking feature after 3 months of discovery with logistics managers at 8 companies; feature became the primary sales demo hook”
  • “Runs weekly calls with 5 carrier partners to understand operational constraints that affect the platform — product decisions informed by carrier ops reality, not assumptions”
Total100%69The candidate demonstrates strong alignment with evidence-led decision-making, firsthand discovery, and delivering measurable operational and product improvements. The profile shows high ownership in early product stages and logistics operations, though it lacks clear evidence of navigating messy, cross-functional ambiguous problems through to full closure.
Scoring scale
  • 0: No evidence in the CV
  • 1: Indirect or participation-only evidence
  • 2: Partial: some elements of the description, weak link to outcome
  • 3: One clear example matching the description
  • 4: Clear example with a visible result, candidate's own action linked to it
  • 5: Repeated, strong examples fully matching the description, with results

Weighted contribution = score ÷ 5 × weight. Every quote is checked against the CV text; if none can be verified, the score is capped at 1.

4

Evidence

Verified CV quotes used (PM rubric)
  • “Built a delivery SLA monitoring dashboard in Tableau; moved from reactive to proactive exception handling — reduced SLA breaches by 22% over 2 quarters” · Problem -> Change -> Result
  • “Rebuilt the daily exception report format that the ops team sent to clients — reduced back-and-forth by removing ambiguity from the status descriptions” · Problem -> Change -> Result
  • “Renegotiated rates with 3 underperforming carriers using a performance data model I built; saved n18L annually on one account” · Problem -> Change -> Result
  • “Shipped 5 features in 12 months; killed 2 — one after a week (data showed the behaviour we assumed didn't exist), one after a month (adoption was strong but the right customers weren't using it)” · Evidence-Led Decisions
  • “Renegotiated rates with 3 underperforming carriers using a performance data model I built; saved n18L annually on one account” · Evidence-Led Decisions
  • “Rebuilt the daily exception report format that the ops team sent to clients — reduced back-and-forth by removing ambiguity from the status descriptions” · Builds Repeatable Ways of Working
  • “Built product documentation from scratch; created the first user manual that didn't exist when I joined” · Builds Repeatable Ways of Working
  • “Managed carrier planning and exception management for 4 FMCG client accounts across South India — 600+ shipments monthly” · Carries Ambiguous Problems Through to Closure
  • “Designed carrier rate benchmarking feature after 3 months of discovery with logistics managers at 8 companies; feature became the primary sales demo hook” · Gets to the Source Before Designing the Fix
  • “Runs weekly calls with 5 carrier partners to understand operational constraints that affect the platform — product decisions informed by carrier ops reality, not assumptions” · Gets to the Source Before Designing the Fix
Outcomes stated in the CV
  • Shipped 5 features in 12 months and iterated by killing 2 non-viable features based on data
  • Designed a carrier rate benchmarking feature that became the primary sales demo hook
  • Reduced SLA breaches by 22% over 2 quarters via a custom Tableau dashboard
  • Saved 18L annually on one client account through data-backed carrier rate renegotiation
Anonymised CV (exactly what the AI saw)
[CANDIDATE]
Product Manager
[PHONE REDACTED] · [EMAIL REDACTED] · Chennai · [PROFILE URL REDACTED]
Professional Summary
Product Manager with 2 years in product, preceded by 3 years in supply chain planning and carrier operations at a
national 3PL. Built operational instincts in logistics before moving into product. Own things end to end. Ship and
learn in short cycles. Have killed two features I championed after the data proved me wrong.
Work Experience
Product Manager
Routemaster Technologies Pvt. Ltd. (Last-Mile & Carrier SaaS), Chennai · Apr 2023 – Present
— Sole PM for carrier integration and route planning modules — only PM in the company for the first 8 months
— Shipped 5 features in 12 months; killed 2 — one after a week (data showed the behaviour we assumed didn't exist),
one after a month (adoption was strong but the right customers weren't using it)
— Designed carrier rate benchmarking feature after 3 months of discovery with logistics managers at 8 companies;
feature became the primary sales demo hook
— Built product documentation from scratch; created the first user manual that didn't exist when I joined
— Runs weekly calls with 5 carrier partners to understand operational constraints that affect the platform — product
decisions informed by carrier ops reality, not assumptions
Senior Supply Chain Analyst
TCI Supply Chain Solutions Pvt. Ltd., Chennai · Sep 2021 – Mar 2023
— Managed carrier planning and exception management for 4 FMCG client accounts across South India — 600+
shipments monthly
— Built a delivery SLA monitoring dashboard in Tableau; moved from reactive to proactive exception handling —
reduced SLA breaches by 22% over 2 quarters
— Renegotiated rates with 3 underperforming carriers using a performance data model I built; saved n18L annually
on one account
Supply Chain Analyst
TCI Supply Chain Solutions Pvt. Ltd., Chennai · Jul 2020 – Aug 2021
— Demand forecasting, carrier scheduling, and delivery exception management for 2 manufacturing client accounts
— Rebuilt the daily exception report format that the ops team sent to clients — reduced back-and-forth by removing
ambiguity from the status descriptions
Education
B.E., Industrial Engineering · Anna University, Chennai · 2016–2020 · CGPA 8.4/10
Skills & Certifications
Product strategy · Supply chain operations · JIRA · Figma · SQL · Tableau · Mixpanel · Notion · Excel
APICS CSCP (2022) · Product Analytics – Amplitude (2024)
Redacted: name ×1, email ×1, phone ×1, profile url ×1
5

Interview brief

Briefs are written when you shortlist a candidate.

6

Email draft

An offer or rejection draft is prepared once you make a decision. Nothing is ever sent without your approval.

Audit trail (2)
  • 9/29/2026, 11:02:07 AMsystemanalysis completed{"PM_score":69,"SPM_score":53}
  • 9/29/2026, 11:01:25 AMsystemcv ingested{"file":"pm_05_ananya_rajan.pdf","role":"PM","redactions":{"name":1,"email":1,"phone":1,"profile_url":1},"name_detected":true}