Dashboard / Candidate
Prashant Kumar
Applied for Product Manager · pm_06_prashant_kumar.pdf
Private: squad_6@pg27.mesaschool.co · +91 99001 43278
Applied-role score
45/100#16 of 34 PM applicants
PM score
45/100SPM score
32/100Current status
AnalysedBelow shortlist (AI suggestion)
Your decision
1
Why they fit
- Problem -> Change -> Result 25%
The candidate provides a clear example of analyzing support tickets to identify UX friction, executing a settings redesign, and achieving an 18% reduction in support volume. The action is directly linked to a concrete, measurable outcome.
- Gets to the Source Before Designing the Fix 15%
The candidate demonstrates firsthand discovery by interviewing 8 freight forwarding sales managers to build a domain-specific spec, as well as conducting 6 weeks of discovery with logistics procurement teams. Evidence that an initial design or assumption changed as a result of what was uncovered is missing.
2
Where they fall short
- Carries Ambiguous Problems Through to Closure −20 pts
Evidence is not present. The CV describes structured product development and feature launches, but does not provide an example of navigating an ambiguous escalation, operational failure, or cross-functional issue to full resolution.
- Evidence-Led Decisions −12 pts
The CV shows evidence being used to inform a redesign based on ticket analysis. However, it lacks examples of decisions being altered, halted, or reprioritized away from an initial direction based on data or post-mortems.
- Builds Repeatable Ways of Working −12 pts
The candidate introduced OKR-based roadmap planning and post-launch metric tracking at their company. However, there is no evidence demonstrating that peers or other squads subsequently adopted or reused these methods.
| Criterion | Weight | Score | Weighted | AI reasoning | Evidence from CV |
|---|---|---|---|---|---|
| Independent Decision Ownership | 30% | 1/5 | 6.0/30 | The candidate outlines ownership of product modules and features while reporting to a VP of Product. However, there is no evidence of consequential decisions made independently under uncertainty, nor any explanation of trade-offs and their resulting consequences. |
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| Problem -> Change -> Business/Operational Result | 20% | 4/5 | 16.0/20 | The candidate links their own analysis of support tickets to a UX redesign that yielded a measurable 18% reduction in support ticket volume, alongside tracking 85%+ adoption across 14 shipped features. While results are present, evidence of repeated operational or business transformations remains limited. |
|
| Evidence-Led Prioritisation and Reversal | 20% | 1/5 | 4.0/20 | There is indirect evidence of using data to prioritize UX fixes via support ticket analysis. However, there is no evidence of stopping an initiative, pivoting, or materially reversing a prior direction based on new evidence. |
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| Creates Systems Others Run | 15% | 2/5 | 6.0/15 | The candidate introduced OKR-based roadmap planning and established 30/60/90-day feature success tracking cadences. However, evidence is missing to show that this system was adopted by others or became a sustained practice run across the broader organization. |
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| Multi-Party Resolution Under Pressure | 15% | 0/5 | 0.0/15 | The CV contains no evidence of resolving multi-party issues under pressure, handling critical escalations, driving post-mortems, or navigating ambiguous failures. | Evidence not present in the CV. |
| Total | 100% | 32 | The candidate demonstrates solid baseline PM execution, highlighted by a tangible outcome linking support ticket analysis to an 18% volume reduction. However, the profile falls short of Senior Product Manager expectations on this rubric, showing no evidence of multi-stakeholder resolution under pressure, lack of direction reversals based on evidence, and minimal demonstration of independent, high-stakes decision ownership. | ||
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)
- “Analysed 2,000+ support tickets to identify top UX friction points; resulting insights drove a settings redesign that reduced support volume by 18%” · Problem -> Change -> Result
- “Analysed 2,000+ support tickets to identify top UX friction points; resulting insights drove a settings redesign that reduced support volume by 18%” · Evidence-Led Decisions
- “Introduced OKR-based roadmap planning; first PM at the company to measure feature success at 30, 60, and 90 days post-launch” · Builds Repeatable Ways of Working
- “Led discovery for a new logistics vertical pilot — interviewed 8 freight forwarding sales managers; built the feature spec that became the first domain-specific product offering” · Gets to the Source Before Designing the Fix
- “Led a supply chain vendor management feature that required 6 weeks of discovery with logistics procurement teams at 4 manufacturing companies — closest I have come to understanding how freight and vendor data flows in a real ops environment” · Gets to the Source Before Designing the Fix
Outcomes stated in the CV
- Shipped 14 features over 2 years with 85%+ adoption tracked at the 90-day mark at WorkflowAI Technologies
- Reduced support volume by 18% following settings redesign informed by analysis of 2,000+ support tickets at Salesken AI
- Built feature spec for the first domain-specific product offering for a logistics vertical pilot at Salesken AI
Anonymised CV (exactly what the AI saw)
[CANDIDATE] Product Manager [PHONE REDACTED] · [EMAIL REDACTED] · Bengaluru · [PROFILE URL REDACTED] Professional Summary Product Manager with 4 years of experience in B2B SaaS — CRM, workflow automation, and analytics products. Strong in discovery, PRD authoring, and cross-functional execution. MBA from TAPMI. Led a supply chain automation project during an engagement that gave me exposure to how logistics firms manage their data. Looking to apply product skills to a more operationally complex domain. Work Experience Product Manager WorkflowAI Technologies (B2B SaaS, 90 employees), Bengaluru · Aug 2022 – Present — Owns the workflow automation and integration module — 200+ enterprise clients across manufacturing, retail, and logistics verticals — Shipped 14 features over 2 years; maintained 85%+ adoption on launched features tracked at 90-day mark — Led a supply chain vendor management feature that required 6 weeks of discovery with logistics procurement teams at 4 manufacturing companies — closest I have come to understanding how freight and vendor data flows in a real ops environment — Manages a 3-person squad: 2 engineers and 1 designer; reports to VP Product — Introduced OKR-based roadmap planning; first PM at the company to measure feature success at 30, 60, and 90 days post-launch Associate Product Manager Salesken AI (Conversation Intelligence SaaS), Bengaluru · Jul 2020 – Jul 2022 — Supported PM on the call analytics and coaching dashboard — owned 3 features from spec to release in 2 years — Led discovery for a new logistics vertical pilot — interviewed 8 freight forwarding sales managers; built the feature spec that became the first domain-specific product offering — Analysed 2,000+ support tickets to identify top UX friction points; resulting insights drove a settings redesign that reduced support volume by 18% Education MBA, Marketing & Product Management · T.A. Pai Management Institute (TAPMI), Manipal · 2018–2020 B.Tech, Computer Science · NIT Surathkal · 2014–2018 · CGPA 7.9/10 Skills & Certifications Product roadmapping · PRD writing · Agile/Scrum · JIRA · Figma · SQL · Amplitude · Mixpanel · Salesforce Reforge Member (2023–24) · Product School PM Certification (2021)
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, 11:02:06 AMsystemanalysis completed{"PM_score":45,"SPM_score":32}
- 9/29/2026, 11:01:25 AMsystemcv ingested{"file":"pm_06_prashant_kumar.pdf","role":"PM","redactions":{"name":1,"email":1,"phone":1,"profile_url":1},"name_detected":true}