How to handle dependencies in a PM execution case
In execution cases, identify dependencies early, clarify ownership, and assess impact on timelines and quality. Map out inter-team links, evaluate which are critical, and propose mitigation steps. Always explain the trade-offs and how new evidence could change your approach.
PMMockr.comMisjudging dependencies: a common pitfall
Imagine a PM tasked with launching a new user onboarding flow, who commits to a launch date without clarifying that email triggers depend on a backend team update. As the deadline nears, the backend work slips, blocking the onboarding launch. This mistake—failing to surface and manage dependencies—risks missed deadlines, blame, and a poor user experience. Effective PMs recognize that execution success relies not just on their own team, but on mapping and managing all external dependencies from the outset.
What counts as a dependency?
A dependency is any task, deliverable, or decision outside your direct control that your initiative needs to succeed. These can include engineering work by another team, third-party integrations, legal approvals, or even content from marketing. The critical step is distinguishing between dependencies that are merely helpful and those that are absolutely required for your plan to work.
For example, if your feature rollout needs API changes from a platform team, that is a hard dependency. If marketing assets would enhance the launch but aren't required for functionality, that's a soft dependency. Being precise here helps you focus on what to monitor most closely.
Mapping dependencies: a systematic approach
Start by listing every function or deliverable your feature needs. For each, ask: "Who owns this? When could it be delivered? What will block us if it slips?" Clarify ownership with named contacts, not just team names. Then, build a simple visual map or spreadsheet with dependencies, owners, dates, and risk levels.
In interviews, stating your process aloud shows clarity. For example: "I'd map all required backend endpoints, identify which are owned by my team versus the platform team, and explicitly reach out to confirm their delivery dates and constraints."
Worked example: dependency management in a mobile app launch
Assume you're launching a new loyalty feature in a food delivery app. The feature awards points for every dollar spent, redeemable on future orders. To ship this, your team needs:
- Backend support to track points (owned by a core platform team) - Updated designs from the design team - Legal approval on the loyalty terms - QA resources for end-to-end testing
You segment users into three groups: high-frequency (20% of users, 60% of orders), occasional (50% of users, 30% of orders), and new users (30% of users, 10% of orders). Your assumption: high-frequency users will drive initial adoption, so you prioritize an MVP that supports their flows first.
Key dependency: the platform team must deliver an API to track and redeem points. You learn (for this exercise, assume this is via email) that their next sprint is already committed. If you wait, your launch slips by four weeks, missing the start of the summer promo period.
You have two options:
Option A: Wait for the full API, launch to all users later. Option B: Build a lightweight interim solution—your team tracks points for high-frequency users in a local database, with a manual reconciliation step, and launches to this segment only. This avoids the critical dependency but adds operational overhead and risk of data mismatch.
You choose Option B, prioritizing speed and learning over perfect automation. The trade-off: your team must build reconciliation tools and handle support tickets for errors. You plan a small-scale rollout to high-frequency users, monitor support load and redemption accuracy, and check adoption. If error rates exceed 2% (assumed threshold), or if support costs exceed $5k/month (assumed), you pause and revert to Option A.
New evidence that would change your recommendation: if the platform team unexpectedly frees up and can deliver in two weeks, or if feedback from high-frequency users indicates confusion or lack of adoption, you should reconsider and possibly delay for a more robust solution.
Prioritizing dependencies: critical path vs. nice-to-have
Not every dependency deserves equal attention. The critical path is the sequence of tasks that determines your earliest finish date. Dependencies on the critical path can delay your launch if they slip; others may just affect polish or secondary features.
Check each dependency: will a delay block the user experience or core value? If so, prioritize managing this one, finding workarounds, or escalating early. For secondary dependencies, monitor but avoid over-investing scarce time.
Communicating and negotiating for clarity
Discussing dependencies openly builds trust and reduces surprises. When you flag a risk, frame it as a shared challenge: "To hit the summer promo, we need the API by June 1. Is that feasible? If not, what alternatives could we consider?"
Negotiation is often necessary. If a dependent team can't meet your timeline, explore options: can you narrow the initial scope, deliver in phases, or provide resources to help? Document agreements and assumptions in writing, so everyone is aligned.
Assessing risks and building contingency plans
Every dependency introduces risk; the more external the dependency, the less control you have. Identify the highest-impact risks and outline what you’ll do if they materialize. For example, if legal review might delay launch, prepare a fallback launch plan without the contested terms.
In your interview answer, speak to both your primary plan and your contingency. This demonstrates forward-thinking and realism.
Weak reasoning versus thoughtful analysis
A weak approach: "We depend on the platform team, so we'll just ask them to deliver the API." This underestimates risk and ignores other options.
A stronger answer: "Since the platform team is unavailable, I'll propose a phased launch for our most valuable segment, with a manual tracking workaround. We'll explicitly monitor support burden and error rates, and if those exceed our threshold, we’ll pause and revisit our approach." The difference is in anticipating obstacles, making a reasoned trade-off, and specifying how you’ll respond if things go wrong.
Practice: timed dependency mapping
Set a timer for 12 minutes. Pick a hypothetical case: "You are launching a new messaging feature in a fitness app." List all dependencies, noting which teams or external parties own each. For each, decide if it is on the critical path. Propose at least one mitigation for a likely risk.
Self-review checklist: - Did I explicitly identify each dependency and owner? - Did I distinguish critical from non-critical dependencies? - Did I propose a concrete mitigation or fallback? - Did I state what evidence would cause me to change my plan?
Practice this cadence once per week, varying scenarios and dependency types, to build fluency. For additional practice, PMMockr offers tailored execution case prompts.
FAQ
How detailed should I get when mapping dependencies in an interview?
Be specific enough to show you understand the full scope—name teams, functions, and key deliverables. You don't need to list every minor detail, but call out anything that could block your launch or meaningfully impact quality or timing.
What if a dependency is outside my influence?
Acknowledge the limit of your influence, but show proactive risk management: escalate early, seek alternatives, or adjust your plan to reduce reliance on that dependency. Suggest a concrete fallback if the dependency slips.
How do I know if a dependency is critical?
Ask: if this dependency is delayed, does it block the core user experience or business objective? If yes, it's critical and should be monitored and managed closely. If not, it's secondary and can be deprioritized.