The five frameworks are:
- STAR: Situation, Task, Action, Result
- CARL: Context, Action, Result, Learning
- SOAR: Situation, Obstacle, Action, Result
- SAO: Situation Action Result
- PARADE: Problem, Approach, Role, Action, Decision, Effect
Important points to remember:
- Applying one framework is more important than worrying about which is the best one
- Framework is just the vehicle, sharing specific examples and impact metrics is key
- Understanding the question behind the question (QBQ)
- Answer with details they actually care about and answer the QBQ
Let’s dig in!
Let's take an example question: "Tell me about a time you had to work with a team with opposing views about a project."
My specific answer in bullets:
- Opposing views in a hybridization project
- One team wanted to do a full hybrid and another a mild hybrid
- We did a short EXCEL study to prove our point and showed results
- Got the buy-in to do a dedicated study and showed a 105% fuel economy improvement.
I use an automotive industry example, but you can use this for any domain!
STAR (Situation, Task, Action, Result)
Situation:
"In a recent hybridization project, we encountered a disagreement between the stakeholders. My client preferred a mild-hybrid powertrain, while the other key members of the team insisted on a full-hybrid because it was more aligned with industry trends."
Task:
"I was tasked with providing solid evidence to prove that a mild-hybrid powertrain would be more efficient and cost-effective, despite opposition from others on the team."
Action:
"We started by running Excel simulations to model the impact of different hybridization levels at key engine operating points. The results encouraged us to run a more detailed 1D simulation using GT-SUITE, focusing on key performance parameters such as fuel efficiency and cost."
Result:
"Ultimately, the GT-SUITE simulation demonstrated a 105% improvement in fuel efficiency for the mild-hybrid during city drive cycles. This data convinced the stakeholders to move forward with the mild-hybrid option, proving that it was the better choice."
CARL (Context, Action, Results, Learning)
Context:
"There was a situation in a hybridization project where there were opposing views. My client wanted to showcase the benefits of their engine with a mild-hybrid powertrain, but key stakeholders pushed for a full-hybrid, as it was seen as more relevant to industry trends."
Action:
"We believed that with the novel GCI engine, the same rules didn’t apply to traditional hybrids. To support our case for a mild hybrid, we ran an Excel simulation to demonstrate the impact of hybridization levels at key engine operating points. After seeing positive results, we expanded our analysis with a 1D simulation using GT-SUITE."
Result:
"This detailed simulation revealed a 105% increase in fuel efficiency on the city drive cycle, clearly showing that the mild-hybrid powertrain could provide better performance at a lower cost."
Learning:
"Through this experience, I learned the importance of data-driven decision-making and aligning technical results with stakeholder priorities, which will allow me to navigate similar challenges in future roles."
SOAR (Situation, Obstacle, Action, Result)
Situation:
"During a hybridization project, we had conflicting opinions within the team. My client preferred a mild-hybrid powertrain, but the internal stakeholders advocated for a full-hybrid configuration, believing it was more consistent with industry trends."
Obstacle:
"The main challenge was overcoming the resistance of stakeholders who were committed to a full-hybrid solution despite the specific advantages of the novel GCI engine that would work better with a mild-hybrid system."
Action:
"We began by conducting an Excel simulation to assess the performance of different hybridization levels. When we saw promising results, we deepened our analysis using GT-SUITE, a more advanced tool for hybrid system simulations, to compare various configurations."
Result:
"The final simulation showed a 105% improvement in fuel efficiency for the mild-hybrid, particularly in the city drive cycle, and successfully persuaded the stakeholders to adopt the mild-hybrid solution."
SAO (Situation, Action, Outcome)
Situation:
"In a project focused on hybridization, there was a disagreement within the team. My client wanted to go with a mild-hybrid powertrain, while other stakeholders pushed for a full-hybrid because of industry trends."
Action:
"To resolve this, we ran an initial simulation in Excel to demonstrate the performance benefits of the mild-hybrid system. After seeing positive results, we carried out a more detailed analysis using GT-SUITE to confirm our findings and quantify the benefits."
Outcome:
"Our detailed simulations revealed a 105% improvement in fuel efficiency in the city drive cycle, which ultimately led the stakeholders to adopt the mild-hybrid system."
PARADE (Problem, Approach, Role, Action, Decision, Effect)
Problem:
"During a hybridization project, the team was divided between two options: my client wanted a mild-hybrid powertrain, but other stakeholders favored a full-hybrid configuration because it was perceived as the standard in the industry."
Approach:
"We decided that data-driven analysis would be the best way to settle the debate. We planned to use simulations to provide quantitative evidence of the advantages of the mild-hybrid system."
Role:
"My role was to lead the simulation work and gather the data to build a compelling case for the mild-hybrid system. I worked closely with my technical team to run multiple scenarios."
Action:
"We began by running an Excel simulation to model different hybridization levels and identify key performance points. After seeing positive results, we transitioned to a more detailed 1D simulation using GT-SUITE to refine our analysis."
Decision:
"The data from the simulation showed a significant 105% improvement in fuel efficiency for the mild-hybrid system, which convinced the stakeholders to move forward with this solution."
Effect:
"As a result, the project adopted the mild-hybrid configuration, leading to a more efficient, cost-effective solution that aligned with both the client’s and stakeholders' goals.”
Summary:
STAR: Breaks down the situation, your task, the action you took, and the result.
CARL: Focuses on the learning outcomes alongside the context, action, and result.
SOAR: Adds the element of identifying the specific obstacle you had to overcome.
SAO: More concise, focusing only on the situation, action, and result.
PARADE: Goes deeper, explaining the problem, your approach, your role, and the decision-making process.
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They all can be effective, so choose one and get going.
What is more important is:
A. Sharing specific examples and impact metrics
B. Answering with details they actually care about
C. Understanding the question behind the question
Good luck interviewing 💪🏽