General Advice for Novice AI Users
1. Be specific: The more details you provide (role, goals, constraints), the better the AI’s output.
2. Use placeholders: Start with generic placeholders ([ROLE], [AIM], [INPUT]), then replace them with your actual project details.
3. Include context: If you have any data or background info (like user surveys, logs, or a specific scenario), mention it.
4. Iterate: After the AI responds, refine your prompt if something’s missing or unclear.
1. R‐T‐F (Role → Task → Format)
Framework Explanation
Role: Tell GPTs what “role” or persona you want it to take on.
Task: Describe the specific job or problem you need solved.
Format: Specify how you want the output presented (e.g., bullet points, story, table, step‐by‐step).
A. Project Management Use Case
Role: Act as a Senior Project Manager
Task: Develop a project timeline for a two‐month software implementation project with four major milestones. Include major tasks, deadlines, and responsible stakeholders.
Format: Present the plan as a Gantt‐chart‐style bullet list.
Example Prompt
Role: You are a Senior Project Manager.
Task: Create a two‐month project timeline for implementing a new software system. Identify four major milestones, including tasks, deadlines, and responsible parties. Also include potential risks at each milestone.
Format: Present the final timeline and risk analysis as a bullet list that resembles a Gantt chart layout.
Task: Create a two‐month project timeline for implementing a new software system. Identify four major milestones, including tasks, deadlines, and responsible parties. Also include potential risks at each milestone.
Format: Present the final timeline and risk analysis as a bullet list that resembles a Gantt chart layout.
Why It Works
Specifying the role ensures the AI “thinks” like a project manager.
Stating the task in detail (with milestones and stakeholders) focuses the response.
The format request ensures an easy‐to‐read structured output.
B. Supply Chain Use Case
Role: Act as a Logistics Coordinator
Task: Propose an optimal shipping schedule to minimize delays and costs across three distribution centers.
Format: Present the schedule in a simple matrix table with columns for “Distribution Center,” “Shipping Frequency,” “Transport Mode,” and “Cost Estimation.”
Example Prompt
Role: You are a Logistics Coordinator.
Task: Devise an optimal shipping schedule for three distribution centers in different regions, aiming to minimize both transit time and shipping costs. Take into account current fuel prices, inventory levels, and shipping frequency.
Format: Provide the schedule in a matrix table, labeling each row with the distribution center and including columns for frequency, transport mode, and approximate costs.
Task: Devise an optimal shipping schedule for three distribution centers in different regions, aiming to minimize both transit time and shipping costs. Take into account current fuel prices, inventory levels, and shipping frequency.
Format: Provide the schedule in a matrix table, labeling each row with the distribution center and including columns for frequency, transport mode, and approximate costs.
C. Data Analytics Use Case
Role: Act as a Data Analyst specialized in retail sales
Task: Provide a weekly sales dashboard overview for a chain of electronics stores, highlighting best‐selling products, total revenue, and sales trends.
Format: Present the dashboard summary as short text sections with bullet points for each key metric.
Example Prompt
Role: You are a Data Analyst focusing on retail sales. Task: Summarize the weekly sales performance of a chain of electronics stores. List the top five best‐selling items, total revenue vs. last week’s revenue, and any notable trend in buyer behavior (e.g., surge in online vs. in‐store sales). Format: Output the summary in short text blocks, each with bullet points, for easy reading in a weekly team report.
2. T‐A‐G (Task → Action → Goal)
Framework Explanation
Task: Clearly define the job or problem to be tackled.
Action: Specify what the AI must do or how it must do it.
Goal: State the intended outcome or success criteria.
A. Project Management Use Case
Task: Evaluate the performance of a cross‐functional project team.
Action: Act as a performance auditor to identify strengths, weaknesses, and potential bottlenecks. Provide suggestions for improvement.
Goal: Improve team efficiency by 20% in the next quarter.
Example Prompt
Task: We need to evaluate the performance of our cross‐functional project team. Action: Act as a performance auditor. Identify key strengths, weaknesses, and bottlenecks that hinder smooth project execution. Provide specific recommendations and action items. Goal: Increase overall team efficiency by at least 20% over the next quarter.
B. Supply Chain Use Case
Task: Streamline the warehouse picking and packing process.
Action: Propose a new warehouse layout and process flow, referencing industry best practices.
Goal: Reduce average order fulfillment time by 30%.
Example Prompt
Task: We need to optimize our warehouse’s picking and packing processes.
Action: Act as an industrial engineer specialized in supply chain. Suggest a new layout (e.g., zone picking, wave picking) and outline standard operating procedures.
Goal: Reduce the average order fulfillment time by 30% and cut associated labor costs.
Action: Act as an industrial engineer specialized in supply chain. Suggest a new layout (e.g., zone picking, wave picking) and outline standard operating procedures.
Goal: Reduce the average order fulfillment time by 30% and cut associated labor costs.
C. Data Analytics Use Case
Task: Detect emerging sales trends in a dataset covering the last 12 months.
Action: Analyze the dataset for seasonal patterns, product category spikes, and anomalies.
Goal: Identify 3 actionable insights for the marketing team to capitalize on in the upcoming quarter.
Example Prompt
Task: We want to uncover emerging trends in 12 months of sales data.
Action: Act as a data analyst. Perform a time‐series analysis looking for seasonal spikes, anomalies, or rapidly growing categories.
Goal: Deliver at least three data‐backed recommendations for marketing strategies next quarter.
Action: Act as a data analyst. Perform a time‐series analysis looking for seasonal spikes, anomalies, or rapidly growing categories.
Goal: Deliver at least three data‐backed recommendations for marketing strategies next quarter.
3. B‐A‐B (Before → After → Bridge)
Framework Explanation
Before: Describe the current or initial situation or problem.
After: Clarify the desired future state or outcome.
Bridge: Outline how to get from “Before” to “After.”
A. Project Management Use Case
Before: Project scope creep is causing missed deadlines and budget overruns.
After: The project is back on track with clearly defined scope and on‐time milestones.
Bridge: Provide a step‐by‐step scope management plan, including how to handle changes without delaying the schedule.
Example Prompt
Before: Our project is plagued by scope creep, leading to missed deadlines and budget overruns.
After: We want to realign the project schedule and define the scope so the team can stick to deadlines and remain within budget.
Bridge: Propose a scope management plan detailing how we can prevent or control changes, reallocate resources, and communicate effectively with stakeholders.
After: We want to realign the project schedule and define the scope so the team can stick to deadlines and remain within budget.
Bridge: Propose a scope management plan detailing how we can prevent or control changes, reallocate resources, and communicate effectively with stakeholders.
B. Supply Chain Use Case
Before: The distribution network is scattered and disorganized, leading to frequent stockouts and excess inventory at different locations.
After: A centralized, optimized distribution network with balanced stock levels and minimal waste.
Bridge: Provide a restructuring plan that involves selecting optimal warehouse locations, implementing an inventory management system, and setting up real‐time monitoring.
Example Prompt
Before: Our distribution network is unbalanced: some warehouses are overstocked while others constantly face stockouts.
After: We want an optimized network that maintains stable stock levels, minimizes costs, and meets customer demand swiftly. Bridge: Propose a plan for redistributing inventory, choosing warehouse locations, and implementing real‐time data solutions to monitor supply and demand.
After: We want an optimized network that maintains stable stock levels, minimizes costs, and meets customer demand swiftly. Bridge: Propose a plan for redistributing inventory, choosing warehouse locations, and implementing real‐time data solutions to monitor supply and demand.
C. Data Analytics Use Case
Before: Sales reports are manually compiled, often inaccurate, and delayed by at least a week.
After: Automated, real‐time dashboard that stakeholders can access anytime, with minimal errors.
Bridge: Suggest a data pipeline workflow to automate data collection, cleansing, and visualization, including recommended tools.
Example Prompt
Before: We rely on spreadsheet‐based reporting that’s inconsistent and at least a week behind.
After: We want a real‐time dashboard that gives up‐to‐the‐minute sales figures, automatically updated.
Bridge: Outline the technical steps, tools (ETL, BI), and best practices needed to build and maintain this automated data pipeline.
After: We want a real‐time dashboard that gives up‐to‐the‐minute sales figures, automatically updated.
Bridge: Outline the technical steps, tools (ETL, BI), and best practices needed to build and maintain this automated data pipeline.
4. C‐A‐R‐E (Context → Action → Result → Example)
Framework Explanation
Context: Lay out the situation or background information.
Action: Explain what you want the AI (or user) to do in that context.
Result: Clearly state the desired outcome.
Example: Offer an illustration or comparison to guide or inspire the solution.
A. Project Management Use Case
Context: A construction project is behind schedule due to frequent material delivery delays.
Action: Identify the main scheduling gaps and propose a revised plan with buffer times.
Result: Deliver a feasible timeline that accounts for delivery uncertainties and ensures no more than a 5% increase in total cost.
Example: Compare your revised plan to a standard critical path method timeline, demonstrating how buffer times mitigate delays.
Example Prompt
Context: Our building construction project is 10% behind schedule because materials often arrive late. We have a limited budget for expedited shipping.
Action: Provide a detailed analysis pinpointing where schedule gaps occur and propose a revised timeline incorporating safety buffers.
Result: A feasible schedule that ensures no more than 5% cost overrun.
Example: Include a brief example comparing your solution to a typical CPM (Critical Path Method) chart, showing how buffer times protect the overall schedule.
Action: Provide a detailed analysis pinpointing where schedule gaps occur and propose a revised timeline incorporating safety buffers.
Result: A feasible schedule that ensures no more than 5% cost overrun.
Example: Include a brief example comparing your solution to a typical CPM (Critical Path Method) chart, showing how buffer times protect the overall schedule.
B. Supply Chain Use Case
Context: New environmental regulations require greener logistics solutions.
Action: Recommend eco‐friendly transportation modes and packaging alternatives for shipping goods internationally.
Result: Achieve a 20% reduction in carbon footprint while maintaining or slightly reducing shipping costs.
Example: Reference a successful case study (e.g., a major global retailer) that cut shipping emissions without drastically increasing costs.
Example Prompt
Context: We operate an international shipping operation and must comply with new eco‐regulations.
Action: Advise on greener transport modes (sea, rail, alternative fuels) and more sustainable packaging options (recyclable, biodegradable, etc.). Provide a cost vs. benefit breakdown. Result: Attain a 20% reduction in carbon emissions with no significant cost increase.
Example: Refer to how major retailers have successfully implemented greener shipping solutions while preserving margins.
Action: Advise on greener transport modes (sea, rail, alternative fuels) and more sustainable packaging options (recyclable, biodegradable, etc.). Provide a cost vs. benefit breakdown. Result: Attain a 20% reduction in carbon emissions with no significant cost increase.
Example: Refer to how major retailers have successfully implemented greener shipping solutions while preserving margins.
C. Data Analytics Use Case
Context: The marketing team struggles with ad campaign performance data that comes from multiple sources.
Action: Set up a unified dashboard or data warehouse to consolidate Facebook Ads, Google Ads, and email marketing metrics.
Result: A single source of truth that allows the marketing team to track and compare campaign ROI in real time.
Example: Show how a well‐structured data warehouse can offer consistent, reliable reporting—similar to top analytics platforms like Google Data Studio.
Example Prompt
Context: Our marketing data is scattered across Facebook Ads, Google Ads, and email platforms, causing confusion in ROI calculations.
Action: Design a data warehouse or unified dashboard approach that integrates these sources, outlines the schema, and automates data refresh.
Result: A single source of truth that helps marketing teams quickly evaluate campaign performance in near real time. Example: Demonstrate how solutions like Google Data Studio or Power BI unify multi‐platform data to produce consistently reliable reports.
Action: Design a data warehouse or unified dashboard approach that integrates these sources, outlines the schema, and automates data refresh.
Result: A single source of truth that helps marketing teams quickly evaluate campaign performance in near real time. Example: Demonstrate how solutions like Google Data Studio or Power BI unify multi‐platform data to produce consistently reliable reports.
5. R‐I‐S‐E (Role → Input → Steps → Expectation)
Framework Explanation
Role: Specify which perspective or expertise the AI should assume.
Input: Provide the data or details the AI needs to process or consider.
Steps: Request a step‐by‐step solution, plan, or procedure.
Expectation: Clearly define the end state or standard for success.
A. Project Management Use Case
Role: Project Planner for a new product launch
Input: Sales targets, budget constraints, team size, and a 6‐month timeline
Steps: Create a high‐level schedule with monthly milestones, indicating resources needed at each stage.
Expectation: The plan should ensure an on‐time launch and alignment with the marketing campaign.
Example Prompt
Role: You are an experienced project planner for a product launch.
Input: We have a team of 8, a total budget of $200k, a 6‐month window, and a first‐year sales target of $1M.
Steps: Outline a monthly project plan, specifying resource needs (people, tools, budget) and any gating milestones. Expectation: Deliver a plan that meets the launch deadline, fits the budget, and dovetails with the marketing rollout dates.
Input: We have a team of 8, a total budget of $200k, a 6‐month window, and a first‐year sales target of $1M.
Steps: Outline a monthly project plan, specifying resource needs (people, tools, budget) and any gating milestones. Expectation: Deliver a plan that meets the launch deadline, fits the budget, and dovetails with the marketing rollout dates.
B. Supply Chain Use Case
Role: Supply Chain Optimization Specialist
Input: Current inventory levels, forecast demand, lead times from suppliers, and historical data on shipping delays
Steps: Formulate an inventory optimization strategy that uses reorder point formulas and safety stock calculations.
Expectation: Achieve a 95% service level while reducing carrying costs by 10%.
Example Prompt
Role: You are a Supply Chain Optimization Specialist.
Input: We have real‐time data on inventory levels, three‐month demand forecasts, average supplier lead times of 14 days, and records showing a 10% shipping delay frequency.
Steps: Propose reorder point calculations, define safety stock policy, and outline how we can implement these changes operationally.
Expectation: Reach a 95% fill rate (service level) while cutting overall inventory holding costs by 10%.
Input: We have real‐time data on inventory levels, three‐month demand forecasts, average supplier lead times of 14 days, and records showing a 10% shipping delay frequency.
Steps: Propose reorder point calculations, define safety stock policy, and outline how we can implement these changes operationally.
Expectation: Reach a 95% fill rate (service level) while cutting overall inventory holding costs by 10%.
C. Data Analytics Use Case
Role: Business Intelligence Consultant
Input: Customer transaction data (online + in‐store), demographic data, and marketing spend for the last 6 months
Steps: Create an end‐to‐end BI implementation plan (data ingestion, cleaning, modeling, visualization).
Expectation: A BI dashboard that correlates marketing spend with customer segments and calculates ROI per campaign channel.
Example Prompt
Role: You are a Business Intelligence Consultant.
Input: We have 6 months of transaction data (both online and in‐store) plus demographic info and marketing spend data across three channels (social media, TV, and email). We need actionable insights.
Steps: Show how to ingest the data, clean it, combine it, and set up a BI model or star schema. Then outline a plan to visualize ROI by customer segment and channel.
Expectation: Deliver a final BI dashboard that directly links marketing spend to ROI by segment, helping us optimize future campaigns.
Input: We have 6 months of transaction data (both online and in‐store) plus demographic info and marketing spend data across three channels (social media, TV, and email). We need actionable insights.
Steps: Show how to ingest the data, clean it, combine it, and set up a BI model or star schema. Then outline a plan to visualize ROI by customer segment and channel.
Expectation: Deliver a final BI dashboard that directly links marketing spend to ROI by segment, helping us optimize future campaigns.
How to Use These Frameworks
1. Pick a framework that best matches your communication style and needs.
2. Identify the domain (Project Management, Supply Chain, or Data Analytics).
3. Plug in your specifics (roles, tasks, context, data) into the framework.
4. Run the prompt in ChatGPT or another AI tool, then refine based on the response.
5. Iterate until the AI’s output satisfies your requirements—tweak Role, Task, Format, or other elements as needed.
By structuring prompts with these frameworks, novice AI users in Project Management, Supply Chain, or Data Analytics can more reliably produce focused, on‐target responses from ChatGPT. Whether you need strategy documents, scheduling help, or data analysis, these templates will help you ask the right question in the right way—no fluff, no wasted time.
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