Schedule Management: Estimating and Reserves 🎯
The Story of Building a Treehouse
Imagine you want to build the coolest treehouse ever for your backyard. Before you start hammering, you need to figure out: How long will this take?
That’s exactly what Estimate Activity Durations means in project management. It’s like being a fortune-teller for time!
🏠 What is Estimate Activity Durations?
Simple idea: Guessing how long each task will take before you start.
Think of it like planning a birthday party:
- Baking a cake = 2 hours
- Decorating = 1 hour
- Setting up games = 30 minutes
In projects, we estimate:
- How many days to write code
- How many weeks to test
- How many months to build
Example: Building our treehouse:
- Buying wood = 1 day
- Building the floor = 3 days
- Adding walls = 2 days
- Painting = 1 day
🔮 The Four Magic Ways to Estimate
1. Analogous Estimating (The “Remember Last Time” Method)
What is it? Looking at something similar you did before.
Real-life example:
“Last summer, I built a doghouse. It took 2 days. A treehouse is bigger… maybe 3x bigger. So, 2 days × 3 = 6 days for the treehouse!”
When to use:
- When you’ve done something similar before
- When you don’t have much information yet
- When you need a quick guess
graph TD A["Past Project: Doghouse"] --> B["Took 2 days"] B --> C["Treehouse is 3x bigger"] C --> D["Estimate: 6 days"]
Pros: Fast and easy Cons: Not very accurate
2. Parametric Estimating (The “Math Formula” Method)
What is it? Using numbers and formulas to calculate time.
Real-life example:
“Each wall takes 4 hours to build. The treehouse has 4 walls. 4 hours × 4 walls = 16 hours for all walls!”
The formula is simple:
Time = Rate × Quantity
Another example:
- Painting 1 square meter takes 15 minutes
- The treehouse is 20 square meters
- 15 minutes × 20 = 300 minutes = 5 hours
When to use:
- When you know exactly how long one unit takes
- When you can count how many units you need
- When you want more accuracy
Pros: More accurate than analogous Cons: Needs good data to work
3. Three-Point Estimating (The “Best, Worst, Most Likely” Method)
What is it? Making three guesses and averaging them.
The three points:
- 🌟 Optimistic (O): Best case, everything goes perfect
- 😊 Most Likely (M): Normal case, what usually happens
- 🌧️ Pessimistic (P): Worst case, everything goes wrong
Real-life example for building walls:
- Optimistic: 1 day (sunny, all tools work)
- Most Likely: 2 days (normal weather, normal work)
- Pessimistic: 4 days (rain, broken tools, helper sick)
Two formulas:
Simple Average (Triangular):
Estimate = (O + M + P) ÷ 3
Estimate = (1 + 2 + 4) ÷ 3 = 2.3 days
PERT Formula (Weighted Average):
Estimate = (O + 4×M + P) ÷ 6
Estimate = (1 + 4×2 + 4) ÷ 6 = 13 ÷ 6 = 2.2 days
PERT gives more weight to “Most Likely” because that’s usually what happens!
graph TD A["Optimistic: 1 day"] --> D["Three-Point"] B["Most Likely: 2 days"] --> D C["Pessimistic: 4 days"] --> D D --> E["PERT: 2.2 days"]
Pros: Considers uncertainty Cons: Takes more time to calculate
4. Bottom-Up Estimating (The “Add All The Pieces” Method)
What is it? Breaking the big task into tiny pieces, estimating each piece, then adding them up.
Real-life example:
Building a treehouse wall:
- Cut wood pieces = 30 minutes
- Sand the edges = 20 minutes
- Nail frame together = 45 minutes
- Attach to tree = 25 minutes
- Check stability = 10 minutes
Total for one wall = 130 minutes = 2 hours 10 minutes
Do this for every part, then add everything!
graph TD A["Cut Wood: 30 min"] --> F["Total: 2hr 10min"] B["Sand Edges: 20 min"] --> F C["Nail Frame: 45 min"] --> F D["Attach: 25 min"] --> F E["Check: 10 min"] --> F
When to use:
- When you need the most accurate estimate
- When you have time to plan carefully
- When the project is important
Pros: Most accurate method Cons: Takes longest to do
🛡️ Reserve Analysis: Your Safety Net
What are Reserves?
Imagine you’re going on a road trip. You bring:
- Enough gas to reach your destination
- Extra gas in case you get lost
- Money in case something breaks
That “extra” is your reserve! In projects, we save extra time (and money) for surprises.
Contingency Reserves (Known Unknowns)
What is it? Extra time for things that might go wrong.
Real-life example:
“Rain might delay painting. Let me add 1 extra day just in case.”
Key facts:
- For risks you can think of but aren’t sure will happen
- The project manager controls this
- Part of the project schedule
- Based on risk analysis
Example calculation:
- Building walls: 2 days
- Risk: Rain (30% chance of 1-day delay)
- Contingency: 0.30 × 1 day = 0.3 days extra
- Total estimate: 2.3 days
graph TD A["Base Estimate: 2 days"] --> C["Total: 2.3 days"] B["Contingency: 0.3 days"] --> C C --> D["Project Manager Controls"]
Think of it as: Umbrella in your bag when clouds look gray
Management Reserves (Unknown Unknowns)
What is it? Extra time for things you can’t even imagine going wrong.
Real-life example:
“What if a tree falls on our supplies? What if there’s an earthquake? I don’t know what will happen, but I’ll save 10% extra time!”
Key facts:
- For risks you cannot predict
- Senior management controls this
- NOT part of the regular schedule
- Usually a percentage of total time (5-10%)
Example:
- Total project: 10 days
- Management reserve: 10% = 1 day extra
- Total with reserve: 11 days
graph TD A["Project Schedule: 10 days"] --> C["Total: 11 days"] B["Management Reserve: 1 day"] --> C C --> D["Management Controls"]
Think of it as: Emergency savings for things you never expected
🎯 Quick Comparison
| Reserve Type | Who Controls? | For What? | Part of Schedule? |
|---|---|---|---|
| Contingency | Project Manager | Known risks | ✅ Yes |
| Management | Senior Management | Unknown risks | ❌ No |
📊 Comparing All Estimation Methods
| Method | Speed | Accuracy | Best For |
|---|---|---|---|
| Analogous | ⚡ Fast | Low | Early planning |
| Parametric | ⚡ Fast | Medium | Repeated tasks |
| Three-Point | Medium | Medium-High | Uncertain tasks |
| Bottom-Up | 🐢 Slow | High | Important projects |
🌟 The Big Picture
graph TD A["Estimate Activity Durations"] --> B["Analogous"] A --> C["Parametric"] A --> D["Three-Point"] A --> E["Bottom-Up"] A --> F["Reserve Analysis"] F --> G["Contingency Reserves"] F --> H["Management Reserves"]
🎪 Remember This Story!
Building a treehouse taught us:
- Analogous = “My doghouse took 2 days, so…”
- Parametric = “4 walls × 4 hours each = 16 hours”
- Three-Point = “Best 1 day, worst 4 days, probably 2 days”
- Bottom-Up = “Add every tiny task together”
- Contingency Reserve = “Umbrella for expected rain”
- Management Reserve = “Emergency fund for surprises”
💡 Pro Tips
- Start with analogous when you know little
- Use parametric when you have good data
- Apply three-point when uncertainty is high
- Do bottom-up for critical activities
- Always add reserves — things NEVER go perfectly!
🎯 Key Takeaway
Good estimates = Base time + Contingency (what might go wrong) + Management reserve (what could surprise you)
You’re now ready to estimate like a pro! 🚀