# Why I created the “PLAI Score” — a simple way for homebuyers to judge lift adequacy in high-rise buildings

Over the past few months, I’ve seen (and personally experienced) how painful life becomes in high-rise societies once they’re fully occupied — especially in Hyderabad and Bangalore.

Long waiting times for lifts. Crowded lobbies during office hours. Frustration that no one warned buyers about this.

That’s what inspired me to create the **PLAI (Passenger Lift Adequacy Index)** — a simple score that helps homebuyers quickly gauge if a building has *enough* and *fast enough* lifts for its height and density.

Inspiration also came from this insightful [post](https://x.com/HydSpeaks/status/1980233939391484324) by [@HydSpeaks](https://x.com/HydSpeaks/status/1980233939391484324) — which highlights how many under-construction projects ignore lift planning even in 40–60 floor towers.

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### 💡 The problem

Most homebuyers never ask:

> “Are there enough lifts for all these floors and flats?”

By the time they realize it — years later — the society is full, lift waiting time is 10+ minutes, and nothing can be changed.

As cities like Hyderabad, Bangalore, and Pune move toward 40–60 storey projects, lift adequacy is not a luxury issue anymore — it’s a **daily convenience issue**.

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### ⚙️ The PLAI formula (works well for 30+ floor towers comparison)

To make lift adequacy measurable, I created a simple formula that balances key factors:

![](https://cdn.hashnode.com/res/hashnode/image/upload/v1762080562760/0bb33eb2-c68c-4b22-9d5f-ad59c9168ad5.png align="center")

Where:

* **L** = Number of lifts in the building
    
* **C** = Capacity of each lift (number of people) (mentioned officially in the lift)
    
* **v** = Lift speed in meters per second
    
* **F** = Total number of floors
    
* **f** = Flats per floor
    
* ***What this formula captures***
    
    ✅ **Penalizes height linearly (via F)**  
    Taller buildings naturally need more or faster lifts. The formula applies a direct penalty with F — doubling the number of floors roughly halves your score (if everything else stays constant).
    
    ✅ **Penalizes density moderately (via √f)**  
    If more flats share the same set of lifts, wait times and crowding go up. But the penalty is moderate (using the square root) — doubling flats per floor doesn’t double the penalty.
    
    ✅ **Rewards speed, size, and number of lifts — with more weight on lift count**  
    Lift count (L) now has a slight exponent of **1.1**, which means every additional lift contributes *more than linearly* to the score.  
    This reflects reality — adding an extra lift often improves experience disproportionately, especially in tall or high-density towers.  
    It reduces waiting time, congestion, and crowding far more effectively than just making existing lifts faster or larger.
    
    ✅ **Keeps the formula compact and interpretable**  
    Each component plays a clear role. The formula balances simplicity with realism — good enough to compare buildings meaningfully, without requiring simulation-level complexity.
    

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## 📊 Examples — How PLAI Reflects Real-World Lift Adequacy

These are not hypothetical calculations — they’re based on actual building configurations from modern residential towers across India.

![](https://cdn.hashnode.com/res/hashnode/image/upload/v1762080382392/b5a2f982-748f-43b1-8463-f52d794bb7ed.png align="center")

These are not theoretical values — they correspond closely to real building designs across India.

Each example illustrates how **PLAI** translates physical parameters into an intuitive adequacy score.

* **Tower A (32 Floors, 8 flats/floor, 8 lifts, 3 m/s, 12-person capacity)** → **PLAI = 3.92 → Excellent**
    
    > A well-planned high-rise with ample lift capacity and speed, ensuring smooth traffic flow even during peak times.
    
* **Tower B (32 Floors, 5 flats/floor, 4 lifts, 3 m/s, 12-person capacity)** → **PLAI = 2.31 → Good**
    
    > Balanced configuration with reasonable waiting times; performs well for its scale.
    
* **Tower C (31 Floors, 8 flats/floor, 4 lifts, 2.5 m/s, 14-person capacity)** → **PLAI = 1.83 → Moderate**
    
    > Adequate for typical usage, but some delays may occur during high traffic hours.
    
* **Tower D (29 Floors, 5 flats/floor, 3 lifts, 3 m/s, 10-person capacity)** → **PLAI = 1.55 → Poor**
    
    > Under-lifted for the number of residents; noticeable congestion during rush periods.
    

These examples highlight how the **PLAI** model dynamically adjusts for both **tower height** and **lift provisioning**, giving a realistic sense of user experience across a variety of designs.

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## 🧩 The Service Lift Reward Function

In many premium buildings, **service lifts** play an important role in overall experience.  
They handle movement for:

* Housekeeping staff
    
* Pets and bicycles
    
* Deliveries, maintenance, and logistics
    

Having multiple service lifts doesn’t just help convenience — it **reduces load on passenger lifts**.  
However, since service lifts are often slower, their contribution shouldn’t overpower the main score.

### ✅ When to Apply the Reward

You should apply the **Service Lift Reward Function** only when:

* The building has **more than one** service lift, and
    
* The **ratio of service lifts to flats per floor** is **greater than 0.2** (i.e., 1 service lift per 5 or fewer flats).
    

In such cases, a **small 5% reward** is added to the PLAI score to reflect improved real-world experience.

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### ⚙️ Reward Function Formula

![](https://cdn.hashnode.com/res/hashnode/image/upload/v1762139326592/25ef6603-6084-4770-9de1-245c85d94eff.png align="center")

This ensures that:

* Projects with genuinely supportive service lift infrastructure get a small bump
    
* Those with none or one aren’t penalized
    

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## 🎯 PLAI Rating Guide

The PLAI score translates into five intuitive rating levels:

| PLAI Score | Rating | Interpretation |
| --- | --- | --- |
| ≥ 3.2 | **Excellent** | Lifts are generous and responsive even at peak hours |
| 2.1 – 3.19 | **Good** | Adequate for comfort with occasional wait during rush times |
| 1.7 – 2.09 | **Moderate** | Functional but queues likely in high-traffic periods |
| 1.3 – 1.69 | **Poor** | Frequent waiting, especially at morning/evening peaks |
| < 1.3 | **Very Poor** | Under-served lift capacity for tower size and population |

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## 🧭 How to use this as a home buyer

1. **Get these details** from the builder’s specs:
    
    * Total floors (F)
        
    * Flats per floor (f)
        
    * Number of lifts (L)
        
    * Lift capacity (C, usually 8–14 persons)
        
    * Lift speed (v, typically 1.5–3.5 m/s)
        
2. **Plug them into the formula or this Google Sheets formula:**
    
    ```plaintext
    =(POWER(C2,1.1)*E2*D2)/(A2*SQRT(B2))
    ```
    
    **Compare the PLAI score** with the rating guide above.  
    If your building’s score is below 1.7 → ask tough questions before booking!
    
3. **Rating Assignment:**
    
    ```plaintext
    =IF(F2>=3.2,"Excellent",
     IF(F2>=2.1,"Good",
      IF(F2>=1.7,"Moderate",
       IF(F2>=1.3,"Poor","Very Poor"))))
    ```
    
    (Where F2 contains the computed PLAI value)
    
4. if you want to add a service lift reward function :
    
    ```plaintext
    =IF(AND(G2>1, G2/B2>0.2), F2*1.05, F2)
    ```
    
    (Where G2 contains the number of service lifts, B2 contains total flats per floor)
    
5. You can then apply the same PLAI rating system to the resulting **PLAI\_final**.
    

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## 🏗️ What PLAI doesn’t cover (yet)

PLAI is designed to give a **practical first-level indication**, not an engineering-grade simulation.  
Some real-world factors it doesn’t model yet:

* Actual **floor height** (affects travel time slightly).
    
* **Flat size & population density** (large 4BHKs vs 1BHKs).
    
* **Zoned or express lifts** that serve only a subset of floors.
    
* **Reward function for shared lobbies**
    

Still, for **under-construction projects** or early evaluation, PLAI gives a much better comparative view than just “number of lifts”.

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## 💡 Why this matters

In Indian metros, developers often prioritize amenities or facade over **vertical mobility efficiency**.  
But as towers rise to 40–60 floors, **lift adequacy directly impacts your quality of life** — from morning rush hours to late-night returns.

A well-designed lift system is not just convenience — it’s **core infrastructure**.

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## 🧩 Final thoughts

The **Pankaj Lift Adequacy Index (PLAI)** is a simple attempt to bring **rational thinking into high-rise evaluation**.  
It encourages buyers and builders alike to **quantify lift adequacy**, not leave it to guesswork.

Next time you visit a project brochure or marketing office, just ask:

> “What’s your PLAI score?” 😄

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