Understanding implications of rating systems in apartment management platforms

Probing into Service, System, and Infrastructure

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Rating systems have become a new trend in the industry. From rating products to rating deliveries, we have come to a point where we are rating people now a days. Many a times, we don’t know the consequences these ratings have on the people who receive them.

With the increase in the number of gated societies in the cities, new apps are coming in the market for apartment management. The apps have features like maintenance payment, rating helps, accessing control at the main gate, forums and discussions about the society, finding helps and local services instantly, etc. Where the apps have made it easy for residents to choose the best domestic worker instantly based on ratings, the same rating may lead to the discontinuation of the worker.

Our approach and findings

We were introduced to this idea by means of an article by the Huffington post(HP). The article talks about how the apartment management apps are affecting the livelihoods of the domestic workers because of the inefficient rating system.

We also studied the current entry/exit and rating scenario in gated societies.

Then we looked at one of the apartment management app called MyGate. This app has replaced the intercom calling in many of the gated societies. The app has a dedicated rating system for domestic workers and local services like laundry, milkman, newspaper, car cleaner, etc. It’s easy to select any maid/cook by seeing the rating. Now, here’s the problem. We have a tendency to pick a worker who has a nice rating of 4 or 5 out of 5. As a result of this, they might keep getting better and better ratings while the workers with low ratings might not get a chance to improve their ratings.

My Daily help feature in MyGate App of a resident of a gated society

Why is it important?

Factors that might affect the rating of helpers (gathered from secondary research):

  1. The employer is having a bad day
  2. A bad experience or a slight argument with the helper
  3. Helper took a leave without asking/informing
  4. Helper asked for advance payment

These factors cannot determine a helper’s quality of work. One should be conscious while giving such ratings as quantitatively speaking, the number of people rating house helps are considerably less than the number of people rating a delivery person. A delivery person may get around 200–300 ratings in a month while a house help may get only 20 or less depending on the number of houses she works. This creates a large difference in the average ratings.

The culture of rating products on Amazon or movies on Netflix has instilled in us the concept that anything that has a lower rating is bad. But people are not products. A bad day or a bad experience might cause an employer give bad ratings but it doesn’t necessarily account to the worker’s worth. For example, after interviewing a resident of a society that uses MyGate app, we found that her maid had a rating of 1. On asking if the rating of the maid mattered to her, the resident replied that she had no idea why someone rated her low because she does a good job at her place.

We feel that by looking deeper into the dynamics of rating systems, we can understand it’s implications on the domestic help. We also want to speculate on how we can create a better system where there is a transparent rating system. This might include adding extra features in the existing apartment management applications.

Research Area

Understanding the implications of rating system on the livelihoods of the domestic helpers. Do we really need a rating system for them? What was the system like before the rating system came?What is the scenario in the societies where the rating system is not implemented?

Methods

We will be doing interviews and surveys to collect data. Apart from that, we will be reading about the psychology behind the rating systems in parallel.

Expected Outcome

We expect to create an empathy map through our findings and also visualization of the same. We will also create journey maps for our speculated system.

Timeline

Team Night Fury

Saroj Tailor, Sindhu Neti, Vipul Negi

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Saroj Tailor
Gigs, Service-systems & Platforms, and Design

Designer in making. I love dogs, food, books, smell of books, and historical fiction. I try to write and design. I’m here: https://www.behance.net/sarojt