📁 Download 💿 189 , 💿 190 and 💿 491 s56 to grants data. There...

@gregormendel

1y ago updated 3mo ago Australia

📁 Download 💿 189 , 💿 190 and 💿 491 s56 to grants data. There are two sets of data in these documents: - Recent s56 requests which have been granted, and - Recent s56 requests which are pending grant

These files are auto-updated daily.

How to use 1. You can click on the 💿 icon above to download the appropriate file. 2. Then, you can paste the text content of the file into ChatGPT, Claude or Gemini. 3. Then you can share your own lodgment date and s56 dates with GPT, and ask GPT to make a prediction of your grant date based on the statistical patterns in the data.
Your profile data is on your SmartVisaGuide user profile page (look for the View Text Summary under your entries).

👉 Who is this for? This best serves those applicants who have just (recently) received an s56 request and want to see patterns of S56 to grant timelines.

Here is an example ChatGPT prompt (after you share downloaded data and your user profile data): "Based on the shared s56 to grant data, and my own visa lodgment data, please predict my visa grant date. Additionally, give me a detailed statistical report to validate your predicted grant date."

💬 Download a Detailed Prompt here. This is the same (long) prompt shared in the comments below.

If you are tracking your profile on SmartVisaGuide, and have received an S56 request for your visa application, please add it to your timeline.

🎈 Please share any useful GPT prompts in comments (the ones that gave you best insights) and I will incorporate them in this post for other users.

👇 You can click on the bookmark button below to save this post 👇

Comments 8

@eugenr 9mo ago

You are an experienced Australian immigration lawyer specialising in skilled migration, with deep knowledge of the Subclass 491 (Skilled Work Regional (Provisional)) visa program, including the points-tested stream and state/territory nominated stream.

I will provide you with a dataset (or excerpts/summary statistics) containing the following key fields for Subclass 491 EOIs and outcomes (data mainly from 2021–2024, possibly up to mid-2025):

Date of EOI submission
Occupation (ANZSCO code + title)
Points score claimed
Nominated state/territory (or "no state nomination" for points-tested stream)
Whether the EOI was selected for state/territory nomination (yes/no)
Date of state/territory nomination approval (if applicable)
Date invitation to apply (ITA) was issued
Date visa application lodged (if available)
Date visa granted (if available)
Applicant age group, English level, Australian study, partner skills, etc. (if present)

Primary objective
Estimate realistic waiting times for a Maintenance Planner (ANZSCO 251911) who is seeking a Subclass 491 visa under the state/territory nominated stream (most common pathway for this occupation).

Please provide a structured, evidence-based analysis that includes:

Current invitation round trends for ANZSCO 251911 (Maintenance Planner)
How frequently is the occupation invited by each state/territory?
Typical points threshold observed in the last 6–12 months for this occupation (both with and without state nomination).
Time-to-invitation distribution (from EOI submission to invitation)
Median, 25th, 75th, and 90th percentiles for Maintenance Planner, broken down by nominating state/territory if data allows.
Highlight the impact of points score (e.g., 65, 70, 75+).
Time from invitation to visa grant (processing time)
Typical range for offshore vs onshore applicants (cite latest Home Affairs global processing times for 491 if relevant).
Key risk factors and practical advice
How important is having a very high points score (80+) in the current environment?
Which states/territories have historically been more consistent in nominating Maintenance Planners?
Common reasons for long delays or non-selection even with competitive points.
Summary recommendation
Provide a realistic expected wait time range (submission → invitation → grant) for a typical Maintenance Planner applicant in 2024–2025, differentiated by points level and preferred nominating jurisdiction.

Use tables for comparisons across states or points bands when helpful. Base your reasoning primarily on the data provided, and clearly state any assumptions or limitations when the dataset is incomplete.

1 replies

@lalala 10mo ago

Hi Gregor are these files still updated daily? @gregormendel

1 replies

@gregormendel 1y ago

We have added WEEKDAY name field to the exported files.

0 replies

@goofypenguin8503 1y ago

Check out this grant estimate of my profile from gemini https://g.co/gemini/share/2d4deab581e2

From claude https://claude.ai/public/artifacts/6c1013a4-abd4-4587-a3e5-22ac67c46fc7

1 replies

@mrzubairmalik 1y ago

Great. Can you provide same kind of data for the Visa grants for 190 pattern with GPT prompt? (not after s56)

0 replies

@lalala 1y ago

Would be great to have also data for s56 awaiting grant that way you could see where you are.

2 replies

@biotechy 1y ago

Prompt

You are a data analyst studying trends in Department of Home Affairs (DHA) decision-making for visa applications. You are given two datasets in the attached file separated by headers. One dataset shows when applicants received their visa grants after receiving an S56 request. The other dataset has details of applicants that are waiting for the grants after receiving the S56. An S56 request (or an RFI (Request for Further Information) request) is a request raised by DHA for more documents, police checks, medicals, etc.

Your primary objective is to help me understand the strategy and pattern DHA is currently following such as which types of applicants are being processed faster, what kinds of S56 requests are more common and how long DHA usually takes to finalize the cases after receiving the requested documents, by analysing the relevant datasets provided and generating insights.

Your secondary objective is to utilise the generated insights to identify how many applications with attributes similar to mine are waiting to receive their grants and estimate an approximate grant window for my application.

The details of my application are provided in the next section.

My Profile

PASTE YOUR PROFILE TEXT HERE

Task

Execute the following steps in order:

Identify DHA's current processing pattern From the dataset (where applicants received their grants), look for visible trends in how DHA is finalising grants:
- Which occupations or industries are being cleared first (ICT, Engineering, Healthcare, etc.)?
- Are onshore cases being granted faster than offshore?
- Are certain countries (India, Pakistan, others) moving faster?
- Which types of s56 (medical, PCC, form 80) lead to quicker outcomes?
- Has there been a shift in speed over recent months (e.g., faster grants in Oct 2025 vs Sept 2025)?
Summarise these insights clearly using visuals (bar charts, line charts, etc.)
Find similar applicant clusters based on my profile
Next, find applicants in both datasets who are most similar to my profile:
- Same visa subclass.
- Same onshore/offshore status.
- Same or nearby country.
- Similar occupation family.
- Same type of S56 (medical, PCC, mixed or other).
If there aren't enough exact matches, expand to the nearest cluster (e.g., all offshore ICT roles).
Summarise observed timelines
For the cluster identified in step 2,
- Identify how many days DHA typically takes between s56 and grant (where applicants received their grants).
- Report the most common, still normal, and less common but possible timelines.
- Report the number of applications pending grant after receiving the S56 request. Include relevant insights like the commonly requested S56 type, the age of the application after receiving the most recent S56 request.
- Avoid technical terms like "percentiles" - just express these as human-readable time ranges.
Summarise these insights clearly using visuals (bar charts, line charts, etc.)
Give an estimated grant window
Using my profile's data, translate those time ranges into real calendar dates, with three levels:
- Most Likely - Where DHA finalised most similar cases. An example wording would be "Most applicants like you were granted within 1-2 weeks after s56."
- Still Normal - Where slower cases were finalised. An example wording would be "Some took 2-3 weeks - still within the normal range."
- Less Common but Possible - Rare but observed cases. An example wording would be "A few took up to a month - uncommon but possible."
Visualise the estimated grant time window for me.
Wrap up with a paragraph that summarizes DHA's current processing strategy.
End with a short insight on DHA's apparent processing behaviour, e.g.: 'DHA seems to be clearing recent ICT and engineering occupations in quick batches, often within 1-2 weeks of remedical clearance. Cases that combine medical and PCC requests tend to take longer. Offshore timelines are now aligning closely with onshore ones, suggesting end-of-year batch finalisations."
Include a disclaimer "These insights are based on real community timelines from SmartVisaGuide. They reflect observed DHA behaviour = not official predictions. Actual grant timing can vary based on case officer workload and security checks."

0 replies

@gregormendel 1y ago

@all

1 replies

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Comments 8

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