What should ProjectEngine support next?

[TMailletFR]

ProjectEngine has now reached a stable point where the main scheduling, simulation and Gantt workflows are in place.

The next useful features should come from real-world needs rather than from adding functionality for its own sake.

This discussion is for ideas such as:

• missing scheduling workflows;
• integrations with Jira, Power Query or other data sources;
• import and export requirements;
• industry-specific or more generic planning templates;
• reporting and analytics improvements;
• usability or onboarding friction;
• anything that would make ProjectEngine easier to adopt in a real team.

When suggesting an idea, please include:

1. the problem you are trying to solve;
2. how you handle it today;
3. why the current ProjectEngine workflow is not sufficient;
4. what a useful result would look like.

The goal is not to reproduce every feature of Microsoft Project or Primavera.

The goal is to identify the highest-value gaps for teams that already work in Excel and need real scheduling capabilities.

[phobo3s]

Hi @TMailletFR,

Thanks for sharing this project. I'd like to suggest an improvement regarding how daily forecasts/remaining work are distributed to calculate the S-Curve. Currently, as we can see in s-curve graph the gray bars, the remaining work is divided evenly (linear/flat distribution) over the given time periods.
If we could introduce options to model progress rate using different distribution shapes, such as triangular, inverted triangular, or bell curve (normal distribution?), we could generate much more realistic S-Curves and this would allow for better resource planning and forecasting by reflecting real world dynamics.

[TMailletFR]

Hi,

Thanks for the suggestion. Yes, this is something I had considered before, but it has not been prioritized so far because I was not sure how often these alternative distribution profiles are actually used in day-to-day planning.

The current S-Curve logic uses a flat/linear distribution for the remaining work, so adding selectable distribution profiles could definitely make the forecast more realistic in some cases.

The shapes you mentioned (triangular, inverted triangular, and bell/normal distribution) are exactly the kind of options I had in mind.

Do you use these kinds of profiles regularly in your work?

If so, I’d be very interested in knowing which ones are actually the most useful in practice. If you had to rank the most commonly used profiles in your field, what would your top 3 be?

That would help me prioritize the implementation around real usage rather than just adding options for the sake of having them.