The scenario side is what I end up reaching for most. It lets us model support volume and capacity across teams or regions and quickly see what happens when inquiries spike or staffing changes. The Excel add-in is useful when I want to dig into the numbers in the way I’m used to, and the dashboards make it easier to understand planned versus actual results without having to rebuild everything from scratch each time. Review collected by and hosted on G2.com.

It still feels heavier than it needs to be for straightforward operational planning. Adjusting or setting up models takes time and usually requires bringing in someone who knows the system better. Larger scenario runs can slow down somewhat, and new people on the team often need a while to get comfortable using it. Review collected by and hosted on G2.com.

Undoubtedly, the key benefit is the clarity it brings to implementing a workflow step by step, using turbointegrator processes to integrate information from a datawarehouse, applying business rules to prevent users mistakes and finally, the interface prevents wasted time because of the drag and drop functionality Review collected by and hosted on G2.com.

it is not very intuitive, sometimes is slow at the moment to open views too large or execute some processes that deal with rules into cubes. Also, there's a lack of documentation for some topics. Review collected by and hosted on G2.com.

The speed of the TM1 engine. When a planner can change a driver and see the impact across the model right away, they stop treating the budget as a once-a-year exercise and start using it to answer questions. Planning Analytics for Excel is the other big one. Finance teams don't have to give up Excel, and you still get one governed model underneath it. Review collected by and hosted on G2.com.

The learning curve on rules and TurboIntegrator is real. A well-built model is great for years, but a poorly built one is painful, so who builds it matters a lot. Planning Analytics Workspace has gotten much better, though some admin tasks still take more clicks than they should. Review collected by and hosted on G2.com.

I really like how IBM Planning Analytics handles complex requirements effortlessly and allows us to model sophisticated processes without any compromise. Compared to other platforms, IBM Planning Analytics stands out because it doesn't require workarounds for complicated modeling. I also appreciate the powerful "Spread and Hold" feature, which simplifies global adjustments and shows deltas almost immediately with just a few clicks, especially when used with the sandbox feature. Additionally, integrating Microsoft Excel with IBM Planning Analytics for Excel is a big plus as it combines a familiar tool with robust data handling capabilities and supports large data volumes and complex calculations. Review collected by and hosted on G2.com.

PAoC does not work in China due to the firewall. It would be great if IBM could build some data centers in China to support PAoC. Additionally, setting it up on-premise requires some technical knowledge, which can be a bit challenging. Review collected by and hosted on G2.com.

The TM1 engine handles the heavy lifting with ease: even with massive datasets and complex calculations, IBM Planning Analytics stays responsive and doesn’t freeze up. It also solves version-control headaches by moving everyone out of disconnected, error-prone spreadsheets and into a single, dependable system. Adoption has been smooth for our team, since business users can keep working in Excel through PAfE, while managers can jump into Workspace (PAW) for clear, visual web-based reports. On top of that, it cuts turnaround time by shrinking long budgeting and month-end close cycles from weeks down to just a few days. Review collected by and hosted on G2.com.

The backend has a steep learning curve. Building models, writing TurboIntegrator (TI) scripts, and tuning rule feeders all require specialized skills, and even small mistakes in feeders can quickly bog down server memory. Migration between environments can also feel clunky. Moving dashboards, views, and books across Dev, Test, and Prod in Workspace (PAW) still takes too much manual tweaking, rather than offering clean, one-click deployments. The Excel add-in (PAfE) occasionally hangs. When I’m working with huge, dynamic sheets or running heavy MDX queries, Excel can freeze or I end up having to clear the cache to get a proper refresh. Integrations often need extra work as well. Connecting to traditional SQL is straightforward, but native syncing with modern cloud data warehouses frequently requires custom scripting or middleware. Finally, the total cost is high. Between licensing and the need for specialized developers to maintain it, it’s difficult to justify for smaller teams. Review collected by and hosted on G2.com.

What I like best about IBM Planning Analytics is its fast, powerful TM1 engine paired with native Excel integration. It lets finance teams run real-time consolidations and unlimited what-if scenario planning on complex multidimensional models, cutting manual spreadsheet work dramatically. It provides a single trusted source of truth for budgeting, forecasting and planning, supports collaboration, and scales well for large enterprise datasets. Review collected by and hosted on G2.com.

What I dislike most about IBM Planning Analytics is its steep technical learning curve. Creating and updating TM1 models and rules demands specialist knowledge, meaning less technical business users often need support from developers to make ad-hoc changes. This can create minor delays and raise ongoing model maintenance overhead. Review collected by and hosted on G2.com.

It allows working with large volumes of data quickly, creating scenarios and simulations in real time, and reducing the reliance on scattered Excel sheets. Its integration with Excel facilitates adoption by users accustomed to this tool, maintaining a centralized and controlled data model. Additionally, it allows different departments to collaborate on a single source of information, improves traceability of changes, and reduces manual errors. It is especially powerful for performing multidimensional analyses and easily comparing actual data, budgets, and forecasts. Review collected by and hosted on G2.com.

Its main disadvantage is complexity: it requires technical knowledge, has a steep learning curve, and its implementation and maintenance can be costly compared to simpler solutions. Review collected by and hosted on G2.com.

Very powerful for very complicated planning calculations. Scalable to any extent. While it replaces excel it has the interface with excel which lets you work in very familiar environment. Integration with Cognos Analytics takes the distribution into a all together different level. The predictive analytics and sandboxing features are very good. While the tool appears expensive against its competitor, I have experienced that this toll gives a very good ROI and always wins against eh competitors in Total cost of ownership. IBM support has been very good for this tool. Review collected by and hosted on G2.com.

There are a few areas of improvement I can think of (But these are not something I dislike): Data Integration can be modernized. Turbo Integrator can be upgraded for a vey huge volume of data. Review collected by and hosted on G2.com.

The biggest advantage for me is how powerful it is for planning and forecasting. Once everything is set up, it handles large datasets really well and updates are fast. I also liked the Excel integration because it makes it easier to work with if you’re already used to spreadsheets. The TM1 engine runs in-memory, so calculations and updates happen quickly. Review collected by and hosted on G2.com.

The learning curve is definitely there. It’s not something you can just pick up and start using fully right away. The interface also feels a bit outdated in some places, and setting things up initially can take time. Getting the most out of it usually requires technical knowledge or dedicated support. Review collected by and hosted on G2.com.

I especially value IBM Planning Analytics for its flexible budgeting and forecasting models, strong scenario analysis, and smooth integration with existing data sources. Being able to build multidimensional models and quickly adjust assumptions makes the financial planning process more efficient and easier to manage. Its Excel integration is particularly helpful for finance teams that want familiar reporting tools while still benefiting from centralized planning. Review collected by and hosted on G2.com.

The biggest challenge is the learning curve for new users. Setting up dimensions, hierarchies, cubes, and business rules often requires specialized knowledge, and some administration and configuration tasks can feel more complicated than with other cloud-based planning tools. More intuitive workflows, a simpler model-development experience, and additional out-of-the-box templates would help make adoption easier for business users. Review collected by and hosted on G2.com.