IBM Planning Analytics for IBM Cloud Pak for Data

What do you like best about the product?

IBM Planning Analytics is a very strong and capable enterprise planning and analysis tool, especially well-suited for large organizations with complex, multidimensional data and heavy calculation needs. It's TM1 database is the best in category

What do you dislike about the product?

High cost and set up efforts. UI tools are not enough to build attractive dashboards.

What problems is the product solving and how is that benefiting you?

This has been a good replacement for our fragmented, local spreadsheet-based planning. I was able to build dashboards to support forecasting and budgeting, which made the overall process clearer and easier to manage

What do you like best about the product?

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.

What do you dislike about the product?

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.

What problems is the product solving and how is that benefiting you?

We implement it for clients who've outgrown spreadsheet-based budgeting and forecasting. The usual problem is version control: a dozen workbooks emailed around, nobody sure which numbers are current. Moving that into Planning Analytics gives them one source of truth and frees up the time they used to spend consolidating. We have multiple clients that use IBM Planning Analytics, but one that comes to mind is using it for budgeting and forecasting across 7 divisions. We working directly with the CFOs of each division and with their central financial technology team to ensure that each model is independent but still ties out to an overall, company-wide model. The ability of IBM PA to allow us to do this is one of its biggest benefits. It allows full customization and limitless scale.

What do you like best about the product?

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.

What do you dislike about the product?

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.

What problems is the product solving and how is that benefiting you?

Capacity and workload planning used to live in spreadsheets that were hard to keep up to date and easy to get out of sync. Evaluating different scenarios meant a lot of copying, tweaking, and recalculating by hand. Planning Analytics has made it much faster to run realistic cases and keep our operational plan aligned, so we’re better prepared when support volume shifts and we spend less time dealing with file versions and manual updates.

What do you like best about the product?

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.

What do you dislike about the product?

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.

What problems is the product solving and how is that benefiting you?

Very general use case is collaboration. I have worked with a team of 10+ analysts who were creating excels going beyond GBs size and then merging the data and keeping complex calculations has eventually created a mess. Doing the same via Planning analytics let them focus on business rules and see the results live and in parallel. What-if analysis helps the users to forecast and take better decisions.

What do you like best about the product?

It is multidimensional and make it similar to excel pivot table

What do you dislike about the product?

Less mathematical functions like in excel like LINEST, or Regression

What problems is the product solving and how is that benefiting you?

Solving banking data that stores millions of account in less than 1 hour

What do you like best about the product?

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.

What do you dislike about the product?

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.

What problems is the product solving and how is that benefiting you?

IBM Planning Analytics helps centralize budgeting, forecasting, and financial planning that might otherwise depend on spreadsheets and disconnected data sources. By bringing planning into one place, it improves visibility into financial performance, enables faster scenario analysis, and supports more consistent planning across teams. As a result, it reduces manual effort, strengthens collaboration between finance and business groups, and helps drive better-informed decisions.

What do you like best about the product?

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.

What do you dislike about the product?

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.

What problems is the product solving and how is that benefiting you?

IBM Planning Analytics handles budgeting, forecasting, HR planning, and complex financial tasks without compromising on sophistication, unlike other tools. It's ideal for the CFO's office, modeling intricate requirements with ease, and using "Spread and Hold" streamlines adjustments, showing changes instantly.

What do you like best about the product?

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.

What do you dislike about the product?

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.

What problems is the product solving and how is that benefiting you?

Shrunk month-end close: Mawgif cut its monthly reporting cycle from 20 days to 4 days, and converted trial balances to P&L in 10 seconds instead of two days. Fast-tracked annual budgeting: Al Rabie reduced its annual budget process from 60 days to 15 days by automating data flow directly into the P&L. Handled massive data volume: Mawgif tracked 200,000+ daily parking transactions with hourly drill-downs, improving operations by 10% and catching revenue leaks. Delivered SKU-level profitability: Al Rabie gained clear visibility into unit margins and production costs across products and channels, helping guide pricing decisions. Enabled rolling forecasts: Replaced rigid yearly budgets with dynamic 12-to-24-month rolling plans, helping leadership make more forward-looking decisions.

What do you like best about the product?

Outstanding performances, flexibility on calculation

What do you dislike about the product?

the possibility to upload external documents on PAW

What problems is the product solving and how is that benefiting you?

faster budgeting and closing process, possibility to perform what-if scenarios

What do you like best about the product?

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

What do you dislike about the product?

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.

What problems is the product solving and how is that benefiting you?

Many companies wish to upload their sales budgets using a template and subsequently review the data in a more detailed cube. The model utilizes drag-and-drop functionality for file uploads, streamlining data entry via the interface; it prevents cell errors by validating information before insertion and allows users to view what is being uploaded, providing full control over the process, time saved and cost reduction.