Planning Analytics Design Future Proof
April 15, 2025

Planning Analytics Design Future Proof

Gisel Bustamante | TrustRadius Reviewer
Score 9 out of 10
Vetted Review
Verified User

Overall Satisfaction with IBM Planning Analytics

From the use of this platform, it is evident that this has changed the way product design strategy is approached. Its workspace enables the optimization of the models with respect to desired design parameters and key performance indicators. It employs historical data along with forecasts, making the design decision sensitive.

Pros

  • It stands out by the multidimensional model, where one can perform modeling across several dimensions to get a holistic look into the impact.
  • Its planning analytics engine is based on analyzing the tendencies for client usage.
  • Integration of dynamic workflows makes it possible for various teams to work together immediately in efforts to decide on the strategies that have to be implemented.

Cons

  • Spending much time and effort to set the right dimensions and structures.
  • Despite the inclusion of many features, the interface provides too much information to the user.
  • Some components of the visualization can be not customized enough, and in some cases, they must be exported to other tools in order to be presented.
  • The application of this platform has served to achieve several business goals.
  • The system has been able to analyze and ensure that it has met the requirements of users during the period before the point of conversion.
  • Business development has improved by means of comprehensive and focused features of a product.
These are its ability to model certain scenarios and given designs across the different users and the different seasons. The alternative analysis tools allow modeling changes to be made in order to foresee the effect of such changes. Dynamic dimension modeling tracks evolving user preferences. ​ Learning how to use the software has been useful, in particular in the aspect of being able to develop sandboxed scenarios for testing new designs.
The availability of this platform has made it possible to have capabilities that could not be done by the former tools. Today, forecasting the needs in designs depending on the season takes only several hours. By applying design decisions in fashion designing, the amount of return on investment can be estimated with less variability.
Other options, namely Anaplan, Oracle ePm Cloud, and SAP Analytics Cloud, were also considered. Anaplan's interface lacked analytical depth. For product design metrics, flexibility was not as good in Oracle ePm Cloud. The final choice was moved by the fact that it was driven by analysis of business needs through multidimensional modelling of the platform.

Do you think IBM Planning Analytics delivers good value for the price?

Yes

Are you happy with IBM Planning Analytics's feature set?

Yes

Did IBM Planning Analytics live up to sales and marketing promises?

Yes

Did implementation of IBM Planning Analytics go as expected?

Yes

Would you buy IBM Planning Analytics again?

Yes

This platform is good at seasonal cyclic patterns to support the design decisions; it is also good at recognizing the changes of the UI facets in relationship to the conversion ratings among the demographics. It is less preferred for the UX metrics that demand second analysis. It is especially effective at planning in the medium to long term concerning the effect of seasons for the user and distribution of resources.

IBM Planning Analytics Feature Ratings

8.4
Long-term financial planning
8
Financial budgeting
9
Forecasting
8
Scenario modeling
9
Management reporting
8
8.3
Financial data consolidation
8
Journal entries and reports
9
Multi-currency management
8
Intercompany Eliminations
8
Minority Ownership
8
Local and consolidated reporting
9
Detailed Audit Trails
8
8.2
Financial Statement Reporting
8
Management Reporting
8
Excel-based Reporting
9
Automated board and financial reporting
8
XBRL support for regulatory filing
8
8.0
Personalized dashboards
8
Color-coded scorecards
8
KPIs
8
Cost and profitability analysis
9
Key Performance Indicator setting
8
Benchmarking with external data
7
7.3
Flat file integration
7
Excel data integration
8
Direct links to 3rd-party data sources
7
8.3
Pixel Perfect reports
8
Customizable dashboards
8
Report Formatting Templates
9
8.0
Drill-down analysis
8
Formatting capabilities
8
Integration with R or other statistical packages
8
Report sharing and collaboration
8
8.3
Publish to Web
8
Publish to PDF
8
Report Versioning
9
Report Delivery Scheduling
8
8.0
Pre-built visualization formats (heatmaps, scatter plots etc.)
8
Location Analytics / Geographic Visualization
8
Predictive Analytics
8
Pattern Recognition and Data Mining
8
8.4
Multi-User Support (named login)
9
Role-Based Security Model
8
Multiple Access Permission Levels (Create, Read, Delete)
8
Report-Level Access Control
8
Single Sign-On (SSO)
9
7.7
Responsive Design for Web Access
8
Mobile Application
8
Dashboard / Report / Visualization Interactivity on Mobile
7

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