IBM Planning Analytics and Domo are competing in business intelligence and analytics markets. While IBM Planning Analytics is renowned for its financial planning prowess, Domo is favored for its extensive data visualization and integration features, making Domo potentially more appealing for data-driven organizations.
Features: IBM Planning Analytics provides robust financial planning, budgeting, forecasting capabilities, integration with Excel, and fast in-memory processing. Domo offers exceptional data visualization, real-time integration, dashboard customization, and numerous pre-built data connectors.
Room for Improvement: IBM Planning Analytics could enhance real-time data integration, simplify its programming language, and expand mobile capabilities. Domo might benefit from improved data processing speeds, advanced analytics beyond standard visualizations, and more intuitive interface navigation.
Ease of Deployment and Customer Service: IBM Planning Analytics typically involves complex deployment processes due to its extensive features, with excellent customer service to support implementation. Domo's cloud-based deployment is straightforward and rapid, backed by agile, on-demand customer service ideal for fast-paced environments.
Pricing and ROI: IBM Planning Analytics generally offers lower initial setup costs, appealing to financially cautious users, but ROI depends on leveraging its comprehensive planning features. Domo, with higher setup costs, provides significant ROI with its extensive data visualization and management capabilities, proving valuable for data-centric decision making.
They were quite professional and in around three to five working days, they had identified where they suspected there was an issue and I was able to fix it.
While they eventually provide the correct answers, their support for smaller customers could be improved.
The main benefits of using Domo are that the support is good, and comparing it with other BI tools, it has specific specialties.
We have a multi-level support system, with the initial level handled by the company we bought the license from and subsequent support from IBM.
Instead, we rely on third-party partners recognized by IBM, who provide cost-effective support.
The fact that you're able to easily identify the pipelines or flows that have errors, and it notifies you when you're building a pipeline where you can run previews and tell where to fix issues, is helpful.
Sigma, which is written for Snowflake, scales more easily than Domo.
The response time is longer than desired, but sometimes they provide the correct solution while other times they don't provide the needed scenarios.
Scalability is quite hard to implement in TM1, largely since the on-premise installation chosen back in 2014.
Scalability is straightforward but it is pricey since it's a SaaS model priced per user.
In recent years, I haven't had such cases. It's quite stable and I don't have any reservations on its stability.
The setup of Domo is challenging as the cache and serialization part still causes errors; since it's fully cloud-based, they need to improve the connectivity part.
This stability is really important as we use it for budget calculation, which is time-consuming.
End users require a license to run their own reports and dashboards, which are fairly expensive.
Some technical aspects such as Beast Mode calculation could be improved in Domo, as it would provide more clarity and help in giving insights to clients or customer business team requirements.
One of the areas where we've had frustrations with Domo is the aesthetics. The aesthetics are quite limited compared to other BI tools such as Tableau and Power BI.
The abundance of features results in complexity, requiring strict guidelines for developers to ensure simplistic approaches are adhered to.
IBM's visualization needs significant improvement.
Domo's pricing is high compared to other BI tools, and it is costly.
Domo is expensive compared to other solutions.
TM1 is quite expensive, and I'd rate the pricing as an eight out of ten.
While IBM's solutions were costly before, the introduction of SaaS models has reduced prices significantly.
App Studio is valuable because it allows all the customization we needed; we can decode it, with the view and grid which are all I need, drill-downs, and everything can be done the way I need it.
I have been using it for four years and have been able to extract the information I need from it.
The most valuable feature of Domo is the fact that you can connect multiple inputs and you don't have to have a data warehouse.
Its stability helps controllers win time in their planning processes.
It also integrates machine learning and AI engines, enabling us to use algorithms for inventory forecasting which optimizes our inventory and replenishment rates.
Product | Market Share (%) |
---|---|
IBM Planning Analytics | 6.4% |
Domo | 1.8% |
Other | 91.8% |
Company Size | Count |
---|---|
Small Business | 13 |
Midsize Enterprise | 11 |
Large Enterprise | 17 |
Company Size | Count |
---|---|
Small Business | 16 |
Midsize Enterprise | 4 |
Large Enterprise | 7 |
Domo is a cloud-based, mobile-first BI platform that helps companies drive more value from their data by helping organizations better integrate, interpret and use data to drive timely decision making and action across the business. The Domo platform enhances existing data warehouse and BI tools and allows users to build custom apps, automate data pipelines, and make data science accessible for anyone through automated insights that can be shared with internal or external stakeholders.
Find more information on The Business Cloud Here.
IBM Planning Analytics is an integrated planning solution that uses AI to automate planning, budgeting, and forecasting and drive more intelligent workflows.
Built on TM1, IBM’s powerful calculation engine, this enterprise performance management tool allows you to transcend the limits of manual planning and become the Analytics Hero your business needs. Quickly and easily drive faster, more accurate plans for FP&A, sales, supply chain and beyond.
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