IBM Planning Analytics, powered by IBM TM1®, is an integrated planning solution designed to promote collaboration across the organization and help keep pace with the speed of modern business. With its calculation engine, this enterprise performance management solution is designed to help users move beyond the limits of spreadsheets, automating the planning process to drive faster, more accurate results. Use it to unify data sources into one single repository, enabling users to build…
$825
per month 5 users
SAP Analytics Cloud
Score 8.1 out of 10
N/A
The SAP Analytics Cloud solution brings together analytics and planning with integration to SAP applications and access to heterogenous data sources. As the analytics and planning solution within SAP Business Technology Platform, SAP Analytics Cloud supports trusted insights and integrated planning processes enterprise-wide to help make decisions without doubt.
$36
per month per user
SAP Predictive Analytics
Score 7.0 out of 10
N/A
SAP Predictive Analytics is, as the name would suggest, a statistical analysis and data mining platform that can be deployed with SAP HANA.
N/A
Pricing
IBM Planning Analytics
SAP Analytics Cloud
SAP Predictive Analytics
Editions & Modules
Essentials
$825
per month 5 users
Standard
$1,650
per month 10 users
SAP Analytics Cloud for Business Intelligence
$36.00
per month per user
SAP Analytics Cloud for Planning
Price upon request
per month per user
No answers on this topic
Offerings
Pricing Offerings
IBM Planning Analytics
SAP Analytics Cloud
SAP Predictive Analytics
Free Trial
Yes
Yes
No
Free/Freemium Version
Yes
No
No
Premium Consulting/Integration Services
Yes
No
No
Entry-level Setup Fee
Optional
No setup fee
No setup fee
Additional Details
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A 30-day trial with SAP Analytics Cloud is available, supporting analytics enterprise-wide. A trial can be extended up to 90 days on request.
I am personally trying to explore the features of SAP Analytics Cloud in order to find if it's possible to integrate other sources of data and api based integrations, but I'm still on it while using the IBM planning analytics for my project currently. But looking at the intial …
Prior to making the decision to go with IBM Planning Analytics, we had considered such options as Anaplan, Oracle Hyperion, and SAP Analytics Cloud. Despite the collaborative solutions offered by Anaplan and the good connection with other systems by SAP, the superb set of tool …
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 …
IBM allows to build flexible models from the scratch. IBM Planning Analytics with Watson does not include non-planning features in one package, so you don't pay for something you may not need.
IBM Planning Analytics was by far the most robust tool we evaluated among several top competitors. It stood out for its place in the industry to provide detailed, integrated, and aggregate integration for data governance. I was impressed with the approach from the sales team to …
In the past, I did a bit of exploring of tools such as Tableau and Microsoft Power BI. However, these platforms have very good visualization capabilities, and SAP Analytics Cloud's integration with other SAP products is tightly woven and gives a very seamless experience that …
Both Planning Analytics with Watson and Analytics Cloud are robust CPM tools offered by trustworthy vendors. However, unlike SAP Analytics Cloud, Planning Analytics with Watson [does] not allocate BI and CPM tools in a unified platform, it requires third-party applications …
Very powerful modeling capabilities. It has a really good OLAP engine memory. Strong scenario planning for what if analysis. Flexibility of integration with ERPs or WM systems for both cloud and on premises. Centralized planning and alignment of governance is also a plus. Having one single system for many different functions.
>> Using SAC predictive analytics capabilities for inventory management in a Production line setup has helped generate Purchase Requisitions and Purchase Orders for raw or semi-finished goods without much head-banging into Demand management rules. It does it beautifully with seamless integration with HANA core MM and PP modules, along with BI integration. It has resulted in 30% greater warehouse storage capacity, thereby saving revenue from piled-up inventory and associated manpower costs. >> SAC sometimes shows latency in working out a large data set, thus giving a poor user experience compared to its competition. Also, it may occasionally show misinterpretations when embedding data from 3rd-party systems into the HANA core dataset.
It's a great tool to merge actual data analysis (which Lumira doesn't do that well) with visualization (which Lumira does well) - so it can be seen as Lumira for data analysts. However, a lot of the 'predictive' side is hidden/black box which can be frustrating for those analysts, so you could argue it is too complex for casual users, but too 'black box' for analysts.
It makes it easier yo analyse order and related records easily.
We can easily maintain and track the performance of employees in organisation.
Can easily track various aspects for the growth of an organisation thus allowing real time analysis and tracking of organisation's growth and performance.
It doesn't require you to have a Ph.D. to build models!
You can use it to address a very large and wide dataset without worrying about sampling.
Automation is in the product DNA. You can prepare your data, ingest it into the "Kernel", then get insights about what was found, decide to publish it and schedule scoring tasks or model refresh in the same product.
SAC supports various data sources, but improvements in the ease of connecting to and integrating with certain data repositories, especially non-SAP databases, would enhance the platform's versatility and integration capabilities.
An offline mode for SAC could be valuable for users who need to access and analyze data without an internet connection. Additionally, optimizing performance for large datasets and complex visualizations would contribute to a smoother user experience.
Since IBM Cognos Express is suitable only for medium data warehouse environment, we are not sure if this tool solves the long term need as the business keeps growing rapidly. So its a 50/50 ratio to renew Express license. But having said that, the components of IBM Cognos Express are also available in other Cognos BI suites like Cognos 10.x version. So we will probably upgrade our environment to IBM Cognos 10.x which comes with more new features.
We are planning to review the licensing as we have issues with SAC dealing with huge datasets. Analytics area is good for import models but when we have live connections in place that's when we have issue with SAC dealing with huge datasets in live be it BW or be it HANA models in the backend.
IBM Planning Analytics is generally good in terms of functionalities. It can be used reduce time for budget planning, resource planning, demand forecasting, etc. The performance of IBM Planning Analytics is acceptable, but user interface can be improved. It would be good to see new features that allow users to customise the dashboard.
On a scale of 1 to 10, I would rate 8 SAP Analytics Cloud's overall usability as a 7. SAC has a clean, modern user interface with drag-and-drop features. It is an integrated platform that combines reporting, planning, and predictive analytics in one tool. It has Real-time connectivity with SAP data sources like S/4HANA.
Self-service analytics capabilities allow non-technical users to build simple dashboards.
I would rate SAP Analytics Cloud an 8 out of 10 for scalability. It offers a flexible, cloud-based architecture that supports expansion across departments and geographies. The platform adapts well to growing data volumes and user needs, making it a strong choice for organizations looking to scale analytics capabilities efficiently.
I would rate SAP Analytics Cloud’s performance an 8 out of 10. Pages generally load quickly, and reports run within a reasonable time frame, even with complex datasets. Integration with other systems is smooth and doesn’t noticeably affect performance. Overall, it’s a responsive and efficient tool for business analytics. But
IBM support has been very quick to respond and handle the very few issues we've had. We've had a third-party who partners with IBM to be our consulting team which has helped greatly reduce the need for us to contact IBM directly. I highly recommend researching and selecting a well-respected partner to help with an implementation as well as ongoing support as needed.
Since the implementation stage, the support team has been very helpful and assisting. Even in the later stages, the tech team had quite a rapid response. In general, SAP has provided us with great customer support, let it be for a specific product of SAP or for integration of different modules.
The documentation provides an explanation about what features are available but not necessarily what's happening behind the scenes. On the other side, the "community" has grown since the acquisition and most questions are properly addressed by SAP folks. Since the "product maintenance" mode announcement was made, there wasn't much new content published except on the Smart Predict side (which is built by the SAP Predictive Analytics team)
In hindsight, it would have been easier to have someone there in person. Questions were answered, but with 11 participants, it got a bit chaotic online
SAC is a simple solution ad it works fine when connecting it to other SAP tools. On the other hand, connecting it to third party solutions brings difficulties when there's no previous design and the objetives are not clear. It is really important to integrate Business users from the start to provide with valuable business insights
As it is related to MS Excel, IBM Planning Analytics is a much more robust and complete solution for the CFO or COO in mind. Oracle Hyperion stacks up nicely against IBM Planning Analytics. However, IBM's investment in AI allows Planning Analytics users more options and speed.
SAP Analytics Cloud and Power BI are both tools that help businesses understand their data, but they have some differences. SAC, made by SAP, works well if your company already uses other SAP products. It's in the cloud, easy to use, and has features for analyzing data, getting insights, and planning for the future. Power BI, made by Microsoft, can be used in the cloud or on your own computers. It fits well with Microsoft tools, is easy to use, and can do advanced data analysis. SAC has built-in planning tools, while Power BI needs extra tools for detailed planning
We have typically used Spotfire for data analysis but decided to move to SAP Business Objects due to its innate connection with SAP. I found Lumira to be good for visualizations but it is not meant for data analysis. Therefore, we have introduced Predictive Analytics to see if it can fill that gap. So far, it's been far less intuitive than Spotfire to get started, and as far as I am aware so far, it does not bring many additional capabilities. I do, however, like that it utilizes the Lumira look/feel and integrates very well.
Is good for use across multiple locations. It allows users to access data and reports from anywhere, regardless of their location. Can consolidate data from various sources, including different SAP systems and external sources, which facilitates cross-location analysis. SAC enables access to data and models from SAP Datasphere to create new stories. Detailed permissions can be defined for cross-departmental use.
Many manual data manipulations and exports in Excel have been replaced by the tool, providing management with improved insight into the amount of time spent at each stage of an invoice's lifetime, allowing bottlenecks to be discovered.
We now have more insight into the data, and people with little technical experience can easily build stories.