Item: SAP Analytics Cloud
Rating: 5
Author: Raymond Savage

Use Cases and Deployment Scope

It is a challenging product to use. First it is complicated and not intuitive. If you don't have a model in mind the tool is not going to work well no matter how well intentioned you are. That may not be SAP's fault but an important prerequisite that the marketing team ignores because they will not sell the product if that is acknowledged up front. From a business perspective, SAP is to blame even if the model is weak.
It is also very expensive, twice as much a Microsoft's visualization products. So comparing the two just for visualization, Microsoft wins hands down for cost and intuitive use. That is not a winning combination. We had to back away from the product because of thee challenges that SAP was not in a position to help us will.

Pros and Cons

Connection to SAP, therefore a much more secure and SOX compliant tool
Master data is aligned and less data cleansing is required.
Hierarchies come from the HANA system and are intuitive and prebuilt

Too expensive. Twice the cost of Microsoft
Not able to one click into a report. Requires too much set up and replacement when updated.
A more intuitive interface, there were a lot of gotchas when building a model from scratch.

Return on Investment

Wasted time trying to make our model fit the tool
Are to change on the fly - both positive (SOX Compliant) and negative to long and hard and change management to executives
Big cost when trying to roll out to a broader audience, therefore not cost effective with the expensive monthly subscription per user. Lots of time rationing licenses.

Usability

It is the start, it is not very mature. Power BI is more mature for visualizations. Really only good for SAP data in its current form since bringing in external data sources is painful.

Key Differentiators

Scalability
Integration with Other Systems

We wanted to do better planning but our model never worked in SAC. It took longer, was less intuitive for the user and never delivered on the promise of predicative analytics. We may have been able to make it work but after 6 months of trying, we didn't feel the effort to keep going was going to pay off or be worth it in the end.