Anaplan is a scenario planning and analysis platform designed to optimize decision-making in complex business environments so that enterprises can outpace their competition and the market. By building connections and collaboration across organizational silos, the Anaplan platform surfaces key insights.
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GoodData.AI
Score 8.8 out of 10
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GoodData is an analytics platform used by organizations to deliver real-time, governed insights, embedded into products, customized for users, and integrated into any data environment.
With its versions and native time features Anaplan is well suited for all activities around planning in time and scenarios. Tasks involving calculating across multiple dimensions make Anaplan shine - the easiness to build complex calculation and present results on customizable pages. With its access restrictions it's well suited also for working with sensitive data (employee and customers personal data).
I think it works nicely for shops that want the analytical power and are ok to host their own infrastructure for the data and etl. For smaller operations with limited budgets but still high demand for analytical features the math may not work out.
Anaplan removes the time consuming process of integrating the results of individual spreadsheets.
Anaplan facilitates the standardization of assumptions across all sub-processes
Anaplan provides full transparency of the calculations and source inputs
Anaplan allows us to automate certain planning processes that would have been impossible when relying on the computational capabilities of an individual computer.
The source datasets are often complex, semi-structured and un-linked to key entities. With GoodData, all of these datasets are unified to serve as a central semantic data model layer, building into a galaxy schema with dimensions, bridge, and facts, which then forms the backbone that powers the [...] data intelligence cloud. Building insights and dashboards become a much easier task once the underlying data model is designed. GoodData enforces certain best practices as a BI tool, which must be adhered to get the true value of the raw data. For e.g. the source FDA dashboard may just show inspection data but the Site Profile dashboard built on GoodData goes beyond the standard information and shows more insight into site risk scores and can be drilled into details. There is blog written on this topic: [...].
GoodData provides a rich collection of visualization options that help us create compelling story-telling via dashboards. Being well-prepared for FDA inspections is essential for maintaining product quality, regulatory compliance, and avoiding serious business setbacks. FDA inspections are critical events that can shape a company’s market access and reputation. The FDA itself offers the FDA Data Dashboard, but it doesn’t make every document available. There is a blog written on this topic: [...].
Medical devices and technologies do not stop evolving after they receive regulatory approval. Once a product hits the market, it faces real-world usage, compliance challenges, and an array of regulatory scrutiny. Managing these postmarket dynamics is critical to a product’s long-term success and patient safety. However, many companies struggle to keep track of relevant events across a product’s markets, from adverse event reports to changing regulations. Postmarket Intelligence developed on GoodData platform enables us to solve that problem. It empowers MedTech companies to efficiently monitor, assess, and act on postmarket data—saving time, improving decision-making, and ensuring compliance with industry standards. Anyone who is used to trying to get the data they need from the various FDA, and other regulatory agency websites, knows that collecting, cleaning, and structuring that data takes hours. And that’s before any analysis can get done. We enable customers to free up time to focus only on the high-value analysis and subsequent recommendations to leadership, rather than wrangling the data.
The data pipeline refresh that is provided by GoodData Platform is also quite useful from data engineering perspective. The Automated Data Distribution v2 or commonly called as ADD refresh follows a set pattern of identifying the analytical data model through output stage which helps abstract the complex table definition to simpler views that can help with quick rebuild at the data warehouse level while loading the data into GoodData's ADS storage layer. The import first way of loading data into GoodData's cloud storage, followed by querying for any aggregations or metrics on the GoodData analyzer, makes this simple and fast.
GoodData's latest product i.e. Cloud also offers several good features like Analytics as Code which helps software engineering teams follow a code-first approach to analytics, where building insights, dashboards or even datasets can be done in YAML templates or serviced by REST APIs. This is particularly forward thinking in the modern technology stack and evolving industry requirements. These provide seamless integration options to front-end and backend code, embedded analytics with multiple choices from HTML to React based workloads. At [...], we are currently exploring most of these features while planning for a future migration from Platform to Cloud.
Good Data is already have certain customizable options. However, having more flexibility in customizing reports and dashboards & control over the visual aspects would enhance the overall user experience.
To make Good Data even more powerful tool, improving the speed and responsiveness of the tool, especially during data-intensive tasks, would be a significantly helpful.
For new users, the interface can be made more user friendly which would promote easy navigation through features of tool.
Anaplan is a very strong multi-dimensional modeling tool that provides a calculation engine to empower a complex planning process. It is fairly easy to learn for those with experience in similar tools, or excel. It forces structure and auditability that spread sheets do not have, along with extensive security capabilities
Because gooddata really helps us in processing data to make reports or dashboards. So we are very satisfied when we use it. What we like is the flexible use of charts. We change at will the use of charts to display in reports or dashboards. Thank you Gooddata for helping companies like us who need flexibility in usage
Anaplan's usability is dependent on who is implementing the project and how clear business processes are at the beginning of the implementation. Complex business processes with many inputs and reviews will still be complicated in Anaplan; however, the UX is very flexible in how to help people through the process and there are also other items such as Workflow that can help people move through the system.
From a customer perspective it is incredibly usable. We have more users building their own reports that would normally need custom work from our support team. The back end can be daunting when trying to configure things like new data elements or push changes to a report to all existing customers.
There are very few outages. Maintenance is scheduled on two or three Saturdays per month, so as not to affect businesses. When there is an outage, users are kept informed of progress to restore the platform and typically this takes no more than an hour. Anaplan customer support is very responsive if we ever have questions about platform issues
Everything is calculated in memory in the cloud. It's nearly instantaneous updates when you make changes. The only time things get a little slow is when you have a massive model with very intricate calculations...but "slow" for Anaplan is not what I would call "slow" for something like Hyperion. We used to have Hyperion calcs that ran for 60 mins before you could use data. The equivalent would be 60 seconds in Anaplan.
Support quality has dropped since Thoma Bravo has taken over. I think some serious re-focus needs to happen here -- part of the beauty of being in the Anaplan community was how involved you felt in it before. Before I didn't dread sending a support ticket, now I am starting to.
Support team has been highly responsive and helpful from our first initial deployment to present day. They engage and work with us. know when to escalate for more challenging problems. They also follow up. Overall have had a very good experience with support
In my opinion, in-person training is always the best if you have the option to do so. This allows real-time interactions with the instructions, whereas the online training I took required me to write-down questions, email them, and wait for responses. This slows down the process, as you can imagine. That said, in-person training is an extra cost and it likely isn't needed for everyone. I would suggest selecting a small number of people to take in-person training and then having them act as mentors to the rest of your team. That way, as the rest of the team takes the online training, they have a resource to help them in real time.
Anaplan training materials are clear, simple, easy to understand and to follow. Visuals are excellent. The vendor is good at updating training materials in a timely manner and encouraging users and administrators to keep coming back to Academy site for refresher courses or new feature courses. I really like their interactive diagrams
One key insight from implementing Anaplan is that success comes from focusing on designing the process, not just building the model. Anaplan is extremely flexible—there are very few planning scenarios it cannot support—but that flexibility means the project needs strong governance, clear ownership of requirements, and a well-defined data model. When those foundations are in place, implementations are fast, iterations are easy, and users can quickly see value. In our projects, both Financial Planning and Integrated Business Planning models were adopted smoothly because we involved business users early, kept the model design intuitive, and leveraged Anaplan’s Excel-like syntax and user-friendly dashboards. The result was more efficient day-to-day work, reduced manual tasks, and increased collaboration across teams. In short: when you combine Anaplan’s flexibility with a structured implementation approach, adoption and value realization happen quickly.
Implementations are hard and we had limited technical resources. We relied too heavily on GD care team. When we found technical gaps, they weren't simple to overcome
Anaplan is more powerful than Pigment considering that it is an Enterprise class system and is able to manage bigger data sets. Anaplan allows for advanced scenario modeling and formula capabilities along with custom reporting functionalities. Anaplan has proven its capabilities and stability across various use cases and across bigger enterprises when compared to Pigment which is still in earlier phases of its development
GoodData comparing to other platform is very easy to use, customer support and on-boarding support. Set of features, speed of integration in our platform. Also great benefit for us was very competetive pricing.
We have managed to leverage Anaplan for financial planning and forecasting across the business. It is now used by almost every department, with more than 50 users (but I know of companies that have hundreds of users) and still the platform is quick and reliable. It is easy to make changes to divisions and departments or add users and apply different user settings - the core part of the model is not affected and end users can continue their work without any disruption
Anaplan's implementation led to a significant reduction in planning cycle errors and bugs, streamlining processes and improving overall accuracy in data inputs
Standardizing the planning process and enabling cross-functional collaboration through Anaplan enhanced our ability to adapt swiftly to changing business needs, resulting in improved agility in decision-making
The platform's capabilities, especially in Demand Planning and Supply Chain, positively impacted our ROI by optimizing resource allocation and solving complex business problems efficiently across multiple functions
