Highly required at Lululemon: They have 15 different test models corresponding to 15 different situations and configuration of the model. Fixing 1 bug and manually syncing to 15 models is unsustainable. Please consider this as a high priority. Thank you
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We have used Guillaume's dashboard planning methodology recently with two of my CS customers across 6 different use cases. It seems counterintuitive to many at first but always works like a champion. One of the major challenges (that at the same time represents a transformational opportunity) is user's attachment to their current process. A typical mentality when it comes to analysis is "Ok. This is my data. What can I make out of it?". Starting with UI and Dashboard design turns it all around and makes the user think of the ideal state aka "What do I want to analyze to be effective in my role?" and then subsequently think of how to get there. The ability to take this approach is one of the biggest strengths of Anaplan due to its flexibility. At the same time, starting with UI enables creative thinking which always is a great start for a positive experience.
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If you’re familiar with Anaplan, you’ve probably heard the buzz about having a data hub and wondered why it’s considered a “best practice” within the Anaplan community. Wonder no more. Below, I will share four reasons why you should spend the time to build a data hub before Anaplan takes your company by storm.
1. Maintain consistent hierarchies
Hierarchies are a common list structure built by Anaplan and come in a variety of options depending on use case, e.g., product hierarchy, cost center hierarchy, and management hierarchy, just to name a few. These hierarchies should be consistent across the business whether you’re doing demand planning or financial planning. With a data hub, your organization has a higher likelihood of keeping hierarchies consistent over time since everyone is pulling the same structure from one source of truth: the data hub.
2. Data Optimization
As you expand the use of Anaplan across multiple departments, you may find that you only need a portion of a list, rather than the entire list. For instance, you may want the full list of employees for workforce planning purposes, but only a portion of the employees for incentive compensation calculations. With a data hub, you can distribute only the pertinent information. You can filter the list of employees to build the employee hierarchy in the incentive compensation model while having the full list of employees in the workforce planning model. Keep them both in sync using the data hub as your source of truth.
3. Separate duties by roles and responsibilities
An increasing number of customers have asked about roles and responsibilities with Anaplan as they expand internally. In Anaplan, we recommend each model have a separate owner. For example, an IT owner for the data hub, an operations owner for the demand planning model, and a finance owner for the financial planning model. The three owners combined would be your Center of Excellence, but each has their separate roles and responsibilities for development and maintenance in the individual models.
4. Accelerate future builds
One of the main reasons many companies choose Anaplan is for the platform’s flexibility. Its use can easily and quickly expand across an entire organization. Development rarely stops after the first implementation. Model builders are enabled and excited to continue to bring Anaplan into other areas of the business. If you start by building the data hub as your source of truth for data and metadata, you can accelerate the development of future models since you already have defined the foundation of the model, the lists, and dimensions.
As you begin to implement, build, and roll out Anaplan, starting with a data hub is a key consideration. In addition to this, there are many other fundamental Anaplan best practices to consider when rolling out a new technology and driving internal adoption.
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These dashboards are absolutely critical to good usability of a model. Dashboards are the first contact between the end users and a model.
What SHOULD NOT be done in a landing dashboard:
Display detailed instructions on how to use the model. See "Instruction Dashboard" instead.
Use it for global navigation, built using text boxes and navigation buttons.
It will create maintenance challenges if different roles have different navigation paths.
It's not helpful once users know where to go.
What SHOULD be done in a landing dashboard:
Display KPIs with a chart that highlights where they stand on these KPIs, and highlight gaps/errors/exceptions/warnings.
A summary/aggregated view of data on a grid to support the chart. The chart should be the primary element.
Short instructions on the KPIs.
A link to an instruction-based dashboard that includes guidance and video links.
A generic instruction to indicate that the user should open the left-side sliding panel to discover the different navigation paths.
Users who perform data entry need access to the same KPIs as execs are seeing.
Landing dashboard example 1:
Displays the main KPI, which the planning model allows the organization to plan.
Landing dashboard example 2:
Provides a view on how the process is progressing against the calendar.
Landing dashboard example 3:
Created for executives who need to focus on escalation. Provides context and a call to action (could be a planning dashboard, too).
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Deal with monthly dashboards
Many FP&A dashboards will need to display all 12 months in the current year, as well as Quarter, Half, and Total Year totals. Doing this is likely to create a very large grid, especially if more than one dimension is nested on the rows.
The grid displayed here is what may be requested when Anaplan is replacing a spreadsheet-based solution. The requirement being "At minimum, do what we could do in the spreadsheets".
Avoid the trap of rebuilding this in Anaplan. Usually, this simply creates an extra requirement to export this into Excel ® , have users work offline, and then import the data back into Anaplan, which kills the value that Anaplan can bring.
Instead, build the dashboard as indicated below:
Have end users view the aggregated values on the Cost center (the first nested dimensions) that will provide an overview on where most OPEX are spent
Have end users highlight a cost center, and enter its detailed sub-accounts
Visualize the monthly trend using a line chart for the selected sub-account
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