Building and Configuring Planning Views for Data Entry and Analysis

Explanation

Once the underlying planning area is modeled with the right master data, time profiles, and key figures, the intermediate-level work in the SAP IBP Excel Add-In is designing planning views that make planners productive without overwhelming them with unnecessary data. A planning view is created and maintained either in the web-based configuration UI or directly from within the Excel add-in itself using the 'planning view' definition dialog, where a consultant selects the planning area, chooses relevant key figures, sets default navigational attribute levels (for example, showing product family instead of individual SKU by default), and defines a default filter (such as a specific region or planning segment) so planners are not forced to filter manually every session. A critical configuration decision is choosing which key figures are input-enabled versus calculated/read-only. Input key figures (like planner override or manual adjustment) allow direct typing in the grid; calculated key figures (like final forecast, often computed via a formula referencing override and statistical forecast) update automatically after a save and recalculation cycle. Consultants must also decide the level of disaggregation/aggregation behavior: when a planner enters a value at an aggregated level, the system needs rules (typically proportional spread based on a reference key figure) to disaggregate that number down to the lowest planning level, and misconfigured disaggregation is one of the most common sources of planner distrust in the numbers. Beyond the grid, the add-in supports linked charts that visualize the same selection as a line or bar chart, updated dynamically as filters change, which is valuable for reviewing trends during S&OP meetings. Alerts can be configured against key figures (for example, forecast error exceeding a threshold, or supply shortages), and these surface in an alert overview pane inside Excel, letting planners jump directly to the affected data slice. What-if / simulation scenarios are another important intermediate capability: planners can create a private simulation version of the plan, make changes, evaluate impact through the same grids and charts, and then either discard the simulation or promote it into the actual planning version if approved. This is particularly used in supply and inventory planning where a planner tests the impact of a supplier delay or a demand spike before committing to the live plan. From a runtime perspective, every grid refresh, filter change, or save triggers a request-response cycle with the IBP back end; poorly designed planning views (too many key figures, too low aggregation level, too many navigational attributes) can lead to slow response times, especially for large planning areas with millions of combinations. Consultants need to balance planner usability against performance by scoping default views tightly and encouraging drill-down rather than loading everything at once. Troubleshooting slow or failing views typically starts by checking the filter scope, the number of open key figures, and whether the planner is on a current add-in version, before escalating to planning area-level performance issues.

Code example

# Excel Add-In planning view definition (conceptual, not executable code)# This represents parameters typically set via the add-in's# 'Manage Planning Views' dialog, not a scripting API. Planning View: DEMAND_REVIEW_WEEKLY  Planning Area: DEMAND_PLANNING_AREA  Time Profile: WEEKLY (rolling 26 weeks)  Navigational Attributes:    - Product Family (default aggregation level)    - Region (default filter = 'EMEA')  Key Figures:    - STATISTICAL_FORECAST   (read-only, calculated upstream)    - PLANNER_OVERRIDE       (input-enabled)    - FINAL_FORECAST         (calculated: override if entered, else statistical forecast)    - FORECAST_ERROR_PCT     (calculated, used for alert threshold)  Alert:    - Name: High Forecast Error    - Condition: FORECAST_ERROR_PCT > 20%    - Scope: same filter as view (Region = EMEA)  Chart:    - Type: Line    - Series: STATISTICAL_FORECAST, FINAL_FORECAST    - X-axis: Week

Real project scenario

During an S&OP implementation, the demand planning lead wants a single weekly review workbook that shows statistical forecast versus planner override at product family level for EMEA, with a chart for trend discussion and an alert when forecast error exceeds 20%. The IBP consultant builds this as a governed planning view, tests disaggregation behavior by entering an override at product family level and verifying it spreads correctly to SKU level using historical volume as the reference key figure, then distributes the workbook template to all EMEA planners ahead of the first live S&OP cycle.

Common mistakes

• Exposing too many key figures and navigational attributes in a default view, causing slow load times and planner confusion. • Leaving disaggregation logic unconfigured or using an inappropriate reference key figure, causing unrealistic SKU-level splits. • Mixing input-enabled and calculated key figures without clearly labeling them, leading planners to try editing read-only cells. • Not testing alert thresholds with realistic data before go-live, resulting in alert fatigue or missed real issues. • Building what-if simulations without a clear process for promoting or discarding them, leaving orphaned simulation versions in the system.

Best practices

• Scope default planning views tightly and rely on drill-down rather than loading maximum detail by default. • Clearly separate and label input-enabled key figures from calculated ones in the view design. • Validate disaggregation behavior with real data before rolling out a planning view broadly. • Set alert thresholds based on historical data analysis rather than arbitrary numbers to avoid alert fatigue. • Define a clear governance process for what-if simulation versions, including naming conventions and expiry/cleanup rules.

Interview angle

Candidates should be able to explain the trade-off between planning view usability and system performance, describe how disaggregation works conceptually, and articulate the difference between input and calculated key figures. Scenario questions often ask how you would design a view for a specific planning process like weekly demand review or S&OP consensus.