In the age of data-driven decision-making, a dashboard is more than just a collection of charts—it is a critical communication tool. It’s the lens through which stakeholders interpret performance, identify opportunities, and execute strategy. When designing these powerful visual narratives within a tool like IBM Planning Analytics Workspace (PAW), a systematic approach is non-negotiable. 

This guide details a comprehensive framework and methodology for designing insightful and impactful dashboards, ensuring they don't just display data, but tell a compelling, actionable story. 

Part I: The Framework – Know Your Audience, Know Your Data 

The foundation of any successful dashboard is an intimate understanding of the end-user and their environment. This is the Know Your Customer/Stakeholder phase. 

1. Know Their Requirements

Before dragging a single chart onto the canvas, you must define the dashboard's purpose. Ask the critical questions: 

• Who is the primary user? (Executive, Analyst, Operational Manager) 
• What decisions will they make based on this dashboard? 
• What are their Key Performance Indicators (KPIs)? 
• What is the minimum information they need to act? 

A dashboard designed for a CFO tracking budget vs. actuals will be fundamentally different from one built for a Sales Manager tracking regional quota attainment. Requirements drive design. 

2. Background Study of Customer’s Previous Reports & Dashboards 

History offers valuable clues. Reviewing existing reports helps you understand: 

• What data conventions are they accustomed to? (e.g., green for good/red for bad, specific terminology) 

• What visualizations did they like or, more importantly, dislike? 

• What information was constantly missing or requested as an add-on? 

  
  

IBM PAw offers vast flexibility, but adhering to existing, trusted corporate visual standards promotes faster adoption and less user training. 

Part II: The Methodology – From Dashboard to Data Story 

The shift from a mere "dashboard" to a "data story" is crucial. This methodology ensures the design process is focused on narrative and impact. 

1. Dashboard's Background (Image, Colour Combination, Design)

The look and feel set the emotional tone and professionalism. 

• Colour Palette: Use colours strategically. Adhere to corporate branding, but reserve contrasting colours for highlighting key performance variances or calls-to-action. Overuse of bright, varied colours leads to visual noise. 

• Minimalism: PAw's flexibility allows for a clean, professional background. Avoid busy, distracting background images. The focus should be only on the data 

• Layout: Use a grid system. Place the most important KPIs (often summary numbers) in the top-left, following the natural reading flow (F-pattern or Z-pattern). 

2. It’s Not a Dashboard, It’s a Story (But in Reverse Mode) 

Traditional storytelling moves from beginning to end. Data storytelling moves from the end (the key outcome) to the beginning (the drivers). 

• The Outcome (Headline): What is the main message? (e.g., "Profit is down 15% this quarter.") This is your dashboard's headline, displayed clearly with the top KPIs. 

• The Narrative (Supporting Data): Why did this happen? (e.g., "Revenue flatlined, but operating expenses increased.") This is supported by trend charts and key comparisons. 

• The Detail (Actionable Insight): Where exactly is the issue? (e.g., "High-Cost Region X saw a 30% jump in logistics.") This is where drill-down and filter capabilities come into play. 

Part III: Dashboard Visualisation (The Three Pillars) 

Great visualisation hinges on simplicity, relevance, and action. 

1. Style Design – Keep a Simple & Known Design for the Client

Familiarity breeds acceptance. Use: 

• Standard Layouts: Group related charts logically. 

• Intuitive Navigation: If using multiple tabs in PAw, label them clearly. 

• Consistent Formatting: Ensure axis labels, legends, and number formats (e.g., $M, %) are identical across all visualisations. A simple style reduces cognitive load.

2. Graphic Design – Choose Charts that Best Tell the Story 

The wrong chart can obscure the truth. 

3. Interactivity – Filters & Drill Down/Up Can Be Built into Each Dashboard 

IBM PAw excels at dynamic analysis. Enable users to explore the data for themselves: 

• Global Filters: Use a common set of filters (e.g., Year, Region, Product) that update all relevant charts simultaneously. 

• Drill-Down/Up: Allow users to seamlessly move from a summary view (e.g., Total Revenue) to a detailed view (e.g., Revenue by Sales Rep). This supports the "Story in Reverse" methodology, moving from outcome to root cause. 

• Contextual Help: Add brief descriptions to complex charts or KPIs to guide the user. 

Part IV: Design & Execution (The Acquisition Funnel)

Treat your dashboard like a product that needs to attract, engage, and deliver value.  

Step 1 – Acquisition: What are the key facts that make people interested in? 

The first two seconds are critical. The user must instantly understand: "Is this relevant to me right now?" This is achieved by displaying the most impactful KPIs clearly on the initial screen. 

Step 2 – Behaviour: Is your dashboard strong enough to make people interested? 

Engagement is measured by interaction. If users are actively clicking filters, drilling down, and switching between tabs, the dashboard is working. If they simply print the screen and leave, it's a static report, not an analytic tool. 

Step 3 – Outcome: What is the impact on the defined conversation? 

The ultimate goal is impact. A good dashboard changes the conversation from: "What happened?" to "What should we do next?" Measure the dashboard's success by the action it inspires. 

Part V: Execution – The Continuous Improvement Loop 

Dashboard design is not a one-time project; it is an iterative process of refinement. 

1. Create – Create Your Dashboard Design 

Build the initial version in IBM Planning Analytics Workspace based on the approved wireframes and data sources. Leverage PAw's powerful cube viewer and visualization capabilities. 

2. Report – Showcase It to Other People for Opinion 

Present the working draft to the target audience and a few critical users. This is not a final sign-off; it's a crucial feedback session. Pay close attention to confusion points. 

3. Analyse – Analyse It for Better Outcome 

Did the users focus on the intended KPIs? Were the drill-downs intuitive? Use their interaction patterns to analyze the dashboard's effectiveness. 

4. Test – Learn & Evolve (Apply the Changes) 

Implement the feedback. The best dashboards are often the third or fourth iteration. Don't be afraid to scrap a chart that users consistently misunderstand or ignore. 

5. Improve – Improve Your Dashboard 

Launch the final version, but continue to solicit feedback periodically. As business needs and data change, your IBM PAw dashboard must evolve to remain the single source of truth and insight for the organisation. 

By following this rigorous framework and methodology, you transform the act of building a dashboard in IBM Planning Analytics Workspace into a powerful exercise in Visual Analysis—delivering not just data, but tangible, impactful business intelligence.