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Week 5: Business Reporting, Visual Analytics & Dashboards (Performance…

- - - - Help manage business performance through metrics (SLAs for external, KPIs for internal)
      - Can be used as Six Sigma &/ Total Quality Management
    - - Graphical presentation of several performance indicators in a single page
    - - Include financial, customer, business process and learning & growth indicators
- - - - visual memory buffer
      - Preattentive processing (preconscious)
        
        Things that stand out
        
        Grouping of objects
    - - Limited storage capacity
        
        Information the belongs together should not be fragmented into multiple dashboards
        
        Scrolling should not be regulated
      - Stores 3-9 chunks of visual information at a time
      - A "chunk": pattern formed by 1 or more lines in a line graph
    - - Permanent
  - - - Purpose: monitor key performance metrics
      - Dashboards for Strategic Purposes (Monitoring)
        
        Focus on high-level measures of performance
        
        Forecasts
        
        Indicator of performance
        
        Contextual information
        
        Don't require real-time data, static snapshots will do
    - - Purpose: explore information from multiple dimensions
      - Dashboards for Analytical Purposes (Analysis)
        
        Should support interactions with the data
        
        Show patterns for further exploration (find out causes)
        
        More sophisticated display media
    - - Purpose: examine details before taking action
      - Dashboards for Operational Purposes (Managing)
        
        Real-time information is needed for constantly changing environment
        
        Must grab attention immediately to alert abnormalies
        
        Deeper level of details is needed - can be accessed by drilling down
  - - - Timeframe determined by objectives of dashboard
      - eg. year/quarter/month/week to date
    - - Provide context
      - eg. current year VS last year
    - - Quick evaluation of whether data is good/bad
      - Usually encoded as visual objects
      - Serves as alerts on state of measures
      - Should not have too many states for the data
    - - eg. top 10 customers, issues to be investigated, schedules, due dates
  - - - Display multiple instances/measures rather than single instance/measure
      - Great for displaying measures associated with items in a category
      - Scale of Y axis does not start from 0 gives wrong perception of data
    - - Good for displaying multiple instances of whole and its parts with emphasis on the whole but is harder to read (stacked column)
      - Bar graphs reveal the shifts in the distribution of sales between the 4 channels more clearly than the stacked bar graph
    - - Reveal shape of data, trends, fluctuations, cycles, rates of change
      - Best for time-series data
      - Present overall picture rather than detail values
    - - Data is being expressed as part of a whole
      - Useful for displaying 6 elements or less
    - - Data is being expressed as part of a whole
      - Useful for displaying more than 6 elements
    - - Data with the same median & data range but different distribution
      - Good for describing distribution of data, median, range of values
    - - Display whether or not and the direction and degree that 2 paired sets of a quantitative values are correlated
      - Involving more than 1 set of data
      - Shows the strength & positivity of correlation
      - Exhibits a curve rather linear correlation between the values
  - - - uses 2 scales to eliminate wasted space that would appear in the gap between total revenue & individual sales
      - Good use of combination bar & line graphs
        
        some data can be best displayed using bars & some using lines
      - Individual values displayed as columns
      - Cumulative tital of values displayed as line
      - What it shows?
        
        Slope of line: the steeper the line, the greater the sub-category's revenue was relative to the next best sub-category
        
        Line shows how evenly distributed the contributions of the sub-category are/how much they are skewed towards the top sub-categories
        
        Good for analyzing 80-20 Rule
  - - - Prone to inaccurate interpretation and often to occulsion
  - - - series of horizontally aligned small multiples displayed revenue split between 3 channels
      - to eliminate redundancy, avoid repeating the region labels, legend and overall title for each chart