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Dashboard for Statistical Visualization of Client Service Events

2. Dashboard for Statistical Visualization of Client Service Events. The raw data: Creation – Received –First_Contact_SW – First_Contact_HW – Request – Pending – Closed. TSC Events: Creation – Received – First_Contact_SW – First_Contact_HW – Request – Comp_Pending – Closed.

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Dashboard for Statistical Visualization of Client Service Events

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  1. 2 Dashboard for Statistical Visualization of Client Service Events The raw data:Creation – Received –First_Contact_SW – First_Contact_HW – Request – Pending – Closed TSC Events: Creation – Received – First_Contact_SW – First_Contact_HW – Request – Comp_Pending – Closed Types: HW Platforms, Products, Geo, Owner, …

  2. Sorted data Case DateTime Event Type Time PrEv Case1 T1 Ev1 Type1 0 0 Case1 T2 Ev3 Type1 T2-T1 E1 Case1 T3 Ev7 Type1 T3-T2 E3 Case2 T4 Ev3 Type1 0 0 ……

  3. OLAP dimensions.

  4. Dashboard for Statistical Visualization of Client Service Events Consists of three key elements: • Run chart for longitudinal (in time) representation of data • Matrix bar chart for types of cases • Flower bed chart for time between events representation. The flower bed and matrix bar charts can be plotted for any specific interval of time: week, month, or year. All features of these three charts are clickable, switching is easy between charts, and drilling down can be done to detailed lists of individual cases. These interactive capabilities facilitate identification of the most business important cases.

  5. 6 Longitudinal Analysis: Run Chart TTR = Time-To-Resolve = DateTime(CaseClosed) – DateTime(CaseCreated)

  6. 7 Cross-Sectional Analysis –Time Between Events: The raw TSC data:Creation – Received –First_Contact_SW – First_Contact_HW – Request – Pending – Closed Events: Creation – Received – First_Contact_SW – First_Contact_HW – Request – Comp_Pending – Closed Types: HW Platforms, Products, Geo, Owner, …

  7. 8 Cross-Sectional Analysis –Time Between Events:

  8. 9 Cross-Sectional Analysis –Time Between Events:

  9. 10 Cross-Sectional Analysis –Time Between Events: MTBE MTBE MTBE • Traditional wayto represent 2 (pivot) tables: Freq and MTBE (Event x PrevEvent )‏

  10. 11 Cross-Sectional Analysis –Time Between Events: Variants of possible designs for 2 parameters (Fr and T) • Area of Circle (“house”) is proportional to frequency of the event. • Width of Petal (arrow, bar) is proportional to frequency of transitions between events. • Length of Petal is proportional to mean time between events. • Color of Petal is the same as color of “To” Circle (“house”)

  11. 12 Cross-Sectional Analysis –Time Between Events: Flower Bed Chart Petal direction points to next event, with matching petal-circle color. Circle size ~ frequency. Length of petal ~ time and width of petal ~ frequency. Data visualization – variants of design

  12. 7 7 3 3 1 3 3 1 1 1 13 Cross-Sectional Analysis – Tower Charts f(i) = Q( i / N) = ECDF-1(i / N) . 3D Towers Figure 5. Empirical CDF (left) and sorted sequence (right) of TBE = {1, 1, 3, 3, 7}. f(i) = Q( i / N) = ECDF-1(i / N) 3D Towers

  13. 14 Cross-Sectional Analysis –Time Between Events: Flower Bed Chart with Tower Petals

  14. 15 Cross-Sectional Analysis – Evolution of Elements

  15. Cross-Sectional Analysis by Types of Cases: Traditional wayTo represent 2 (pivot) tables: Freq and TTR (HW Platform) x (Product)‏

  16. Cross-Sectional Analysis by Types of Cases: Matrix Bar Chart Width of cuboid is proportional to time and height is proportional to square root of frequency.

  17. Dashboard for Statistical Visualization of Client Service Events

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