KPI’S “R” US

1. KPI’S “R” US Wai Phyo Kyaw | Seetoh Yong Chuen | Daryl Lee

2. Motivation for Project • Gain an understanding on how a logistics business measures their operations performance • Industrial Practice - Using operational data to derive the key performance indicators • Y3 maintains a large number of logistics and delivery operation related information systems • These charts give insights on operation performance against various KPI measures • Tedious and have maintenance overheads, limited user interaction • Y3 is currently planning on providing its users with a visual analytics tool that would be able to offer interactivity and yet be simple enough for users to learn

3. Objectives of Project • Develop an end user reporting tool that effectively communicates the various KPI scorecards used to assess the level of performance in the firm • Create a user manual package for the clients in order to assist in user training of tool

4. Methodology Used • Data used for our analysis is provided by Y3 Technologies • Extracted data are stored in numerous MS Excel files • Compile these data into a single file • Use JMP to compile and prepare the data before loading into a database

5. Project References (Internal) • Description: Customer Satisfaction Project by Team Statisfied that uses a Heatmap to assess customer satisfaction across different touchpoints in a hospitals. Source: https://wiki.smu.edu.sg/1011t1is428/IS428_Visual_Analytics_Project:_IS428_2010-11_VA_Project_T14

6. Project References (External) Description: A order fulfillment dashboard application used to track incoming orders, incoming fiscal orders for 2 warehouses for the previous year, shipping orders, fiscal orders shipped for the previous year, top 10 shipping customers for the previous year and backlog by month. Source: http://examples.idashboards.com/idashboards/?guestuser=wpman1

7. Project References (External) Description:  Strategic Solutions by Unyson Logistics, a 3PL, who provides tech solutions for similar logistics company. The dashborad shows the overall shipment volumes and number of shipments across the different states in North America. Source: http://www.unysonlogistics.com/whatwedo/index.aspx?id=78

8. Data Structure (Sample)

9. Dashboard Hierarchy

10. Proof of Concept – Trans Agent Performance Filter: Month

11. Proof of Concept – Trans Agent Performance Filter: Month

12. Proof of Concept – Trans Agent Performance Filter: Month

13. Proof of Concept – Y3 Delivery KPI 1. Overview

14. Proof of Concept – Y3 Delivery KPI

15. Proof of Concept – Y3 Delivery KPI

16. Proof of Concept – Y3 Delivery KPI (Drill Down)

17. Proof of Concept – Damages (KIV)

18. Proof of Concept – Damages (KIV)

20. Schedule • Iteration 1: • Design of File Loader • JSON Output Generator Modules • Iteration 2: • Trans Agent Performance • Y3 Delivery KPI Scorecard • Iteration 3: • Damages InfoVis • Post-Poster Day Changes: • Modifications to Dashboard from feedback received

21. Milestones • Milestone 1: Approval of Project Proposal and Client Review of Training Documents • Milestone 2: File Loader + JSON Generator • Milestone 3: Trans Agent Bullet charts + Y3 Delivery Scorecard • Milestone 4: Damage Chart • Milestone 5: Final Client Review and Completion of Poster Day • Milestone 6: Submission of Deliverables

22. Roles and Responsibilities • Daryl Lee Ker Hwa : Data Analyst + InfoVis Developer • Modules Assigned – Data Loader Classes, Trans Agent Performance InfoVis • LexSeetoh Yong Chuen : InfoVis Architect • Modules Assigned – JSON Output Generator, Trans Agent and Damages InfoVis • Wai PhyoKyaw : Client Liaison + InfoVis Developer • Modules Assigned – JSON Output Generator, Y3 Delivery Scorecard InfoVis

23. Development Environment • JMP Pro 9 • Data manipulation, transposing, etc • Tableau Public • Creation of initial mockups • NetBeans • JSP csv upload + JSON format conversion • Inkscape • Initial design of InfoVis + SVG output • NotePad++ / TextWrangler • Creation of D3.js scripts • Browser Inspectors • To debug javascript errors

24. Project Risks • #1 Unfamiliar Development Tools • Description: • New languages such as D3 • Integration with Javascript and output files such as JSON and SVG which are new to the team • New frameworks to be adopted • Mitigation Strategy: • Each member takes charge of at least on InfoVis in order to ensure that team has an understanding of how to code in D3 • Set aside days to learn new tools

25. Project Risks • #2 Inconsistent Data Format • Description: • Massive operations data in inconsistent formats • Repopulate certain columns ourselves, replacing certain information • Mitigation Strategy: • Work closely with client’s operations manager to understand the columns used in current scorecards • Consolidate relevant data into one integrated sheet • Create calculated columns for visualization purposes (i.e. % late deliveries)

26. Project Risks • #3 Technical Limitations • Description: • Unearthed limitations of D3.js, JSON format, etc. • Could affect feasibility of chosen InfoVis designs • Mitigation Strategy: • Consider as simple InfoVis designs as possible • Damages InfoVis used as backup plan should team fail to deliver TreeMapInfoVis

27. Q&AThank you!