kpi’s “r” us

KPI’S “R” USWai Phyo Kyaw | Seetoh Yong Chuen | Daryl

Lee

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

Store Operations Data in various Information

Systems

Extract data monthly to derive the KPIs (inventory

& delivery operations)

Use MS Excel to collate and generate score card

Motivation for Project

Objectives of ProjectDevelop 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

Methodology Used

Data used for our analysis is provided by Y3 Technologies

Extracted data are stored in numerous MS Excel filesCompile these data into a single fileUse JMP to compile and prepare the data

before loading into a database

Project References (External)

Description: Bullet Charts reference taken from D3.js web site.

Source: http://mbostock.github.com/d3/ex/bullet.html

http://examples.idashboards.com/idashboards/?guestuser=wpman1



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





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

http://www.unysonlogistics.com/whatwedo/index.aspx?id=78



Data Structure (Sample)

Dashboard HierarchyMain Dashboard

TransAgent/Buyer

Performance

Pass/Fail Ratio Cases

Y3 Overview Scorecard

Growth Rate Running Total Cases

Damages Scorecard (KIV)

Breakdown of damages per TransAgent

Cases

Proof of Concept – Trans Agent Performance

MonthFilter:

Proof of Concept – Y3 Delivery KPI

1. Overview

Proof of Concept – Y3 Delivery KPI

Proof of Concept – Y3 Delivery KPI (Drill Down)

Proof of Concept – Damages (KIV)

Ttl. 2009

Ttl. 2010

Av. 2009

Av. 2010

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec0.000%

0.015%

0.030%

0.045%

0.060%

0.075%

0.090%

0.105%

0%

1%

2%

3%

4%

5%

6%

7%

8%

9%

DAMAGE DURING TRANSPORTATION

Percentage (Ctn) Target Allowance Percentage (Cases)

by

ctn

by

case

s

Proof of Concept – Damages (KIV)

June July August September0

100

200

300

400

500

600

700

Number of Claims Damage from Transporter

D1 (3% of goods price) D2 (20% of goods price) D3 (100% of goods price)

Quantity

ADIGUNA

ALAM W

IJAY

ALAMUI

ANTARIKSA

ANUGERAH

ARTHA

CARGO

CV RASIT

A

CV. AL O

NEDES

DHESTA

DINOYO

DKUDM

P

GADINGGM

THJP

INDAH

JAPALIN

DOJA

YA

KECE

KOM

BA

MERAPI

NATIMAKS

NKM

RAMASAKTI

RPP

SARIJASA

SEGORO

R A SLI

SPTTFT

WIN

DU PERSADA

WIN

TAGES0

4080

120

June: Number of Claims Damage from Transporter

D1 (3% of goods price) D2 (20% of goods price) D3 (100% of goods price)

Quantity

DO_Number No_Pol TPTCustomer_Na

meMaterial Damage Qty Remarks

Status_on_DO

Comments_YCH

COMPANY GatePass_No. Data_Month

80713159 R1632HB ADIGUNA XXX 103395 D1 1

D1 - REPACKABLE

AND RESALEABLE

EXCEPT INDUCED BY

FFI TALLY AAA

2011-60600

June

80720461 B9003JR ADIGUNA YYY 103448 D1 1

D1 - REPACKABLE

AND RESALEABLE

EXCEPT INDUCED BY

FFI TALLY AAA

2011-63681

June

80722618 B9528OT ADIGUNA YYY 103450 D1 4

D1 - REPACKABLE

AND RESALEABLE

EXCEPT INDUCED BY

FFI TALLY AAA

2011-64481

June

80722894 G1773CG ADIGUNA ZZZ 103450 D1 4

D1 - REPACKABLE

AND RESALEABLE

EXCEPT INDUCED BY

FFI TALLY AAA

2011-65273

June

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

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

Roles and Responsibilities•Daryl Lee Ker Hwa : Data Analyst + InfoVis Developer

Modules Assigned – Data Loader Classes, Trans Agent Performance InfoVis

•Lex Seetoh Yong Chuen : InfoVis Architect Modules Assigned – JSON Output Generator,

Trans Agent and Damages InfoVis

•Wai Phyo Kyaw : Client Liaison + InfoVis Developer Modules Assigned – JSON Output Generator, Y3

Delivery Scorecard InfoVis

Development EnvironmentJMP Pro 9

Data manipulation, transposing, etcTableau Public

Creation of initial mockups NetBeans

JSP csv upload + JSON format conversionInkscape

Initial design of InfoVis + SVG output NotePad++ / TextWrangler

Creation of D3.js scriptsBrowser Inspectors

To debug javascript errors

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

Project Risks#2 Inconsistent Data Format

Description: Massive operations data in inconsistent formats Repopulate certain columns ourselves, replacing

certain informationMitigation 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)

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 TreeMap InfoVis

Q&AThank you!