with no loss of information, but greater insight. …have made money on cipla with an average return...

1
Vendor Consol Decon IW DC Store Vendor1 Vendor2 Vendor3 Vendor4 c1 c2 c3 c4 c5 D1 D2 D3 D4 IW 1 IW 2 IW 3 IW 4 DC1 DC2 DC3 DC4 S1 S2 S3 S4 $15,745 2.02 Days $326,642 1.69 Days $360,146 2.15 Days $305,806 1.94 Days $313,688 2.06 Days $310,214 $301,933 $322,790 $295,705 $308,447 $314,381 PORTFOLIO AND RISK MANAGEMENT MANAGING THE SUPPLY CHAIN Worldwide $288.0mn A: Accelerate $68.9mn B: Build $77.2mn C: Cut down $141.9mn Worldwide: $288 mn PORTFOLIO PERFORMANCE VISUAL The visualization shows the market opportunities across various countries to identify areas of focus. This chart has been built as an interactive-app to present the key findings, while letting user click-through and drill-down to a custom view across 4 different levels. ANALYSING TEXT Accenture Acquisition America Apple Asia Australia BRIC Balance Sheet Big Data Bottom Line Brazil Business Mix Business Model Business Performance Business Services CRM California Canada Capital Management Capital Market Capital Spending Cash Flow Challenging Environment China Cloud Cloud Infrastructure Commercial Communications Constant Currency Consulting Business Consumer Core Business Cost Management Cost Reduction Credit Currency Impact Customer Base Customer Demand Customer Experience Customer Satisfaction Data Center Demand Environment Digital Media EPS ERP Eastern Emerging Euro Europe Expense Growth Expense Reduction GAAP Gartner Global Google Growth Opportunity Growth Rate Growth Strategy HP Health IBM IDC IP Impact Income Growth India Industry Standard Infrastructure Intel Interest Income International Japan Latin Latin America Leadership Team Line Growth Linux Macro Environment Margin Improvement Market Growth Market Place Market Share Marketing Medium Business Mexico Microsoft Mix Shift Mobile Network New York New York City North America OEM Operating Cash Operating Margin Operating Model Operating Profit Operating System Operations Oracle Pacific Point Improvement Prior Year Product Line Product Mix Product Portfolio Products Profit Growth Proxy Real Estate Regulatory Repurchase Program Retail Revenue Base Revenue Growth Revenue Impact Revenue Performance Revenue Stream Russia SEC Securities Server Server Business Service Service Revenue Share Buyback Share Price Shareholder Value Software Stock Price Storage Supply Chain Tax Benefit Tax Credit Tax Rate Technology Term Debt UK Unit Growth Value Proposition Western Western Europe Windows Wireless Worldwide Year Growth Keywords used in shareholder meetings at IBM vs at Microsoft IBM is asked … Microsoft is asked … Real time visualization for transfer of goods from vendor to warehouse to store Low volume High volume Route to be addressed immediately Bottleneck Smooth flow Over 80 pages of data visualized in a single page, with no loss of information, but greater insight. Shift Evening Morning Night Weekday Fri Mon Sat Sun Thu Tue Wed Product category FAH N70 RPP TDS ZDH Part shipment 20-40% 40-60% 60-80% <20% Full Recovery times are worst on Fridays, and best on Saturdays & Wednesdays. Specifically, Friday mornings are particularly bad. So are Thursday mornings. The FAH product category has the best recovery time, while ZDH is much worse. However, RPP on Sundays is unusually slow. Part shipped products tend to perform worse than full-shipments. Specifically the <20% and 40-60% part-shipments. This is especially problematic for ZDH Profits Made: Over the last 6 years, you would have beaten a 10% Inflation about 82% of the time and lost out about 18% of the time. So, mostly, you would have made money on Cipla with an average return of 14.9%. Highest Returns: An average return of 14.1% has been observed when held for a period of one year. with a maximum of 79.6% if sold in Dec 2009, after being held for a year. And a maximum of 486.9% if sold at the end of Nov 2007 after holding for a month. The highest stock price was Rs 414 in Nov/Dec 2012. -50% +50% returns Hosted visuals link summaries with underlying raw data Allowing users to graphically comment on visuals and share them Annotations Mobile/tablet ready Generate native output for Android, iOS, Microsoft Office, videos, etc. Visual exploration Automated analysis Visualizations created automatically based on unsupervised analysis 68 64 37 27 22 22 18 18 55 18 24 36 38 33 30 -14 -23 -18 British Pound 59 39 45 10 45 30 24 60 12 27 39 45 40 20 -3 -20 -10 Silver 68 67 46 36 32 11 56 14 38 32 33 51 43 10 -2 -1 Euro 85 67 63 62 -10 62 19 46 27 45 68 42 38 17 23 Australian Dollar 51 58 61 -17 58 23 53 36 48 71 23 17 2 3 Brazilian Real 70 69 31 23 -30 -20 -39 -4 7 55 68 62 63 Russian Rouble 83 36 42 -29 -14 -24 20 15 51 67 58 61 Canadian Dollar 28 37 -27 -8 -22 24 18 44 54 48 48 Indian Rupee -26 -68 -67 -61 -44 -55 54 43 51 49 Pakistani Rupee 56 63 63 86 78 -3 -14 -32 -26 Malaysian Ringitt 85 86 69 79 -63 -63 -77 -72 Japanese Yen 94 76 94 -35 -50 -68 -64 Chinese Yuan 78 85 -43 -64 -81 -76 Gold 82 -27 -40 -54 -52 Philippine Pso -22 -30 -51 -46 Singapore Dollar 68 67 66 Hong Kong Dollar 94 98 Dow Jones Index 98 FTSE S&P

Upload: others

Post on 17-Jul-2020

1 views

Category:

Documents


0 download

TRANSCRIPT

Page 1: with no loss of information, but greater insight. …have made money on Cipla with an average return of 14.9%. Highest Returns: An average return of 14.1% has been observed when held

Vendor Consol Decon IW DC Store

Vendor1

Vendor2

Vendor3

Vendor4

c1

c2

c3

c4

c5

D1

D2

D3

D4

IW1

IW2

IW3

IW4

DC1

DC2

DC3

DC4

S1

S2

S3

S4

$15,745

2.02 Days

$326,642

1.69 Days

$360,146

2.15 Days

$305,806

1.94 Days

$313,688

2.06 Days$310,214 $301,933 $322,790 $295,705 $308,447 $314,381

PORTFOLIO AND RISK MANAGEMENT

MANAGING THE SUPPLY CHAIN

Worldwide$288.0mn

A: Accelerate$68.9mn

B: Build$77.2mn

C: Cut down$141.9mn

Worldwide:$288 mn

PORTFOLIO PERFORMANCE VISUAL

The visualization shows the market

opportunities across various countries to

identify areas of focus. This chart has

been built as an interactive-app to

present the key findings, while letting

user click-through and drill-down to a

custom view across 4 different levels.

ANALYSING TEXT

Accenture

Acquisition

America

Apple

Asia

Australia

BRIC

Balance Sheet

Big Data

Bottom Line

BrazilBusiness Mix

Business Model

Business PerformanceBusiness Services

CRM

California

Canada

Capital Management

Capital Market

Capital Spending

Cash Flow

Challenging Environment

China

Cloud

Cloud Infrastructure

Commercial

Communications

Constant Currency

Consulting Business

Consumer

Core Business

Cost Management

Cost Reduction

Credit

Currency Impact

Customer Base

Customer Demand

Customer Experience

Customer Satisfaction

Data Center

Demand Environment

Digital Media

EPS

ERP

Eastern

Emerging

Euro

Europe

Expense Growth

Expense Reduction

GAAP

Gartner

GlobalGoogle

Growth Opportunity

Growth RateGrowth Strategy

HP

Health

IBM

IDC

IP

Impact

Income Growth

India

Industry Standard

Infrastructure

Intel

Interest IncomeInternational

Japan

Latin

Latin America

Leadership Team

Line Growth

Linux

Macro Environment

Margin ImprovementMarket Growth

Market Place

Market Share

Marketing

Medium Business

Mexico

Microsoft

Mix Shift

Mobile

Network

New York

New York City

North America

OEM

Operating Cash

Operating Margin

Operating ModelOperating Profit

Operating System

Operations

Oracle

Pacific

Point Improvement

Prior Year

Product Line

Product Mix

Product Portfolio

Products

Profit Growth

Proxy

Real Estate

Regulatory

Repurchase Program

Retail

Revenue Base

Revenue Growth

Revenue Impact

Revenue Performance

Revenue Stream

Russia

SEC

Securities ServerServer Business

Service

Service Revenue

Share Buyback

Share Price

Shareholder Value

Software

Stock Price

Storage

Supply Chain

Tax Benefit

Tax Credit

Tax Rate

Technology

Term Debt

UK

Unit Growth

Value Proposition

Western

Western Europe

WindowsWireless

Worldwide

Year Growth

Keywords used in shareholder meetings at IBM vs at Microsoft

IBM is asked … Microsoft is asked …

Real time visualization for transfer of goods from vendor to warehouse to store

Low volume High volumeRoute to be addressed

immediately Bottleneck Smooth flow

Over 80 pages of data visualized in a single page,with no loss of information, but greater insight.

Shift Evening Morning Night

Weekday Fri Mon Sat Sun Thu Tue Wed

Product category FAH N70 RPP TDS ZDH

Part shipment 20-40% 40-60% 60-80% <20% Full

Recovery times are worst on Fridays, and best on Saturdays & Wednesdays.

Specifically, Friday mornings are particularly bad. So are Thursday mornings.

The FAH product category has the best recovery time, while ZDH is much worse.

However, RPP on Sundays is unusually slow.

Part shipped products tend to perform worse than full-shipments. Specifically the <20% and 40-60% part-shipments.

This is especially problematic for ZDHProfits Made: Over the last 6years, you would have beaten a 10% Inflation about 82% of the time and lost outabout 18% of the time. So, mostly, you would have made money on Cipla with an average return of 14.9%.

Highest Returns: An average return of 14.1% has been observed when held for a period of one year.with a maximum of 79.6% if sold in Dec 2009, after beingheld for a year. And a maximum of 486.9% if sold at the end of Nov 2007 after holding for a month. The highest stock pricewas Rs 414 in Nov/Dec 2012.

-50% +50%returns

Hosted visuals link summaries withunderlying raw data

Allowing users to graphicallycomment on visuals and share them

Annotations Mobile/tablet ready

Generate native output for Android,iOS, Microsoft Office, videos, etc.

Visual explorationAutomated analysis

Visualizations created automatically based on unsupervised analysis

68 64 37 27 22 22 18 18 55 18 24 36 38 33 30 -14 -23 -18 British Pound

59 39 45 10 45 30 24 60 12 27 39 45 40 20 -3 -20 -10 Silver

68 67 46 36 32 11 56 14 38 32 33 51 43 10 -2 -1 Euro

85 67 63 62 -10 62 19 46 27 45 68 42 38 17 23 Australian Dollar

51 58 61 -17 58 23 53 36 48 71 23 17 2 3 Brazilian Real

70 69 31 23 -30 -20 -39 -4 7 55 68 62 63 Russian Rouble

83 36 42 -29 -14 -24 20 15 51 67 58 61 Canadian Dollar

28 37 -27 -8 -22 24 18 44 54 48 48 Indian Rupee

-26 -68 -67 -61 -44 -55 54 43 51 49 Pakistani Rupee

56 63 63 86 78 -3 -14 -32 -26 Malaysian Ringitt

85 86 69 79 -63 -63 -77 -72 Japanese Yen

94 76 94 -35 -50 -68 -64 Chinese Yuan

78 85 -43 -64 -81 -76 Gold

82 -27 -40 -54 -52 Philippine Pso

-22 -30 -51 -46 Singapore Dollar

68 67 66 Hong Kong Dollar

94 98 Dow Jones Index

98 FTSE

S&P