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