Out of the Box --

Thoughts on Data Evolution

-- Mahboob Hussain

Contents• whoami• Analytics• BI• Big Data and Logistics• The Box• Future directions : some thoughts• Things I want to explore• Q & A

whoami• VNIT Nagpur, Webster University

• Vice President (Technology), Four Soft Limited. Previously with Mukand, Parametric Technology Corporation, FedEx

• http://bit.ly/mahboob

Tom DavenportUniversity of Houston ISRC

November 15, 2007

Analytics : Starting source

Definitions and Insights• What are analytics?

• Comparison with DM, BI

• How is it different from before?

• Is the claim valid?

6 | 2007 © All Rights Reserved.

The Planets Are Aligned for Analytics

• Powerful IT• Data critical mass• Skills sufficiency• Business need

Source : http://bauer.uh.edu/uhisrc/ppt/ISRC_CompetingonAnalytics_T.Davenport.ppt

7 | 2007 © All Rights Reserved.

What Are Analytics?Analytics

What’s the best that can happen?

What will happen next?

What if these trends continue?

Why is this happening?

What actions are needed?

Where exactly is the problem?

How many, how often, where?

What happened?

Co

mp

etit

ive

Ad

van

tag

e

Degree of Intelligence

Reporting

Decision Optimization

Predictive Analytics

Forecasting

Statistical models

Alerts

Query/drill down

Ad hoc reports

Standard reports

http://bauer.uh.edu/uhisrc/ppt/ISRC_CompetingonAnalytics_T.Davenport.ppt

8 | 2007 © All Rights Reserved.

What Should Organizations Do with

Analytics?• Using analytics is good

o Finding the best customers, and charging them the right price

o Minimizing inventory in supply chainso Allocating costs accurately and

understanding how financial performance is driven

• Competing on analytics is bettero Making analytics and fact-based

decisions a key element of strategy and competition

Subset of BI

http://bauer.uh.edu/uhisrc/ppt/ISRC_CompetingonAnalytics_T.Davenport.ppt

Gartner : The source• What is BI? (Gartner)

o Integration• BI Infrastructure• Metadata management• Development tools• Collaboration

o Information Delivery• Reporting• Dashboards• Ad hoc query• Microsoft Office Integration• Search Based BI• Mobile BI

o Analysis• OLAP• Interactive Visualization• Predictive modeling and data mining• Scorecards• Prescriptive modeling, simulation and optimization

Our own tool @ 4S

© 2011 FOUR SOFT LIMITED. All rights reserved. “This presentation is for informational purposes only and may not be incorporated into a contract or agreement.”

for Informed Decision Making

The next-gen Business Intelligence Tool for Supply Chain Domain

The Product

4S Infotips is a futuristic SCM BI tool which helps the company CXOs, Managers, Supervisors & executives across all departments;

Visualize the Business Performance across various parameters through Dashboards

*Analyze huge volume of Data to understand relationships, trends in business through a very simple, powerful and user-friendly GUI

Identify exceptional events, analyse the causes and make informed decisions by studying the required information represented on the dashboard.

* Some Features limited for Enterprise Edition User Licenses

What’s Infotips?

DATA

INFORMATION

KNOWLEDGE

DECISION

So what are the Critical Success Factors?

(2) *The Ability to study the info from any angle

(1) The Ability to combine Data from multiple sources

(3) The Speed of Analysis

* Feature limited for Enterprise Edition User Licenses

4S PRE DEFINED KPIs

4S PREDESIGNED DASHBOARDS

Customer

Views with 4S Predefined KPIs* Defines New KPIs with available data fields

4S Infotips Service

Model

4S Extraction based on

Customer Request

eTrans

eCustoms

Visilog

Visilog Plus

eLog

4S eProducts DB

4S Extraction

Exte

rnal

pro

duct

s D

B

4S Data Modeling & Loading

eTrans-FF

eCustoms-

Customs

Visilog - Visibility

eLog- Warehousing

VisiLogPlus- Shipper

4S Creates new KPIs & related changes in Data Modeling as per Customer Request

* Feature limited for Enterprise Edition User Licenses

Standard KPIs for Shipper Logistics (Visilog Plus)

1. Purchase Order Response Time

2. Purchase order Quantity Fulfillment

3. Purchase Order Lead time

4. Carrier delivery efficiency

5. Item profitability Against Storage

6. Inventory Ageing Analysis

Sample Dashboard

What is the current state in the field?

Current State

• Descriptive to Diagnostics

• Emphasis on DD (what is it)

• Big Data: The ability to find patterns, correlations and insights across multistructured data will become a mainstream requirement as companies try to better innovate and find operational efficiencies across business processes that leverage data. These include capabilities that enable the collection, storage, management, correlation, organization, exploration and analysis of multistructured data. (Gartner 2013)

(JasperSoft with native interfaces to MongoDB, / HBase , Oracle Big Data Appliance, Tibco Spotfire for Big Data Analytics, SAP Data Integration with Hadoop / Hive etc).

The source

Key points• Term origin• Definition• What it is not?• Three major mindset shifts

o N = allo Loosen up our desire for exactitudeo Correlation over causality

• Datafication

Let’s talk about what’s happening in the enterprise.

8 Business Functions TCS Explored for Big

Data PracticesIn addition to surveying IT and analytics executives, TCS also wanted to collect the experiences of senior managers in eight core business functions:

• Marketing and Sales• Customer service (post-sale)• Manufacturing (or production in services companies)• R&D/product development/product engineering• Logistics/distribution• Human resources• Finance/accounting

These managers accounted for 62% of the total survey population.

http://sites.tcs.com/big-data-study/big-data-pie-business-function/

Cutting the pieHow Companies Cut the Big Data Pie by Functional Area

Departmental Impact

Highlights:• Sales and marketing get the biggest shares of the Big Data pie• However, finance and logistics expect the highest ROI on Big

Data• Eight business functions vary significantly in where they see the

benefits from Big Data – and the biggest challenges they face in gaining those benefits

http://sites.tcs.com/big-data-study/findings-business-functions/

Logistics : The source

The Story• Gripping story of globalization• McLean’s total involvement• Coastal route – container ships

Cargo cost of the past

  Cash Outlay Percent of Cost

Freight to U.S. port city $341 14.3%

Local freight in port vicinity $95 4.0%

Total port cost $1,163 48.7%

Ocean shipping $581 24.4%

European inland freight $206 8.6%

Total $2,386  

Cost of Shipping One Truckload of Medicine from Chicago to Nancy, France (estimate ca. 1960)

The SS Warrior : Cost and Time

  Number of Pieces Percent of weight

Case 74,903 27.9%

Carton 71,726 27.6%

Bag 24,036 12.9%

Box 10,671 12.8%

Bundle 2,880 1.0%

Package 2,877 1.9%

Piece 2,634 1.8%

Drum 1,538 3.5%

Can 888 0.3%

Barrel 815 0.3%

Wheeled vehicles 53 6.7%

Crate 21 0.3%

Transporter 10 0.5%

Reel 5 0.1%

Undetermined 1,525 0.8%

Total 194,582 98.4%

5,015 tons, 194582 individual items, 95 days, $237577, 36.8%

Impact of the box• Cut costs• Cut time• Destroyed old economy• Helped build a new economy• Massive global trade• Combined with the computer, it lead to JIT

Pondering : Out of the boxThe Box Big Data

A self – made ruthless business magnate

???

Excessive focus on cost cutting ???

Consolidating items into the container

???

End to end innovations ???

Standardizations ???

A couple of Box inspired innovations mentioned in the book. And I want to explore more.

Things I want to explore• Hazy• Big Data and Philosophy• Brain : The ultimate domain

Questions ???

Thanks