Capability Overview

DSQUARE SOLUTIONS

THE VISION

Inferior Data

Superior Decisions

To help our customers traverse the path from Data to Decisions quickly,

effectively and efficiently

THE APPROACH

Idea

• Frame the Decision need

Analysis

• Manage the necessary data, models and analysis

Decision

• Support Decision making through insight generation

Execution

• Monitor and track decision execution and effectiveness

Value

• Measure and report value

Full Lifecycle support for a truly Analytical decision making process

THE FOUNDATIONS

Content

• Relevant and Reliable Information

Carrier

• Appropriate business application to deliver the insights at the right point

Consumption

• Present the insights in a form that is easily consumed by the business

Cost

• All of this at a cost that needs no justification!

OUR CAPABILITIES

Data Infrastructure Management

Our Structured Information Framework (SIF) is a fast

implementation data management solution that has

been deployed at varying scales (Large Enterprise to Localized Business Unit)

Modeling and Optimization

We also build and deliver mathematical models custom

tailored to the customer needs that cover areas like statistical predictive models,

optimization models (LP, MIP) using Open source tools like

COIN-OR, R

STRUCTURED INFORMATION FRAMEWORK

Source Data

(Uncertain

Hygiene)

Business Value through

better decisions

Useable Data

(Analytical Data

Store)

Data Staging –

Tested, Filtered,

cleansed

Analytical Data Store

(Commercial

Database)

Data Integrity

Dashboard, Data

quality metrics

Relevant & Actionable

analysis

Strategic Modeling

Exceptions and Alerts

Operational

Dashboards

Metrics Definition and

Tracking

Collaborative

Decision

Support and

Analysis

RESOURCE MANAGEMENT – ALLOCATION AND

OPTIMIZATION

Situation / Problem Statement

• Customer has multiple simultaneous projects with varying deliverables and skill requirements

• Globally distributed work force, with varying cost and competencies

• Manage allocation of resources to projects to optimize on margins and delivery SLA

Solution

• Web based Resource Management and Allocation

• Captures Resource Cost, Skills and Competencies

• Project Requirements – Timelines, Skill requirements and target margins

• Global Allocation Optimizer identifies “Best” resource to assign to each project based on

• Skill / Competency matching

• Margin maximization

• Operational constraints

• MIP Formulation solved using open source solver

• Identifies Skill and competency gaps for further Training and Development

CUSTOMER ATTRITION AND LOYALTY

Situation / Problem Statement

• B2C customer facing a Customer Attrition challenge

• How to identify potential customer attrition and initiate preventive measures

Solution

• Statistical model “Predicts” individual customers propensity to attrite and identifies critical factors that precipitate attrition

• Identifies “High-Risk” customers with clear callouts of the reason for the attrition risk

• Define a “Play Book” that triggers action from the provider for each High-Risk customer based on the identified factors

ENGAGEMENT MODEL

ENGAGEMENT MODELS TO SUIT EVERY

BUSINESS NEED

Consultative Engagement

• Identify problems, opportunities and challenges

• Time and Material based costing

Services Delivery

• Build custom solutions and models to solve critical problems

• Fixed price engagements, Pay-Per-Use

Embedded expertise – Retainer model

• Invest, Build and manage customer specific expertise and knowledge

• Annual subscription model

BOT

• Transfer expertise and personnel to customer for continued in-house support

• To be discussed

DELIVERY MODEL GEARED TO UNLOCKING

VALUE

SaaS delivery model

Hosted on Cost-

Effective Cloud

infrastructure – No upfront

costs involved

Only pay for what you use

Pay-Per-Use or

Subscription models

available

Ramp up consumed solutions

Consulting and Analytics offerings can be added „a la carte‟ to the solution

Rapid ROI Realization

Extremely fast delivery

cycles ensures

rapid ROI realization

THE PEOPLE

• Anand Srinivasan

• Anand is the founder and CEO and brings several years of experience managing the R&D and modeling teams at Sabre and Dell.

• He has vast and rich expertise in solving large optimization problems for Fleet and Crew optimization, Revenue Management etc.

• He has also worked with the Supply Chain team at Dell building models for manufacturing optimization, logistics, lean manufacturing, supply network optimization, inventory staging and management and pricing for demand shaping

• Anand Srikumar

• Anand Srikumar brings several years of experience in the Banking and Financial Services industry with GE and Standard Chartered Bank

• He brings expertise in Consumer Credit scoring, Portfolio Risk Management and Financial Modeling

CASE STUDIES

Optimization and Advanced Analytical solutions from DSquare

HOTEL REVENUE MANAGEMENT

WHAT IS REVENUE MANAGEMENT AND WHY IS IT

RELEVANT?

• The practice of selling the right room, for the right price, to the right customer, through the

right channel

• Industry benchmark standards have established that Implementing a Revenue Management

solution can increase Room Rent Revenues by 3% to 6% with minimal increase in operational

costs

• Revenue increase of 17% have been reported in some cases

REVENUE MANAGEMENT COMPONENTS AND

ALGORITHMS

• Observed Historical Bookings is a “end state” of bookings after some bookings have been rejected due to capacity constraints

• Statistical models Forecast the “Unconstrained” (Without capacity restrictions) demand for various price points.

• “How many people wanted to buy?” from “How many people bought”

Unconstrained Demand Forecasting

• Optimization algorithm to identify the “Best” price point to sell rooms at

• A Dynamic programming formulation that uses the unconstrained forecast for a given occupancy day and works backward to determine the optimal selling price on any given day leading up to the occupancy

• Can be re-optimized periodically to reset prices based on actual observed demand

Optimization of Inventory controls

RM SOLUTION – SYSTEM SAMPLE

Today

Forecasted Occupancy for

various Price Points (Baseline,

Low Fare, and High Fare)

RM price recommendations

for future dates

Estimated Benefits of

recommended controls

Target Occupancy

Date

MARKETING PLAN OPTIMIZATION

Consumer Markets

THE PERSONAL COMPUTER MARKET

• Consumers are flooded with choice

• Brands, Models, Configurations, Form Factors, Special Offers

• Guaranteed to find a model (configuration) that meets the need of all but the most

esoteric consumer requirement

• Brand Equity has been significantly diluted

• Informed consumers look to other brands for the right configuration/price

• Extremely critical to hit the right configuration in the market at the right price point

Only possible approach to find the “Sweet Spot” is using Choice Models

CONSTRUCT

Group Customers by Segment

• Laptop, Tablet etc.

Choice Set visible to the Segment

• Available makes, models, configurations

Significant Product Attributes

• Memory, Screen Size, HD Capacity, Price etc.

Estimate importance of each attribute

• Statistical Techniques

Predict probability (Market Share) of each possible configuration introduced into the market

Optimize promotional activity and Marcomm spend to drive customers to high margin sales

MODEL PREDICTED AND ACTUAL SHARES

COMPARISON

0

10

20

30

40

50

Acer Compaq Dell HP Lenovo Sony Toshiba

Feb 12 (Calibration)

Forecasted Actual

3.4%

0

10

20

30

40

50

60

Acer Compaq Dell HP Lenovo Sony Toshiba

Mar 12 (Prediction)

Forecasted Actual

16.3%

Error

0

10

20

30

40

50

Acer Compaq Dell HP Lenovo Sony Toshiba

Apr 12 (Prediction)

Forecasted Actual

42.6%

Error

0

10

20

30

40

Acer Compaq Dell HP Lenovo Sony Toshiba

May 12 (Prediction)

Forecasted Actual

12.8%

Error

Apr Data shows large deviation from Prediction – Possibly due to heave promotional activity by Dell

HOW TO USE THE MODEL

• Profitability Enhancement

• Clearly identified attributes that impact sales

• Can choose high margin components between “nodes of indifference”

• E.g. Screen Resolution

• Sales Target Setting

• The Model predicts “Fair Share” based on product attributes. Any share capture above that can be attributed to Sales and Marketing Activity

• MarCom ROI

• Can quantify the uplift generated in sales in a given month due the MarCom Spend.

• Apr Marcom/Promotions resulted in +20% market share for Dell

• Competitive Response

• Evaluate the impact of new product launch or price move by competition and respond appropriately