Gregory Seltzer

Business Analytics Partner Manager

Agenda

What is Big Data? What is Business Analytics?

Four Pillars5 StrategiesImportance of AnalyticsInternal ProcessesExternal ProcessesCase Studies

It is all about InsightDimensions of big data

Every day, we create 2.5 quintillion bytes of data — so much that 90% of the data in the world today has been created in the last two years alone. This data comes from everywhere: sensors used to gather climate information, posts to social media sites, digital pictures and videos, purchase transaction records,

and cell phone GPS signals to name a few. This data is big data.

Volume

Data at rest

Velocity

Data in motion

VarietyData in many

forms

Veracity

Data in doubt

CIO Survey – Key Drivers

In a recent survey, these were the common levers that the most successful companies used to deploy Big Data Analytics solutions.

Their key common themes of the leading companies leverage analytics as a component of their competitive advantage

Four Pillars of Analytical Competition

Four Pillars of Analytical Competition

Analytical Competitors. “Analytical nirvana” Use analytics across the enterprise as a competitive advantage.

Analytical Companies. “Good at analytics.” Highly data oriented, have analytical tools, and make wide use of analytics. Lack commitment to fully compete or use strategically

Analytical Aspirations. “Se the value of analytics.” Struggle mobilizing the organization and becoming more analytical

Localized Analytics. “Use reporting.” And analytics or reporting is in silos.

Analytically Impaired. “Not data-driven.” Rely on gut feel and plan to keep doing so. They aren’t asking analytics questions and/or lack the data to answer them.

Competing on Analytics Stages

Stage Distinctive Capability/Level of Insights

Questions asked Objective Metrics/Measure/value

1. Analytically Impaired

Negligible, “flying blind”

What happened in our business?

Get accurate data to improve operations

None

2. Localized analytics Local and opportunistic – may not be supporting company’s distinctive capabilities

What can we do to improve this activity? How can we understand our business better?

Use analytics to improve one or more functional activities

ROI of individual applications

3. Analytical aspirations

Begin efforts for more integrated data and analytics

What’s happening now? Can we extrapolate existing trends?

Use analytics to improve a distinctive capability

Future performance and market value

4. Analytical companies

Enterprise-wide perspecive able to use analytics for point advantage, know what to do to get to next level, but not quite there

How can we use analytics to innovate and differentiate?

Build broad analytic capability – analytics for differentiation

Analytics are an important driver of performance and value

5. Analytic competitor

Enterprise-wide, big results, sustainable advantage

What’s next? What’s possible? How do we stay ahead?

Analytical master – fully competing on analytics

Analytics are the primary driver of performance and value

Internal Processes

Financial Dashboards & balanced scorecards Cost management & allocation

Manufacturing Profit InSight Manufacturing quality – Minitab &

Spotfire DecisionSite Configuration - FordDirect

R&D Hypothesis testing, control groups,

statistical Vertex Pharmaceutical Entelos – computational testing Test & Learn – CapitalOne Healthways improve health outcomes

Human Resource HRIS – analytics for hiring Sports Team management

Typical Analytical Applications Activity-based costing (ABC) Bayesian inference Biosimulation Combinatorial optimization Constraint analysis Experimental design Future-value analysis Monte Carlo simulation Multiple regression Neural network Textual analysis Yield

External Processes

Customer CRM Dynamic pricing Churn Econometric analysis for advertising & brand Google web analytics Tesco clubcard Samsung M-Net Anheuser-Busch - BudNet Best Buy – customer interactions into sales

Jill Stores Barry Stores – audiophile and video file -

convenience

Supplier Wal-Mart requires Retail-Link to track

movement of products Modular Category Assortment Planning Amazon developed proprietary inventory

modeling using non-stationary stochastic optimization

Optimize supply constraints: integral min-cost flow problem with side constraints.

Typical Analytical Applications in Marketing CHAID Conjoint analyisis Lifetime value Market experimentation Multiple regression analysis Price Optimization Time series experiments

Typical Analytical Applications in Supply Chains Capacity planning Demand-supply matching Location analysis Modeling Routing Scheduling

Hospitality Case Studies

Harrah’s Strategic focus; Loyalty plus Service CEO: Gary Loveman – constantly

pushes entire executive team to use testing and analysis, fact-based decisions.

Newly legalized gaming jurisdictions in the mid-1990s ground to a halt, Harrah’s managers realized that growth could no longer come from new casino’s

Customer loyalty and Service Data to improve customer experience

while streaming casino traffic. Waiting customer is not spending.

Bottlenecks occur at certain slot machines, they offer a customer a free game at a slot machine located at another part of the casino

Ho wling they sit at a different gaming tables, optimize the range, configuration of their games

Marriott’s Revenue Management – optimal

price for their rooms Power to override the automated

systems, example was Hurricane Katrina evacuees

Enterprise wide revenue management system called One Yield

Marriott rewards deploying a sophisticated Web analytics capability. Constantly doing tests to understand changes to their website.

Analytic group reports to office of the CIO

Roadmap to Becoming an Analytic Competitor

Stage

1

Analytically

Impaired

An organization has some data and management interest in analytics Stag

e

2

Functional management builds analytics momentum

and executives’ interest through appli8cation of basic

analytics

Managerial

Support:

Prove-it path

Executives commit to analytics by align resources and setting a timetable to build a broad analytical capability

Enterprise-wide analytics capability under development; top executives view analytics capablity as a corporate priorty

Organization routinely reaping benefits of its

enterprise-wide analytics capability and focusing on

continuous analytics renewal

Terminal stage: some companies’ analytics efforts never receive management support and stall here as a

result

Analytically

Aspirations

Analytically

Companies

Analytically

Competitors

Stage

3

Stage

4

Stage

5

Top management support: full-steam-ahead path

Choosing a Strategic Focus

Harrah’s: Loyalty plus service New England Patriots: Player

selection plus fan experience Dreyfus Corporation: Equity

analysis plus asset attrition UPS: Operations plus

customer data Wal-Mart: Supply chain plus

marketing Owens & Minor: Inernal

logistics plus customer cost reduction

Progressive: Pricing plus new analytical service offerings

Key Elements in Analytical Capability

Organization Insight into performance drivers Choosing a distinctive capability Performance management and strategy

execution Process redesign and integration

Human Leadership and senior executive

commitment Establishing a fact-based culture Securing and building skills Managing analytical people

Technology Quality data Analytic technologies

Where to focus resources

How can we distinguish ourselves in the marketplace? What is our distinctive capability? What key decisions in those processes, and elsewhere,

need support from analytical insights? What information really matters to the business? What are the information and knowledge leverage points

of the firms performance?