strength in numbers: ace! - predictive analytics world · 2010-06-08 · fostering analytic...

Copyright © 2009, SAS Institute Inc. All rights reserved.

Strength in

Numbers: ACE!

Predictive Analytics World

October 2009


Discussion Topics

Fostering Analytic Competency & Culture

Analytics & Innovation: Best Practices (examples where an analytic view can yield better results)

Options for Analytic Bandwidth



What is an Analytic Center of Excellence?

A resource to facilitate use of analytics across functional and geographic areas of the enterprise.

A central point for

developing and evolving analytic infrastructure

promoting collaboration and analytic best practices

driving growth, cost reduction, and profitability

A means to support strategy and operations through objective analysis.



“Change is the one constant.” -Heracleitus

Address, assess and evolve your analytic infrastructure

People

Process

Technology

Culture



People: Optimize Use of Scarce Analytic Talent

Promote collaboration & sharing

Internal presentations

Guest speakers

Assignments to cross-pollinate and collaborate on strategic projects

Recognize specialized skills and experience

Numerically

ChallengedHighly Creative Problem

Solvers / Numerati




Process: Assess & Evolve for Efficiency/Effectiveness

Business processes cross departmental boundaries

Limited-to-no central view, coordination or repeatability

Some analysis never done—no assigned resource or clear priorities

Manage, monitor & archive models (knowledge management)

Commit to ongoing experimentation, training learning

Measure the effectiveness of your efforts



Technology: The easy part!

Challenges Keeping current

Knowing and assessing options

Should you take advantage of in-database analytics & scoring?

Is your analytic workbench optimized for productivity?

Do you have the capabilities to best solve old & new problems?

…


Culture: Does your organization have a learning culture?How many decisions are data / analytics-driven?

How are high-risk decisions made?

How old are processes driving key decisions?

Is the answer to “Why don’t we try something new…?”



Analytics & Innovation

“But we’ve always managed risk in silos…”

“The biggest failure…is the lack of consolidating individual risk models and being able to audit them.” -Dr. Sam Savage

“Incentives are a main culprit.” -Andrew Freeman, McKinsey & Co

“Effectiveness of risk management is almost never measured.” -Douglass Hubbard

No experimentally verifiable evidence that many risk management methods are effective

Some that have been measured don’t work.



Ideas for Risks & Modeling Them

Consider 4 completeness perspectives

Internal

External

Historical

Combinatorial

Do a Pre-Mortem (Gary Klein)

Look to risks from others

Include everyone

Do peer reviews

“Research has shown that the extent of errors in spreadsheet calculations is

probably far beyond what most managers would like to believe.” -Douglass Hubbard



“But we’ve always politicized forecasting.”Webinar Today: What Management Needs to Know About Forecasting

Table 2. Calculating Value Added at Cisco

AnalystForecast Accuracy

Naïve Accuracy

Value Added

A 75% 80% -5%B 60% 60% -

C 55% 50% 5%For further discussion of this topic, see Michael Gilliland, "Fundamental Issues in

Business Forecasting," Journal of Business Forecasting, Summer 2003

Source: Cisco

“…the analytics team can market its success and demonstrate its

competency to bring analytic insights, skills and techniques to managing

other business processes within Cisco.”

Source: Gartner RAS Core Research Note G00167426 Case Study: Cisco Improves Demand Forecast Accuracy

With Advanced Analytics, Domain Expertise and a Consensus Process, Bill Hostmann, 2 October 2009

http://www.sas.com/reg/gen/corp/623866

http://www.gartner.com/technology/media-products/reprints/sas/vol6/article4/article4.html

http://www.gartner.com/technology/media-products/reprints/sas/vol6/article4/article4.html


Investors had reason to smile last week. As expected, neither rising energy costs nor high short-term interest rates stopped a stream of strong second-quarter earnings news. And the Federal Reserve chairman,

Alan Greenspan, added to the cheer on Thursday, when traders interpreted his comments as a signal that the economy was slowing and that the Fed might be done raising rates, at least for a while.

That news sent the Nasdaq composite up more than 3 percent, putting it back into positive territory for the year, and the Dow industrials and Standard & Poor's 500 also rallied. So for at least one weekend, Wall

Street's biggest concern is likely to be nothing more than the weather in the Hamptons.

All in all, the picture is pretty, said Abby Joseph Cohen, chief market strategist at Goldman Sachs. With the economy slowing a bit but earnings still strong, she thinks the S.& P. 500 could hit 1,575 by the end of the

year, a 5 percent gain. ''Second-quarter numbers have been quite good,'' she said.

Agreed. But that is not the whole story. After all, the fundamentals were just as good three months ago, when the Nasdaq plunged into a sickening tailspin that pushed it from 5,000 to 3,300 in a matter of weeks,

leaving many investors bruised and some broke.

Person

PersonPublic Company

GS, NYSE

Organization

Organization

Organization

Organization


“But we’ve always manually tagged these documents.”

Automatic Metadata Extraction/Tagging for Better Search

Use entity extraction to better define metadata and taxonomies.

Facilitate more relevant search results.


“But we’ve always used [method x] to model customer attrition.”

Know when not just if a customer will leave, upgrade, default…

Forecast attrition and other events of interest

Estimate future expected life-time value of customers

Prospect

Acquisition

Cost

Revenue

Generation

Servicing

Costs

X-/Up Sell

Promotion

Migration

Attrition

Prevention

Revenue & Profit

Modeling

Segmentation

Enhanced

Analytics

Targeted

Campaigns

Bad Debt…

Fraud Detection

Win-back

V

A

L

U

E

Base

Management

ACQUISITION CONVERSIONVALUE

ENHANCEMENTRETENTION RE-ACTIVATION

LIFE CYCLE

Less Profitable Lifecycle

Profitable Lifecycle


Past

Current

Potential


“But we’ve always had text-heavy, tabular, tree-killing reports.”

Help the data tell the story—visually!

Put the data in context for the intended audience.


C:/PAW/Swine Flu LL.htm


Options for Analytic Bandwidth

Analytic Center of Excellence for optimal resource utilization

Optimized analytic workbench

In-database analytics & scoring

Automation where appropriate

Analytic Community expands beyond your organization

External consultancies (like many who are here!)

Proof-of-Value projects

Hosted options (with ability to transfer on-premise if desired)

Opportunities to collaborate with Academia

…


Executive Sponsorship & Priority

Data Quality & Availability

Data (measurements) as a strategic asset

Measurement (data collection) as a process

Talent Acquisition & Management

Provide opportunities to try new things

Career paths for individual contributors

ACE Structures & Rules of Engagement

Consolidated, Coordinated, or Federated

Senior management requests projects, directs priorities

Analytic governing body manages priorities and engages others as appropriate

Measure the effectiveness of your efforts!

Other Considerations for Analytic Bandwidth


Many Goals of Analysis

Explore

Explain/Describe/Clarify

Decide

Predict

Understand

Forecast

Visualize

Optimize

Minimize/Maximize

Group/cluster/segment/categorize

Allocate/distribute

SimulateDesign

Monitor

Manage Share

Estimate/approximate

Schedule

Locate

Detect

RevealBalance

Experiment/learn

PreventQuantify Substantiate

Evaluate

Manage

Formulate

Innovate Inform

Streamline/simplify/distill

Guide

PricePromote

DiscountWeight

Adjust

Defer

Recover

Suspend

Recognize

Compensate

Collaborate

SupportAugment

CoordinateRecommend

ImplementScoreDeploy

Solve

Experience is inevitable. Learning is not. -Paul J.H. Schoemaker

Discover

Act

Anticipate

Hedge

Simulate

Illuminate

Eliminate

Contain

Understand

ReduceDecide

Constrain

Justify

Model

Conserve

Limit

Recycle BetterFind

Filter

Isolate

Pinpoint

Improve


Question for You

At Predictive Analytics World in February 2009

Andreas Weigend asked:

What are the bottlenecks to doing analytics at your organization?

Data Integration

Data Quality

Documentation About What the Data Mean

Mentality of Some People

Communication

strength in numbers: ace! - predictive analytics world · 2010-06-08 · fostering analytic...

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