Business Intelligence 9 11 08 Cio Breakfast 1

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1 BUSINESS and COMPETITIVE INTELLIGENCE Paul Gray CIO Breakfast Round Table 9-11-08

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Transcript of Business Intelligence 9 11 08 Cio Breakfast 1

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BUSINESS and COMPETITIVE INTELLIGENCE

Paul Gray

CIO Breakfast Round Table

9-11-08

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Aims Of This Talk

To tell you what the shouting is about Help you decide whether business intelligence

is: Simply a new name A repackaging of DSS in a more appealing wrapper The true future of decision support

Examine the ROI from BI and CI Examine the impact of Web 2.0 Examine business considerations

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Definition Of BI Systems

Business intelligence systems combine: Data gathering Data storage and Knowledge management with Analysis

to evaluate complex corporate and competitive information and present the results to planners and decision makers.

Objective: Improve timeliness and quality of the input to the decision process

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Implicit In Definition

Business intelligence systems provide:actionable information and knowledge at the right time in the right location in the right form

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BI Relation to Other Software

Data Mining

DSS/ EIS

Business Intelligence

Data Warehouse

KnowledgeManagement

CRM/dB Marketing

Web 2.0

GIS

OLAP

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What BI does

Strategic use Corporate performance management Optimizing customer relations Packaged standalone BI applications Management reporting of BI/CI data

Tasks Creating forecasts and estimates of future

direction “What if” analysis of alternative scenarios. Ad hoc access to answer non-routine questions. Strategic insight

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Implications

Ordinary reports of a firm’s performance and competitor performance (what BI software gives) is not enough. Need analysis to put it in context

For too many firms, BI (like DSS and EIS before them) is still inward looking and is used only by a small subset of people

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BI Application

Company that sells natural gas to homes builds dashboard to support

Operational performance metric measurementReal time decision making

Result: No. of repeat repair calls reduced saving $1.3 million

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Return on Investment

CostsUpfront cost and upkeep are high

($200/seat for Cognos) Cost efficiencies in IT can be forecast but

not in BI or CIBenefits

Cost reductions don’t pay costGet new opportunities, discover problems,

and avoid difficulties

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Return on Investment

Costs include:

Additional hardware

Large amt. of software

Purchased external data

A dependent data mart for BI

Analysts and support staff

Hardware, software update

and maintenance

User time thinking about BI outputs

Benefits mostly soft;

include:Hope for ‘big bang’ returns

in the future (but can’t forecast them or their timing)

Better understanding of the business and the competitor’s business

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Change: BI for the Masses

BI tools are moving to the whole mass of knowledge workers, not just few specialists

A way of closing gap between analysis and operations, moving to multiple levels in the organization

Previously, typical analyst use is ‘one-off’ study

Large deployments of BI include 70,000 at French Telecom, 50,000 at US Military health systems. Other examples at 20,000 users

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Web 2.0 Example:5 Bashups

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Web 2.0 Example: GIS,BI

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WEB 2.0 IMPLICATIONS

Does not require much end-user skills(<20% of users in most orgs. Use reporting, ad

hoc query, and online analytic processing) Web 2.0 results in intuitive interface, better

data mgmt. and access Get “bashups” in std. format from variety of

sources. Brings together, e.g., GIS, on-demand BI,

external sources (e.g., Web) Lets businesses see value in analytics

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WEB 2.0 EXAMPLE

Mass. Housing Finance Agency Mapping capabilitiesExternal MapInfo SoftwareCognos DashboardNow used by 300 , not just 12 analystsFuture: show housing units, loan data,

public transportation visually on one screenIn insurance: link claims and wellness

data to allow employers to evaluate ROI of different programs and benefits

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CHALLENGES

Data quality (governance, master data management, performance indicators)

Agreeing on common data definitions, meaning of performance indicators

Having right infrastructure in placedIn some firms, IT’s relies on ‘name’

vendors (SAP, Salesforce.com), not small startups in BI space

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WEB 2.0 BI AND THE CIO

Put more capabilities in user hands. Make IT enabling infrastructure

IT should allow users to get data without programming “IT should get out of developing interfaces and become

involved in data quality and data integration IT should not fight emerging BI technologies to enforce

standards –Schlegel, Gartner group. Should put them into the BI architecture to avoid rogue BI capabilities

Use a self-service BI strategy to reduce cost, speed delivery

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Competitive Intelligence

“No more sinister than keeping your eye on the other guy, albeit secretly” –Claudia Imhoff

More formal definition by Society of Competitive Intelligence Professionals (SCIP)

“CI is a systematic and ethical program for gathering, analyzing, and managing external information that can affect your company’s plans, decision and operations”

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Definition Of CI In Practice

CI ensuring marketplace competitiveness

Through understanding:

-competitors

- over-all competitive environment--------

Can use whatever you find in the public domain to make sure you’re not surprised by your competitors.

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Examples Of CI

Comshare bought a competitor after monitoring the competitor’s hometown newspaper

Texas Instrument made $100m acquisition by figuring out competition’s potential bids

Merck developed counter-strategy about competitor’s upcoming product, saving $200M

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Sources of CI

Government informationOnline databasesInterviews and surveysSpecial interest meetings such as SIMCompetitors, suppliers, distributors,

customersMedia (newspapers, journals, wire

services, financial reports, speeches by executives bragging about their firm)

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Competitive Intelligence Tools

Simulations to test ‘what if’ conditionsData mining about competitor & firmTrack patents to assess competitor

technologiesScan public record, Internet, press

release, mass media Talk with customers, suppliers,

partners, industry experts, sales people

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Notes on CI

Problem is not lack of information but too much information

Once you start CI, you try to find ways to make task of finding out about you more difficult.

Get CI, CCI, CCCI, … CnISame game is played in politics, int’l

competition

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BI Market

Market size (IDC) $6.3 billion (2006)

Trend in pre-built analytic applications because home-built systems take too long (>6 mos.) and cost too much ($2-3 million)

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VENDORS-Gartner 2008

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Managerial Issues

Is BI an oxymoron?BI is really about understanding your own

position, your customer, your competitorAn important part of planning and

operations CI is a way of finding out about your

market position

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Managerial Issues

What do I know once I deploy BI?Capabilities available in firmState of the art, trends and directions in the

marketsThe technologies and regulatory

environment Competitor actions and their implications

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Managerial Issues

What capabilities do investments in BI create?Complex corporate and competitive

information for planners and decision makers

Improved timeliness and quality of input to the decision process

(Occasionally) major breakthrough

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Managerial Issues

How do you gather, transfer BI?BI a form of knowledge; includes both

explicit and tacit knowledgeSome knowledge bought (scanner

data), other created internally from analysis of public and private data

Must disseminate to many people in firm; customize by individual, group

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Managerial Issues

Organization for BI?Not necessarily; both centralized and

decentralized org. work What technologies are available?

Specialized software packages, many still quite crude

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CONCLUSIONS

Business Intelligence is a part of DSS but certainly not all of it.

BI name gives DSS a new skin. Semantics matter

The technology for BI and CI is getting better, broader, and more universally available. Web 2.0 is coming

The capabilities of the DSS analyst in business improve as both structured and unstructured data grows

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CONCLUSIONS

BI and CI are steps along the way. They are the short-term future of DSS in the commercial world.

In the long term, we will inevitably find new ways of thinking about and solving decision problems.