2 Jørgen Steines Platon

8/15/2019 2 Jørgen Steines Platon

1/40

WWW.PLATON.NET

Hvordan sikres (mere) værdi af

Business Intelligence projekter? [email protected]

1


2/40

© Platon

● A leading Independent Information Management consulting company

● Headquarters in Copenhagen, Denmark

● 220+ employees in 9 offices

● 300+ clients in 8 countries

● Founded in 1999

● Employee-owned company

Platon – The Company

“Platon received good feedback in our satisfaction survey. Clientscited the following strengths: experience and skill of consultants,business focus and the ability to remain focused on the needs of

the client, and a strong methodological approach”

Gartner Jul y 2008


3/40

© Platon

Side 3

• Fokus på Business Intelligence og Master Data Management• Unikke internationale eksperter• Netværksreception med underholdning af Jonatan Spang• Afsluttende netværksmiddag

Vi glæder os til at se dig og dine kollegaer d. 12. oktober 2011.

Nordens største Information Management konference: Keynote:

JAMES TAYLOR

Vi er stolte over at annoncere årets

keynote-taler: én af de største Business

Intelligence-guruer hele vejen fra San

Francisco i USA. James er en ledende

ekspert og forfatter indenfor regelbaseret

beslutningsstøtte (Decision Management

& Predective Analytics) og en anderkendt

keynote-taler ved diverse globale

konferencer.

28 unikke præsentationer, bl.a:

Book allerede datoen i din kalender i dag!

Du kan følge udviklingen af programmet påwww.IM2011.net.


4/40

© Platon

Agenda

● What is BI● BI Governance

● BI Adoption

● BI requirement specification

● Summing up

4


5/40

© Platon

Data Warehouse & Business

Intelligence

Page 5

Analyticalapplications

OLAP

DataMining

Enterprise

reporting

Business Intelligence

?!?

DataWarehouse

The term Business Intelligence (BI) covers

the use of information to drive businessinsight.

Basically it‟s about providing a betterfoundation for decision makers by providing

information in the right form, in the right

quality, at the right time.

The term Data Warehouse covers the management of data

Data is extracted from operational systems and integrated inthe Data Warehouse environment in order to provide an

enterprise wide perspective, one version of the truth.


6/40

© Platon

Drivers for Business Intelligence

Page 6

Procurement

Production and logistics

Sales Service

HRMany types of employees

High employee turnoverBad employee satisfaction

Decreasing competencies

Need for collaboration

. . .

MarketingDecreasing market share

Missing cross/up-salesBad campaign response

Slow time to market

CRM aspirations

. . .

ITHeterogeneous infrastructure

Data quality issuesReporting back-log

Project delivery issues

. . .

FinanceCash flow problems

Low profitabilityLosses on debts receivable

Inflexible planning process

CPM aspirations. . .

CEOLow profitability

Decreasing market shareSlow reaction to threats and opportunities

Challenges implementing business strategyChallenges with mergers

. . .

Falling revenueMissing cross/up sales

Increasing COGS

Missed opportunities

Bad forecasting

Decreasing prices

Complex markets

. . .

Bad customer satisfaction

Increasing response time

More complaints

Random service levels

. . .

Quality issuesFalling service levels

Increasing lead time

Rising inventory levels

Resource bottlenecks

Increasing distribution costs

Inefficient processes

Extended value chain aspirations

Process outsourcing

Just-in-time aspirations

. . .

Unattractive pricesBad service levels

Lack of supplier insight

Lack of market insight

Rising stock levels

. . .

The

MultidimensionalManager:

”24 Ways to Impact yourBottom Line in 90 days”


7/40© Platon

An example

Page 7


8/40© Platon

● It is estimated that 10% of all insurance claims are attempts to fraud

● For Codan this equals 400 mill. DKR per year

Predictive analytics

Codan - Fraud

Insurance claim- collect information

Standard caseLoss consultant

investigates

??

Insurance claim- collect information

Standard case

Loss consultantinvestigates

Risk of fraud is predictedthrough a

data mining tool

Page 8


9/40© Platon

Predictive analytics

Codan - Pricing

Old model – postal codes New model – 100 x 100 meter cells

Low risk

High risk

• Several parameters to determine the risk• Only a few from the customer• The rest is based on data

Page 9


10/40© Platon

Agenda


● BI Adoption


● Summing up

10


11/40© Platon

IT Governance

11

IT Governance: Specifying the decision rights and

accountability framework to encourage desirable

behavior in the use of IT

Governance Corporate governance

● The opposite of Governance: Anarchy (from Greek: ἀναρχίᾱ anarchíā,"without ruler“)

● "No rulership or enforced authority.” ● "Absence or non-recognition of authority and order in any given sphere.”

● "Act[ing] without waiting for instructions or official permission... The root ofanarchism is the single impulse to do it yourself: everything else follows fromthis.”


12/40© Platon

BI Governance

12

BI Governance is the framework and processes fordetermining the priorities, deployment practices, and

business value of enterprise business intelligence initiatives.

How do we get exe-

cutive level awareness

and support?

How do we resolve

conflicting interests?

Who decides what to

work on next?

How can we be more

proactive and

anticipate changing

business needs?

How do we quantify

and track the values of

our BI investments?


13/40© Platon

BI Governance

- Business and IT standpoints

13

BusinessInnovation

Flexibility

Responsiveness

Train

Users

Recommend

Actions

Analyze

informationDBA

Develop

ETL

Datamodelling

RequirementSpecs

Design

Front endDevelop

reports

User

support

Execute

Bus. Proc.

Standards

for reporting

IT

Cost effectiveness

Operational efficiency

ReliabilityScalability

BICC

IT

DW Business

unit

Business

unit

Business

unit


14/40© Platon

BI Governance

- Organisational structure

14

ProgramBoard

Coordinate &

prioritize

Coordinate& prioritize

Program level

Project C

SteeringCommittee

Project B

SteeringCommittee

Project A

SteeringCommittee

Project level

Operation level

BICC DW


15/40© Platon Page 15

IT Governance

Infrastructure and

operational applications

BI Governance

Business performance

and decision support

Governance relationships

Data Governance

Information quality

and processes

● The purist would claim they are independent


16/40© Platon Page 16

IT Governance

Data Governance BI Governance

Infrastructure

and operational applications

Information qualityand processes

Business performance

and decision support

Business strategy alignment

Legal compliance

Knowledge management

Project portfolio management

Service Level Agreements

Governance relationships

Business value tracking

…


17/40© Platon

Step 1: Define the governance

level of the BI Program

17

BI Methodology

BI Policies

BI Organisation

Common Data Definitions

BI Tools & Systems

One way Ad hoc Degree of federation

BI Architectures

BI Project prioritization

Step 1: Define the governance level of the BI Program

Step 2: Identify decision making ‟bodies‟ Step 3: Define decision areas and decision rights

Step 4: Design and implement governance processes


18/40

© Platon

Agenda


● BI Adoption


● Summing up

18


19/40

© Platon

What can drive better

deployment and adoption

Better BIadoption

Strategyclarification

Focus on usage

OrganisationalChange

Management

Communication,marketing and

branding

Other

19


20/40

© Platon Page 20

Change Management

I can not live

without my

Excel sheets.

Let‟s buildit and they

will come.

We earn

money

anyway.

The users

The managers

The BI people

I need my own

definitions.I don‟t want my

results to be

visible for all.

We know

what they

need.

Similar to ERP implementations?

The successful companies focuses 70 % of

the implementation resources on processes,

education and other soft aspects and only 30

% on technology


21/40

© Platon

● Branding…

● Provides a single identity when communicating about your BI Program

● Differentiates your „product‟ from other choices

● Create a logo

● Use it on reports, the intranet and all communications like newsletters,

status reports, presentations etc.

● Extend your brand through report certification

● A process of promoting a report to a mass audience

● Further drives the data integrity of your BI program and builds userconfidence

● Creates a adoption effect as management only wants to view reportsthat have been branded and/or certified

Communication, marketing and

branding

Page 21


22/40

© Platon

Agenda


● BI Adoption


● Summing up

22


23/40

© Platon

Does this look familiar?

23

Analysis Design Development Implementation

Increasing costs to fix defects

discovered later due to

incorrect requirements


24/40

© Platon

BI solution types

24

Dashboards / cockpits

Predictive analytics / data mining

Ad hoc analytics / OLAP

Reporting

Alerts and exception

GIS and other visualization

Balanced scorecard

Performance management

Analytical CRM

http://images.google.dk/imgres?imgurl=http://www.miamidolphins.com/email5.gif&imgrefurl=http://www.miamidolphins.com/dolphinstonight.asp&usg=__bZ48XzbMPTLVU40NQs5LJsMxMS4=&h=350&w=315&sz=85&hl=da&start=3&tbnid=-z2A-JbUsqleuM:&tbnh=120&tbnw=108&prev=/images?q=email&ndsp=18&hl=da&sa=Nhttp://www-01.ibm.com/software/data/cognos/images/screenshots/c8bi-analysis-screenshot1.jpghttp://www.cognos.com/products/business_intelligence/applications/Analytics_Financial.jpg


25/40

© Platon

Types of (BI) requirements

● Business requirements

● Information requirements

● Functional requirements

● Detailed report / usage requirements

● Other requirements

● How about defining the business processes that apply the newinformation to managerial actions?

25

What is the business

need, pain or problem?

What business questions

do we need to answer?

What data is necessary to

answer those questions?

How do we need to use the

resulting information to

answer those questions?

All the other stuff – AKA nonfunctional requirements

Detailed layout etc


26/40

© Platon

David McCandless: The beauty of data visualization

Design inspiration

http://www.ted.com/talks/david_mccandless_the_beauty_of_data_visualization.htmlhttp://localhost/var/www/apps/conversion/tmp/scratch_6/catalog/0636920000617/previewhttp://www.ted.com/talks/david_mccandless_the_beauty_of_data_visualization.htmlhttp://www.ted.com/talks/david_mccandless_the_beauty_of_data_visualization.htmlhttp://www.ted.com/talks/david_mccandless_the_beauty_of_data_visualization.html


27/40

© Platon

The requirement specification

document – The simple version

27

● Introduction


● Business process requirements



● Detailed report / usage req.

● Other requirements



29/40

© Platon


document – The expanded version

29

● Executive summary

● Introduction


● Business process requirements



● Detailed report / usage req.

● Security requirements

● Performance requirements

● Operational requirements● Migration requirements

● User doc. and training requirements

● Other requirements http://www.volere.co.uk/template.htm


30/40

© Platon

Business process requirements

● “Change” is the keyword

● Textual description is ok

● Or use a swim lane design where the workflow or supportinginstructions, procedures or use cases are changed

30

Procedure

–Prioritize order based oncustomer rating by…

Use Case

–When the sales rep enters… The system shows…


31/40

© Platon

Cover all information

requirements

● Ask, ask, ask…

● Explain and exemplify - with all stakeholders

● Facts

● Business rules

● Dimensions and hierarchies

● Value sets

● Timeliness

● How „fresh‟ should the data be (update frequency)

● Specific dates the new data is needed

● History

● How much calendar time should be covered

● How about changes in hierarchies - program requirement could betype 2 SCD and project requirement could be type 1 SCD

31


33/40

© Platon

The process & methods

33

Identifystakeholders

Clarify methodof collecting

requirements

Plan and invitefor meetings

Prepare andsend materialor mindset at

meeting

Conduct /collect

Consolidate/ document Validate/prioritize

Update

requirementspec.

Send forreview Verify andsign off

● The sub activities for specification process is outlined in the figure

below.


34/40

© Platon

The process & methods

34

Identifystakeholders

Clarify methodof collecting

requirements

Plan and invitefor meetings

Prepare andsend materialor mindset at

meeting

Conduct /collect


37/40

© Platon

BI Requirements

- Business and IT standpoints

37

Innovation

Flexibility

Ease of use

Reliability Scalability

Accuracy

CorrectnessSpeed

User Experience

BICC ?


38/40

© Platon

Pay attention to data quality

● Poor data quality is the second most common reason for BI

failure

● Data quality is a big risk

● Get a clear picture on data quality issues as early aspossible - during analysis or even before

● Don‟t wait until the development takes place

38


40/40

Summing up

● Value comes from decisions and changed behavior – notfrom providing reports

● Information requirements are key in all BI projects

● Make the right balance between time and perfection

● Expect change and expect to manage change

2 Jørgen Steines Platon

Documents

Transcript of 2 Jørgen Steines Platon