bi end to end summary - 13mar13

7/29/2019 BI End to End Summary - 13Mar13

1/62

Business Intelligence

IT solutions and businesspractices used for transforming

data into information through

the integration of sales,

marketing, ops, and other

business data sources

Analytics

A way of thinking and acting inthe breaking of problems into

parts and using inferences

based on data to drive

decisions


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IT solutions and business practices

used for transforming data into

information through the

integration of sales, marketing, ops,

and other business data sources

Analytics

A way of thinking and acting in the

breaking of problems into parts and

using inferences based on data to

drive decisions

Data Warehouse Warehouses

Data Marts

Subject Areas

Data

Data Integrity

Single Source of

Authority

Governance

Metrics

Terms/Definitions

Metric Definitions

Source Systems

Configuration

Governance

Dashboards &Reports

Modeling

Dash-Boarding

Enterprise and

Functional

Support

Business Objectives

Desired Results

Answering the

Whys

Measurement

Leading In-Progress

Lagging

Analysis

Trending Forecasting

Decision-Making

Progress Measurement

Innovation & Continuous Improvement

Business Practices Org Structure

End-to-End

Consistent

Managed Change


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Level 1Initial: Processes unpredictable, poorly controlled, reactive;

zero to 20% work complete.Level 2Managed: Projects of organization ensure requirements are

managed and, processes are planned, performed, measured, and

controlled; 21% - 40% work is complete.

Level 3Defined: Processes are well characterized and understood,

and are described in standards, procedures, tools, and methods; 41% -60% work is complete.

Level 4QuantitativelyManaged: Sub-processes are selected that

significantly contribute to overall process performance. These sub-

processes are controlled using statistical and other quantitative

techniques; 61% - 80% work is complete.

Level 5Optimizing: Processes are continually improved based on a

quantitative understanding of the common causes of variation

inherent in processes; 81 100% work is completeDerived / Source:

http://www.tutorialspoint.com/cmmi/cmmi-maturity-levels.htm


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TechnologyBusiness

Practice

Analytics Decision-Making

Data

Data W-

House Metrics Analysis Goals Base-Line Trends/FC

Academic

Finance /

HR

Mkt / Sales

Operations

Foundation




information through the integration of

sales, marketing, ops, and other


Analytics


breaking of problems into parts

and using inferences based on data

to drive decisions


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BUSINESSTECHNOLOGY

DATA AND GOVERNANCE

OUTPUTSDECISIONS & INNOVATIONS

BI Pieces & Parts

3/13/2013 By Ed Jarecki 5


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BI: Pieces & Parts

Business

Policy

Terms & Definitions

Measures & Metrics

Business Process &

Practice

Technology

Application

Configuration &Setup

Security

BI Platform

Data & Gov.

Security

Config. & Setup

Policy

Changes

Outputs

Dashboards &Reports

Trends,Forecasts

Decisions &Innovations



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BI: Pieces & PartsTodays Focus Areas

Business

Policy

Terms & Definitions

Measures & Metrics

Business Process &

Practice

Technology

Application

Configuration &Setup

Security

BI PlatformData & Gov.

Security

Config. & Setup

Policy

Changes

Outputs

Dashboards &Reports

Trends,Forecasts




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BUSINESSTECHNOLOGY

DATA AND GOVERNANCE


BI Pieces & Parts

Business

Policy

Terms & Definitions

Measures & Metrics

Business Process &Practice

Technology

Application

Configuration & Setup

Security

BI Platform

Data & Gov.

Security

Config. & Setup

Policy

Changes

Outputs

Dashboards &Reports

Trends, Forecasts




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Terms &Definitions

Metrics

Coding Structure

SystemCoding &

GapAnalysis

SystemConfiguration &

Set-Up

BusinessProcess

Alignment

Operations Marketing Product Executive

Outputs

Data &Reports

Trends &Forecasts

BI Pieces & Parts: Business

General Approach



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Terms & Definitions

Term: a word or group of words designatingsomething in a particular field, as atom in physic,quietism in theology, adze in carpentry, or districtleaderin politics.

Source: http://dictionary.reference.com/browse/term

Definition: the act of making definite, distinct, orclear; a defining: We need a better definition ofher responsibilities.

Source: http://dictionary.reference.com/browse/term


Terms &Definitions

Metrics

Coding Structure

SystemCoding &

GapAnalysis


Set-Up

BusinessProcess

Alignment

Outputs

Data &Reports

Trends &Forecasts
http://dictionary.reference.com/browse/termhttp://dictionary.reference.com/browse/termhttp://dictionary.reference.com/browse/termhttp://dictionary.reference.com/browse/termhttp://dictionary.reference.com/browse/termhttp://dictionary.reference.com/browse/termhttp://dictionary.reference.com/browse/term


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Terms & DefinitionsOf course, when considering the question from

business and business intelligenceperspectives, the important questions include

What are the terms used in communicating

and explaining your business?

What regulatory, industry, and legal terms and

definitions are important for your business?

Is the organization aligned on the terms and

their respective meanings?



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Terms & Definitions - Examples

Re

f#

Reporting

Dime

nsion

(Opsvs.

Mktg)

Future State

Dimension

Business Definition for Data

Dictionary Definition Notes

7 OPSRequirements of

Completion

% Complete as calculated by the degree

audit (including # of applicable credits)

Future State - Level 3 Dimensions (another

sub-set of requirements of completion

dimensions) e.g., What percentage of core vs.

non-core have been completed?

16c OPS "Other" Course(s) Placeholder for future innovationWould include non-credit training to be

developed.

18b OPS Non Credit Unit(s)Indicates participation in a class that

does not accrue credit hours

Would include non-credit training to be

developed.

System needs to house the number of non-

credit units for financial conversion (e.g. non-

credit course "A" is worth 2 non-credit units)

35b OPS Enhanced CourseA course offered in class with optional

online components

From our dimensions visio document: 0-25% of

class activity is offered in a virtual environment.

35c OPS Blended CourseAn online course with in-class

components

From our dimensions visio document: 75% or

more of class activity is offered in a virtual

environment.



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Metrics

Parameters or measures of

quantitative assessment used

for measurement, comparisonor to track performance or

production.Source:

http://www.investopedia.com/terms/m/metrics.asp#ixzz2MKH0oB7Z


Terms &Definitions

Metrics

CodingStructure

SystemCoding &

GapAnalysis

SystemConfiguration& Set-Up

BusinessProcess

Alignment

Outputs

Data &Reports

Trends &Forecasts
http://www.investopedia.com/terms/m/metrics.asphttp://www.investopedia.com/terms/m/metrics.asphttp://www.investopedia.com/terms/m/metrics.asphttp://www.investopedia.com/terms/m/metrics.asphttp://www.investopedia.com/terms/m/metrics.asphttp://www.investopedia.com/terms/m/metrics.asphttp://www.investopedia.com/terms/m/metrics.asphttp://www.investopedia.com/terms/m/metrics.asphttp://www.investopedia.com/terms/m/metrics.asphttp://www.investopedia.com/terms/m/metrics.asphttp://www.investopedia.com/terms/m/metrics.asp


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Metrics: Getting to Metrics

In support of organizational,

department, or team goals,what are the areas ofperformancethat need to

be measured?



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Metrics: Definitions

Is there a consistent understanding?

PersistenceMeasured by initial term

student enrolls and

remains enrolled in

subsequent terms.

RetentionMeasured annually for

student enrollment in

initial term in initial year,

and subsequent year(s)thru completion.

Graduation RateMeasure at 6 year mark for

IPEDS, 6-9 years for CSRDE

and, 2-11 years for BU.

Student completes programrequirements and is

conferred.

EnrollmentEnrollment count (head

count, hours, revenue.

Drop / WithdrawalMeasured by Term and by

Course.Student dropping from

courses.

Time sensitive.

Student CountsComparison between

previous term/year countsand variances.

Show growth/decline trends

over time.

Identify trends and forecast.



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Metrics: Outline desired outputs

PersistenceMeasured by initial term

student enrolls and

remains enrolled in

subsequent terms.

RetentionMeasured annually for

student enrollment in initial

term in initial year, and

subsequent year(s) thru

completion.

Graduation RateMeasure at 6 year mark for

IPEDS, 6-9 years for CSRDE

and, 2-11 years for BU.

Student completes program

requirements and is

conferred.

EnrollmentEnrollment count (head

count, hours, revenue.

Drop / WithdrawalMeasured by Term and by

Course.

Student dropping from

courses.

Time sensitive.

Student CountsComparison between

previous term/year counts

and variances.

Show growth/decline trends

over time.

Identify trends and forecast.

Show and measure growth/decline rates over time.

Identify trends and forecasts.

Establish root cause(s).3/13/2013 By Ed Jarecki 16


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MetricsMetrics

Understanding requires analyzing from many

perspectives

Academic Level

Freshman

SophomoreJunior

Senior

5+ Senior

Student AttributeActive

Inactive

Degree Awarded

Student State

New

Continuing

Instructional

Format

Retail

Custom

Delivery Format

Traditional

Cohort

Other

Student Type

Degree Seeking

Non-degree Seeking

TransferFirst-time Freshman

Visiting

Vertical MarketInternational

Corporate

ComCollege

Military

Other



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** OverallRetention

Rate

Metrics: Planning and Organizing

Retention* Measure

revenue

earned from

increased

retention

Grad

Under-grad

Online

In-class

Part-Time

Full-Time

Current:

75%; $XX

Goal:80%; $XX

Note**: Sample data only

Traditiona

l

Cohort

Note*: Define; 1% retention rate improvement = $XX revenue



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** OverallRetention

Rate

Retention* Measure

revenue

earned from

increased

retention

Grad

Under-grad

Online

In-class

Part-Time

Full-Time

Current:

75%; $XX

Goal:80%; $XX

Traditiona

l

Cohort

Of course, there is still much to do

Note: Sample data only

Key Questions & Actions

Is the revenue recognition

method in alignment with?

How are drops to be

considered? Need to align

How is student value

calculated?3/13/2013 By Ed Jarecki 20


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And



Are system configurationsappropriately setup?

Terms &Definitions

Metrics

Coding Structure

SystemCoding &

Gap

Analysis

SystemConfiguration

& Set-Up

BusinessProcessAlignment

Outputs

Data &Reports

Trends &Forecasts


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Coding Structure: BU Example

Current State Coding Analysis

Analyze SIS (Student Information System) codes currently in use Define standard parameters and definitions of each code type

Analyze codes in scope against SIS parameters/definitions to

identify coding inconsistencies, etc.

Complete a detailed analysis of non-optimized/exception basedcoding to capture specific business requirements

Conduct research to increase understanding of system functionality

Future State Coding Analysis

Complete detailed mapping for all future state coding metrics,formulas, and dimensions to understand system equivalents

Develop recommendations to support identified gaps and coding

requirements



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Coding Structure

BU Summary Results

Currentstate analysis 355 total codes analyzed

49 of 133 service indicators were categorized as exceptions

98% of student groups manually maintained increasing risk

of errors

Future state analysis 84 future state dimensions

and eight operational reports analyzed

67 of these codes tied to existing fields in the database

Seven dimensions tied to an existing student code

10 dimensions identified as current gaps in coding set up



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Coding Structure

BU Summary Recommendations

Establish standard governance processes and practices to

maintain consistency among student coding

Establish project team to complete all process, coding, and

system configuration changes to support the student

operations Future State metrics and dimensions

Optimize current state codes leveraging system functionality

for automation while completing maintenance and clean upof inactive codes

Defer long-term opportunities and align with project priorities



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Business Process & BI


Terms &Definitions

Metrics

Coding Structure

SystemCoding &

GapAnalysis


Set-Up

Business

ProcessAlignment

Outputs

Data &Reports

Trends &

Forecasts


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Often missed in the evaluation and

selection of a Business Intelligence solution

is the need for alignmentbetween desiredoutputs and the data generated from

business processes and practices




information through the integration

of sales, marketing, ops, and other


3/13/2013By Ed Jarecki

26


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As organizations evolve from leveraging

available data to developing management

reports, scorecards, dashboards and real-time BI, the need to align and optimize

business practices is essential

3/13/2013 27




information through the integration

of sales, marketing, ops, and other


By Ed Jarecki


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Outputs



What are the questions to beanswered?

What trends and forecasts are

required?

What are the drill-down

requirements?

Terms &Definitions

Metrics

CodingStructure

SystemCoding &

GapAnalysis

SystemConfiguration

& Set-Up

BusinessProcess

Alignment

Outputs

Data &Reports

Trends &Forecasts


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What actions are necessary to grow overall enrollments by

10% year-over-year?

What is the enrollment (FTE and hours) trend over

the past 10 years?

What programs have grown and shrank by

>10% year-over-year over the past 5 years?

What is the profile for students in the

top 5 growth programs? Top 5

declining programs?3/13/2013 By Ed Jarecki 29

Outputs: ExampleWhat questions need to be answered?

GettingTo

Action


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OutputsEXAMPLE REPORT DEFINITION

Student Retention

Report Description: Measured annually for student enrollment in initial term in initial year and subsequent year(s)

thru completion.

Purpose: Measures how students persist year-over-year

Assumption Report will allow defined comparison of same point in time for previous periods of time (multiple)

Primary Reports: N/A

Attributes:

How a student persists year-to-yeara. Can start any time within Academic Year

If student attends at least one term each year, will be part of retention reportb. Final check is run 21 days (class start +21 days)

i. 14 days to account for Drop/Add period and Attendance Verificationii. 7 days for business processing

c. Spot checks are done w/in current year

Report Frequency:

Monthly

As necessary / on demand

Policy Items: Do not change Students original cohort start date unless the level of degree changes. The

cohort start date remains the same. Students can transfer between active and inactive statusuntil they reach status of Awarded. Non-degree seeking students will be excluded.



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Outputs: ANALYTICS COMPETENCY

What is analytics competency?

Knowledge of what tools are available and how to use them Knowledge of data

Where the data is located

What the data source of authority is

Critical thinking The best data, models and tools will notproduce results without the right people supporting analytics

efforts

People: People generate insights from models. The same people are

also critical in gaining leadership support for analytics-based outcomes

driving organizational change

Modeling: Beyond the creation and purchase of analytic models,

analytics capabilities will evolve, environmental conditions will change,

and integration challenges will intensify resulting in a need to change

data, models, and outputs

Level of data integrity

Access to data



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Business Practice: Key Lessons

Culture analytical vs. intuitive decision-

making, broad vs. focused strategy Analytic Mindset breadth of business

users understanding; often limited to

current duties

Terms &Definitions

Metrics

CodingStructure

SystemCoding &

GapAnalysis

SystemConfiguration

& Set-Up

BusinessProcess

Alignment

OutputsData &Reports

Trends &Forecasts

Varying Skills range

and limit of end-userunderstanding

relative to best/most

proper use of source

applications (e.g.,

campus solutions) Roles & Responsibilities fundamentally

important to understand, define, and establish at

project start



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Business Checklist Are terms used in communicating and explaining your business defined?

Are regulatory, industry, and legal terms and definitions important for your business

defined?

Is the organization aligned on the terms and their respective meanings?

In support of organizational, department, or team goals, are areas of performance that

need to be measured defined?

Are goals defined in alignment with each of area of performance?

Have measurement dimensions been defined?

Are metric formulas aligned? Are system configurations setup in alignment with metrics, formulas, and desired

outputs?

Are business processes in alignment with data needs and desired outputs?

Have business questions to be answered been defined?

Have trends and forecasts requirements been defined?

Are report and dashboard drill-down requirements been defined?

Are resources available and accessible that have the necessary dataknowledge?

Are resources available and accessible that have the necessary toolknowledge?

Are resources available and accessible with necessary problem solving and critical

thinking skills?



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BUSINESSTECHNOLOGY

DATA AND GOVERNANCE


BI Pieces & Parts

Business

Policy

Terms & Definitions

Measures & Metrics


Technology

Application


Security

BI Platform

Data & Gov. Security

Config. & Setup

Policy

Changes

Outputs

Dashboards &Reports

Trends, Forecasts



BI S C


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BI System ComponentsMetrics, Baselines,

& Goals,

Business

Process Inputs

Data Sources, System Configuration, Data

Management and Governance

Data Architecture, Data Models, Dashboards &

Reports



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BI System: Getting to Value



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Data Warehouse: Basic Structure


SubjectArea

Student Information System

(Campus Solutions)

Campus Community

StudentTab

le

2

Stude

ntTable

3

Student Table 1

StudentTable 4

Student Table 5


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Campus Solutions

Data Warehouse: Basic Structure


SubjectArea

Campus Community

Student

Table

2Student

Table 3

Student Table 1

Student

Table 4

Student Table 5

Student Financials

SF Table 5

SFTable

2SF

Table

3

SF Table 1

FMS

General Ledger

GL Table 1

GL Table

4

GL Table 5

Accounts

Payable

AP Table 5

AP Table

3

AP

Table

4

G

LTable

2

SF Table

4

AP Table

1


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Data Warehouse: Setup & Configuration

Ensure there is appropriate time to provision

Roles and responsibilities clearly defined (business andtechnology)

Create and execute a plan to fill skill gap areas

Define organizations initial questions to be answered

Sponsor needs to clearly define the requirements of a

successful implementation


Plan, plan, plan Create a planthat outlines clearly defined goals,

architecture, sources of data,tasks, delivery timelines, etc.

Consider turnoverOrganizational and vendor (whenapplicable)

h


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Data Warehouse: Data Structure

ETL Translation of relational model to Star schema.

Star Schema Normalized with each dimension represented by a single

table

Facts/related facts in center

Star points are different dimensions in which, to filter and analyze data

Snowflake schema Logical arrangement of tables in a

multidimensional database. Centralized fact table connected withmultiple dimensions.

Trade-offs: Performance (driven by additional joins ETLs more complicated

versus Star Schema)

Changing Dimensions Necessary for point-in-time analysis and

trending Rapid Change: Snapshot (daily event/change capture)

Easier to apply supporting need for rapid change

Slow Change: CDC (Change Data Capture effective date driven table)

Saves space3/13/2013 By Ed Jarecki 40

h


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Data Warehouse: Security

Security: Keep structure as simple as possible Will naturally become more complicated over time

Start with Report-levelof security (i.e., restrictions based on report

access rules)

Move to Columnar-levelof security (i.e., who has access to what facts

and dimensions)

Row-levelsecurity is the limits access based on content of data being

analyzed (e.g., ability to access drops for College of Business but, not for

College of Science and Technology)

Governance: Must control what gets published

Similar to other reporting methods, free sharing of data and reportswithout controls, can easily result in unmanageable list of reports

Without appropriate controls, ability to consistently produce one version

of the truth is reduced dramatically over time


h


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Data Warehouse: Key Lessons

ETL, ETL, ETL expertise, maintenance and,

resource requirements, constancy of change,etc.

Performance right sizing for performance

Security Complexity security of source

apps needs to be in correct state

Education relative to data available, dataneeded, business practices, and sources of

data, etc.

ReportingDoes not initially ever? Replace

other operational reporting solutions?

SaaS vs. In-House lessons learned inhosting vs. in-house (e.g., reliance on

provider to provide correct competencies in

environment set up)


T h l Ch kli t


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Technology Checklist

Are BI roles and responsibilities, technology and business, clearly defined

and understood?

Has the organization defined the questions to be answered? (at least the

initial set of questions to be answered)

Has senior leadership / sponsor outlined requirements for success?

Has a comprehensive plan been established and aligned with senior

leadership / sponsor expectations

Has the data schema been selected that is in alignment with planned use anddemand?

Has a data warehouse data and report/dashboard security plan been

established?

Has governance been established that ensures/delivers to the required level

of data integrity? Do senior leadership and other key stakeholders understand all of the BI

Pieces and Parts?

Is there appropriate understanding of the role and mission of BI versus

operational reports?



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BUSINESSTECHNOLOGY

DATA AND GOVERNANCE


BI Pieces & Parts

Business

Policy

Terms & Definitions

Measures & Metrics


Technology

Application


Security

BI Platform

Data & Gov. Security

Config. & Setup

Policy

Changes

Outputs

Dashboards &Reports

Trends, Forecasts



D


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Data What Is Data?...

Items of information Bing Dictionary

Individual facts, statistics, or items of information Dictionary.com

Factual information used as a basis for reasoning, discussion, or

calculation Merriam-Webster.com

The correct question?What business questions are we trying to answer?

Of course, this leads to the data questions

What data is needed?

What data is available?

Where is it located?

What is the integrity level of the data?

and, many more



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Getting to Answers

Business

Question

or

Problem

Statement

Modeling

Evaluation

Data

Preparation

Information,Knowledge,

Decision-

making

Data

Understanding



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What data is needed?...

Business Question or Problem Statement Understand and define the business problem

Data Understanding Collect, describe, and explore the data

Identify quality problems of the data

Data Preparation Develop data models

Collect, cleanse, and format data

Prepare data for modeling tool by selecting

tables, records, and attributes ensuring meaningof data is notchanged

Create new derived attributes (e.g., average,

range, minimum, maximum, etc.)

Partnership

between IT

and business

is critical

Business

Questionor

ProblemStatement

Modeling

Evaluation

DataPreparation

Information,

Knowledge,

Decision-making

DataUnderstanding



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DataMap Example

CS CRM

stdnt

_enrl

class

_tbl

crse

_offe

r

scc_priorw

ork

bv_ea_

bellu

_tbl

scc_pe

rdata_

qvw

srvc_ind

_data

stdnt

_car

_term

instr_

class

_vw

stdnt

_grps_his

t

acad

_plan

acad

_plan

_tbl

rq_grp

_tbl

a

System Table (Record) CSSystem Table (Record) CS

l

ad_plan

_vw

FieldPe

rsist

ance

(8)

Reten

tion(8)

GraduationR

ate(9)

Enrollm

ent(2)

Add/

Drop/

With

draw

al(2)

StudentC

ount

(

Comp

leti

Cl

Metrics Metrics

Student Characteristics / x x x x

Active

x x x x

Inactive

x x x x

eturning Students, etc) -

Degree Completed x x

Degreee Awarded

x x

Degree Approved x x

-

Derived

Derived

-

completion_term

degr_chkout_stat

degr_chkout_stat

x x x x x

x8 x8 x2

x8 x8 x2

x9 x9 x9 x

x x x x

x x x x

Academic Structure x x x x x x x

uirements of Completionx x x

Other Dimensions (TBD) -

Section x x

Course x x x

Major x x

College x x x

Session x x

-

Derived

-

class_section

Derived

Derived

acad_group

session_code

x x x x x

x

x1 x1 x1

x2 x2 x2 x4

x9 x9 x9 x9

x2 x2 x2 x4

x2 x2

Business

Question

orProblem

Statement

Modeling

Evaluation

Data

Preparation


Decision-making

DataUnderstanding



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Modeling Data selected

Modeling and evaluation activities loop

until desired outcome is achieved

Evaluation Models evaluated Does model achieve business objective?

Have all business issues been considered?

Business owners decide how to use results

Deployment Reports and dashboards created

Outputs leveraged for decision-making

Generating results...

Partnership

between IT

and business

is critical

Business

Question

orProblem

Statement

Modeling

Evaluation

Data

Preparation


Decision-making

DataUnderstanding


Data: Key Lessons


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Data: Key Lessons Data Needs

How willing/flexible is your organization to change practices to support data /

solution needs?

Is there process consistency / standardization?

What does your institution want to know?

Business

Question

or

Problem

Statement

Modeling

Evaluation

Data

Preparation

Information,

Knowledge,

Decision-

making

Data

Understanding

Data RefreshHow real-timedoes the data need to be?

Data GovernanceWhat are

your data integrity & securitycontrols? Are they enough?

Data Source

Where is the source data?

Is there support for

integrating / pulling data

from non-owned sources? Data Speed

Processes and utilities/tools for warehouse integration

Skill and tools for setting up / modifying data marts and subject areas

Data KnowledgeHow it is used? Where it is at?

ResourcesCosts (e.g., hosting, fte, consulting, etc.) for adding data marts, etc.?3/13/2013 By Ed Jarecki 50

Data The foundation for


51/62

Data The foundation for

knowledge for understanding

Business

Questionor

Problem

Statement

Modeling

Evaluation

Data

Preparation

Information,

Knowledge,

Decision-making

Data

Understanding

for decision-making3/13/2013 By Ed Jarecki 51

G


52/62

Governance What is Governance?...

Governance is about promoting organizational fairness,transparency and accountability. The governance structure

specifies the distribution of rights and responsibilities of

organization executives, managers, and other stakeholders,

and spells out the rules and procedures for making decisions.Definition derived from: KnowledgeLeaderSM provided by Protivity

The real question?

Why is Governance so important?

Personal information is valuable and private

Data and information are important organization

assets


G S Att ib t


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Governance Success Attributes

Governance structures will vary; however, there are

characteristics necessary for success Participation:Appropriate participants; constructive participation

Policy: Clearly defined; enforced impartially

Transparency:

Processes & information directly accessible to those concerned

Enough information is provided to understand and monitor

Responsiveness: Institution and processes try to serve all stakeholders

Consensus Orientation: Mediate differing interests to reach a broadconsensus on what is in the best interests of the organization

Equity: All have opportunities to improve or maintain their well-being

Derived From / Source: UNDP (1997) Governance for Sustainable Human Development. United Nations

Development Program


b


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Governance Success Attributes

Governance structures will vary; however, there are

characteristics necessary for success cont.

Effectiveness and Efficiency: Processes produce results that meetneeds while making the best use of resources

Accountability: Decision-makers are accountable to the organization,students, and stakeholders of the organization

Strategic vision: Leaders and the public have a broad and long-termperspective on good governance and human development, along with a

sense of what is needed for such development. There is also an

understanding of the historical, cultural and social complexities in which

that perspective is grounded.

Derived From / Source: UNDP (1997) Governance for Sustainable Human Development. United

Nations Development Program


Governance: Example


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Governance: Example

Policy & Decision-Making Actions

Review policy relative to inactive, recycled, and/or

reactivating codes

Define ownership for codes shared across

departments (e.g., first time freshman) Review recommendation and policy for effective-

dating practices

Provide feedback & decisions required to support

development of future state reporting criteria

Review future coding parameter changes/updates to

identify process and reporting impacts


G D i i ki


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Automate Student Groups Eliminate 23 manual student

groups

Conduct Fit-Gap: Leverage PeopleSoft Graduation Process

Complete end-to-end process analysis to developunderstanding of requirements and implement a

delivered and automated solution to replace manual

graduation process by Nov 2012

Based on findings develop configuration & set-up plan tosupport implementation for January 2013

System Maintenance & Clean Up Inactivate 54 unutilized

codes

Governance Decision-making

Bellevue University Examples


Governance: Model Example


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Governance: Model ExampleStudent Coding Governance Committee Structure

StudentCoding

AnalysisTeam

Policy

Committee

Governance

Committee

Con

figuration&

SetUp

Committee

VPCommittee

Project Phase Ops & Maintenance Phase

Develop, integrate, &

management of

practices aligned with

Policy Committees

vision

Communication roll-out

to staff & faculty

Milestone:

Current state

Analysis

complete

Mapping of future state

reqts to current state

code

High Level Analysis of CS

& CRM data

More detailed analysis

of BUs exception coding

Recommendation

for pending policies

to VP committee

Direction & Vision

for governance

process & set up

Milestone:

Policies Defined

Milestone:

Governance Set-

up

Milestone:

Student Coding

Recommendation

Conduct system &

best practice research

for functionality

Complete formal

Recommendation

Configuration team

set-up

Understanding of

governance process

& defined policies

Implementation of

student codingrecommendation

Milestone:

CS & CRM

System Set-up

Continued

maintenance of

ongoing policy

recommendations &

continuous

improvement

Evaluation &

decisions of new

code requests

Continued

enforcement of

practices aligned

with policies

Ongoing maintenance

& configuration of

systems & continuous

improvement

PROJECT TEAM 1

AVPS

DIRECTORS

Initial policy

decisions

Initial policy

decisions to kick-off

the project & create

context for

governance set-up

Ongoing review of

Policy commiitee

recommendations &

final decisions

VPs

PROJECT TEAM 2

Pending Policies

Policy

Recommendations

Policy Decisions

Milestone:

Governance

Vision

completed

Policy

Recommendations

Final Policy

Decisions

New Policies

New codes & practices

per policy

Policy Decisions


Governance: Key Lessons


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Leadership Is there

leadership buy-in?

Change Management

Day-to-day: What is the

impact of changes in

one function on

activities in another?

Data Maintenance

How will data integritybe maintained or,

improved?

Change Management

Organizational: How do

you plan to handlechanges in strategy and

business needs

Governance: Key Lessons

Student Coding Governance Committee Structure

Stud

entCoding

Ana

lysisTeam

Policy

Committee

Governance

Committee

Configuration&

SetUp

Committee

VPCommittee

Project Phase Ops & Maintenance Phase

Develop,integrate, &

management of

practices alignedwith

Policy Committees

vision

Communication roll-out

to staff& faculty

Milestone:

Current state

Analysis

complete

Mapping offuture state

reqts to current state

code

HighLevel Analysis ofCS

& CRM data

Moredetailed analysis

ofBUs exception coding

Recommendation

for pending policies

to VPcommittee

Direction& Vision

for governance

process & set up

Milestone:

Policies Defined

Milestone:

GovernanceSet-

up

Milestone:

Student Coding

Recommendation

Conduct system&

best practiceresearch

for functionality

CompleteformalRecommendation

Configurationteam

set-up

Understanding of

governanceprocess

& definedpolicies

Implementationof

student coding

recommendation

Milestone:

CS& CRM

SystemSet-up

Continued

maintenanceof

ongoing policy

recommendations &

continuous

improvement

Evaluation&

decisions ofnew

coderequests

Continued

enforcement of

practices aligned

withpolicies

Ongoing maintenance

& configurationof

systems & continuous

improvement

PROJECT TEAM 1

AVPS

DIRECTORS

Initial policy

decisions

Initial policy

decisions to kick-off

theproject & create

context for

governanceset-up

Ongoing reviewof

Policy commiitee

recommendations &

final decisions

VPs

PROJECT TEAM 2

Pending Policies

Policy

Recommendations

Policy Decisions

Milestone:

Governance

Vision

completed

Policy

Recommendations

Final Policy

Decisions

NewPolicies

Newcodes & practices

per policy

Policy Decisions


Data & Governance Checklist


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Data & Governance Checklist


What business questions is your organization trying to answer?

What data is needed?

What data is available?

Where is the data located?

What is the integrity level requirement for the data?

How real-time does the data need to be?

Is there process consistency / standardization?

What are your data integrity & security controls? Are they enough?

Is there support for integrating / pulling data from non-owned sources?

Data Knowledge Is it available?

Are all costs (e.g., hosting, FTE, consulting, etc.) understood for adding

data marts, ETL management, etc.?

Has data ownership been defined (i.e., edit, read, no access)?

Has data and system Governance been established?

Have data and security policies and practice guidelines been reviewed and

updated?

Has a change management plan been established to handle changes in

strategy and business needs?

BI and Analytics


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BI and Analytics

Are You Ready?Exercise 20 minutes

Considering the BI inputs discussed today, on the chart

on page 84, rate your organizations readiness in the

area(s) in which BI is focused or planned. (5-10 minutes)

In teams of three to five,discuss your

organizations readiness

for success? (10 15

minutes) Note what actions you

will you take to improve

readiness?



IT solutions and business practices used

for transforming data into information

through the integration of sales,

marketing, ops, and other business data

sources

Analytics


breaking of problems into parts and using

inferences based on data to drive

decisions

Data Warehouse Warehouses

Data Marts Subject Areas

Data

Data Integrity Single Source

of Authority

Governance

Metrics

Terms/Definition

s

Metric

Definitions

Source Systems Configuration Governance

Dashboards & Reports

Modeling Dash-

Boarding

Enterpriseand

Functional

Support

Business Objectives

Desired Results

Answering the

Whys

Measurement

Leading

In-Progress

Lagging

Analysis Trending Forecasting

Decision-Making Progress Measurement

Innovation & Continuous Improvement

Business Practices Org

Structure

End-to-End Consistent

ManagedChange


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IT solutions and business practicesused for transforming data into

information through the integration of

sales, marketing, ops, and other


Analytics

A way of thinking and acting in thebreaking of problems into parts

and using inferences based on data

to drive decisions

TechnologyBusiness

Practice

Analytics Decision-Making

Data Data W-House

Metrics Analysis Goals Base-Line Trends/FC

Academic

Finance /

HR

Mkt /Sales


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Level 1Initial: Processes unpredictable, poorly controlled, reactive;

zero to 20% work complete.

Level 2Managed: Projects of organization ensure requirements are

managed and, processes are planned, performed, measured, and

controlled; 21% - 40% work is complete.

Level 3Defined: Processes are well characterized and understood,

and are described in standards, procedures, tools, and methods; 41% -60% work is complete.

Level 4QuantitativelyManaged: Sub-processes are selected that

significantly contribute to overall process performance. These sub-

processes are controlled using statistical and other quantitative

techniques; 61% - 80% work is complete.Level 5Optimizing: Processes are continually improved based on a

quantitative understanding of the common causes of variation

inherent in processes; 81 100% work is completeDerived / Source:

bi end to end summary - 13mar13

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