01 high maturity in complex information management...

High Maturity in complex Information

Management environment

Standardization is the key

Deloitte Consulting India Pvt Ltd.

High Maturity Best Practices (HMBP) 2012

Chandu Mukkavalli

Monica Kavatkar

Neetu Kar

High Maturity in complex Information

Management environment

Standardization is the key

High Maturity Best Practices (HMBP) 2012

Agenda

• Introduction

• Challenges

• Approach and Solution

• Critical Success Factors

High Maturity in complex Information Management2 © 2012 Deloitte Global Services Limited

Introduction

3 © 2012 Deloitte Global Services Limited

Background

Objective was to build an effort forecasting modelInformation Management (IM) practice.

The model would enable converging the differenceacross the following phases:

• Project Planning phase (Initial effort planned by projects)

• Execution phase (Additional effort due to planned / unplanned

High Maturity in complex Information Management

• Closure phase (Total actual effort expended in the project)

This translated to the need of having predicting the probability of meeting effort

4

model for all technology framework projects in

difference between planned and actual effort

effort planned by projects)

planned / unplanned scope changes)

© 2012 Deloitte Global Services Limited

(Total actual effort expended in the project)

of having a Process Performance Model for predicting the probability of meeting effort across lifecycle phase

Challenges in IM

IM practice faced some of the below challenges in realizing the objective:

• Varied capabilities (BI/DW, EDM, ECM etc.) with multiple technologies, adding to the

complexity

• Estimation model and Work Breakdown structure

capabilities, but not across combination of capabilities


BI/DW – Business Intelligence/Data Warehousing

EDM – Enterprise Data Management

ECM – Enterprise Content Management

5

IM practice faced some of the below challenges in realizing the objective:

Varied capabilities (BI/DW, EDM, ECM etc.) with multiple technologies, adding to the

and Work Breakdown structure common across individual

capabilities, but not across combination of capabilities


Challenges in IM - Project complexity

Enterprise

Business Intelligence(BI/DW)

• Business

Intelligence

• Enterprise Data

Warehouse/Data

Marts

• Enterprise

Information

Management

• Analytics

• ETL for BI/DW

Solutions

IM has varied work streams with multiple technologies, which adds to


Enterprise

Management

Enterprise Data Management (EDM)

Solutions

• Data Conversion, Retention & Archiving

• Metadata Management

• Master Data Management

• Data Quality Management

• Broad range of capabilities across BI/DW, PMT, EDM, ECM further integrated with various technologies like IBM, SAP and OPT

6

Project complexity

Enterprise Information

Planning

Management Technique(PMT)

• Planning, Budgeting, & Forecasting

• Corporate Scoreboards, Dashboards

• Management & Financial Reporting

• Financial Performance Mgmt

varied work streams with multiple technologies, which adds to the project complexity


Enterprise Information

Management

Enterprise Content Management (ECM)

• Enterprise

Collaboration

• Document

Management

Broad range of capabilities across BI/DW, PMT, EDM, ECM further integrated with various technologies like IBM, SAP and

Challenges in IM – Project Estimation and Data Collection

Effort estimated at the planning stage changes through the remaining stages

Inconsistent set of tasks defined in projects due to different nature of projects


Multiple estimation methods (capability dependent)

due to different nature of projects

In absence of a consistent historical data for each capability, it is difficult envision or forecast if the project would meet the business objectives

7

Project Estimation and Data Collection

planning stage the remaining stages

projects

Historical data was disparate and could not be

utilized directly to build a


Multiple estimation methods (capability dependent)

build a standard PPM for

IM practice

consistent historical data for each capability, it is difficult to envision or forecast if the project would meet the business objectives

Approach


Approach

A phased approach was identified as the solution to overcome the existing challenges

Stabilization

• Homogenize projects based

• Implement PPM in projects

• Collect data from projects

Maturity

Initiation


• Homogenize projects based on technology / frameworks

• Understand the current estimation mechanism

• Identify common tasks and base of estimation

• Build a PPM on top of the common estimation framework

• Re-calibrate PPM model using data received

• Pilot the model in additional projects

• Re-calibrate PPM model using

data received

• Compare results of PPM implementation

9

A phased approach was identified as the solution to overcome the existing challenges

Stabilization

Institutionalization

Implement PPM in projects

Collect data from projects

• Implement PPM across eligible projects

• Standard Work Plan to be developed based on common tasks


calibrate PPM model using

Pilot the model in additional

calibrate PPM model using

Compare results of PPM

• PPB to be revised based on the data collected as per common estimation framework

• PPM Model to be enhanced with additional control knobs (for what-if analysis)

• PPM to be enhanced to predict additional parameters (like defects for each phase)

• PPM to be enhanced to include

additional capabilities

Time

InitiationCreation of Baseline 1 of


of Baseline 1 of PPM

Initiation

• Homogenize projects based on technology / frameworks

• Understand the current estimation mechanism

• Identify common tasks and base of estimation

• Build a PPM – Baseline 1 on top of the common estimation framework

High Maturity in complex Information Management11

Homogenize projects based on technology / frameworks

Understand the current estimation mechanism

Identify common tasks and base of estimation

common estimation framework


Initiation – Selection of common framework

Most commonly executed component identified as BI/DW. Key tasks

capability were taken up for creating the PPM:

• Plan Phase

− Define reporting and data conversion requirements

− Assess application landscape

• Design Phase

− Application Architecture & Infrastructure requirements

− Conceptual, Logical and Physical Data Modeling

− Report Functional / Technical Specifications


− Report Functional / Technical Specifications

− Data Transformation/Conversion solution architecture

− Unit test plan and cases

• Build Phase

− Develop connections, mappings, workflows, semantic layer and reports

− Develop unit test scripts and conduct unit testing

• Deliver Phase

− Functional Integration Testing – Workflows and Reports

− User Acceptance Testing – Workflows and Reports

− Implement mappings, workflows, user security and reports

− Deployment and cutover activities

12

Selection of common framework

as BI/DW. Key tasks pertaining to BI/DW

Define reporting and data conversion requirements

Application Architecture & Infrastructure requirements

Conceptual, Logical and Physical Data Modeling

Specifications


Specifications

Data Transformation/Conversion solution architecture

Develop connections, mappings, workflows, semantic layer and reports

Develop unit test scripts and conduct unit testing

Workflows and Reports

Workflows and Reports

Implement mappings, workflows, user security and reports

Initiation Phase Activities

BI/DW Component

Identify a common base of estimation /

data collection

Understand the

project’s estimation

mechanism


Select past projects on BI/DW components

Baseline 1 of PPM created

13

BI/DW Component

Understand the

standard estimation

framework (PEPS)

in IM method

Shortlist common tasks for data

collection across phases


Build the PPM on top of PEPS framework

Baseline 1 of PPM created

Initiation Phase Outcome - PPM

Baseline 1 of PPM was based on the standard Project Estimator

application in IM, used for scoping, estimating, and planning projects.

• Standard estimator tool had complete list of applicable tasks for BI/DW components

• Each of the task had a basic estimated hours defined as per complexity level

• Sizing (IM points) based on the simplest task in DW components was introduced, with

help of SME’s


help of SME’s

• Input parameters identified (based on number of items and complexity)

• Based on the actual effort provided by the past projects, the estimation tool was modified.

• Guidance for using the estimation tool was defined and shared with selected projects

14

PPM – Baseline 1

Baseline 1 of PPM was based on the standard Project Estimator

application in IM, used for scoping, estimating, and planning projects.

Standard estimator tool had complete list of applicable tasks for BI/DW components

a basic estimated hours defined as per complexity level

(IM points) based on the simplest task in DW components was introduced, with


Input parameters identified (based on number of items and complexity)

Based on the actual effort provided by the past projects, the estimation tool was

tool was defined and shared with selected projects

StabilizationCreation of Baseline 2 and Creation of Baseline 2 and

Baseline 3 of PPM

15

of Baseline 2 and


of Baseline 2 and

Stabilization

•Baseline 1

PPM Baseline 1 shared with past projects

•Baseline 2

PPM Baseline 2 created by


PPM Baseline 2 created by

from Baseline 1

•Baseline

PPM Baseline

from Baseline

16

recalibrating data received


recalibrating data received

Baseline 3

Baseline 3 created by recalibrating data received

Baseline 2

Stabilization Phase Activities

• Data collected from Past Projects based on PPM Baseline

• Distribution updated for tasks which had effort from at least 5 past

• Remaining tasks were calibrated with triangular distribution

• Baseline 2 of PPM was created

High Maturity in complex Information Management17

Phase Activities – PPM Baseline 2

on PPM Baseline 1

for tasks which had effort from at least 5 past projects

Remaining tasks were calibrated with triangular distribution


• Baseline 2 of PPM was used for forecasting across new projects

• The output of the model was to predict effort with certainty percentage across build and design phase

Stabilization Phase Activities


• Metric data collected (based on tasks in PPM) from all projects

• Distribution updated for tasks which had effort provided

• Baseline 3 of PPM was created

18

Baseline 2 of PPM was used for forecasting across new projects

The output of the model was to predict effort with certainty percentage across build

Phase Activities – PPM Baseline 3


Metric data collected (based on tasks in PPM) from all projects

effort provided

Baseline Results Comparison

19

Baseline Results Comparison


PPM Results Comparison

• A BI/DW project was identified to run through all baseline versions of the

• Objective was to compare the effort variance between the forecasted effort and the project actual effort at phase level (mainly Design and Build

• Inputs of Project X was run across the three different

• Actual effort was collected and compared against forecasted effort of Project X, across


• Actual effort was collected and compared against forecasted effort of Project X, across

all baselines

20

identified to run through all baseline versions of the PPM

Objective was to compare the effort variance between the forecasted effort and the project actual effort at phase level (mainly Design and Build)

run across the three different baselines to forecast effort

Actual effort was collected and compared against forecasted effort of Project X, across


Actual effort was collected and compared against forecasted effort of Project X, across

Results Validation for Project X

-15.64

-7.03

-1.98

-18.00

-16.00

-14.00

-12.00

-10.00

-8.00

-6.00

-4.00

-2.00

0.00

Baseline 1 Baseline2 Baseline3

Overall Effort Variance


-16.32

-26.98

-8.03

-29.48

16.20

3.67

-40.00

-30.00

-20.00

-10.00

0.00

10.00

20.00

Baseline 1 Baseline2 Baseline3

Phase-wise Effort Variance

21

Results Validation for Project X

Project X

Overall Effort Variance - Inferences

• There is a consistent decrease in

effort variance across baselines for

the identified projects

• This indicates that the forecast

(planned) value is closer to the

project actuals through baselines


Design

Build

Phase wise Effort Variance -Inferences

• Effort variance range has reduced

across baselines for build phase

• Effort variance has reduced with

Baseline 3 for design

phase, Baseline 2 had some

additional design tasks, due to which

higher effort variance was seen.

InstitutionalizationRoad Ahead

22

Institutionalization


Institutionalization Activities

• Implementation Plan

− Roll out Baseline 3 of PPM across new

− Modify metrics report at organization level, in

− Revise Process performance baseline (PPB) for BI/DW tasks in IM Practice

• Model Enhancement Plan

− Recalibrate the model, as appropriate


− Recalibrate the model, as appropriate

− Introduce control parameters in the PPM (

− Include additional parameters for prediction as applicable, like defects per phase

− Pilot PPM for additional IM capabilities like

23

new projects

at organization level, in line with PPM tasks / phases

performance baseline (PPB) for BI/DW tasks in IM Practice


Introduce control parameters in the PPM (for what-if analysis)

Include additional parameters for prediction as applicable, like defects per phase

Pilot PPM for additional IM capabilities like PMT, EDM etc..

Critical Success FactorsCritical Success Factors

24

Success Factors


Success Factors

Critical Success Factors

High Maturity is NOT just about

• Strong Leadership commitment and stakeholders

• Inculcating a culture change for using standard

• Collecting and reporting accurate data as per suggested framework


• Diligent support by process consultants in enabling the projects to use the PPM

25

is NOT just about numbers and statistical tools

Strong Leadership commitment and stakeholders support

standard framework and tools

Collecting and reporting accurate data as per suggested framework


Diligent support by process consultants in enabling the projects to use the PPM

Any questionsAny questionsAny questions?


Any questions?

Contacts

Chandu Mukkavalli

Director

Monica Kavatkar

Manager


Deloitte Consulting India Pvt. Ltd.

U.S. India Quality

Fairmont Level 2,

Hiranandani Business

Park, Powai, Mumbai - 400 076.

India

Tel (India): 6113 7788

Mobile: +91 9967054611

[email protected]

27


U.S. India Quality

Fairmont Level 2,


Park, Powai, Mumbai

India

Tel (India): +91 6113 7171

Mobile: + 91 9821536571

[email protected]

Monica Kavatkar Neetu Kar

Manager





6113 7171

9821536571

[email protected]


U.S. India Quality

Fairmont Level 2,



India

Tel (India): 6113 7175

Mobile: +91 9920735369

[email protected]


As used in this communication, ‘Deloitte’ means Deloitte Touche Tohmatsu Limited and its member firms.

Deloitte refers to one or more of Deloitte Touche Tohmatsu Limited, a UK private company limited by guarantee, and its networ

firms, each of which is a legally separate and independent entity. Please see www.deloitte.com/about for a detailed descripti

structure of Deloitte Touche Tohmatsu Limited and its member firms.

Deloitte provides audit, tax, consulting, and financial advisory services to public and private clients spanning multiple ind

connected network of member firms in more than 150 countries, Deloitte brings world

succeed wherever they operate. Deloitte's approximately 170,000 professionals are committed to becoming the standard of excel

This publication contains general information only, and none of Deloitte Touche Tohmatsu Limited, its member firms, or their

(collectively, the “Deloitte Network”) is, by means of this publication, rendering professional advice or services. Before ma

taking any action that may affect your finances or your business, you should consult a qualified professional adviser. No ent

Network shall be responsible for any loss whatsoever sustained by any person who relies on this publication.


As used in this communication, ‘Deloitte’ means Deloitte Touche Tohmatsu Limited and its member firms.

Deloitte refers to one or more of Deloitte Touche Tohmatsu Limited, a UK private company limited by guarantee, and its network of member

firms, each of which is a legally separate and independent entity. Please see www.deloitte.com/about for a detailed description of the legal

Deloitte provides audit, tax, consulting, and financial advisory services to public and private clients spanning multiple industries. With a globally

connected network of member firms in more than 150 countries, Deloitte brings world-class capabilities and deep local expertise to help clients

succeed wherever they operate. Deloitte's approximately 170,000 professionals are committed to becoming the standard of excellence.

This publication contains general information only, and none of Deloitte Touche Tohmatsu Limited, its member firms, or their related entities

(collectively, the “Deloitte Network”) is, by means of this publication, rendering professional advice or services. Before making any decision or

taking any action that may affect your finances or your business, you should consult a qualified professional adviser. No entity in the Deloitte

Network shall be responsible for any loss whatsoever sustained by any person who relies on this publication.

01 high maturity in complex information management...

Documents