Data-driven (Project) Management From a theoretical data management revolution

to real business solutions

Presentation to ULB Master in management Antonio Nieto Rodriguez

V5.1.

Thibaut De Vylder, CEO 12th of December 2012

Intro

Deployments Factory SA

Created in Sept 2000

25 consultants active in Benelux

Turnover 3.200.000 € in 2010/2011

Active in Financial, Dredging, Parking,

Retail industries

Belgian & European public institutions

Thibaut De Vylder

Commercial Engineer ‘96 Louvain School of Management

Co-founder in 2000

Current CEO

PMP, « Administrateur agréé » Guberna

Objectives

Understand current management challenges & opportunities linked to modern data management

Underline the lack of “information virtuous cycle” in most organisations

Understand the “DataFactory” concept

Present some real applications in project, program & portofolio management.

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Agenda

Part 1 - Management revolution: Data Driven Decision Making

Part 2 - From data to decision : the Information Virtuous Cycle

Part 3 – Real & Future Applications

Conclusion

Performance?

Recent topic in HBR about "Bigdata : The Management Revolution"

BigData: the management revolution, Andrew mcAfee & Erik Brynjolfsson, Harvard Business Review, Oct 2012, pp 61-68

Performance of data-driven companies

First study about 330 executives from North American companies

executed by McKinsey, MIT Center for Digital Business, Warton... Results

Data driven companies perform better on operational and financial objectives

Companies in the top 1/3 of their industry, considering themselves as ‘data-driven’, were, on average, 5% more productive and 6% more profitable

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VVV & Challenges

What's New? Three key differences with business analytics (VVV)

Volume

Velocity

Variety

2 examples

Amazon vs. Traditional library

Sears' Hadoop solution to reduce a promotion process from 8 weeks to less than one.

Challenges

Technical Challenges

From ‘90 BI infrastructure (created before Internet) to Bigdata Tools

From ‘Kendall’ & dimensional analysis to Bigdata Techniques

Management Challenges

Mute “hippo” (highest-paid person's opinion) decising making that rely on experience and 'intuition' using scarce and incomplete information

into question raisers ‘Computers are useless, they can only give you answers‘, Pablo Picasso

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Source http://www.kaushik.net/

Areas impacted & conclusion 5 areas for change management

Leadership : new type of leaders

Talent Management : scarcity of data scientists

Technology

Data-Driven Decision Making (DDDM) shall replace HiPPO style decision making

Company Culture

From What do we think? : hippo style intuitive decisions

To What do we know? decisions based on evidence

Conclusion

Data-driven decisions tend to be better decision

Existing decision making processes will mute

Leaders will either embrace this or be replaced by others who do

‘Data Science’ will become a key strategic resource for future competitive advantage

Companies that figure out how to handle domain expertise and 'data science' will have competitive advantage on their peers

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Source : http://www.micfarris.com/2011/10/hillion-on-what-is-a-data-scientist/

Agenda

Part 1 - Management revolution: Data Driven Decision Making

Part 2 - From data to decision : the Information Virtuous Cycle

Part 3 – Real & Future Applications

Conclusion

Organisations experience problems and issues

rogram

Organisation

Process issues

Project Management

Maturity

Reporting Issues

Governance problems

Management Staff

Business Intelligence projects

Specific Architecture

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that they try to solve…

rogram Organisation

Hire/Train PM

Implement EPM tools

Implement BPM solutions

Launch BI Initiative

Buy Reporting

tools

New Structure

New Organisation

Hire Senior Mgmt

Analyse Reporting

needs

Implement ERP solutions

Hire experts

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But most of the time, our clients observe that…

little or no synergies & effective collaboration impossible.

Many existing tools…

… with functional overlapping

quality issues everywhere.

Little time is spent in analysing.

People are looking for information anyway.

Improving requires much human and financial resources.

In yours?

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What do they want?

Make better decisions

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What does make better decision mean?

Through data-driven decision making processes

Fed by reliable, high-quality, fresh, qualified & complete information

Information that fits to the users’ specific needs & produced by a reliable, qualitative, auditable, fast information system that generates trustful & comparable info on a periodic manner

Based on real data coming from a variety of sources coming from …

Inside the organisation

From structured sources such as operational systems (accounting, ERP’s, EPM’s, Budgets, Referentials…)

And/or from semi-structured sources (Excel)

And/or from unstructured sources (Text documents, mails…)

Outside the organisation (such as benchmarks, social networks…)

Sources delivered by acknowledged teams that receive DQ feedback to improve their quality on a recurrent manner

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Consider the information virtuous cycle

rogram

Data Information

Governance

Organisations generate data (referentials,

progress, budgets, orders, invoices,

forecasts, meteo...)

Decisions impact the organisation

Organisation

Data is controlled & transformed into intelligent Information (KPIs, trends...)

Input is available to make data-driven

decisions (faster, better and more reliable)

decisions

Other sources

Organisations use other data to

complete theirs

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3 possible levers for improvement

rogram

Data Information

Governance Organisation

Focus of DepFac intervention

Capture of data 3 Restitution of right info, at the right time & in the right format

2

Transformation of data into info

Other sources

1

4

Driving actions through existing management

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A single DataFactory solution

rogram

Data Information

Governance Program

1

2

3 Rep.

Dash. Tra

nsf

orm

atio

n 1 3 2

« Extractors » used as a selective tool that only focus on key data sourced

from multiple systems & referentials

Transformation of data into enriched information not available as such in the

orignal data sources

DQ issues identification and direct feedback to the source owners

Using historical data to analyze trends & make decisions that affect the future success

of the organisation

Management reports and dashboards with a few charts, some metrics and

drilldown capacity

Distribution process to feed the right governance bodies with the right info

at the right moment

“systems produce data,

not information”

“actionable information is

the key”

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Agenda

Part 1 - Management revolution: Data Driven Decision Making

Part 2 - From data to decision : the Information Virtuous Cycle

Part 3 – Real & Future Applications

Conclusion

PROJECT, PROGRAM, PORTOFOLIO MANAGEMENT SOLUTIONS

Data-driven

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Application 1 : Enterprise PPPM (Project, Program, Portfolio management)

PMO DATAFACTORY

Top

Management

Portfolio

Managers

Financial

Management

Program &

Project

Management

Enterprise Program & Project

Management tool

EPM reporti

ng

ERP Accounting ERP reporti

ng

Budget & Plans

XLS

CSV

35 different sources connected to fulfill all user needs @ IT PMO BNPP Fortis

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Phase 0

• Merger decision

Phase 1

• 40 taskforces

Phase 2

• 200 Workgroups

Phase 3

• 400 Programmes

• 1600 Projects

CPMO DATAFACTORY

Top

Management

Domain

Governance

Metier &

Functions

Governance

Program &

Project

Governance

Application 2 : Central Transformation Office

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BUSINESS SOLUTIONS

Data-driven

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Application 3: Financial Reporting

FINANCIAL DATAFACTORY

Top

Management

Financial

Department

Metier &

Functions

Program &

Project

Head-office

International projects

Financial informations

450 projects Dredging, Civil Works,

Offshore and Environment

Tender Budget Actuals Forecast

Project management informations

Project operational informations

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Risk & Basel 2 CHAIN

Input

Entity 1

Entity 2

Entity 3

…

Entity N

Storing

Ref 1

Ref 2

Ref M

B2 Preparing

B2 Calculating

B2 Reporting

Application 4 : Risk & Basel 2 chain

BASEL2 DATAFACTORY

Top

Management

Regulators

Risk

Governance

Stress Testing

& Simulations

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Application 5 : Corporate Reporting

CORPORATE DATAFACTORY

Top

Management

Risk

Governance

Finance

Governance

Strategic

Governance

Global Factoring

Belgium

Sales

Finance

HR

Risk

Operations

France

Sales

Finance

HR

Risk

Operations

Nederland

Sales

Finance

HR

Risk

Operations

Italy

Sales

Finance

HR

Risk

Operations

… England

Sales

Finance

HR

Risk

Operations

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FUTURE SOLUTIONS

Data-driven

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Application 6 : Strategic Execution Office (1/2)

TOP Management

Management

Operations

‘Change’ and ‘Run’ always coexist in organisations

Strategy deals with both dimensions & experience two types of gaps

STRATEGY

Strategic change gap

Strategic run gap

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Application 6 : Strategic Execution Office (2/2)

STRATEGIC EXECUTION OFFICE

CHANGE DATAFACTORY

RUN DATAFACTORY

STRATEGIC DATAFACTORY STRATEGIC MODULE Strategic

Governance

Change Governance

Run Governance

Run Actions

Change actions

Strategic Actions

STRATEGY

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Agenda

Part 1 - Management revolution: Data Driven Decision Making

Part 2 - From data to decision : the Information Virtuous Cycle

Part 3 – Real & Future Applications

Conclusion

Conclusion (1/2)

Every single organisation in the world has the impression to be very different from its peers.

Surprisingly, however, when it comes to the resolution of its problems, issues or to the improvement of its efficiency, it tends to rely on generic solutions proposed (or pushed) by the market.

Not surprisingly, the latest solution implemented has to adapt to pre-existing items (referentials…) and often increases both the perceived and the real complexity.

Experience showed us that even if management commitment and allocated resources are important, the benefits are not always present at the end, which generates a lot of dissatisfaction at all levels.

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Conclusion (2/2)

We think that organisations should first focus on leveraging on past investments, on existing solutions and processes and try to make them work more efficiently together, pushing them to their limits.

For this, considering the information cycle as a whole, and acting simultaneously on the 3 levers, is a first important step towards global understanding and pragmatic implementation of a data-driven decision making management culture.

This can be done short term, with limited resources, in a non intrusive manner and drive a positive attitude that benefits to all stakeholders.

If successful in a particular domain, it can be extended to other contexts, showing then its real potential as new management practice.

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Remember…

Replace the hippo style decision making in your organisation or someone else will…

Periodic & reliable information allow you to watch informational ‘movies’ and analyse trends that are far better than static pictures.

Unstructured data’s are knocking on the door. They want to be taken into account.

No quality, no trust

Focus on what people want to know and see. Do not listen to those who tell you that what you want is not possible: they just don’t know.

Be curious!

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Thank you

Thibaut De Vylder Deployments Factory SA tdv@depfac.com Mobile : +32 478 69 21 86 @Thibaut73

Deployments Factory SA Rue Guillaume Stocqstraat 79 1050 Brussels http://www.deploymentsfactory.com @depfac Tel : +32 2 290 63 90 Fax : +32 2 290 63 99

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Appendix

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D. Restitute C. Transform A. Capture

B. Store

Concept#01 : DataFactory Architecture (level 1)

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Concept#01 : DataFactory Architecture (level 2)

D. Restitute C. Transform A. Capture

Structured Extractors

Enrichments

Data Quality

Analysis

Distribution

B. Store

Raw data

Measures & KPI’s

Quality indicators

& KQI’s

Reporting data

Unstructured Extractors

Reporting - Reports - Dashboards - Triggers & exceptions - Other

ERP’s, EPM’s…

Proprietary Solution

Web & custom

tools

XLS, CSV, XML…

Documents, emails, pdf…

Semi- Structured Extractors

…

Simulations

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Concept#02 : Unit Bridge

OPERATE

ENGINEER

Back Office Biz

Tech

Gov

DF Management System

TRANSVERSAL KNOWLEDGE - Strategy Execution - Transformation - Entreprise PPPM - DQ governance - PMO - Deployment…

FUNCTIONAL KNOWLEDGE - Risk - Finance - Facility - IT

Unit Bridge engineering & operations

Front Office