Most IT projects fail due to people losing touch with reality. Regular project reviews can help identify issues and keep projects grounded. This presentation discusses a project review simulation exercise where participants reviewed the status of a mock project called "Project Airfix" over three days to identify any potential problems or failures. Common reasons for IT project failures and tips for effective project reviews are also presented.
Planning Data Analysis and Completing the Design Matrix 规划数据分析与完成设计矩阵Dadang Solihin
Shanghai International Program for Development Evaluation Training Asia-Pacific Finance and Development Center; 200 Panlong Road-Shanghai, October 15, 2008
For more classes visit
www.snaptutorial.com
WEEK 1DQ 1 What is Total Quality Management
WEEK 1DQ 2 A System Perspective
WEEK 2DQ 1Dr. Deming's 14 Points
Planning Data Analysis and Completing the Design Matrix 规划数据分析与完成设计矩阵Dadang Solihin
Shanghai International Program for Development Evaluation Training Asia-Pacific Finance and Development Center; 200 Panlong Road-Shanghai, October 15, 2008
For more classes visit
www.snaptutorial.com
WEEK 1DQ 1 What is Total Quality Management
WEEK 1DQ 2 A System Perspective
WEEK 2DQ 1Dr. Deming's 14 Points
Business analysis interview question and answersGaruda Trainings
Business Analysis is the process of understanding business change needs, assessing the impact of those changes, capturing, analyzing and documenting requirements and then supporting the communication and delivery of those requirements with relevant parties.The person who carries out this task is called a business analyst or BA.
Short overview of how to identify a problem, gather buy-in, develop consensus and plan a meaningful project... too short for the amount of material... Much leveraged from LEI
For more classes visit
www.snaptutorial.com
WEEK 1DQ 1 What is Total Quality Management
WEEK 1DQ 2 A System Perspective
WEEK 2DQ 1Dr. Deming's 14 Points
For more classes visit
www.snaptutorial.com
WEEK 1DQ 1 What is Total Quality Management
WEEK 1DQ 2 A System Perspective
WEEK 2DQ 1Dr. Deming's 14 Points
WEEK 2DQ 2 Quality Philosophies, Awards, and Standards
WEEK 3DQ 1 TQM Leaders
Monitoring at scale - Intuitive dashboard designLorenzo Alberton
At a certain scale, millions of events happen every second, and all of them are important to evaluate the health of the system. If not handled correctly, such a volume of information can overwhelm both the infrastructure that needs to support them, and people who have to make a sense out of thousands of signals and make decisions upon them, fast. By understanding how our rational mind works, how people process information, we can present data so it's more evident and intuitive. This talk will explain how to collect useful metrics, and to create the perfect monitoring dashboard to organise and display them, letting our intuition operate automatically and quickly, and saving attention and mental effort to activities that demand it.
Slides from the session I ran for APM PMO SIG at MMU business school on 12 Dec. (Most of the session was taken up with the simulation, but these slides cover some of the lessons you might learn as a project reviewer.)
Four major causes of difficulty in gathering system requirement and business requirements, Reasons projects were
abandoned.Three Generations of System Development:1. Direct Contact 2. Business Analyst 3.Team Based.
Data Science. Business Analytics is the statistical study of business data to gain insights. Data science is the study of data using statistics, algorithms and technology. Uses mostly structured data. Uses both structured and unstructured data.
Catalyst 2010 Presentation - Enterprise 2.0 and Observable Workbtullis
Presentation from Catalyst 2010 conference in San Diego. Presenters were Joe Crumpler and Brian Tullis. Describes principles of Observable Work and how they are applied in practice on a large virtual team.
How to build a data science project in a corporate setting, by Soraya Christi...WiMLDSMontreal
"Applied data science in the industry: How to build a data science project in a corporate setting - best practices and a real-world example"
By Soraya Christina, Senior Data Scientist at Morgan Stanley
Abstract:
- Which platforms/technology to use for your analytics project and why? (Spark, Hadoop, vendor products, open source, Python, Scala, etc?)
- How to build your data science flow and what to avoid? (Occam's razor, testable and structured flow)
- How to presents results in a way business stakeholders understand them? (Making complex concepts easy to understand by business lines)
- A real-world example of a real-time failure prediction using Spark streaming and ML components.
The purpose of this talk is to present the challenges and solutions when building data science projects in a corporate environment. Generating insights for better business decision making is what drives data science projects. But working with business side by side, being able to build a reliable flow and properly communicating results and key elements are more than crucial, it is what will guarantee the success of your data science projects.
General introduction to agile practices like Scrum and Kanban. Also covers what situations Agile is best at, what situations Agile doesn't help with, and what an Agile team should look like. This deck is a general intro to Agile for OpenSource Connections clients.
The Role of a BA on a Scrum Team IIBA Presentation 2010scrummasternz
What is your role as a BA on a Scrum team? How do you fit in? This presentation was given to the IIBA conference in NZ in 2010 by Stephen Reed. Stephen had worked extensively as a BA and moved into using Scrum with multiple teams at a large Insurance company. This experience led to a lot of questions around what the BA should be doing on a Scrum team. This presentation goes some way to listing what worked in the teams Stephen was involved in. The BA role does not change and all the skills of a great BA are necessary still on a great Software Development team, just more focused on being a team member and utilising those skills for the Scrum process of getting working software to the customer with more focus and clarity for the user.
Pin the tail on the metric v00 75 min versionSteven Martin
This presentation shows a different approach to metrics. Instead of listing the Top 10 field-tested metrics, we first talk about goals as prerequisites for metrics. Next, we discuss characteristics of good and bad metrics. We end with walking through an activity called “Pin the Tail on the Metric,” a technique to facilitate the critical thinking needed to determine what types of metrics can help your organization discuss trade-offs, options, and ultimately make better forward-looking decisions.
Product Management in the Era of Data ScienceMandar Parikh
My slide-deck from a webinar on the same topic for the Institute of Product Leadership, April 4th, 2017
What does it take to build killer products in the “AI-first” era? What makes for a great Data Science-driven product and how do great Product Managers leverage Data Science to drive value for customers? Find out how to avoid the pitfalls of hype-chasing Data Science tactics. Learn how to work with Data Science and Engineering to build a compelling product and solve real problems.
Mandar takes a practitioner’s approach to present his recipe for success for building Data Science-driven products that drive enduring value for customers.
Pin the tail on the metric v01 2016 octSteven Martin
This presentation takes a different approach to metrics. Instead of listing the Top 10 field-tested metrics, we first talk about goals as prerequisites for metrics. Next, we discuss characteristics of good and bad metrics. We end with walking through an activity called “Pin the Tail on the Metric,” a technique to facilitate the critical thinking needed to determine what types of metrics can help your organization discuss trade-offs, options, and ultimately make better forward-looking decisions.
Business analysis interview question and answersGaruda Trainings
Business Analysis is the process of understanding business change needs, assessing the impact of those changes, capturing, analyzing and documenting requirements and then supporting the communication and delivery of those requirements with relevant parties.The person who carries out this task is called a business analyst or BA.
Short overview of how to identify a problem, gather buy-in, develop consensus and plan a meaningful project... too short for the amount of material... Much leveraged from LEI
For more classes visit
www.snaptutorial.com
WEEK 1DQ 1 What is Total Quality Management
WEEK 1DQ 2 A System Perspective
WEEK 2DQ 1Dr. Deming's 14 Points
For more classes visit
www.snaptutorial.com
WEEK 1DQ 1 What is Total Quality Management
WEEK 1DQ 2 A System Perspective
WEEK 2DQ 1Dr. Deming's 14 Points
WEEK 2DQ 2 Quality Philosophies, Awards, and Standards
WEEK 3DQ 1 TQM Leaders
Monitoring at scale - Intuitive dashboard designLorenzo Alberton
At a certain scale, millions of events happen every second, and all of them are important to evaluate the health of the system. If not handled correctly, such a volume of information can overwhelm both the infrastructure that needs to support them, and people who have to make a sense out of thousands of signals and make decisions upon them, fast. By understanding how our rational mind works, how people process information, we can present data so it's more evident and intuitive. This talk will explain how to collect useful metrics, and to create the perfect monitoring dashboard to organise and display them, letting our intuition operate automatically and quickly, and saving attention and mental effort to activities that demand it.
Slides from the session I ran for APM PMO SIG at MMU business school on 12 Dec. (Most of the session was taken up with the simulation, but these slides cover some of the lessons you might learn as a project reviewer.)
Four major causes of difficulty in gathering system requirement and business requirements, Reasons projects were
abandoned.Three Generations of System Development:1. Direct Contact 2. Business Analyst 3.Team Based.
Data Science. Business Analytics is the statistical study of business data to gain insights. Data science is the study of data using statistics, algorithms and technology. Uses mostly structured data. Uses both structured and unstructured data.
Catalyst 2010 Presentation - Enterprise 2.0 and Observable Workbtullis
Presentation from Catalyst 2010 conference in San Diego. Presenters were Joe Crumpler and Brian Tullis. Describes principles of Observable Work and how they are applied in practice on a large virtual team.
How to build a data science project in a corporate setting, by Soraya Christi...WiMLDSMontreal
"Applied data science in the industry: How to build a data science project in a corporate setting - best practices and a real-world example"
By Soraya Christina, Senior Data Scientist at Morgan Stanley
Abstract:
- Which platforms/technology to use for your analytics project and why? (Spark, Hadoop, vendor products, open source, Python, Scala, etc?)
- How to build your data science flow and what to avoid? (Occam's razor, testable and structured flow)
- How to presents results in a way business stakeholders understand them? (Making complex concepts easy to understand by business lines)
- A real-world example of a real-time failure prediction using Spark streaming and ML components.
The purpose of this talk is to present the challenges and solutions when building data science projects in a corporate environment. Generating insights for better business decision making is what drives data science projects. But working with business side by side, being able to build a reliable flow and properly communicating results and key elements are more than crucial, it is what will guarantee the success of your data science projects.
General introduction to agile practices like Scrum and Kanban. Also covers what situations Agile is best at, what situations Agile doesn't help with, and what an Agile team should look like. This deck is a general intro to Agile for OpenSource Connections clients.
The Role of a BA on a Scrum Team IIBA Presentation 2010scrummasternz
What is your role as a BA on a Scrum team? How do you fit in? This presentation was given to the IIBA conference in NZ in 2010 by Stephen Reed. Stephen had worked extensively as a BA and moved into using Scrum with multiple teams at a large Insurance company. This experience led to a lot of questions around what the BA should be doing on a Scrum team. This presentation goes some way to listing what worked in the teams Stephen was involved in. The BA role does not change and all the skills of a great BA are necessary still on a great Software Development team, just more focused on being a team member and utilising those skills for the Scrum process of getting working software to the customer with more focus and clarity for the user.
Pin the tail on the metric v00 75 min versionSteven Martin
This presentation shows a different approach to metrics. Instead of listing the Top 10 field-tested metrics, we first talk about goals as prerequisites for metrics. Next, we discuss characteristics of good and bad metrics. We end with walking through an activity called “Pin the Tail on the Metric,” a technique to facilitate the critical thinking needed to determine what types of metrics can help your organization discuss trade-offs, options, and ultimately make better forward-looking decisions.
Product Management in the Era of Data ScienceMandar Parikh
My slide-deck from a webinar on the same topic for the Institute of Product Leadership, April 4th, 2017
What does it take to build killer products in the “AI-first” era? What makes for a great Data Science-driven product and how do great Product Managers leverage Data Science to drive value for customers? Find out how to avoid the pitfalls of hype-chasing Data Science tactics. Learn how to work with Data Science and Engineering to build a compelling product and solve real problems.
Mandar takes a practitioner’s approach to present his recipe for success for building Data Science-driven products that drive enduring value for customers.
Pin the tail on the metric v01 2016 octSteven Martin
This presentation takes a different approach to metrics. Instead of listing the Top 10 field-tested metrics, we first talk about goals as prerequisites for metrics. Next, we discuss characteristics of good and bad metrics. We end with walking through an activity called “Pin the Tail on the Metric,” a technique to facilitate the critical thinking needed to determine what types of metrics can help your organization discuss trade-offs, options, and ultimately make better forward-looking decisions.
This document is containing details about Business Analysis & Business Analyst the agendas are as below :
Introduction to Business Analysis
Scope of Business Analyst in IT & Non-IT Organizations
Require Skill Matrix & Prerequisites for Business Analyst
Business Analysis Methodology
Role Business Analyst in SDLC
Alternatives & BA Professional Courses
Introduction to CMMi Levels & Role of BA in CMMi Levels
Startup Systems Engineer's Instruction manual - SREcon17 Europeeffie mouzeli
What happens when you take the leap of faith and leave the security of a systems engineering team to become the first systems person at a startup? What should you expect?
This talk is about the challenges of being the sole systems engineer at a young company. The amount of work is overwhelming but the experience is worth it. We will explain the key elements of a newborn infrastructure and the stages leading it to maturity.
The challenges of this role are not limited to solving technical problems. The habits, processes and standards you will establish, will pave the way to go from a single engineer to a team.
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Slides from my talk to APM South Wales and West of England, in Bristol, 20 Feb 2014. Why do projects fail? What sort of failures are OK? How can portfolio and programme managers improve their success rates? How do you set up an effective assurance programme? What is the PMO's role in all this?
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Projects are risky activities. We take on a managed level of risk in order to achieve defined rewards. It's therefore not surprising that some projects fail — completely eliminating failure would be a sign that we're being too risk averse. Problems arise when the level of failure across our program or portfolio is not commensurate with the desired risk/reward profile.
Project reviews and assurance can be a very useful tool to help monitor risk levels across our portfolio, and hence to identify and mitigate the risks which are not being managed effectively. This talk looks at some factors you should consider when setting up an assurance programme.
Slides from my talk to Unicom "Agile in the Public Sector" on 7 March, 2013. Governance is about decision making. If you don't address it head on, then people will waste a lot of time on demarcation disputes & etc.
Agile changes several aspects of decision making -- the locus of authority, the timing of decisions, notions of "best practice" -- but it doesn't change the need to make decisions about priorities, resources, tools, etc. So you need to think about governance.
This talk discusses some work I've been doing to help organisations and teams explore differing views of decision rights and processes. If you can't talk about governance, then you sure as hell can't manage it.
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1. Why Do IT Projects Fail?
Project Review Simulation
Why do IT projects fail
Mar 2013 1
2. Agenda
10 min -- Introductions
60 min -- Project review simulation
45 min -- Debrief (& models)
Why do IT projects fail
Mar 2013 2
3. Objectives
Think a little about why IT projects fail
Explore use of project reviews to help identify failures
Share experience and expertise
Why do IT projects fail
Mar 2013 3
5. People lose touch with reality
The single underlying cause for most project failures…
Why do IT projects fail
Mar 2013 5
6. Role of the reviewer…
… is to help people keep in touch with reality
PMI Research
About 75% of the things that go
wrong on projects, someone knew
about the issue but didn’t know how
to deal with / who to tell about it.
Why do IT projects fail
Mar 2013 6
7. Assessing project Airfix
24:1 scale model
(1 hour = 3 working days)
6 teams
Conduct a health check of
project Airfix
Why do IT projects fail
Mar 2013 7
8. Assessing project Airfix - Rules
1) You have
Project briefing
Team / resource list
Planning framework
2) Read briefing & identify who / what
you want to see over the 3 days
3) I will give document outlines &
interview notes in line with your
plan
4) Analyse notes and present findings
(2 mins)
5) Describe how you got these
findings
Why do IT projects fail
Mar 2013 8
9. Findings
2 minutes (= 45 mins in real time)
1. Present your key findings
2. Describe how you got to these findings
Why do IT projects fail
Mar 2013 9
10. Debrief
What was common to your findings? Different? Why?
What was common to your plans? Different? Why?
How did you feel during the exercise?
What was challenging?
What was confusing?
What was interesting?
How was this like real life? How did it differ?
What would help make reviews easier?
Why do IT projects fail
Mar 2013 10
11. Some possible learnings
Planning Analysis
Knowing who to talk to is tough Knowing what to look for is tough
You can’t cover everyone in You may need technical skills
limited time People will say conflicting stuff –
You will probably identify more you need to probe
people, documents, etc You can’t uncover every issue –
You need to time to analyse you have to focus
and frame an actionable report Balancing breadth versus depth
You have to pace yourself or is tough
you’ll burn out It’s easy to make inferences
based on limited information, or
to be overwhelmed with data
(And you didn’t have to deal with all the negotiating and so on that
happens when managing stakeholders)
There is never enough time!
Why do IT projects fail
Mar 2013 11
12. Some possible learnings
Data Gathering
Getting stakeholders together You may need depth for results
may mean they spark off each to be actionable – evidence
other adds to credibility and specific
details help action.
Two people may make slower
progress together initially (e.g. There’s always a risk that you’ll
interview coverage), but they miss stuff. This damages the
project and your credibility.
may also fill gaps in each
Don’t let this freeze you. Be
other’s coverage organised and open minded to
There’s always noise that you’ll minimize the risk.
need to untangle (if it was
obvious, others would have
covered it)
Organisations & teams have
inconsistent terminology
Why do IT projects fail
Mar 2013 12
13. Some thoughts
Which sources will give you a quick overview?
Review & project sponsors, programme manager
Risk register
Business case
Plans
Are the documents still current? Are they well maintained?
What does your experience tell you to look for?
Patterns in this company or industry?
Bad smells?
How do you hit the ground running?
Define charter up front
Clear process for data gathering, recording and analysis
Checklists to help with planning (what to look for, what to ask)
Heuristics and models to help you plan will buy time for data collection
and analysis
Why do IT projects fail
Mar 2013 13
14. Review process (Chapters 3, 4, 5)
Control parameters Criteria
Baseline Reference Feedback
Models to improve
reference
models
Inputs Review execution Outputs
Artefacts & other Analysis Loop
items to review, plus Go / No -go Improved
supporting details. decision. artefacts.
Recommendations to
improve review artefacts
Why do IT projects fail
Mar 2013 14
15. Analysis Loop (Chapter 6)
Raw Data
(e.g. Documents Structured Data
& Interviews) (e.g. Issues Log)
Analysis drives
additional data gathering
(e.g. to buy information on key risks) Analysis
&
Hypothesis
Generation
Why do IT projects fail
Mar 2013 15
16. Establishing effective reviews
Establish context for regular reviews
Maintain review checklists and guidelines
Monitor effectiveness
Track project-level actions
Support programme- and portfolio-level actions
Embed lessons learned into organisational standards
Provide administrative support
Why do IT projects fail
Mar 2013 16
17. Assurance as an information conduit
Project teams often have
problems communicating key messages:
Lack savvy
Lack credibility
Lack access
Assurance teams can help them frame their messages and
communicate them effectively
Likewise, sponsors often have trouble picking the critical information
from the mass of stuff that comes their way
Assurance teams can help them recognise key information and
frame appropriate interventions
Why do IT projects fail
Mar 2013 17
20. Types of Project Review
Timing Attributes
Event-based Objectives
Periodic Status
Ad hoc Risk
Quality
Degree of Independence Process
Independent assurance Compliance
Peer
Self-assessment Summative vs Formative
Degree of formality
Spectrum
Why do IT projects fail
Mar 2013 20
21. Gate or Regular Review?
Gate Review Regular Review
Depth • Tend to go deep into • Tend to be more
project status and issues lightweight
Trends • Infrequent • Regular reviews can
track trends
Reviewer • Takes time to get up to • Get to know the project
Overhead
speed
Project • Can be disruptive • Small but frequent
Overhead
disruption
Objectivity • Reviewers are well • Risk of going native
separated
Specialist • May be needed for deep • Can often spot trends
skills
review without them
Why do IT projects fail
Mar 2013 21
22. Peer review or independent assurance?
Peer Review Independent Assurance
Availability of • Must find time from own • Dedicated team
Reviewers
projects
Skills of • Non-specialist • Rigorous approach. Develop
Reviewers
skills in gathering evidence,
conducting interviews, etc
Understanding • Reviewers are managing • Reviewers risk losing touch.
of Projects
similar projects themselves.
Understanding • See many projects
of Issues
Relationship to • Open, friendly relationship • Risk being adversarial
Proj Team
Organisational • Good way to share • Risk focusing on assessing
Learning
experiences projects
Match to • Organisational learning • Executive info & assurance
Overall
Objectives
• Formative reviews • Summative reviews
Why do IT projects fail
Mar 2013 22
23. Independent Assurance or Peer Review?
Peer review Independent Assurance
Project team’s peers provide Dedicated team focused on reviews
outside perspective (people may rotate through it)
Probably take time off own projects Work across multiple projects in a
to do it (so it can be hard to get programme or portfolio (so need to
time from reviewers) manage availability for each project)
Provide advice and reality check to Probably focused on checking status
project manager (& sponsor?) (but may provide advice), reporting
to sponsor or external executives
Open and friendly, with emphasis May become adversarial – “project
on 2-way learning from their peers police” – and lose learning focus
Non-specialists may be Can develop review skills and
unstructured in approach, and methods, but need to overcome
reluctant to challenge peers team resistance
Dependent on team goodwill Have authority (if dangerous to use!)
May mix roles, but helps to be clear which hat you wear
Why do IT projects fail
Mar 2013 23
24. Independent Assurance or Peer Review?
Peer review Independent Assurance
Project team’s peers provide Dedicated team focused on reviews
outside perspective (people may rotate through it)
Probably take time off own projects Help across multiple projects in a
Work executives manage
Help the project team
to do it (so it can be hard to get programme or activities need to
manage the project external portfolio (so
time from reviewers) manage availability for each project)
Provide advice and reality check to Probably focused on checking status
project manager (& sponsor?) (but may provide advice), reporting
to sponsor or external executives
Open and friendly, with emphasis May become adversarial – “project
on 2-way learning from their peers police” – and lose learning focus
Non-specialists may be Can develop review skills and
Help sponsors manage interventions
unstructured in approach, and methods, but need to overcome
reluctant to challenge peers team resistance
Dependent on team goodwill Have authority (if dangerous to use!)
May mix roles, but helps to be clear which hat you wear
Why do IT projects fail
Mar 2013 24
25. Types of Project Review
You can mix up the types
Formal, independent gateways at key points during initiation
Regular peer reviews during execution
Occasional health checks
Self-assessments for low-risk projects or high-capability teams
Shift from objectives, risk and process to quality and status
How much to budget?
½ to 2%?
Why do IT projects fail
Mar 2013 25
26. Review process (Chapters 3, 4, 5)
Control parameters Criteria
Baseline Reference Feedback
Models to improve
reference
models
Inputs Review execution Outputs
Artefacts & other Analysis Loop
items to review, plus Go / No -go Improved
supporting details. decision. artefacts.
Recommendations to
improve review artefacts
Why do IT projects fail
Mar 2013 26
27. Control parameters
Baseline Criteria Reference
Outputs
Feedback
Models to improve
reference
models
Review execution
Inputs Outputs
Artefacts & other Analysis Loop
items to review, plus Go / No -go Improved
supporting details. decision. artefacts.
Recommendations to
improve review artefacts
It helps to be clear about the outputs and how they will be used
The review will generally
Produce recommendations to improve the inputs.
Provide input to go/no-go and other decisions (by giving assurance (or otherwise)
as to the fitness-for-purpose of work done to date and proposed)
In defined circumstances, the independent assurance team may
also trigger escalation processes to other stakeholders.
Why do IT projects fail
Mar 2013 27
28. Control parameters
Baseline Criteria Reference
Inputs
Feedback
Models to improve
reference
models
Review execution
Inputs Outputs
Artefacts & other Analysis Loop
items to review, plus Go / No -go Improved
supporting details. decision. artefacts.
Recommendations to
improve review artefacts
What documents, interviews, etc will we be reviewing?
What supporting materials may be needed?
(e.g. historical context, detailed specifications, etc)
We can’t review everything!
Many review teams try to review all elements of a project.
This diffuses effort across low-risk or low-impact items, reducing the overall
effectiveness and efficiency of the review.
By clearly defining the inputs, we ensure that effort is focused where it will do
most to reduce project risk. (Breadth then depth iterations may also help.)
Why do IT projects fail
Mar 2013 28
29. Control parameters
Baseline Criteria Reference
Criteria
Feedback
Models to improve
reference
models
Review execution
Inputs Outputs
Artefacts & other Analysis Loop
items to review, plus Go / No -go Improved
supporting details. decision. artefacts.
Recommendations to
improve review artefacts
Criteria define what aspects of the inputs to focus on.
Can review against many criteria. (Budget, time, process
compliance, security, performance, usability, …)
Reviews that try to cover every angle end up skating across the
surface. What is most important to this review?
For example, if project is constrained by tight budget, let’s focus
energy on costs.
Typically 2-3 criteria per review. Schedule additional reviews to
cover more criteria.
Why do IT projects fail
Mar 2013 29
30. Control parameters
Baseline Criteria Reference
What doesn’t need to
Feedback
Models to improve
reference
models
Review execution
Inputs Outputs
be reviewed? Artefacts & other
items to review, plus
supporting details.
Analysis Loop
Go / No -go
decision.
Improved
artefacts.
Recommendations to
improve review artefacts
Baseline defines what’s been agreed prior to the review.
For example, if we’re reviewing a project plan, we measure it against it’s likelihood
of delivering the objectives.
Input artefacts are “fit for purpose” if they meet their objectives against the
baseline.
The baseline will often have been reviewed in a stage prior to the current review.
Reference Models define external practices agreed for our context.
The input artefacts conform to best practice to the extent that they align to these
reference models.
By agreeing reference models up front, we can avoid many of the debates that
occur between review and project teams as to whether designs or
implementations conform to someone’s perception of “best practice”.
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31. Control parameters
Baseline Criteria Reference
Feedback loops
Feedback
Models to improve
reference
models
Review execution
Inputs Outputs
Artefacts & other Analysis Loop
items to review, plus Go / No -go Improved
supporting details. decision. artefacts.
Recommendations to
improve review artefacts
First feedback loop is to improve the inputs (plans, designs, project
processes, etc).
Second feedback loop updates our database of good practices,
building in organisational learning:
Improvements to organisational standards and processes
Improvements to review checklists (e.g. new questions, retired questions)
Project reviews can be a key contributor to
organisational learning
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32. Control parameters
Baseline Criteria Reference
Execution
Feedback
Models to improve
reference
models
Review execution
Inputs Outputs
Artefacts & other Analysis Loop
items to review, plus Go / No -go Improved
supporting details. decision. artefacts.
Recommendations to
improve review artefacts
One time vs. Ongoing Review (Oversight)?
What time, resources & expertise are available for the review team?
(Will you need subject matter experts to assist with details?)
What access to the project team, documents, etc is available?
How about administrative support?
(Scheduling interviews and meeting rooms can take a lot of time.)
Preserving confidentiality of interviews*
Security requirements for review results or project artifacts?
May preliminary findings be shared to allow confirmation/correction?
Why do IT projects fail
Mar 2013 *You can’t promise confidentiality if you discover illegal activity
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33. Analysis Loop (Chapter 6)
Raw Data
(e.g. Documents Structured Data
& Interviews) (e.g. Issues Log)
Analysis drives
additional data gathering
(e.g. to buy information on key risks) Analysis
&
Hypothesis
Generation
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34. Analysis Loop Raw Data
(e.g. Documents
& Interviews)
Structured Data
(e.g. Issues Log)
Iterations may be based on Analysis drives
additional data gathering
(e.g. to buy information on key risks) Analysis
Breadth then depth &
Hypothesis
Generation
Risk
Dependencies
…
Gather information into “issues log” for analysis and clustering
Hence build models of potential problems, and of information we
might gather to refine our understanding and confirm / disconfirm
Build traceability from problem to issues cluster to detailed issues
and their supporting notes
You’ll often start with some sort of hypothesis: be aware of biases
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35. Interviewing (Chapter 6)
1) Planning
2) Interview Preparation
3) Pre-interview
4) Opening
5) Mid-Interview
6) Closing
7) Post-Interview
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36. Interviewing
1) Planning
How do interviews contribute to review objectives?
Number and scope of interviews
Type of interview – individual, pair or workshop?
Who to interview
Establish relationships
Set up logistics
Quiet, private space to interview in
Timing, maps, water, etc
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37. Interviewing
2) Interview preparation
Review project documentation
Briefing pack (explain objectives and process)
Self-assessment questionnaires
Agree roles (e.g. if interviewing in pairs)
Develop interview protocol
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38. Interview Protocol
Questions
Closed
Open
Clarifying
Metaquestions
Demonstrations
Use a mix of question types!
Directive or non-directive interviewing?
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39. Interviewing
3) Pre-interview
Review objectives
Review background to interviewee
Manage the interview space
Be on time
Be alert & ready to listen
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40. Interviewing
4) Opening
Set people at ease!
Introductions
Names
Organisational roles
Role on this review & interview
Objectives (or review, of interview)
Confirm timing
Confirm note taking, confidentiality & other protocols
Do they have any questions?
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41. Interviewing
5) Mid-Interview
Early questions build rapport
When did you join the project? What is your role?
Gather basic facts
Give people space to expand
Confirm you’ve heard correctly – listen actively, recap
Confirm evidence for opinions, assumptions & assertions:
“What makes you believe that?”
Record notes (What are you recording? How?)
Listen & observe (e.g. body language & emotional issues)
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42. Interviewing
Don’t be afraid of pauses and silences
LISTEN
Use note-taking to create space
Don’t let the protocol dominate
(I throw it away)
Have a plan, but follow the energy
Check opinions, assumptions and assertions: “what
leads you to believe that?”
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43. Interviewing
6) Closing
Respect interviewee’s time – reschedule if necessary
Confirm you’ve heard main messages
Final chance to gather new info
Metaquestions
Is there anything else I should be asking?
What else did you expect me to ask?
Is there anyone else you should see?
Exchange contact details
Confirm next steps and protocol for checking / follow-up
Thank them for their time
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44. Interviewing
7) Post-interview
Debrief
Record notes
I quickly lose ability to read my handwriting…
It helps me think about follow-up activities
Log new documents and other artefacts
Record issues
Confirm notes
This may gather new info.
What people change is often interesting.
Schedule any follow-up activities
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45. Observation
The ability to gather data is essential to assessment. Data comes in
a variety of forms other than documents & interviews:
Interaction
Body language
The environment
“You can observe a lot just by watching”
- Yogi Barra
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