Taking portfolio benefits management to the next level with modern analytics webinar Wednesday 13 June 2018 presented by Ian Stuart, Altis Consulting, Principal hosted by Merv Wyeth, Benefits Management SIG Secretary The link to the write up page and resources of this webinar: https://www.apm.org.uk/news/taking-portfolio-benefits-management-to-the-next-level-with-modern-analytics-webinar/

1. Ian Stuart
Altis Consulting
Taking Portfolio Benefits Management to the next level with Modern Analytics

3. Welcome

4. Goal
Allow you to
Develop awareness and knowledge of data analytics and data
presentation
Understand their use in the context of Portfolio & Programme
Management
How they can address real-life situations
Gain insight into industry Best Practices
Boost value for PM practitioners and their organisations

5. Contents
• Intro
• Typical Project Management Challenges
• Data Visualisation in Project, Programme & Portflio Management
• Real life examples
• Tools
• Demos
• Best practices for Data visualisation
• How to get Started
• Questions & Summary

6. Partnerships with thought leaders
The Kimball Group
Widely recognised
as the inventors of many of
the data warehousing
concepts we take for granted
today.
William McKnight
Strategist, Lead Enterprise
Information Architect, and
Program Manager for sites
worldwide utilising the
discipline of Master Data
Management, Data Quality
and Data Governance.
Stephen Few
A leading expert, educator
and author in data
visualisation techniques. He
is the author of four best
selling books on the topic
with a fifth due out soon.

7. Project Management Challenges

8. Project Management
Lots of knowledge areas and responsibilities
Procurement
Schedule
Management
Costs
Resources
Integration
Management
Scope
Management
Issues
Risks

9. Project Management
Many responsibilities often means many systems
To name a few:
• Project Management Systems
• Schedules, Budgets in Excel
• Customer Data (e.g. CRM)
• Resource planning solutions
• Libraries, repositories (e.g. SharePoint)
• Finance & accountancy systems

10. Project Management
Typical Programme Reporting Issues
• Silos of information
• Poor data quality
• Sporadic data availability
• Manual processing
• Complexity
• Little time available and difficult reports to compile

11. Data Visualisation In Project Management

12. Data Visualisation in Project Management
• Analytics techniques and tools enable
• Collecting data from multiple systems
• Combining and storing in a common view
• Data Visualisation allows
• The data to be explored
• Ability to find patterns and trends
• Clear way to communicate message

13. Portfolio Management Analytics - Construction
Project Management Centre of Excellence
• Very large complex data set available
• Team used to one report per project – and many sources of data
• Allowed commercial analyst to find outliers and patterns that were hidden in the data
• Existing traffic lighting of project was not sufficient

14. Portfolio Management Analytics - Construction
Project Management Centre of Excellence

15. Portfolio Management Analytics - Construction
Project Management Centre of Excellence

16. Portfolio Management Analytics - Construction
Margin Analysis of projects
• Small Construction company
• Analysed which projects were more successful than others

17. Data Visualisation Tools

18. Gartner BI and Analytics Magic Quadrant
Microsoft (Power BI) & Tableau are clear leaders

19. Gartner BI and Analytics Magic Quadrant
Microsoft (Power BI) & Tableau are clear leaders

20. Data Visualisation Demos

21. The importance of using good data
visualisation principles

22. Data Visualisation
The WAY we present data has a HUGE impact on
• If it is understood
• How it is interpreted
• How much it is used
“The goal is to transform data into information, and information into insight.”
Carla Fiorina, Executive and president of Hewlett-
Packard Co in 1999. Chairwoman in 2000.

23. We are company G.
Which contributes more to market
share; Company A or our company?
In order, which are our major
competitors?
Is that easier?
Example 1 – 3D Pie Charts

24. Example 2 - Area
Poll: How much bigger is the right hand circle compared to the left hand?
r=1 cm, 𝐴 = 𝜋𝑟2
Area = 3.14 cm
16 times bigger
r=4 cm, 𝐴 = 𝜋𝑟2
Area = 50.26 cm

25. Are you sure
it’s this
one?
Example 3 – Colour
Which is the darkest of the 4 smaller rectangles?

26. Observe the apparent colour change as the shape moves across
the screen
Example 3 – Colour

27. Visual perception
“We don’t see images with our eyes; we see them with our brains”
Stephen Few

28. Data Visualisation Best Practice

29. Principles
1. Display neither more nor less than is relevant to your message

30. Principles
2. Do not include visual differences in a graph that do not correspond
to actual differences in the data.

31. Principles
3. Differences in the visual properties that represent values should
accurately correspond to the actual differences in the values they
represent.

32. Principles
4. Use the lengths or 2-D locations of objects to encode quantitative
values in graphs

33. Principles
5. Do not visually connect values that are discrete, thereby
suggesting a relationship that does not exist in the data.

34. Do’s and Don’ts
Do’s
• Consider and plan what it is you are trying to present through your table or graph
• Use bar graphs
• Use 2D graphs
• Keep tables clean and simple.
• Use colour in meaningful ways that helps to represent the data effectively
• Align labels left to right (not vertical)
• Consider visual perception and how your data visualisation can be misinterpreted

35. Do’s and Don’ts
Don’ts
• Don’t use pie charts
• Don’t use 3D graphs
• Don’t use background colour fill
• Don’t align labels vertically
• Don’t misrepresent anything that you don’t want to by disregarding visual perception

36. How to Get Started

37. High level steps
• Get a tool
• The top three players (and others) all have a free version
• More than adequate for single developer
• Get some data
• Reliable, repeatable, relevant
• Create some visualisations
• Follow a process
• Get some help
• Training, Coaching, Outsourcing

38. Data Visualisation Design Process

39. Agile Framework
Typical Agile approach
Project Kick off and
Planning
Development
Demo
1
Mon 7th
August
Mon
14th
August
Thu 17th
August
Development
Thu
24th
August
Demo
2
Tue 22nd
August
Testing
Finish
Development
Demo
3
Tue
29th
August
Confirm
Requirements

40. Getting help
• Training
• Data Visualisation Principles
• Public and On Demand
• Specific Tool training
• Free resources available online
• Pre-packaged courses
• Bespoke training
• Coaching
• On the job training
• Outsourcing
• Value for money
• Or a combination

41. Summary
We have shown you how data can be exploited and best presented in
order to address real-life situations in the context of Portfolio
Management
We briefly discussed how to get started with data visualisation and
analytics
We trust you have seen how implementing good data visualisation in your organisation could
save time and money whilst boosting value

42. Tel +44 208 133 5095 or +44 7946 535 454
ians@altisglobal.co.uk
www.altisglobal.co.uk
Connecting with courage,
heart
and insight
8 consecutive years since 2010

43. This presentation was delivered
at an APM webinar
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our website
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