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Monthly Archives: December 2023

Critical Path Characteristics and Definitions

Posted on December 28, 2023 by | 3 comments

I’m wondering what is causing the confusion appearing in so many posts lately concerning the definition of the critical path. Is it:

  1. A lack of knowledge?
  2. People being out of date and using superseded definitions?
  3. People not understanding the difference between a characteristic and a definition?

As most people know (or should know) the definition used by the PMI Practice Standard for Scheduling (Third Edition), the International Standards Organization (ISO) and most other reputable authorities in their standards is similar to:

Critical Path: sequence of activities that determine the earliest possible completion date for the project or phase. 

For more on the development of this definition see: Defining the Critical Path.


To deal with the questions above, in reverse order:

The difference between a characteristic and a definition.

The definition of a phrase or concept (the ‘critical path’ is both) should be a short, concise, statement that is always correct. A characteristic is something that indicates the concept may be present.

Everyone of significance has always agreed the critical path is the sequence of activities determining the earliest possible completion of the project (or if the project has staged completions, a stage or phase).  This is the basis of the current valid definitions. As a direct consequence of this in a properly constructed CPM schedule, the float on the critical path is likely to be lower than on other paths but not always. Low float or zero float is a characteristic that is often seen on a critical path, but this is a consequence of its defining feature, it being longer than other paths. 

Superseded definitions.

In the 1960s and 70s, most CPM schedules were hand drawn and calculated using a day number calendar. This meant there was only one calendar and constraints were uncommon.  When there are no constraints and only a single calendar in use, the critical path has zero float! From the 1980s on, most CPM schedules have been developed using various software tool, all of which offer the user the option to impose date constraints and use multiple calendars (mainframe scheduling tools generally had these features from the 1960s on).

Using more than one calendar can cause different float values to occur within a single chain of activities, this is discussed in Calendars and the Critical Path.  

Date constraints can create positive or negative float (usually negative) depending on the imposed date compared to the calculated date and the type of constraint, this is discussed in Negative Float and the Critical Path.

Consequently for at least the last 40 years, the definition of a critical path cannot be based on float – float changes depending on other factors.

Knowledge?

One of the problems with frequently repeated fallacies is when people do a reference search, they find a viable answer, and then use that information assuming the information is correct. This is the way we learn, and is common across all disciplines.

Academic papers are built based on references, and despite peer review process, can reference false information and continue to spread the falsehood. One classic example of this is the number of books and papers that still claim Henry Gantt developed the bar chart despite the fact bar charts were in use 100 year before Gantt published his books (which make no claim to him having invented the concept), for more on this see: https://mosaicprojects.com.au/PMKI-ZSY-020.php#Barchart. Another common falsehood is Henry Gantt ‘invented project management’ – his work was focused on improving factory production processes: https://mosaicprojects.com.au/PMKI-ZSY-025.php#Overview

Academics are trained researchers, and still make mistakes; the rest of us have a bigger challenge! The spread of un-reviewed publications via the internet in the last 20+ years started the problem. Now Generative AI (Gen AI) and large language models (LLM) are exacerbating the problem. For most of us it is getting harder and harder to understand where the information being presented a person, or in an article originated. Gen AI is built to translate data into language, it has no ability to determine if the data it has found is from a credible source or not. And as more and more text is produced by the various Gen AI tools the more often wrong information will be repeated making it more likely the wrong information will be found and repeated again, and again.   

I’m not sure of the solution to this challenge Gen AI is clearly not skilled in project management practice (even the PMI AI tool), for more discussion on this important topic see: https://mosaicprojects.com.au/PMKI-SCH-033.php#AI-Discussion  

Reference

One reference that is reliable is Mosaic’s Easy CPM.  It incorporates most of what we know, focused on  developing and using an effective schedule in any software tool. The book is designed to provide practical guidance to people involved in developing, or using, schedules based on the Critical Path Method (CPM), and act as a reference and practice guide to enhance the effectiveness of their scheduling practice.

For more see: https://mosaicprojects.com.au/shop-easy-cpm.php 

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LLM and Project Management – The Intelligence in AI is limited!

Posted on December 20, 2023 by | 1 comment

The best known LMM (Large Language Model) is ChatGPT. The developers acknowledge ChatGPT sometimes writes plausible-sounding but incorrect or nonsensical answers. Fixing this issue is challenging, as during the LLM training there is no single source of truth (the app is biased towards what it has been taught). The ‘training source’ for ChatGPT is the internet which has 1000s of incorrect posts on various aspects of project management – GIGO applies.  

To overcome this problem a number of developments based on groomed training materials are in development, some proprietary in-house, and some to be publicly available. Two of these are:

Marvin, a collaboration between Projecting Success and Praxis, Mosaic is supporting this development – watch this space in 2024.

PMI’s Project Infinity, based on the vast library of publications and papers held by PMI.  This tool is still in Beta, but as a PMI member I’ve had access to test the model.

Project Infinity Test (1)

The ‘intelligence’ in LLM applications is the ability to understand and reply to language in a coherent way.  You ask a question, the app understands what you have asked, searches its learning, and formulates an answer you can understand. What seems to be missing is the ability to qualify the information in its systems, particularly when specific facts are required.

My test for Project Infinity was based on asking “What is the critical path?”.  The correct answer to this question based on the PMI Practice Standard for Scheduling (Third Edition) and ISO Standards is something similar to: 

Critical Path: sequence of activities that determine the earliest possible completion date for the project or phase.  See: Defining the Critical Path 

As anyone with even a limited knowledge of CPM scheduling knows, ‘Zero Float[1]’, or float in general cannot be used to define the critical path for the following reasons:

  1. Date constraints can cause changes in the float value, usually to create negative float, see: Negative Float and the Critical Path
  2. Multiple calendars can change float values along the critical path, see: Calendars and the Critical

A summary of my ‘chat’ with Project Infinity is:

Q1 – what is the critical path?

       ‘The critical path is the longest sequence of activities in a project plan which must be completed on time in order for the project to be completed on schedule. It is determined by identifying the activities that have zero slack or float time,….’

Q2 – Why are you claiming the critical path has zero float when it may have negative float?

        ‘Negative float can occur when an activity’s late finish date is earlier than its early finish date, which means that the activity is taking longer than planned and is delaying the project. However, the critical path always has zero float because any delay in the critical path activities will cause a delay in the overall project timeline. …….  In summary, while negative float can occur in non-critical path activities, the critical path always has zero float because any delay in these activities will cause a delay in the overall project timeline.’

Q3 – so what happens when the finish milestone and the project overall have a constrained finish?

        ‘When the finish milestone and the project overall have a constrained finish, total float may be used to provide an early indication of potential project completion slippage.’
[Note: I’m assuming ‘Total Float’ can be negative PI did not say so.]

Q4 – Why does your third answer contradict the first answer?

        ‘My third answer does not contradict the first answer. ……’

The full exchange can be seen at Project Infinity Test 1 – Critical Path. 

Conclusions

This simple test shows at the current level of development Project Infinity has a lot or learning to do:

  • It ignored key PMI documents, in particular the PMI Practice Standard for Scheduling (Third Edition)
     
  • It failed to recognize a direct contradiction in its answers.

Therefore, while LLM tools can help save time bringing together information from diverse sources, their training to date is limited to absorbing information from documents, the next stage of development involving qualifying and grading the data may be a way off. So if you do not know the right answer to a question, you cannot rely on an AI tool using LLM to provide you with a way out.  

To make matters worse, accountability in AI is a complex issue. We know AI systems can misstep in numerous ways, which raises questions about who is responsible? This is a complex legal issue and in the absence of someone else who is demonstrably at fault, you are likely to carry the can!

For more on AI in project management see:  https://mosaicprojects.com.au/PMKI-SCH-033.php#AI

[1] The concept of the critical path having zero total float arose in the 1960s when computer programs were relatively simple and most schedules were manually drawn and calculated. With a single ‘Day Number’ calendar and no constraints the longest path in a network had zero float. The introduction of computer programs in the 1980s that allowed multiple calendars and constraints invalidated this definition.

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The evolution of AI

Posted on December 17, 2023 by | Leave a comment

In our previous blog, AI is coming to a project near you!, we identified a large number of project management software applications using Artificial Intelligence (AI) and the rapid spread of the capability. But what exactly is AI? This post offers a brief overview of the concept.   

AI is not as new as some people imagine. Some of the mathematics underpinning AI can be traced back to the 18th century and many of the fundamental concepts were developed in the 20th, but there was very limited use of AI. The ability to make widespread practical use of AI required the development of computers with sufficient processing capabilities to process large amounts of data quickly.  Each of the developments outlined below were enabled by better processors and increased data storage capabilities.

Types of AI

The modern concept of intelligent processing is more than 50 years old, but the way a computer application works depends on the design of the application.  Very broadly:

Decision tables have been in software since the 1960s, the decision table applies a cascading set of decisions to a limited set of data to arrive at a result.  The ‘table’ is hard-wired into the code and does not change. Many resource levelling algorithms are based on decision tables to decide what resources get allocated to which activities on each day.

Expert systems, known as rule-based systems in the 1960s, use explicitly crafted rules to generate responses or data sets based on an initial question. These systems were the basis of many automated Chatbots and help systems. The system’s rules are ‘hard-wired’ and do not change without external intervention.

Data mining was developed in the 1990s. The application uses generalized instructions to look at large volumes of data to discover previously unknown properties. Generalized processes means the data being examined does not need to be labelled or predefined. The application works out a suitable structure, and then draws classes information from within the data set. These system can be interactive, but are not self-learning. Extracting knowledge from ‘big data’ supports Business Intelligence and other business and marketing improvement initiatives.

Machine learning (ML). Basic ML is similar to data mining. It concerned with the development and study of statistical algorithms that can effectively generalize to perform tasks without explicit instructions. ML focuses on prediction and recognition, based on properties the application has learned from training data. The basic functions of ML were defined in the early 2000s and the concept continues to evolve and develop. The basic ML approach can be seen in a range of project management tools where the application recommends durations, lists likely risks, or performs other predictive assessments on your current project, based on data from previous projects.

Algorithmic Decision Making, a subset of ‘expert systems’ focused on using conventional machine learning and statistical techniques such as ordinary least squares, logistic regression, and decision trees to automate traditional human-based decision-making processes. Research suggests, well designed algorithms are less biased and more accurate than the humans they are replacing, improving predictions and decisions, but care is needed; they can also perpetuate blind spots, biases and be built to be fundamentally unfair.

Generative AI (Gen AI) extends the capability of ML. Gen AI uses generative artificial neural networks and ‘deep learning’ to deliver enhanced performance. Gen AI has been applied to large language models (LLM), computer vision, robotics, speech recognition, email filtering, agriculture, medicine, and many other fields. Each branch of development takes the basic principles of Gen AI and adapts them to the specific needs of the researchers. Latest trends are linking different strands of Gen AI to create new things such as generating pictures from verbal descriptions, and linking Gen AI to the IoT (Internet of Things) and additive manufacturing functions to produce computer designed ‘stuff’.

Large language models (LLM) are the branch of generative AI with most direct relevance to project management. LLM uses deep learning algorithms that can perform a variety of natural language processing (NLP) tasks. They are trained using massive datasets which enables them to recognize, translate, predict, or generate text or other content. LLM applications must be pre-trained and then fine-tuned so that they can solve text classifications, answer questions, summarize documents, and generate text, sound, or images. The challenge with LLM is in the training materials, the system only knows what it has been taught. This branch of Gen AI burst into prominence with the development of ChatGPT. Its developer, OpenAI (a research company), launched ChatGPT on November 30, 2022 – a year later and ChatGPT has world-wide attention.

LLM underpins most of todays advanced AI applications and can generate content across multiple types of media, including text, graphics, and video. While early implementations have had issues with accuracy and bias the tools are improving rapidly.

Progress to date indicates that the inherent capabilities of Gen AI will fundamentally change enterprise technology, and how businesses operate. Rather than simply requiring technical skills, employees will also need critical thinking, people skills, and a good understanding of ethics and governance processes.

In the four months from January to April 2023 the percentage of employees in Australia using Gen AI grew from 10% to 35%[1].  This rapid growth in use raises concerns around safety, privacy and security but businesses that do not explore the use of Gen AI in their organisations or industry risk being left behind.

The technological world is becoming very closely integrated:

Source: ACS Australia’s Digital Pulse | A new approach to building Australia’s technology skills – click to expand.

For more on the application of AI to project management software see: https://mosaicprojects.com.au/PMKI-SCH-033.php#AI

Our next post will look at the use of LLM in project management.

[1] Australian Computer Society research 2023. Australia’s Digital Pulse | A new approach to building Australia’s technology skills

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Is Fishermans Bend heading for the same public transport disaster as Docklands?

Posted on December 11, 2023 by | Leave a comment

Decades after Docklands was built, getting into and out of the commercial side during rush hour is difficult, and getting on a tram is almost impossible. Similarly, there’s still no direct connection from the residential areas on the North side of the harbour to the commercial areas on the South. For public transport users the only way out is into the city crush.

Now the design for Fishermans Bend is focused on making the existing crush worse. The only tram route out of the ‘employment zone’ (dotted blue lines) passes through Docklands and into the CBD.  Add to this the fact that Packenham, Cranbourne, and Sunbury trains won’t even go through Southern Cross once the Metro Tunnel is open and the ‘orange’ Metro 2 underground trainline is 40+ years away, a rethink is needed. 

The overlooked fact is 80% of the tram tracks exist for a direct link between the Fishermans Bend ‘employment zone’ and the new ANZAC Station at the Domain – follow the yellow brick road.  Fill in the missing links and everyone wanting to travel on the Packenham or Cranbourne trains, or to the SE using the St Kilda Rd trams can bypass the city crush and save time. 

Connectivity from Docklands to anywhere but the CBD was a disaster for the first couple of decades and getting into the CBD was not easy.  Lots of improvement projects later it’s still far from good.  Why is the government making the same mistake in Fishermans Bend? Most people working in the new ‘employment zone’ will not be living in the CBD – so why is the planning focused on cramming everyone through the already overcrowded CBD?

This is a Melbourne grumble……  For more on the Fishermans Bend project see: https://www.fishermansbend.vic.gov.au/

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AI is coming to a project near you!

Posted on December 9, 2023 by | 2 comments

Like it or not, Artificial Intelligence (AI) is coming to a project near to you. As well as adaptations of the generic tools such as ChatGPT many new tools are being released and established tools upgraded to embed AI in various ways. But care is needed – “Garbage in, Garbage out” can still diminish the value of AI.

Generative AI tool that create content based on their ‘large language model’ need to be trained on quality resources rather than the mass of misinformation floating around the internet. This is not hard to do and can generate impressive results (but be careful of copyright).  Most project management tools with embedded AI are built around machine learning (ML) and learn from the data you generate; the more advanced tools then apply AI to create insights.

These enhanced tools bring almost limitless processing capabilities to give meaning to data and help make crucial decisions to achieve project strategies. They can take over various technical tasks allowing project managers to deal with more crucial tasks as well as improving various estimating and risk assessment processes by provide insights from previous projects to enable managers to do a better job. These systems can also assist by keeping track of the project and checking key metrics like budgets, milestones, and other resources.

AI is still improving, and so are AI project management tools. All of this creates numerous benefits for the project management process. However, here are some core benefits you can expect right away. 

  • Better Project Estimations 
  • Improved Scheduling and Planning
  • More reliable Roadmaps and Budgets
  • More Predictability

There are a surprisingly large number of tools embedding ML and/or AI, too many to list here!  What we have done is augment the Mosaic PM Software and Tools listing to highlight tools with some ML or AI capability – look for the blue – AI – in the categorized listings at:
https://mosaicprojects.com.au/PMKI-SCH-030.php 

If you know of any additional tools missing from the list (or tools in the list that should be flagged ‘AI’) let me know and I will update the list.

For more on the application of AI to project management software see: https://mosaicprojects.com.au/PMKI-SCH-033.php#AI

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How WPM Works

Posted on December 5, 2023 by | Leave a comment

Work Performance Management (WPM) is a methodology developed by Mosaic Project Services Pty Ltd to offer a simple, robust solution to the challenges of providing rigorous project controls information on projects that cannot (or are not) using CPM and/or EVM. It works by setting an expected rate of working using an appropriate metric, then measuring the actual work achieved to date. Based on this data, WPM can assess how far ahead or behind plan the work currently is, and using this information calculate the likely project completion date and VAC.

The basis of the calculations used in WPM are the same as is used in Earned Schedule (ES), however, WPM is much simpler to set up and use. The only two requirements to implement WPM are:

  • A consistent metric to measure the work planned and accomplished, and
  • A simple but robust assessment of when the work was planned to be done.

Our latest article, How WPM Works, explains in detail the processes and calculations used in WPM, and the outputs produced.

Understanding the current status and projected completion is invaluable management information for Agile and other projects where CPM schedules are not used, and even where a project has a good CPM schedule in place this additional information is useful. Then by plotting the trends for both the current variance (WV) and VAC management also knows how the project is tracking overall.

Download How WPM Works: https://mosaicprojects.com.au/Mag_Articles/AA038_-_How_WPM_Works.pdf

For more on WPM see: https://mosaicprojects.com.au/PMKI-SCH-041.php#Overview

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