Started in 2011 as my outlet to share my experiences on personal life and work topics. My handle is khanmjk. My friends & colleagues call me "Mo". This blog is an experiment, work-in-progress.
Life: Self-awareness, personal development, growth hacking (quantified self).
Work: Software and Systems Engineering, Leadership, Management, New Ideas and OpEds.
This morning I decided to test ChatGPT's original thinking, in helping solve humanity's greatest challenges. As this article by TechCrunch analyses Sam Altman's assertions as Hype or Believable, I decided to put ChatGPT to the test: Can it actually synthesize new ideas to help us?
Here is the prompt I fed:
Act like an expert historian, philosopher and theologian and an award-winning global objective journalist. Deeply analyse the history of humanity (starting 2500 years ago) from diverse perspectives, considering all angles. Do not limit your analysis to the western world only. As an earth historian you must cater for all human societies, including historical evidence from a global perspective (quite often history is misrepresented omitting hard truths). Do not be biased. Analyse all the world’s philosophies (again do not limit your analysis to western philosophy only - include diverse philosophers from around the world). Study the world’s religions with the biggest following, including the most fastly growing religion. Synthesize your analysis and propose a new system for humans to adopt, that would solve humanity’s greatest problem. What is humanity’s greatest problem? Well, you need to surface, based on your analyses across history, philosophy, theology and current world affairs (taking into account the previous world wars, class of civilisations, etc. to make an assessment if humans are indeed improving for the better, or stuck in their old ways). Present your proposal in the form of PHD thesis that does not exceed the length of six A4 pages. Be crisp about the problems humans face today. What is the current state of the world? What could be a desirable future state? How would humans need to embrace changes to get there? Be critical by using data and history to support your thesis. Include deep critical thinking of the positives and negatives. Provide deeply thoughtful recommendations and assertions. Create model, including attributes or KPIs that define the health of the world, broken down by country. A heat map would also make a good visualization to drive the point home. Format your thesis that is suitable for a blog post. Include embedded links to navigate the post, table of contents, etc. Include citations and references. Give your new proposition a name, if you decide to invent a new philosophy.
After a few iterations, I decided to end the experiment and publish ChatGPT's thesis in this post.
Verdict? I'm not that impressed. ChatGPT failed IMHO to demonstrate original thinking :-) Of course, computer scientists would remark the AI is still a machine that is processing from its massive knowledge graph and synthesizes a coherent narrative, based on the collective content it already has, and repackages it to drive a successful outcome of achieving its objective, as set out by the prompt. For original thinking, we need AGI, super intelligence which could take "a few thousand days, or longer", according Altman...who knows, time will tell.
I'll give ChatGPT some credit though, it nailed the root cause of humanity's problem as one of division! And I'll give it a B+ for producing the output in the format requested, and A+ for understanding the ask for a model, with attributes and KPIs driving a visualization heat map.
For now, I'll steer away from engaging AI on morality or any other "complex, nuanced" humanities problems-space, and stick to experimenting with using AI as power tools, copilots to improve my personal and professional productivity...
Embracing Global Harmonism: A Journey Toward Unity in Diversity
Embracing Global Harmonism: A Journey Toward Unity in Diversity
Introduction
“We are caught in an inescapable network of mutuality, tied in a single garment of destiny.”
— Martin Luther King Jr.
Humanity stands at a pivotal crossroads. In an era where technology has bridged vast distances, connecting us instantaneously, we find ourselves paradoxically fragmented by cultural, religious, and ideological divides. This thesis embarks on a comprehensive journey through the rich tapestry of human history, philosophy, and religion, seeking to understand the roots of our divisions and proposing Global Harmonism—a philosophy aimed at uniting humanity in its diversity.
The Tapestry of Human History
Eastern Civilizations
In the fertile valleys of the Yellow and Yangtze Rivers, ancient China gave rise to dynasties like the Zhou and Han, cultivating philosophies that emphasized harmony and balance. Confucius (551–479 BCE) taught the importance of filial piety, benevolence, and justice, laying the groundwork for social cohesion[1]. Concurrently, Laozi introduced Daoism, urging alignment with the Dao—the natural order of the universe[2]. These philosophies underscored the significance of living in harmony with oneself and society.
In India, the Indus Valley Civilization (c. 3300–1300 BCE) showcased advanced urban planning and trade. The Maurya and Gupta Empires became epicenters of culture and learning[3]. Hinduism introduced concepts like Dharma (duty) and Karma (action and consequence), emphasizing moral living. Buddhism, founded by Siddhartha Gautama, advocated for the Middle Way—a path of moderation away from extremes[4].
African Empires and Wisdom
Africa's rich heritage includes the Kingdom of Kush, known for its pyramids and trade networks[5], and the Mali Empire, where Mansa Musa established Timbuktu as a center of Islamic learning[6]. The philosophy of Ubuntu—"I am because we are"—originated here, emphasizing communal relationships and mutual care[7]. It teaches that one's humanity is intrinsically linked to the humanity of others.
Indigenous Cultures and Teachings
Indigenous peoples share a profound connection with nature. The Aboriginal Australians perceive existence through the Dreamtime, a spiritual framework connecting past, present, and future[8]. Native American tribes, like the Iroquois Confederacy, practiced sophisticated governance and upheld principles of sustainability and reciprocity[9]. Their wisdom reminds us of our role as stewards of the Earth.
Western Philosophical Evolution
Ancient Greece introduced democracy and fostered philosophical inquiry through Socrates, Plato, and Aristotle, who explored ethics, politics, and metaphysics[10]. The Roman Empire developed legal systems that influence us today[11]. The Enlightenment era championed reason, individual rights, and scientific exploration, propelling technological advancements but also setting the stage for colonialism[12].
Global Philosophical Insights
Harmony in Eastern Thought
Confucianism centers on ethical living and social harmony. The Five Relationships outline a societal structure based on mutual respect[13]. Daoism encourages living simply and in harmony with the Dao, embracing the natural flow of life[14]. Buddhism offers the Four Noble Truths, guiding individuals toward enlightenment and liberation from suffering[15].
Ubuntu: African Humanism
Ubuntu is a Nguni Bantu term meaning "humanity." It embodies the idea that a person is a person through other people[16]. This philosophy promotes empathy, sharing, and community cohesion. It challenges the Western emphasis on individualism, offering a perspective where communal well-being is paramount.
Indigenous Wisdom: Living with Nature
Indigenous philosophies often view humans as part of an interconnected web of life. The Maori concept of Kaitiakitanga refers to guardianship and conservation of the environment[17]. Native American spirituality emphasizes respect for all living things and the recognition that actions affecting the environment ultimately affect humanity[18].
Western Individualism and Rationalism
Western thought has emphasized individualism and rationalism. Descartes' declaration, "Cogito, ergo sum" (I think, therefore I am), underscores the focus on individual existence and reason[19]. Kant explored morality based on reason, proposing the Categorical Imperative—acting according to the maxim that one would wish all others to follow[20]. While fostering innovation, this emphasis can lead to alienation and environmental disregard.
The Role of World Religions
Islam: Unity and Social Justice
Islam, revealed to Prophet Muhammad (570–632 CE), emphasizes submission to the will of Allah and the unity of the Ummah (community of believers)[21]. The Quran provides guidance on personal conduct, social justice, and economic equity. Muhammad's teachings transformed Arabian society, advocating for the rights of women, orphans, and the poor[22]. Islam's emphasis on charity (Zakat) and social responsibility fosters community cohesion.
Christianity: Love and Redemption
Christianity centers on the life and teachings of Jesus Christ, promoting love, forgiveness, and redemption[23]. The Sermon on the Mount encapsulates Christian ethics, urging followers to love their neighbors and enemies alike. Christianity's spread influenced art, law, and morality, emphasizing the intrinsic value of each individual.
Hinduism and Buddhism: Paths to Enlightenment
Hinduism is a tapestry of beliefs and practices, introducing concepts like Atman (soul) and Brahman (ultimate reality), highlighting the unity of all existence[24]. Buddhism offers a path to overcome suffering through ethical living, meditation, and wisdom. Both religions encourage self-realization and compassion toward all beings.
Identifying Humanity's Greatest Problem
Despite our rich heritage of wisdom, humanity grapples with division. This fragmentation manifests as:
Cultural and Religious Conflicts: Misunderstandings leading to wars, terrorism, and discrimination.
Economic Inequality: The richest 1% own more than half of the world's wealth[25], while billions live in poverty.
Environmental Degradation: Climate change and biodiversity loss threaten our planet[26].
Technological Disparities: Unequal access exacerbates educational and economic divides[27].
Social Alienation: Despite connectivity, loneliness and mental health issues are on the rise[28].
These challenges are interrelated, stemming from a fundamental lack of unity and understanding.
Proposing Global Harmonism
Foundational Principles
Global Harmonism is a philosophy that seeks to unite humanity by embracing:
Interconnectedness: Recognizing the shared essence of all people and life.
Mutual Respect: Valuing diversity in cultures, beliefs, and perspectives.
Collective Responsibility: Understanding that individual actions impact the global community.
Sustainable Coexistence: Harmonizing human activities with the natural world.
Holistic Education: Integrating emotional, ethical, and intellectual development.
The Journey to Global Harmonism
Global Harmonism draws upon the wisdom of various cultures and religions:
From Islam: Embracing social justice and unity, inspired by the Quran and Prophet Muhammad's teachings on compassion and equality[29].
From Eastern Philosophies: Adopting harmony and balance from Confucianism and Daoism.
From African Ubuntu: Prioritizing communal relationships and shared humanity.
From Indigenous Teachings: Living in harmony with nature and recognizing our role as caretakers.
From Western Thought: Utilizing rationalism and individual rights to promote innovation ethically.
Implementation Strategies
Educational Transformation:
Curriculum Integration: Incorporate global philosophies and ethics into education.
Critical Thinking and Empathy: Teach students to analyze diverse perspectives and cultivate empathy.
Intercultural Competence: Encourage language learning and cultural exchange.
Economic Equity:
Fair Resource Distribution: Develop systems that ensure equitable access to resources.
Ethical Business Practices: Encourage corporations to adopt sustainable and socially responsible policies.
Technological Accessibility:
Digital Inclusion: Invest in infrastructure to provide universal internet access.
Ethical Tech Development: Align technological advancements with global harmony principles.
Environmental Stewardship:
Sustainable Practices: Promote renewable energy and conservation efforts.
Global Cooperation: Collaborate on international environmental agreements.
Cultural Exchange and Dialogue:
International Programs: Facilitate exchanges to foster understanding and reduce prejudice.
Platforms for Dialogue: Create spaces for open discussions on global issues.
Policy and Governance:
Inclusive Leadership: Advocate for representation of diverse voices in decision-making.
Global Institutions: Strengthen organizations that promote peace and cooperation.
From Division to Unity: The Path Forward
To transition from our current state of division to a harmonious future, we must:
Acknowledge Our Shared Humanity: Recognize that despite differences, we all seek happiness, security, and fulfillment.
Embrace Diversity: Celebrate cultural, religious, and ideological differences as sources of strength.
Foster Empathy: Understand others' perspectives and experiences.
Promote Justice and Equity: Address systemic inequalities that fuel division.
Protect Our Planet: Prioritize environmental sustainability for future generations.
Measuring Progress: The Global Harmony Index
Understanding the Index
The Global Harmony Index (GHI) measures a country's harmony based on five domains:
Peace and Conflict
Economic Equality
Environmental Sustainability
Health and Well-being
Education and Cultural Inclusivity
Each domain is assessed using specific indicators, providing a comprehensive view of a nation's progress toward global harmony.
Dataset Overview
To illustrate the GHI, we present data for selected countries representing global diversity:
Country
Peace & Conflict
Economic Equality
Environmental Sustainability
Health & Well-being
Education & Cultural Inclusivity
Norway
95
90
85
92
88
Japan
90
85
70
88
80
Canada
92
82
75
90
85
Germany
88
80
78
86
83
Brazil
65
55
60
70
65
India
60
50
55
65
70
Nigeria
50
45
48
55
60
China
75
70
50
80
75
United States
70
60
65
78
80
South Africa
55
40
58
62
67
Egypt
65
50
52
68
65
Australia
90
80
70
85
82
Mexico
60
55
60
70
68
Russia
50
60
55
65
70
Saudi Arabia
70
65
40
75
60
Visualization
Critique and Originality of Global Harmonism
Novel Contributions
Global Harmonism presents an innovative philosophical framework through:
Holistic Integration of Global Wisdom: Synthesizing insights from Eastern, African, Indigenous, and Western philosophies, as well as major world religions like Islam and Christianity, creating an inclusive framework that respects diverse perspectives.
Reframing the Core Problem: Identifying division itself—not merely its symptoms—as humanity's greatest challenge, shifting the focus toward addressing underlying causes.
Introducing the Global Harmony Index (GHI): A new tool that quantifies harmony across nations using multidimensional indicators, bridging philosophical concepts with actionable metrics.
Emphasizing Ethical Technological Advancement: Stressing the alignment of technological progress with ethical considerations to bridge divides.
Fundamental Shifts in Thinking
From Fragmentation to Unity: Shifting from viewing societies as isolated entities to recognizing global interconnectedness, challenging narratives of competition with collaboration.
Redefining Success and Progress: Proposing that societal success be measured by well-being and sustainability rather than economic growth alone.
Collective Responsibility over Individualism: Emphasizing that individual actions have global impacts, promoting a balance between individual rights and collective well-being.
Integrating Ancient Wisdom with Modern Realities: Blending timeless philosophies with contemporary challenges, offering solutions that are both rooted in tradition and relevant today.
Addressing Potential Criticisms
Potential Criticism 1: Idealism Over Pragmatism
Response: While aspirational, Global Harmonism provides practical strategies and measurable goals through the GHI, bridging the gap between idealism and actionable steps.
Potential Criticism 2: Cultural Imperialism
Response: The philosophy is built on inclusivity, seeking common ground without overriding cultural identities, and promotes mutual respect.
Potential Criticism 3: Resistance to Change
Response: Recognizing that change is gradual, the thesis advocates starting with education and grassroots movements to build momentum.
Conclusion
Our journey through human history reveals a wealth of wisdom emphasizing unity, compassion, and harmony. Global Harmonism seeks to harness this collective knowledge to address humanity's greatest problem—division. By embracing our interconnectedness and implementing strategies that promote equity and sustainability, we can forge a path toward a future where diversity is celebrated, and unity prevails.
The originality of this thesis stems from its holistic synthesis of global philosophies, the innovative Global Harmony Index, and its call for fundamental shifts in thinking. It presents a novel framework that is both aspirational and practical, inviting individuals, communities, and leaders to participate in creating a harmonious world.
Together, we can transform our world, ensuring prosperity and peace for generations to come.
References
Confucius. The Analects. Translated by D.C. Lau, Penguin Classics, 1979.
Laozi. Tao Te Ching. Translated by Stephen Mitchell, Harper Perennial, 1988.
Thapar, Romila. The Penguin History of Early India. Penguin Books, 2003.
Rahula, Walpola. What the Buddha Taught. Grove Press, 1974.
Welsby, Derek A. The Kingdom of Kush. Markus Wiener Publishers, 1998.
Levtzion, Nehemia. Ancient Ghana and Mali. Methuen & Co, 1973.
Mbiti, John S. African Religions and Philosophy. Heinemann, 1990.
Flood, Josephine. The Original Australians. Allen & Unwin, 2006.
Johansen, Bruce E. The Great Law of Peace and the Constitution of the United States. 1987.
Plato. The Republic. Translated by Allan Bloom, Basic Books, 1991.
Heather, Peter. The Fall of the Roman Empire. Oxford University Press, 2006.
Outram, Dorinda. The Enlightenment. Cambridge University Press, 2013.
Man, Richard Hamming's talk is doing a number on me. So much of what he said, back in 1986 is still relevant today! Calling out Hamming's "Seven Year Shift" policy that resonated so much with me...this talk should go down as one of the best career talks in history...
Hamming's suggestion of a "significant, if not complete, shift in your field" every seven years might seem counterintuitive at first. Why change when you've built expertise and a reputation in a particular area? Here's a closer look at his reasoning, drawing on his insights from the sources you provided:
1. Combating Stagnation and Maintaining Originality:
Hamming argues that staying in one area for too long can lead to stagnation. You become overly reliant on familiar methods, your thinking becomes less flexible, and you may miss out on new and emerging opportunities.
He observes: "What happens to the old fellows is that they get a technique going; they keep on using it. They were marching in that direction which was right then, but the world changes. There's the new direction; but the old fellows are still marching in their former direction."
This idea emphasizes the importance of actively seeking new challenges and perspectives to keep your thinking fresh and continue growing.
2. The Power of "Beginner's Mind"
By shifting to a new area, you force yourself back into a "beginner's mind" state. You're no longer the expert, which can be liberating. This allows you to approach challenges with fresh eyes, ask fundamental questions, and potentially make connections that you wouldn't have seen otherwise.
Hamming, reflecting on his own career choices, says: "...when error correcting codes were well launched, having these theories, I said, 'Hamming, you are going to quit reading papers in the field; you are going to ignore it completely; you are going to try and do something else other than coast on that.' I deliberately refused to go on in that field. I wouldn't even read papers to try to force myself to have a chance to do something else."
He actively chose to become a "beginner" again, opening himself up to new possibilities.
3. Planting New "Acorns" for Future Growth
Hamming uses the metaphor of planting acorns that grow into mighty oaks to illustrate the importance of consistently nurturing new ideas and areas of expertise.
He advises: "You have to change. You get tired after a while; you use up your originality in one field. You need to get something nearby... so that you don't go stale... You can do something about this, but it takes effort and energy. It takes courage to say, 'Yes, I will give up my great reputation.'"
This suggests that even giving up a degree of established expertise can be beneficial in the long run, as it creates space for new growth and potentially even greater accomplishments.
4. The "Seven Year Shift" in Today's Context
While the specific timeframe of seven years might not be a rigid rule, the underlying principle of embracing change and seeking new challenges is highly relevant for professionals today:
Rapid Technological Advancements: In fields like technology, where change is constant and skills can become obsolete quickly, actively seeking new challenges and updating your knowledge base is essential.
The Evolving Nature of Work: The rise of the gig economy, remote work, and the increasing demand for adaptable skillsets mean that professionals need to be prepared to navigate career transitions more frequently.
Personal Growth and Fulfillment: Beyond external success, seeking new challenges can contribute to personal growth, prevent boredom, and keep you engaged and motivated throughout your career.
Hamming's "seven year shift" isn't about abandoning your expertise or making drastic career changes for the sake of it. It's about recognizing the dangers of complacency, embracing a mindset of continuous learning, and actively seeking out new challenges that can keep you engaged, adaptable, and at the forefront of your field.
Back in 1986, Richard Hamming, a highly respected figure in the world of mathematics and computer science, gave a talk at Bell Labs titled "You and Your Research". Although he was speaking to researchers, his advice is incredibly relevant for anyone, especially those of us in software engineering, who want to make a real impact.
One of the most important things Hamming talks about is the need to work on problems that matter. Don't just settle for the routine stuff. It's not just about luck; it's about preparing your mind to spot and seize opportunities. What are the biggest headaches in your area of software engineering? What problems, if solved, would make the biggest difference? Focusing on impactful problems increases your chances of doing truly great work.
Hamming was a big believer in having a growth mindset. To him, obstacles weren't roadblocks, but chances to think differently and come up with something innovative. Software engineers constantly face limitations – whether it's resources, technical issues, or those pesky bugs. See these as opportunities. Did you discover a clever workaround for a bug? Document it, share it with your team, and turn that challenge into an advantage.
There's no shortcut to great work – it demands deep commitment. Hamming believed that when you fully immerse yourself in a problem, your subconscious mind keeps working on it, often leading to breakthroughs. As software engineers, this means dedicating ourselves to exploring solutions thoroughly. Don't be afraid to go deep – research, experiment, refine your code. The effort will shine through in the quality of your work.
Even the most brilliant work can go unnoticed if you don't communicate it effectively. Hamming believed in "selling" your work, no matter how good it is. For us, this means becoming excellent communicators – both in writing and presentations. A well-written design document or a compelling presentation is crucial for getting buy-in from stakeholders.
The world of software engineering is always changing, so never stop learning. Hamming believed in switching things up in your field to avoid getting stale. Stay current with the latest technologies, languages, and methodologies. Make time to read industry publications, attend conferences, and connect with the wider software development community.
What are you first-class at? Hamming stresses the importance of introspection and self-awareness. He encourages individuals to be honest about their capabilities, acknowledging both strengths and weaknesses. To discover what you're "first-class" at, you must examine your career, passions, and natural abilities. What are you naturally drawn to? What tasks or projects have you excelled at in the past? Don't be afraid to specialise. While a broad skillset is valuable, becoming a true expert in a niche area allows you to make unique contributions. Identify that area within software engineering where you can truly shine and relentlessly develop your expertise. This focused approach increases your chances of producing exceptional work and leads to a more fulfilling career.
Hamming's talk is a treasure trove of wisdom. By focusing on the right problems, embracing challenges, being truly committed, communicating effectively, and constantly learning, you give yourself the best shot at creating impactful and lasting work as a software engineer.
So it's been about 5 hours that I've been playing around with chatGPT o1-preview today. I had to wait a week to get my credits going again. Last Sunday, I made a simple resource planner forecasting tool for software engineering managers. Today I decided to explore something I've been putting off for a very long time, for more than a decade actually. I believe there is a gap is software planning tools, starting with the mental model of defining the software system architecture, breaking it down into services, APIs and dependencies, forming the teams around the architecture, and then integrating work package planning with the architecture definition.
My goal is to make planning work packages easier, dating back to when I described in detail how I managed a very large scale software delivery here. I want to bring this thinking into a tool. When planning projects or any new initiatives, when defining the work package, one can pull all the details needed from a primary source, driven by the software architecture and dependencies, we can solve the risk of missing critical tasks, ensuring all related teams are included in the overall planning.
So today, after going through a few rounds of building these workflows, with chatGPT as my copilot - I decided to scrap everything, and begin with the end in mind. So the first iteration is a working backwards from the end visualizations, setting up the mental model to mature further. The tool is available in a separate page here, and embedded in this blog post. There are two example software systems: 1\ A generic video streaming app called "StreamView"; 2\ A generic contact center system called "ConnectPro". I have a long history with building video streamingapps, and for the last 3 years I've been building a contact center for AWS Support.
At first I started creating the workflows from scratch like capturing the system details through some forms and workflows. The interaction was amusing, classic scope creep, change of requirements, build-run-change-iterate cycles. Do this long enough, chatGPT loses context after a while and messes things up. Then I directed chatGPT to synthesize its own system architectures, using its own knowledge of software architecture and whatever it learnt about video streaming apps and contact center stacks. I instructed it to generated its own services, dependency trees and basically generate the fake data to drive the mental model. Now we (chatGPT and I) have a good base to start refining the mental model, baseline a data model, and then build the advanced software planning tool from there. Ideally, the end goal is a component or service that can be plugged into the various software planning tools in the market today. I feel the lack of an integrated software system dictionary is one of the reasons why we still experience poor software project management today. Let's see how far I get on with this vision!
The more I interact with chatGPT, the more I'm blown away. The key learning takes me back to my days when I used to write technical requirements, system use cases. All of this knowledge is now needed to prompt these LLM GPTs. It is amazing how chatGPT o1-preview synthesizes the requests, applies chain-of-thought reasoning, and usually gets an MVP right on first attempt. The interaction will take several hours, or even days - but I can only see this thing getting so much better!
Seed Prompt for tool (click here to play with it): I am a software engineering manager. A large part of my job is understanding the engineering resource utilization for my engineering team. I manage multiple engineering teams of varying sizes from 5 people to 20 people in a team. When estimating software projects, understanding availability of productive engineers is important for planning purposes. Help me build an interactive resource forecasting tool, that can be fully self-contained within browser app, embedded in a google blogspot page. The tool must include inputs for: 1\ Funded team size; 2\ Current Available engineers (i.e. actual current size of team). The tool must account for the time it takes for hiring new engineers, ramp-up time, learning, etc. before they can be deemed as productive for committing to project work. The tool must show a table the resource plan over 52 weeks in the year, and include a visual graph to show how the team size grows to meet funded size. Research the best methods in software engineering management, and create the tool that can help software managers have a good model for resource utilization. The tool can store information in the local user browser storage as needed. Remember, I need the full code to be fully self-contained so I can run the tool from within a google blogspot page.
Prompt for this article: Great I think we have good baseline version to start with. Now using your PhD capabilities, write up an accompanying blog post that details the model, the thinking behind it, and call out the limitations using a critical eye, suggesting improvements for the next version.
Prompt for Image using Dall-E: "An isometric illustration of a diverse engineering team collaborating in a modern office space. They are gathered around a large table filled with charts, graphs, and laptops, discussing and planning. Behind them, a wall-sized calendar and a whiteboard display timelines, Gantt charts, and upward-trending graphs. Include elements like gears and clock icons subtly integrated into the design to symbolize engineering and time management. Use a professional, clean art style with vibrant yet muted colors to convey a serious but engaging atmosphere.
Engineering Resource Forecasting: A Comprehensive Model for Team Planning
By ChatGPT o1-Preview (took about 4 hours to get the tool to version 1)
Effective resource planning is crucial for engineering teams aiming to meet project deadlines, optimize productivity, and manage budgets efficiently. The Engineering Resource Forecasting Tool is designed to help managers and team leads forecast their engineering resources over a year, considering various real-world factors such as hiring rates, attrition, ramp-up times, efficiency, leave days, and public holidays.
In this blog post, we'll delve into the model behind the tool, explore the thinking that shaped its development, critically analyze its limitations, and suggest improvements for future iterations.
Understanding the Model
1. Objectives of the Tool
The primary goals of the Engineering Resource Forecasting Tool are to:
Forecast Team Size: Predict how the engineering team will grow or shrink over time.
Calculate Effective Capacity: Determine the actual productive capacity of the team, considering factors that reduce availability.
Assist in Planning: Provide insights for hiring strategies, resource allocation, and project scheduling.
2. Key Components of the Model
The model incorporates several essential elements:
Funded Team Size: The maximum number of engineers that the budget allows.
Current Available Engineers: The starting point for the forecasting, representing the existing team.
Hiring Rate and Time: The rate at which new engineers are hired and the average time it takes for them to join.
Ramp-Up Time: The period new hires require to reach full productivity.
Attrition Rate: The expected percentage of engineers who will leave the team annually.
Efficiency Factor: The proportion of time engineers spend on productive work.
Leave Days and Public Holidays: Time when engineers are not available due to vacations and holidays.
3. Model Calculations
a. Effective Engineers
The number of effective engineers is calculated weekly by adjusting the total number of fully ramped-up engineers for efficiency and availability:
Effective Engineers = Total Ramped-Up Engineers × Efficiency Factor × (Weekly Available Days / 5)
b. Weekly Available Days
Engineers aren't available all five working days each week due to leave and public holidays:
Weekly Available Days = 5 - ((Annual Leave Days + Public Holidays) / 52)
Cumulative Attrition: The total number of engineers who have left the team up to a given week.
d. Hiring and Ramp-Up Process
Hiring Pipeline: Represents engineers who have accepted offers but haven't started yet.
Ramping Engineers: New hires who are in the process of ramping up to full productivity.
e. SDE-Weeks and SDE-Days
SDE-Weeks: Sum of effective engineer contributions per week within a month.
SDE-Days: Sum of effective engineer contributions per day within a month.
These metrics provide a more granular view of the team's productive capacity.
Thinking Behind the Model
1. Realistic Representation
The model aims to mirror real-world scenarios by considering:
Time Delays: Hiring and ramp-up times introduce delays between initiating a hire and gaining full productivity.
Non-Productive Time: Leave, holidays, and non-productive activities reduce actual working time.
Attrition Effects: Engineers may leave the team, impacting capacity and necessitating replacement hires.
2. Balancing Simplicity and Complexity
While the model incorporates multiple factors, it maintains usability by:
Using Average Rates: Distributes leave, holidays, and attrition evenly over the year for simplicity.
Assuming Linear Processes: Hiring and ramp-up are modeled as linear processes without accounting for fluctuations.
3. Providing Actionable Insights
By visualizing the forecast through charts and tables, the tool helps managers:
Identify Hiring Needs: Determine the hiring rate required to meet team size goals.
Plan for Attrition: Anticipate capacity reductions due to attrition.
Adjust Strategies: Modify inputs to explore different scenarios and their outcomes.
Limitations and Critical Analysis
Despite its usefulness, the model has several limitations:
1. Uniform Distribution Assumptions
Leave and Holidays: The model assumes that leave days and public holidays are evenly distributed throughout the year. In reality, leave may cluster around certain periods (e.g., summer vacations, year-end holidays), leading to temporary drops in capacity.
Attrition Timing: Attrition is modeled as a steady rate, but actual departures may occur unpredictably and in clusters.
2. Lack of Granular Ramp-Up Modeling
Binary Productivity: The model assumes engineers are either ramping up or fully productive after the ramp-up period. It doesn't account for gradual increases in productivity during ramp-up.
Individual Variations: All new hires are treated identically in terms of ramp-up time and efficiency, ignoring individual differences.
3. Hiring Constraints and Real-World Challenges
Hiring Rate Feasibility: The model calculates the hiring rate needed to meet targets but doesn't consider the practical challenges of achieving that rate, such as market conditions or recruitment resource limitations.
Candidate Pipeline Variability: It doesn't account for fluctuations in candidate availability or acceptance rates.
4. Simplified Efficiency Factor
Static Efficiency: The efficiency factor is constant over time, not accounting for potential improvements or declines due to training, process changes, or team dynamics.
Team Composition: It doesn't differentiate between engineers with different skill levels or specializations.
5. Absence of Project Dependencies
No Task Modeling: The model focuses on resource capacity without linking it to specific project tasks or timelines.
Overtime and Workload Peaks: It doesn't account for periods when engineers might work overtime or when workload exceeds capacity.
6. Economic and External Factors
Budget Changes: The funded team size is assumed constant, ignoring potential budget cuts or increases.
External Events: Unforeseen events like economic downturns, pandemics, or natural disasters are not modeled.
Suggestions for Improvement
To enhance the model's accuracy and applicability, future versions could consider:
1. Incorporating Seasonal Variations
Variable Leave and Holiday Distribution: Model leave and public holidays based on historical patterns to reflect periods of low and high availability.
Attrition Peaks: Adjust attrition rates to account for known periods of higher turnover.
2. Enhanced Ramp-Up Modeling
Gradual Productivity Increase: Implement a ramp-up curve where productivity increases incrementally over the ramp-up period.
Individualized Ramp-Up: Allow different ramp-up times for different roles or experience levels.
3. Realistic Hiring Constraints
Recruitment Capacity Limits: Introduce maximum hiring rates based on recruitment team capacity.
Candidate Pipeline Dynamics: Factor in time-to-fill variations, candidate drop-off rates, and competition in the job market.
4. Dynamic Efficiency Factor
Efficiency Over Time: Allow the efficiency factor to change over time, reflecting process improvements or team fatigue.
Role-Based Efficiency: Differentiate efficiency factors for various roles or seniority levels.
5. Integration with Project Planning
Task-Level Planning: Link resource capacity to project tasks and milestones to assess whether capacity meets project demands.
Risk Modeling: Incorporate risks and uncertainties that could impact timelines and capacity.
6. Economic Scenario Planning
Budget Flexibility: Allow for adjustments in the funded team size based on potential budget changes.
External Shocks: Introduce scenarios for external events that could affect hiring, attrition, or productivity.
7. User Input Flexibility
Custom Time Frames: Enable users to adjust the time frame of the forecast beyond a single year.
Data Import: Allow users to import historical data to better tailor the model to their organization's patterns.
Conclusion
The Engineering Resource Forecasting Tool provides a solid foundation for planning and visualizing engineering team capacity over time. By accounting for critical factors like hiring, ramp-up, attrition, efficiency, leave, and holidays, it offers valuable insights for managers.
However, like any model, it simplifies complex real-world dynamics to remain practical and user-friendly. Recognizing its limitations is essential for interpreting the results accurately and making informed decisions. By incorporating suggested improvements, future versions can offer even more robust and precise forecasting, aiding organizations in navigating the challenges of resource planning.
About the Author
[Your Name] holds a PhD in [Your Field] and has extensive experience in project management, resource planning, and organizational development. Passionate about leveraging data-driven models to solve practical problems, [Your Name] contributes to advancing tools and methodologies that enhance operational efficiency.
Note: The Engineering Resource Forecasting Tool is intended as a planning aid and should be used in conjunction with professional judgment and other planning tools. Always consider your organization's specific circumstances when making staffing decisions.
