Wrap up '23 with my Personal Scorecard RAGE / Wheel of Life review

In 2016 I started to be more intentional with designing my lifestyle across my personal and professional streams. Without studying deeply the literature or taking personal development training courses, I used my  own work experience as a professional engineer to guide me in designing the framework, which I've called "RAGE" that stands for Reality Aspirations Goals Expectations. At the time, I treated myself as a product I'm building, using similes from agile software development, using the concept of Personas (typically products are designed to meet the needs of different user types, i.e. "personas"). Bringing these concepts into personal lifestyle design, I described my aspirations, goals and expectations in the form of agile user stories. 

This helped me in framing my goals to realise tangible outcomes. Almost eight years later, I've maintained discipline in applying the RAGE framework, year-on-year in my pursuit of the various aspirations defined in each persona, i.e. as a Husband, Father,  Professional, Friend, Individual, etc. Coming from an engineering background, I dived deep into prioritising these streams of life, first starting with 20+ personas, having stabilized on a handful of core personas from 2020 onwards.

Interestingly enough, this post, led me to learning about something called "The Wheel of Life". It so happened, according to ChatGPT, the exact date of the creation of the "Wheel of Life" model by Paul J. Meyer is not well documented in public sources -- but it is known that Paul J. Meyer founded the Success Motivation Institute, Inc. in 1960. Honestly, I'm not sure how I missed Meyer's model all this time, but I'm also comforted by the fact that I've created my own model from scratch through my own attempts in crafting a better version of myself through my RAGE model. Anyway, ChatGPT has helped summarize the differences between Meyer's model and Mo Khan's RAGE model in this post. I do like the radial diagram, which is something I hadn't included in my personametry insights as yet.

I'm writing this post in December 2023, the last post for the year - as I break away from the world and embark on a journey making the minor pilgrimage to Mecca (Makkah) for the first time in my life. I've waited a long time to save up for this journey, I made intention at the start of 2023 to do the Umrah, and by the grace of Allah (God), it is about to come true, finishing off 2023 with my most important '23 goal realised - Subhanallah (Glory be to Allah)! And aiming for Hajj (the major pilgrimage) in 4 years time insha Allah (God willing).

Work-wise, my last week was spent completing end of year performance reviews. At Amazon, we treat performance reviews with such seriousness, due care and attention to detail -- that I've never seen done before in other companies I worked with (a post for another day).  For some time now, I have taken mechanisms from my work life and adopted to my personal life. Just as in my RAGE model, breaking down the different domains of life-work streams, I've used business performance scorecards in my tracking progress through the year of my personal performance. If we maintain work logs, performance cards, "baseball cards" for our jobs, is not more important to track our all our streams of life?

Why should we only focus on professional performance reviews and not spare a moment to deeply reflect our performance as a human on this earth? How are we doing personally? How are we performing across the various dimensions of our life? If we live by a value system, how do we know how we're measuring up to that value system? When the year has come and gone, how do you measure progress? Is it only career that matters? Surely not? If not, then why don't we spend as much time, if not more time, doing our own self-assessment and scorecards?? Are we afraid of the reality check? How serious are we in terms of changing ourselves for the better? How are we improving? Do we need to improve? When someone asks you "How's life? How you're doing?" - what's your frame of reference for answering that question? What's the first thing that comes to mind? Is it our work, career? If we're going through a bad patch at work, does this mean our whole life is negative? Often this is exactly what happens. People anchor on the immediate negatives, closest, most recent experiences because without a holistic value system to reference, how should one respond to "How are you doing, really?"

So how am I doing, really - what's my 2023 Performance Scorecard like?

I am sharing my own personal tracking here, not as a means to show off - but as a means to help people, providing an example of how I've managed to use a system that is working for me. This system, called RAGE, may not work for you - but it should give you an idea of the kind of work you need to do, the kind of thinking you need to apply, and the kind of discipline your should consider -- if you are indeed determined to make a concerted effort at changing your current situation, and creating a new trajectory you can aim for to improve the quality, outcome and other aspirations you desire. 

Inspired by Vaugan from Scary Management Playbook's LinkedIn post, here is my Wheel of Life, unpacked in detail, according to my RAGE model. In January '24, I will follow up with the data analytics on time spent in my personas. Given my RAG status, it looks like my wheel of life pretty balanced and aligned with my life-work-stream choices.

My RAGE model compared to The Wheel of Life

 

[I asked ChatGPT to report on the differences between Meyer's Wheel of Life and Mo Khan's RAGE]

Comparative Report: Meyer's Wheel of Life vs. Mo Khan's RAGE Model

Introduction

This report provides a comparative analysis of two influential personal development tools: Meyer's Wheel of Life and Mo Khan's RAGE Model. Both models are designed to enhance self-awareness and personal growth, yet they differ significantly in their approach and methodology.

Meyer's Wheel of Life

• Overview: The Wheel of Life is a holistic self-assessment tool designed by Paul J. Meyer, a pioneer in the field of motivational thinking and self-improvement.
• Components: It typically includes segments such as Career, Personal Growth, Health, Family & Friends, Finances, Spirituality, Recreation, and Physical Environment.
• Function: Users rate their satisfaction in each area, visually representing life balance and identifying areas for improvement.
• Application: Widely used in coaching and self-help, it guides personal development and goal setting.
• Learn More: Success Motivation Institute

Mo Khan's RAGE Model

• Overview: The RAGE Model, an acronym for Reality, Aspirations, Goals, Expectations, is a framework for personal development conceptualized by Mo Khan.
• Components: It involves introspection across various life 'personas', assessing the current reality, setting aspirations, establishing goals, and managing expectations for each persona.
• Function: The model uses agile management techniques and a detailed scoring system for prioritization and tracking progress.
• Application: Khan’s approach is detailed and systematic, suitable for those who prefer an analytical approach to personal development.
• Learn More: Mo Khan’s Blog

Similarities

1. Holistic Approach: Both models provide a comprehensive view of personal life, emphasizing multiple areas or aspects.
2. Self-Reflection: They encourage self-assessment as a means of identifying areas of focus.
3. Goal-Oriented: Each model promotes setting and pursuing personal goals.
4. Personal Development: They are tools for enhancing self-awareness and guiding growth.

Differences

1. Complexity: The Wheel of Life is simpler and more visual, while the RAGE Model is more complex and analytical.
2. Approach: Meyer’s model is qualitative, focusing on self-rated satisfaction, whereas Khan’s model is quantitative, employing a scoring system.
3. Focus Areas: The Wheel of Life has predefined life segments; the RAGE Model allows for personalized 'personas'.
4. Tracking: The RAGE Model includes rigorous tracking mechanisms, unlike the Wheel of Life.
5. Background: Meyer's model stems from motivational training, while Khan’s is influenced by agile product management.

Conclusion

Meyer's Wheel of Life and Mo Khan's RAGE Model, while sharing the goal of fostering personal growth, differ in structure, complexity, and application. The Wheel of Life is a straightforward tool for periodic self-assessment, ideal for a broad audience. In contrast, the RAGE Model offers a detailed framework for systematically setting, prioritizing, and tracking personal development goals, appealing to those who prefer a more structured approach. Both models provide valuable insights into personal development, and the choice between them depends on individual preferences and the desired level of detail and structure in personal growth planning.

Be the leader you wish you had

BE THE LEADER YOU WISH YOU HAD

I use this saying often in my 1:1s with my directs and in my private coaching sessions. It is a powerful way to make one pause for a moment, reflect, adjust to the discomfort, then embrace the excitement of a new energy that is created.

Adopting this mindset has transformed me from standard "manager" to empathetic "leader". Reading Seth Godin's "The Song of Significance" reinforced my instinctual leadership practices. 

Quoting from "13. Let's Get Real or Let's Not Play", Seth says this:

<quote> No one goes to the gym to willingly get punched in the face by the senior vice president of boxing. But some folks eagerly pay for a sparring partner when it's time to get better.  The difference is obvious, but we've forgotten to say it out aloud.  No grades, no check marks, no badges. I'm not in charge of you, and I'm not manipulating you. I'm simply establishing the conditions for you to get to where you said you wanted to go.  You tell me where you're going and what you need. You make promises about your commitment and skills development.  I'll show up to illuminate, question, answer, spar with, and challenge you. I'll make sure you're part of a team of people who are ready to care as much as you do. We can get real. Or let's not play. </quote>

This is not some leadership mumbo jumbo. Some time ago, I developed a model for personal development that borrowed concepts from agile product management by way of user stories (search RAGE tag on this blog). I then used the same methods in the way I work with my direct reports. HR people might call this "contracting with the employee" but I take it further. I get real. It's not about objectives, KPIs & deliver results. I put myself on the line. I reach out. And so when it comes to performance reviews, my reviews are a two-way conversation. My direct also evaluates Mo's performance - because as a leader, I believe leaders mirror & contribute to the performance of their direct reports. 

What's my mechanism then?

I ask each person to write a user story in this format:

In order for me, [Name] to do [XYZ] (e.g. my job | grow | be inspired | learn | etc.) I need my manager (Mo) to support me by doing [....insert your wish-list here] so that I can ....

So I start the year with level setting on our contracts together, and in our 1:1s, we check-in and inspect, comment, re-calibrate, adjust.  

Guess what? 

This mechanism might seem simple but it's quite challenging for people. Usually, it's the first time they're experiencing a manager doing it this way. There's hook both ways. Often, it takes a few iterations to get the user stories crafted in way that is mutually relatable and agreeable. My mechanism goes beyond the standard business SMART goal setting. I make it human. Real. Personal. For me, this is my song of significance.

Here's some real-world examples in play, from senior managers that report into me - See how doing so puts me, Mo, on the hook?

* In order for me to do my job, I need my manager (Mo) to support me by throwing me in the deep end and exposing me to as much as possible so that I can quickly learn and understand this business

* In order for me to do be inspired, I need my manager (Mo) to support me by leading by example so that I can learn from his vast experience

* In order for me to do grow, I need my manager (Mo) to support me by pushing me out my comfort zone so that I can grow in all directions.

* In order for me to do my job. I need my manager (Mo) to support me by throwing me in the deep end and exposing me to as much as possible so that I can quickly learn and understand this business

* In order for me to grow my skillset, I need my manager to support me in blocking out time on my calendar so I can complete the ‘make great hiring decisions’ course (5hrs)

* In order for me to get promoted to L7, I need my manager to support me by identifying key opportunities so that I can start building a roadmap of promotional milestones

Personametry + ChatGPT = personametry.ai (a truly personalised AI)

Around this time of year with 6 months already past us, I spend some time reflecting on my Personametry and RAGE model - keeping in check how I'm performing against my own personal and professional goals -- just like we do in business with mid-year performance reviews. 

If this is the first time you've come across my work on Personametry, here's a view of my time spent in 2022 compared to 2021, click here. 

My workflow until then was:

1) Export data from Harvest

2) Update Amazon Quicksight dataset by importing the Harvest export, creating transforms

3) Create a new analysis

4) Modify all the charts and views to include the latest data, publish a new dashboard

5) Create a Google slide deck 

NO MORE!! ENTER CHATGPT and the NOTEABLE plugin!

My new workflow is now much more simplified:

1) Export data from Harvest

2) Import to Quicksight, creating transforms

3) Export CSV from Quicksight

4) Prompt ChatGPT to produce the insights in Noteable I would normally have manually created

Okay, so I spent my Sunday locked up in my office playing around with ChatGPT geeking out on data analysis & visualisations. So not much gain in time productivity there - but the learning was fun and immensely rewarding. Yes, a good investment of time, spent learning and preparing to adapt for the new world of AI disruption!

I've been on my data capturing journey since 2015. My end goal to end up with an AI personal assistant that truly understands me. I suspect realising my aspiration isn't that far off and neither far fetched for that matter. My entire workflow would be a fully integrated AI assistant that has the ability to track all my activities, by the minute (imagine "personametry.ai"). To get there, the next simpler step would be to automate the data ingestion piece, leaving me with the only manual entry of starting and ending tasks. My next experiment would be to use the raw data export from Harvest, without doing any data transforms and let the AI do that for me. If that works, I can build in automation that does monthly data imports and produces insights for me automatically. Ideally, I would build personametry.ai as a task into my personal assistant. Imagine a time when we're all wearing a device that "just knows" what we're doing, who we're interacting with, and what we're spending our time on? This device, i.e. "my AI" or "personametry" will act as a guide, coaching us along the way to improve - and hold us accountable - calling us out on what we're paying attention to (i.e. deviating from our goals.)

Lessons Learnt - Still early days but very hopeful

• The tools are still early days, but still nevertheless very powerful and will definitely improve my productivity in future.
• It takes a few attempts to load data files with the plugin, CSV seems to cope much better than XLS files.
• ChatGPT/Noteable uses different methods each time for approaching the data analysis - some coaxing on the nature of the dataset produces better insights.
• I didn't need to edit any code myself so there's an immediate empowerment driver right there.
• Don't trust every output though, as the AI can get things wrong
• Double check calculations, ChatGPT still doesn't seem to get some simple math right the first time round
• It is amazing what one can accomplish with simple, clear prompting
• I am definitely going to learn more
• I had so much fun learning, I was in a state of flow for 10 hours and couldn't stop thinking about the world of possibilities of this technology!

Here's a video of ChatGPT prompts - Play at fastest speed (sorry, no time to edit)

Here's the conversation history with ChatGPT

Round 4

Round 3

Round 2

Round 1

Here's the Noteable project that I've released publicly

Here's a screen grab of the visuals in a nice slide view

Here's all the questions ChatGPT answered in various sessions

A blast from the past: my experience building a large-scale tech platform

In the years 2003-2011, I worked for a pure technology service provider, NDS (acquired by Cisco in 2012, then later became Synamedia) which was considered at the time, the world leader in end-to-end digital TV software systems. I was fortunate enough to experience as an engineer every major area of platform development for this complex ecosystem; and then later as a software manager, I would own the software delivery for a core piece of the software stack known as "middleware", for NDS's primary anchor customer BSkyB/Sky Darwin and then later would own the full stack delivery of NDS's flagship Mediahighway Fusion/Unity product. This experience would mark my entry into very complex large-scale technology delivery initiatives, which even to this day, thirteen years later, as I work with the world's largest cloud provider, Amazon AWS, in building out its enterprise cloud support systems (AWS Support Center / Technical contact systems), Fusion still takes the prize for the most intense professional experience, learning and growth, technical complexity, risk and high-stakes projects. So yeah, I find myself having to dig deep into my memory to recall this work experience because it's funny that 13 years on, I'm encountering the same topics of engineering management even though it is supposed to be a different domain, turns out "software is just software"!

NDS had captured almost every top-tier PayTV operator around the globe at the time: Sky, DirecTV, UPC, Sky Italia, Sky Deutschland, Foxtel, Sky LA, Yes, Bharti, etc. NDS was prominently known for its conditional access product, a video content protection system call NDS Videoguard, however, NDS offered more than just security and offered customers a fully vertically integrated ecosystem (think "Apple" ecosystem for PayTV customers). Whilst digital TV was built on open standards and interoperability, most customers limited their integration points. So when they opted for NDS as their security provider, they also had the option of integrating all other services - from broadcast backend services in the headend to consumer device hardware development and software service integration with chipset vendors. The consumer device software was known as TV Middleware. At the time, the main players were NDS Mediahighway, OpenTV & TiVo. NDS was known for convincing customers to migrate to NDS Mediahighway, its technology migration programs were demanding, complex and executed flawlessly. As an engineer, I contributed software to replace TiVo, an overnight win for 40 million devices. Later as a software delivery manager for the Sky Darwin migration project, we would replace OpenTV software almost obliterating its presence from Sky, save for a few ancient, ageing hardware profiles.

NDS, with an increasing number of customers using its security, middleware and application services, couldn't afford to scale out with engineering teams for each custom build. A platform strategy was needed, consolidating the best of software from across the globe (US, UK, India, Israel, France) into a new shared technology stack, that offered flexible customisation and tailoring for any type of customer profile (Tier-1 customers like Sky for advanced applications to Tier-3/4 customers in territories just starting off with basic digital TV), using a shared engineering resource pool - and extensible configuration engine for producing tailored custom releases. So was borne, NDS Mediahighway Fusion.

The flagship customer for Fusion was Sky, which went live in 2010, replacing up to ten variants of its consumer device software services, with new Fusion components and Sky's own custom-developed consumer application "EPG" known then as the "Orchid EPG". Fusion provided an SDK/API for customers to develop their own primary applications, along with an interactive HTML engine, that allowed PayTV operators to add additional mini apps to their devices, like games and weather apps. With Sky being the anchor customer, Fusion had proved itself in the market and thus was ready to onboard new customers like Sky Italia, UPC, Foxtel, Yes, etc. Post Darwin launch, I took the lead for building the new platform vision, called Fusion Snowflake EPG through project Sunrise - birthing the platform that would create customer, tailorable configurations for any customer, maximising reuse and minimising customisation but allowing for a selection of custom user experiences.

Why am I claiming Fusion as large-scale (even in 2023, 13 years later)?

I write this in 2023, after spending 2.5 years with Amazon AWS. I am part of the group that build AWS Support Center and related Contact Center services. We are a team of under 100 people, deemed large- scale and building complex systems. Yet, if I have to be brutally honest with myself, I'm mildly impressed by my exposure to date, because my current work pails in comparison to my work on Fusion, 13 years ago. Yes I know it's a different domain, a different paradigm and culture of Amazon's 2-Pizza team model for software product ownership (which I actually find quite cool)...still I'm finding it hard to rationalise my move to AWS almost 2.5 years on, have I gone too far backwards? Am I living too much in the past & not ready to view things from a new perspective? What am I not seeing? (Topics for another post). So whilst I've defintely adapted my mental models since joining Amazon, yet I really can't ignore some software engineering truths which is the reason for my bringing up the past now. 

In 2012, I wrote the first story about Fusion, introducing the term LSSDP I coined to mean Large Scale Software Development Project. I also dived deep, writing lengthy white papers about the product and engineering management processes:

• How we "scaled agile" to adapt to our unique global challenges
• How to design a global org-structure to deliver a large-scale project in a scaled agile way
• What mechanisms are needed to deliver a large-scale technology initiative in an agile way
• How we executed and raised the engineering & product management bar

Fast forward to 2023, now using my Amazon AWS experience as a lens for defining a large-scale initiative and indirectly checking engineering manager role guidelines for large-scale:

• Business Impact - Fusion started off with a $75 million investment and later a joint-venture with the flagship customer, Sky. The entire company pivoted to focus on Fusion as its next-generation software platform, with up to 3000 engineers world-wide working on multiple streams, some strategic foundational streams kicked off at least 2 years before the mainstream program. In my role as software delivery owner for Sky Darwin project, it was critical the project delivered successfully, flawlessly - as it involved migrating software in 10 million people's homes (their living room TVs) seamlessly with no rollback. To the end customer (the person sitting at home watching TV), they would notice very little change to their experience. Overall, Fusion software components delivered to multiple middleware stacks, at the time of 2011 when I departed NDS, our software was running in excess of 60 million people's homes daily, globally.

• Scope and Size - Fusion introduced a new paradigm of the TV software ecosystem, end-to-end, including broadcast headend components as well as embedded software architecture. The stack was open, based on a Linix/Posix and a complete departure from the initial decade of TV software operating systems. This was before the advent of Android TV or fully open source middleware. Fusion's product backlog captured over 2000 epics in the form of work packages, cutting across multiple customer needs, in parallel. The scope included all layers of the device software stack: Chipset drivers, hardware absraction layer, Linux kernel, Linux abstraction, Middleware services, Application SDK/APIs, multiple frontend application engine proxys for C / C++ / Java / HTML / Flash applications. Take a look at the software architecture diagram - it is multi-layered, multiple service teams. Another point on scope, we managed initiatives or epics in the form of work pacakages (WPs), that could impact up to 25 service teams in one WP, see here.