I was working with a leader on a strange divergence. With stronger AI adoption in the team, their throughput had climbed sharply. However, what was shipped to the customer had not moved proportionately. We were quite struck with what we observed and went looking for where the throughput had gone. It had not gone anywhere, it was just queued.

In a parallel era, Eliyahu Goldratt spent his career telling an uncomfortable truth to factory managers in 1980s.

Every complex system has at least one bottleneck or constraint that limits its ability to reach its highest potential (Theory of Constraints, Eliyahu Goldratt)

If you don’t have a handle on that constraint, your inventory gets piled up there. When you finally unlock the constraint, it does not disappear, but moves somewhere else - the next problem to solve.

For Engineering, that constraint sat at building (code). With AI, that constraint is being removed. Sizing effort based on lines of code per engineer is becoming irrelevant fast. But, the limitation has not dissolved, it has now moved to the pull request/integration points.

Five New Realities for AI Native Organizations

Organizations are at different stages of adoption, but these ground truths hold wherever you are in the journey.

Reality 1: Code Throughput is not the thing anymore

The time taken for producing code is dropping significantly. Your estimation models, your capacity plans, the sizing and composition of team still assume that code is expensive. They are measuring for something that is not the constraint anymore.

Reality 2: Engineering value is shifting from code quality to product quality

Productivity and value is moving from producing code to the ability to orchestrate, integrate and deliver customer outcomes. Expertise over an area, component, feature or customer segment (the nuanced “context”) will drive more value than expertise on a stack.

Reality 3: Reviews are where the Queue forms

Human review is a valued currency now. Generated code still needs to clear the human bar for security and privacy. And this is to stay. It is now often faster to rewrite entire feature/stacks with generated code than integrating generated code into the existing system. If you break the engineering cycle into design, build, test, deploy and iterate, then friction has collected entirely at one point.

Reality 4: Specialist roles are blurring

The lines between functional specialists (quality, program management, science, data) and core engineering are blurring with their focus areas merging into the primary engineering cycle. The interesting angle is what these specialists are doing about it. The key specialists players are building the tools and systems to democratise their expertise, so that everyone can integrate their expertise unaided.

Reality 5: Teams can now own whole parts

The mental model of hyper slicing ownership and binding teams to own parts of the system is losing steam. AI Native teams can exponentially extend their ownership beyond sum parts to whole. Smaller teams organized around singular missions can deliver across domains, platforms and large sphere of influence.

The Trust Tax

I have written about three different taxes you need to manage and design around for organizations to really work. With the new realities, we have a fourth, and AI has made it the expensive one.

Trust tax is the effort required to establish that work is safe to ship. Reviews, security, privacy, testing and all other gates that ensure your organization ships great products make up this effort. It used to be small relative to the cost of building, so we did not structure/design organizations around this flow. That ratio has now inverted.

When the trust tax is low, you could work it with the goodwill of your staff. When it is high, it is your operating model. Every dollar spent on accelerating the build phase pushes the tax number up and it increases with the investment actually funding the bottleneck.

Design Principles for AI Native Organizations

Here are the organizational design principles that will influence how you would organize talent for the the new realities. They will evolve as we experience more ground truths.

Principle 1: Organize around Missions

Fixed ownership of services and components starts being a constraint. Bind teams to a durable mission and let its ownership follow the mission. These teams will extend from owning individual parts to delivering whole outcomes. Enable the team with everything they need to deliver the mission - talent, resources, data, authority. Whenever you reorganize, move missions, not component parts.

Principle 2: Specialists become force-multipliers

Build systems to incentivise your specialist to become multipliers. Their roles are not confined to a specialist function, it is to enable others to do their work upstream. Reframe their goals to one question - how are they democratizing their roles? Every specialist who answers removes one layer from the constraints we identified.

Principle 3: Value Orchestration and Domain Depth

Teams have shifted their value to deliver whole missions, specialist have shifted their value to democratizing. Now, reward systems need to change - hiring assessments, promotion criteria, recognition all have to change. Shift these systems towards the ability to orchestrate outcomes.

Principle 4: Plan against your Trust Tax

With developer-week estimation becoming obsolete, you need to anchor planning around outcomes and the trust tax your teams have to navigate. Review and integration capacity is the new planning unit. The question is not how much you can ship, but how you can responsibly ship.

Principle 5: Optimise the Trust Infrastructure

Automated review, security/privacy gates, testing and iteration loops deserve first class investment and staffing. This is the highest needle mover but the one that receives low attention in any budget today. Organizations that nurture their trust infrastructure convert throughput into shipped products.

What effect does this have on the Organizational Pyramid?

Here’s where change is a super cycle. And, the thing that’s bothering many of us is:

What changes for new hires and entry level employees?

The uncomfortable part is what this asks of entry-level talent. If trust friction is the constraint, then the expectation of the newest person on the team changes fundamentally. You aren’t asking them to produce code now and develop judgement over years. You are asking for orchestration and owning product quality from the start. This is a steeper first year than any of us had and it will not happen by default. It needs a deliberately structured learning curve.

Does this mean you need fewer people/lesser headcount?

Not quite. Mission teams are smaller and self contained. However, the same exponential capacity should flow to product roadmap, design and decision making. If you had to choose between three features for your product’s roadmap with constraints on the engineering cycle, you don’t have that now. You can do all three features. In parallel! As what you can promise your customers gets larger, the scale would tip and utilize your engineering bandwidth.

There is a lot of debates on how the organizational pyramid would look like at full scale AI integration. Some see it as an inverted pyramid and some see it evolving into a diamond with lean middle layer. I think the shape of the pyramid will not materially change - it would just reconstitute into smaller pyramids that would drive more customer outcomes.

Am watching this as the change happens like everyone. Goldratt had decades of data, while we have a very limited observation window. The design principles above are what I hold today and I expect to revise a few of them as the window expands.

Where has the constraint moved for your organization? Let’s talk.

Organizations struggle with innovation. It could be at a certain life stage (mature products for example) or when moving past a certain scale (growing the next million customers for example). There is so much research on what drives innovation, but it remains elusive because innovation is an outcome that is difficult to plan for. It is usually a waiting game and an idea rarely emerges at a certain time.

But the risk is that for some organizations, this moment may never arrive. Remember organizations like Polaroid, where it never arrived? Or Yahoo and Nokia where their pivot was late? Or Netflix, where the pivot from offline to online was perfectly crafted. The difference primarily lies in their ability to fail fast & capitalize on ideas early on and this ability is deep rooted in their culture.

Take 3M’s Post-It-Notes for example. The innovation was never centered around notes. A scientist researching adhesives discovered a peculiar adhesive that stuck lightly to surfaces, while the goal he was working towards was different. He wanted to create adhesives that are extremely strong for industrial use. After years of trying to find a usage for the light adhesive, one of the team members used it for sticking paper on a book as a bookmark. Over forty years, the adhesive helped the company develop a mainstream collaboration product that now has digital applications, including associated apps.

Ideas could come from any part of your organization and at any time. Your ability to translate these ideas into action is enabled by a consciously crafted culture.

Kurt Lewin used a heuristic equation that pretty much summed up driving any kind of behaviour:

Behaviour (B) is a function of a person (P) in an environment (E). The strongest lever to any behavioural change is E (Environment). There are multiple experiments that have reinforced that a small change in the environment lead to significant shifts in behaviour. For example, stocking products at a certain height or position influences purchase behaviour.

If we want to mould behaviour that accelerates innovation, the strongest lever is E (Environment). The core design of your culture of innovation should focus on this very simple rule – It should not be difficult to innovate. Human drive is wired to default to the path of least resistance. Your role as the architect to enabling innovation is to carefully scrape away barriers in the environment and piece together certain accelerators.

Practical To-do

Use “follow the decision” technique (read this post for an overview) on ideas. Identify two ideas that were successful and two that failed in your organization. Map their point of origin, number of reviewers to the idea, who sponsored it, how it kickstarted and where it succeeded or failed. Here’s a idea journey I put together for an idea I worked on.

An Idea Journey

When I charted out an idea that one of my teams have been working on, I realised the effort that get increasingly added when you had to pass through “Gatekeepers” as an idea owner. The effort does not produce any outcomes to the idea. I could quickly recall a few ideas that we had worked on for over 2 years.

Controlling E (The Environment)

Architecting the environment would mean that you craft these two dimensions – Barriers & Accelerators.

There are three primary barriers that increase the effort required to innovate:

Barriers to Sponsorship

Truly nascent ideas are very fragile. The chances of an idea seeing light is inversely proportional to the number of people “reviewing” it. Feedback on ideas should be “feedforward” and focus on inputs that make the idea work. Typically, sponsors/investors, who have the decision making power to say “go” for an idea, are the ones who should review ideas. The point of frustration normally is a series of “gatekeepers” to reaching the actual sponsor. If you have to have more than two reviews before a sponsor reviews an idea, it is a strong indicator to high barriers to sponsorship. The answer to solving this is in the organization’s structure and the decision tax it generates. Read more on decision tax and ways of mitigating them in this article.

Practical To-do

Once you chart an idea journey, try and understand why these idea owners reached out to certain additional leaders for reviews. Are they additional gatekeepers? Or do they actively add value to the idea? How do you ensure that you create access to sponsors at scale? How do you bring down the gating period?

Barriers to Information

Do you think that game changing innovation usually comes from functions/individuals that have closest interactions to the customer? No. It actually is a misconception. This appears to be the case because information is not democratized and customer information is held within a few. It also means that your data system design needs improvement and your capability to innovate primarily resides on tribal knowledge. To scrape away this barrier, you need to invest on systems and teams which manage this information. These investments should focus on generating insights and democratizing it, so that it is accessible to everyone. Read more on information tax and ways of mitigating them in this article.

Practical To-do

Identify 5 individuals from different teams and functions. Interview them for their perspective on “what are features that your customers use most of the time” and “what are the pain-points when using them”. If you get a variety of unconnected answers or if you don’t get an answer at all, then it is a strong indicator to high information barrier.

Intensity Dial-up

Intensity dial up occurs when the organization works on a fast paced environment and decision making over indexes on speed, quantum of delivery. The fallout is that it eats up into your space to innovate. Dialled up intensity leads to a very low priority to work on ideas and high priority to quantum of delivery. The path to resistance for innovating significantly goes up and it starts to feel like a huge effort to work on an idea. People start to see that the effort required to disengage themselves from their daily work is very high and that the environment does not incentivize their behavior. Read more on dialed up intensity and ways to mitigate them in this article.

Practical To-do

If you have employee surveys, dialed up intensity could be recognized by low job satisfaction scores. Watch for phrases like “business-as-usual” (one of the most misused terms on earth), “daily deliverables”, “busy”. The moment your team starts distinguishing between innovative work and “business as usual” work, you can be sure that there is dialed up intensity and that your environment is not conducive.

Accelerators

In addition to scrapping away barriers, you need an ideation process that is well known to everyone. You need distinct systems that accelerate three dimensions of the ideation process – Surfacing, Building and Investing on ideas.

Surfacing

Ideas could start anywhere and you need scalable ways of interacting with ideas early on. A few organizations have a structured system and an intake process for ideas. It’s important that at an early stage, the environment is free from judgement and does not encounter disagreements. It is necessary that your system has an idea backlog where these ideas are hashed.

Building

There’s an element of coaching needed for every idea. At the build phase, you need experts to weigh in on the idea and help shape it. The system needs to be able to connect idea owners with coaches/experts and offer a structured development journey.

Investing

All ideas can’t win. You need to carve out strategic priorities and communicate them. You also need to establish a system of prioritizing your investments. Sponsorship/Investors cannot be at a far distance and if they are, then you need to empower your organization to make these investment decisions.

Practical To-do

A good idea to translate this system into a working program would be having “Innovation Stewards”. They are workgroups that build the process and systems for these three dimensions. A conversation starter to establishing leadership focus on this is to provide a health assessment of these processes and build an inventory of ideas that failed.

Am experimenting a series of things that define these three accelerators and it appears to be gathering steam. In the process, a structured journey for ideas with tools and templates was created to identify customers, define the customer experience, prototyping iteratively, resource planning and garner support/investment.

Are you doing something interesting in this space? What are processes you have for surfacing, building and investing in ideas? Let me know!

Today, global scale makes businesses grow fast. Disruptive business models and platformization translate to 10x growth within months for both start-ups just launching or an established organization focusing on a new idea. Over the last ten years, there has been a lot of research on how businesses adapt to competition, scale and driving innovation in the new environment. The same statement would however not be true and parallel to how businesses build organizations and structure that scales. Even today, cost and ownership remain primary drivers to how organizations are structured.

Like intensity, organizational design is also a key decision that sets direction and culture. Good structural design is based on the “how” work flows through different points in your organization.

Design that centers on cost and ownership come with their own fallacies and binds your organization with constraints including higher cost of collaboration, increased time to make decisions and a workplace that your top talent does not enjoy working in.

I’ve worked with teams where we reference this environment as a “partnership standstill”. A situation where the effort of collaboration and debate is significantly higher than the cost of just doing it yourself. This pushes the culture to avoid collaboration because there is just so much effort required in doing it. Imagine having to jump through multiple hoops to review and get started on a small idea. The cost of debating this would be so high that you would just either drop the idea or you would just do it and not tell anyone else.

Designing Right

Organizational charts represent ownership and reporting structure. It is a primary method to study who owns what and how control is exercised. It would be ineffective to use them as a singular artifact to design structure. The crucial components of design lie in how work flows from one point to the other in your organization, primarily a map of how value gets added to your product. I always start with what I call a “value map” that would generally apply to any organization. When I encounter additional information, I enrich my maps to ensure that it represents the context of the teams I work with.

Practical to-dos

“Follow the money” is a phrase used by finance professionals when auditing. If you follow transactions from the origin (where money is made) to the spend (where the made money becomes zero or even negative), you will have all insights you need on a business model, a forensic audit, etc., Similarly, you need to “follow the decision” to create your own value map of your business. Attach yourself to a business problem, analyze its point of origin and all the decisions it takes to solve them. This helps you develop insights you need for building the value map.

There are three elements to designing structure that enables building great teams that work well together. Good structural design aims at minimizing the cost of these elements.

Consider for a moment that you are reviewing a proposal to build a technology team in another country because talent is cheaper (a cost based decision to structure). To illustrate how these elements play out, I’ll use the default value map I have and add a second location. The moment you set up a team in another country, observe the three design elements and the relative complexity to getting work done significantly going up.

In this illustration, when the tech team is started in another country, the team needs to start coordinating with multiple partners including the parent tech team in the home country, the product team, the operations team and the support team. This increases the coordination tax for all these teams. And imagine a reality of the second country being in a time zone that’s 12 hours away! The teams slow down for being inclusive with time zones and instances for “thread delays” (where team A would have to wait for team B to deliver/respond) start to crop up. It also leaves your top talent with a frustration of not being able to get things done.

Similarly, the number of decision points in tech direction and architecture will increase, with expertise spread across these countries. This increases the touchpoints for the product team with the need to enable tech decision making. This would mean that every idea jumps through additional number of hoops before it sees light. Your team would feel as if they have to pocket a follow-on for every coin and not only for the critical red coin. In a long run, it will result in slower go-to-market and creating a workplace culture that may not be attractive.

Distance to critical information increases for the new team. Customer and market insights shape work in the information age. If the flow of information between these teams is slow, then the second team is probably working with information of decreasing relevance. This stifles their ability to design and deliver products.

Practical to-dos

Build a value map of your team. Attach a shirt-size (XS,S,M,L,XL) to the amount of coordination tax, decision tax and information tax that exists between teams and create an action plan.

If you are evaluating a structural change, build a value map and discuss with your teams. As you manage through the change, set expectations with teams where the costs of the elements will be high. Set up a task force and timeline for building an action plan.

In my exploration, I’ve used a few tools to that help managing the fallout of inefficient structural design.

Mitigating Coordination Tax

Add Roles that absorb coordination tax: Investment in roles that bring delivery predictability and alignment like project management, program management, launch management help reduce the coordination burden from the team. If you have shirt sized the coordination tax in your value creation map, you know exactly where to invest.

Self sufficient teams: Creating task based teams with a representation of all skillsets required to solve the problem help reduce the coordination required. This team comes together delivers on a particular theme and then disbands.

Mitigating Decision Tax

Executive sponsors: If there are multiple decision makers, delegate to an executive sponsor who will make all decisions related to a certain initiative. Your value creation map will help you identifying investment areas where you need an executive sponsor.

Leadership Coverage: Have a ratio based tenet to empower decision making. For instance, if the decision does not impact 2 or more teams, a leader at a “x” level can make the decision. As you focus on designing the organization, you should ensure that this “x” level leadership is available at ease across any two teams.

Mitigating Information Tax

Roles focused on information availability: Invest in a team that focuses on information availability across all your teams. This typically is a business intelligence/analytics capable teams that produces digestible insights on customers. Your value creation maps will help identify investment areas.

Democratize information: Publish critical information at scale to be available at scale. I once worked with a team that had an internal page accessible to everyone in their organization on what appeals most to their customers in certain demographics. I’ve also seen product grids that communicate critical features that retain customers (what most of their customers use most of their time) vs critical features that detractors don’t have alternatives for (what customers who least used their products most of their time). Another innovative practice making crash data for products be available to everyone in the team.

Great leaders are careful architects of their structure. The three elements of structural design directly impact flow of work, information and innovation. At senior leadership, the ability to carefully make structural decision choices is the key lever to success. If you are wondering why this article does not have references to how people and leaders are mapped to a structure, that’s the final part that ideally should not affect the design. Your path to value creation should determine structure and you find leaders to manage value creation and not manage value creation basis leaders you have.

Have a point of view? Do you have more tools that you use to manage these elements? Let’s talk!

I once used a block chain analogy to explain culture to a senior leader. Culture is very similar to blockchain. Every decision you take is a transaction recorded across your team members (distributed ledgers). They later reference these decisions to drive their own behavior. What you do and how you do it as a leader is very important as this defines your team’s behavior. Great leaders are careful architects, who intentionally design how their actions get recorded into the culture “blockchain”. There are multiple levers to that determine culture and I am contemplating one of them today – Intensity.

Fast paced and high activity workplaces are a draw to many. This environment is a preference to “achievers” who believe they can use it to their advantage and hone their skills. Intense workplaces are easily identified by their reputation for speed, quantum of work, super flat organizational structure and a high degree of conflicting priorities. Churn is normal. The description fits a lot of great organizations, but these are rather the ones which can keep the dial of intensity in control. Even across these great organizations, there is always that team which had already lost control of intensity.

If you observe organizations that lose control of this lever, you’ll notice three distinct conditions that set in:

The fallout is that customer value from their products erode really fast. What starts to matter is that their team is a well-oiled machine delivering at a frequency, rather than how well the delivery is useful to the customer. Their talent investment would move towards roles that are focused on pushing teams to finish lines rather than roles building their product. The measurement will shift towards volume, frequency and delivery over quality and relevance. The shift of these practices creates a perception of repetitive cycles of “doing the same thing”, causing team members to feel that their learning has reached a saturation point.

To provide an economics analogy, behavior of the team starts to reflect the law of diminishing marginal utility. If you’ve done this for 6 months, you’ve done it for 18 months, and if you’ve done it for 18 months, there is nothing much to gain from the experience. The marginal utility for satisfaction from work declines for every additional unit of the same work done.

Managing Intensity

Prevention and cure for dialed up intensity are similar. The key is to architect the practices that lead to a dial up.

The first element is work design. Every organization has a unit time to deliver work – a sprint, a quarter or a year. They also have a set of focus areas for delivery – could be performance of your product like boot-time, or a channel of touchpoint with customers like screens. Work design is a combination of these two elements. The activity of your teams will be based on this work design.

For example, let’s consider that your work design focus area is device screens and your unit time of work is a quarter. For that quarter, your leadership is going to focus on activities that monetize your screen, your product managers are going to build their customer experience on features related to your screen, your engineering teams are going to work on delivery of related features.

This dials up the intensity on a focus area over a unit time. Most organizations work in this model, unconsciously. Things break when they prolong this work design over multiple units of time. If your work design remains constant for more than three units of work, marginal utility of improved customer experience and work satisfaction diminishes. The key is to alter your work design periodically so that marginal utility never goes negative.

Practical to-dos:

Set up a discussion with your leadership over work design. It is important that you have a deep understanding of key focus areas and how they change over time.

It pays to always be on the lookout for the three conditions of dialed up intensity and generate data over them.

Consult with your leadership team on how to rearrange work design using the 3-work-unit tenet.

The second element is reward design. Remember the last time when there was a sudden issue, causing serious delay or bad experience to your customers? You’ve probably had to put your best people to the problem who produced quick results and were an example to others in the team. Firefighting is heroic, literally and at work. But, how would actual firefighters feel if the same building in the neighborhood caught fire every other week? At work, firefighting is a rewarding experience leaving your team with a feeling of responsibility and a sense of satisfaction. But, it has this effect only a few times. Never appreciate firefighting in public unless it really leaves a problem fixed, at least at an incremental manner or reduces the frequency of fires. By altering what and how you recognize and reward your team, you can make headway into setting the right behavior.

Practical to-dos:

Articulate what behavior you want to recognize and reward. What works really well is adding the right display of the behavior against a misunderstood one. Articulating a “what it looks like” and “what it does not look like” helps you define the expectation across your team. For example, if you want to recognize “Problem Solving”, you might end up encouraging “fixers” who provide quick fixes.

The third element is artificial urgency. Your customers buy your product/service for a great experience. Teams often get lost in the way they deliver this experience. At a team level, goals distil down to units of delivery – releases, signoffs, launches and their timelines. While these are essential for getting things done, your customer does not care about these units of delivery. A typical example is the auto update for apps on your phone. Just because you’ve delivered four releases and updates to your customer does not mean that you’ve delivered a significant customer experience to them. You need mechanisms to ensure your team’s wins are really wins. The way you design and cascade goals and how you celebrate your wins is an important practice.

Practical to-dos:

Have a goal template? Start with a why. You can make your goals S.M.A.R.T, but if they don’t connect with an actual customer problem, they are not really smart. This simple change can help leaders ask the right questions. If you have these rituals of celebrating milestones, celebrate what a customer has gained out of the milestone. If you are a social network and you have a milestone of 1 million signups, celebrate the fact that you have exponentially increased your customer’s ability to express rather than the milestone itself.

Controlling the dial is hard and over-indexed intensity leads to erosion of trust with both your team and your customers. Recognising dialled up intensity and being conscious of it is the first hard step towards making a dent. As a careful architect, you would have not only led your team away from burn-out and churn, but you would have also architected a workplace of choice.

Stuck somewhere? Experimenting something that’s not here? Let me know!

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I recently was in a conversation with a class of aspiring HR professionals. I wanted to provide them a series of practical things that are actionable for their learning. As much as I looked far and beyond for all things that would help them prepare, I realized more that the answer is closer. I decided to look within my own career path, tell them a story of how it panned out for me and give them a learning path that I crafted for myself.

My career path wasn’t as planned as it should be and my education was rather spur of moment decisions. The underlying belief was that I was extremely sure of not ending up doing something I won’t enjoy. So, at about every point of my education, I was probably the last to decide in any given group. And always, I would not end up in premier institutions as I would not have enough time to apply or prepare for their gating tests.

I graduated specializing in Computer Science, not because I wanted to be employed in that area, but because of a natural curiosity of how computers work. I was one of the few people in my cohort who could write good code and problem solve areas that were not part of the curriculum. And again, it was not centered around my passion to code, but my ability to have understanding of how products work and how they benefitted users. This inclination led me to my MBA. I was clear about only one thing – I wanted to learn and not be taught. So, I ended signing up to be part of the first batch of MBAs from a traditional engineering college instead of premier schools with gating tests. But, I started a lot of things that helped me be self-taught. Your daily habits are what define you. You need to stack up your day with small actions that compound to building the right skills over a long term.

The Skillset

When I did an introspection to provide aspiring students an actionable learning path, I found that I regularly flex a set of skills through different stages of my career. These skills apply to a majority of contexts, across industries and organizations at different stages of maturity and sizes.

I also charted out which of these skills are aspiring professionals expected to flex at different stages of their career, so that we can visualize the ones that can be built in student life. Read this as a set of skills that you will “flex” or extensively lean on at each career stage.

Practical to-dos

In every subject pick 5 topics that inspired you and add them to a Practice Backlog. Your goal is to apply these concepts somewhere and learn from it. Even today, I have a practice backlog, where I have a list of things that I learnt and need to find an application for.

Build Business Understanding

For any career, you need to understand how the business machinery works. You need to have a mental model of how value gets added and work passes from one point to the other. Ever wonder why there is friction between two teams? Understanding of the basic machinery helps you identify points of leverage, friction and vulnerability in the flow of work. There are many ways to build understanding, but one that has worked well for me is Strategyzer’s Business Model Canvas. Once you map the key components of a business, learn to derive value maps (learn more about value maps here) that will help you build your ability to deep dive into problems. You will not get it right the first few times. Your effort is compounded by debating in class and inviting point of views from others.

Practical to-dos

You need to exercise this skill to build it. Try building the business model canvas for multiple industries. Make assumptions about points of friction, high leverage activities, etc. Connect your assumptions with publicly available financial/market data. Find an ally who works in the industry and debate your assumptions.

Build Contextual Understanding

Leaders make choices basis assumptions that they derive from years of context. You have years to solidify your own assumptions and context, it is challenging to replicate this. The best way to learn as a student is to follow important decisions leaders have made and place yourself in those shoes. Stay close to business news that bring you major decisions, then play out the decisions and develop your point of view by reasoning these decisions and plotting the fallout. Normally, in due course, the outcome and effect of high impact decisions is often covered in news and it provides a way to validate your thinking. You can learn a lot this way! Am still learning from my plotting of the effects of Gates stepping away from Microsoft. I am still trying to systemize my learning and understanding what happens when a founder CEO steps away.

Practical to-dos

Identify 3 large scale events that you think has high impact to how an organization functions. Typically, these events could range from leadership exits, a new product launching to even a stock split. Develop a point of view on why it happened and what are the difficult choices that were made. Find an ally who you could debate with and make a log of potential fallouts.

Accelerate your Learning

Form your opinion and learn to be open to change them. Your learning accelerates by presenting your point of view and being open to debate them. You need to establish a set of allies (peers & mentors) whose perspectives you value and at least two mentors who can build clarity into your thinking. Your support network undergoes changes as you progress in your career, but what does not change is that you have allies who challenge your thinking.

The key accelerator to your development is doing these things habitually and constantly. You can further learn to program your habits to your advantage with “Atomic Habits” by James Clear. The essence though is learning early what works for you and doing that every single day, compounding your way to accelerating your development.

These ideas worked well for me. But, it has been years since I was a student. I hope that these ideas are actionable even in today’s context. I owe this article to the set of students I had a conversation with as it inspired a lot of thinking and retrospection. Do you have more ideas?

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