Gennaro Cuofano's Blog, page 184

SWOT Analysis vs. Balanced Scorecard

The SWOT Analysis is primarily used for strategic planning and to assess the competitive landscape based on the strengths, weaknesses, opportunities, and threats. The balanced scorecard is a goal-setting and management tool to achieve the strategic goals set by the organization. Therefore the two tools can be used as complementary, with the SWOT analysis to assess the competitive landscape and the balanced scorecard to execute the strategic goals.

[image error]A SWOT Analysis is a framework used for evaluating the business’s Strengths, Weaknesses, Opportunities, and Threats. It can aid in identifying the problematic areas of your business so that you can maximize your opportunities. It will also alert you to the challenges your organization might face in the future.



[image error]First proposed by accounting academic Robert Kaplan, the balanced scorecard is a management system that allows an organization to focus on big-picture strategic goals. The four perspectives of the balanced scorecard include financial, customer, business process, and organizational capacity. From there, according to the balanced scorecard, it’s possible to have a holistic view of the business.

Read Next: SWOT, Balanced Scorecard, OKR, Agile Methodology, Value Proposition, VTDF Framework.

Main Guides:

Business ModelsBusiness StrategyMarketing StrategyBusiness Model InnovationPlatform Business ModelsNetwork Effects In A NutshellDigital Business Models

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Balanced Scorecard vs. OKR

Both balanced scorecard and OKR are management and goal-setting tools to enable an organization to produce the expected outcome from long-term planning. The balanced scorecard is more holistic; the OKR is focused on achieving ambitious goals from an organizational standpoint, which is also why OKR has found wide adoption throughout startups.

[image error]First proposed by accounting academic Robert Kaplan, the balanced scorecard is a management system that allows an organization to focus on big-picture strategic goals. The four perspectives of the balanced scorecard include financial, customer, business process, and organizational capacity. From there, according to the balanced scorecard, it’s possible to have a holistic view of the business.



[image error]Andy Grove, helped Intel become among the most valuable companies by 1997. In his years at Intel, he conceived a management and goal-setting system, called OKR, standing for “objectives and key results.” Venture capitalist and early investor in Google, John Doerr, systematized in the book “Measure What Matters.”

Read Next: OKR, Balanced Scorecard, Agile Methodology, Value Proposition, VTDF Framework.

Main Guides:

Business ModelsBusiness StrategyMarketing StrategyBusiness Model InnovationPlatform Business ModelsNetwork Effects In A NutshellDigital Business Models

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What Is The Jobs-To-Be-Done Framework?

The jobs-to-be-done (JTBD) framework defines, categorizes, captures, and organizes consumer needs. The jobs-to-be-done framework is based on the premise that consumers buy products and services to get jobs done. While products tend to come and go, the consumer need to get jobs done endures indefinitely. This theory was popularized by Tony Ulwick, who also detailed his book Jobs To Be Done: Theory to Practice.

Understanding the jobs-to-be-done-framework



[image error]Source and Credit: jobs-to-be-done.com/the-jobs-to-be-done-canvas-f...

But why do products and services tend to come and go? Most failures occur because of a misalignment with consumer needs. That is, product development teams do not understand the metrics that consumers use to measure success.

To that end, the jobs-to-be-done framework was created. It allows businesses to identify consumer needs that are less likely to become invalid or obsolete over time. By developing products based on these needs, the products themselves are more likely to endure. There is also a higher likelihood that the business has developed an innovative product.

In the next section, we will look at a methodology that guides innovative, needs-based product development.

The eight-step jobs-to-be-done methodology

While there are several approaches to determining customer needs, this methodology allows businesses to identify needs at every stage of the job process.

1 – Define

A customer usually begins by defining what they need to proceed with a job. This includes identifying an objective and then formulating a plan toward achieving that objective. Weight Watchers assists dieters in losing weight by offering a suite of weight-loss plans where the hassle of counting calories has been removed.

2 – Locate

In the second step, the customer locates the items and information required for the job. Here, a business can innovate by making the location process easier. DIY removalist company U-Haul provides moving kits with its range of vehicles, with the number and type of each box specific to every customer’s move.

3 – Prepare

Preparation involves the arranging of necessary inputs within the environment required for the job. Most jobs require some degree of preparation and it can be made less difficult by automation, safeguards, or user guides to name a few.

4 – Confirm

What information does the customer need to verify before proceeding with the job? This step is especially important for jobs that require quick and accurate decisions or checks. Oracle created merchandising software that enabled staff to gauge the best time and markdown percentages for product sales.

5 – Execute

As the job is being carried out, a business should address needs resulting from problems or delays. Identifying needs in the execution stage is vital because customers consider this is the most important part of the job. During surgical procedures, Kimberly-Clark developed a heated water system to avoid fluctuations in patient body temperature.

6 – Monitor

Does the customer need to monitor something that will aid in the successful completion of the job? That is, will adjustments be necessary to improve execution? Nike manufactures shoes containing sensors that give instantaneous data about the exercise session with respect to fitness goals.

7 – Modify

If adjustments are necessary, the business must reduce the number of adjustments required as a matter of priority. When, how, and where will the adjustments take place? Microsoft’s automatic update system saves customers the hassle of finding, downloading, and then implementing updates. 

8 – Conclude 

What does the customer need to do to complete the job? Some jobs are concluded simply, such as the drying of hands after they have been washed. Other jobs including the printing and binding of a completed report are more complex.

Adhesive company 3M simplified the often convoluted process of removing wound dressings after surgery. By designing a dressing that adhered only to itself and not to the skin, the job of removal became quick and painless for the patient.

Key takeaways



The jobs-to-be-done-framework is an innovative approach to product development through a detailed analysis of customer needs.The jobs-to-be-done-framework helps a business address discrepancies between metrics it considers important and metrics considered important by the customer.The jobs-to-be-done-framework features an eight-step methodology that describes the evolution of a job from creating a plan to job execution and adjustment-making. This allows a business to systematically anticipate and then meet customer needs.



[image error]The business model canvas is a framework proposed by Alexander Osterwalder and Yves Pigneur in Busines Model Generation enabling the design of business models through nine building blocks comprising: key partners, key activities, value propositions, customer relationships, customer segments, critical resources, channels, cost structure, and revenue streams.



[image error]The lean startup canvas is an adaptation by Ash Maurya of the business model canvas by Alexander Osterwalder, which adds a layer that focuses on problems, solutions, key metrics, unfair advantage based, and a unique value proposition. Thus, starting from mastering the problem rather than the solution.



[image error]A value proposition is about how you create value for customers. While many entrepreneurial theories draw from customers’ problems and pain points, value can also be created via demand generation, which is about enabling people to identify with your brand, thus generating demand for your products and services.



[image error]A tech business model is made of four main components: value model (value propositions, mission, vision), technological model (R&D management), distribution model (sales and marketing organizational structure), and financial model (revenue modeling, cost structure, profitability and cash generation/management). Those elements coming together can serve as the basis to build a solid tech business model.



[image error]Agile started as a lightweight development method compared to heavyweight software development, which is the core paradigm of the previous decades of software development. By 2001 the Manifesto for Agile Software Development was born as a set of principles that defined the new paradigm for software development as a continuous iteration. This would also influence the way of doing business.

Read Next: Agile Methodology, Business Model Canvas, Lean Canvas, Value Proposition, VTDF Framework.

Main Guides:

Business ModelsBusiness StrategyMarketing StrategyBusiness Model InnovationPlatform Business ModelsNetwork Effects In A NutshellDigital Business Models

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Kanban vs. Kaizen

Both Kanban and Kaizen have been adapted as agile methodologies in continuous software development and borrowed by tech companies as process improvement methods. Both were derived from the lean manufacturing methodology from the Toyota Production System. While the Kanban is a tool for visualizing a process and identifying bottlenecks, the Kaizen approach is a continuous improvement process.

[image error]Kanban is a lean manufacturing framework first developed by Toyota in the late 1940s. The Kanban framework is a means of visualizing work as it moves through identifying potential bottlenecks. It does that through a process called just-in-time (JIT) manufacturing to optimize engineering processes, speed up manufacturing products, and improve the go-to-market strategy.



[image error]Kaizen is a process developed by the auto industry. Its roots are found in the Toyota Production System, which was heavily influenced by Henry Ford’s assembly line system. The word Kaizen is a hybridization of two Japanese words, “kai” meaning “change” and “zen” meaning “good.” Two of the basic tenets of Kaizen involve making small incremental changes – or 1% improvement every day – and the full participation of everyone. 

Read Next: Kanban, Kaizen, Agile, DevOps, DevSecOps, Lean, Sprint, Scrum.

Main Guides:

Business ModelsBusiness StrategyMarketing StrategyBusiness Model InnovationPlatform Business ModelsNetwork Effects In A NutshellDigital Business Models

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Scrum vs. Kanban

Both are methodologies built on top of two different prior frameworks. Scrum is derived from the agile methodology, and it serves as a way to manage complex product development projects. Kanban instead was derived from lean manufacturing, and it also serves as product development and project management methodology in business to get things done.

[image error]Scrum is a methodology co-created by Ken Schwaber and Jeff Sutherland for effective team collaboration on complex products. Scrum was primarily thought for software development projects to deliver new software capability every 2-4 weeks. It is a sub-group of agile also used in project management to improve startups’ productivity.



[image error]Kanban is a lean manufacturing framework first developed by Toyota in the late 1940s. The Kanban framework is a means of visualizing work as it moves through identifying potential bottlenecks. It does that through a process called just-in-time (JIT) manufacturing to optimize engineering processes, speed up manufacturing products, and improve the go-to-market strategy.

Read Next: Scrum, Kanban, Agile, DevOps, DevSecOps, Lean, Sprint.

Main Guides:

Business ModelsBusiness StrategyMarketing StrategyBusiness Model InnovationPlatform Business ModelsNetwork Effects In A NutshellDigital Business Models

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Kanban Framework In A Nutshell

Kanban is a lean manufacturing framework first developed by Toyota in the late 1940s. The Kanban framework is a means of visualizing work as it moves through identifying potential bottlenecks. It does that through a process called just-in-time (JIT) manufacturing to optimize engineering processes, speed up manufacturing products, and improve the go-to-market strategy.

Understanding the Kanban framework

Like many lean manufacturing processes, the kanban framework was first developed by Toyota in the late 1940s. 

Through a process called just-in-time (JIT) manufacturing, Toyota began to optimize its engineering processes based on a model supermarkets were using to control inventory levels. Using this model, supermarkets stock just enough product to meet consumer demand. As inventory levels respond to consumption patterns, the supermarket avoids holding excess stock and the inefficiencies that result. 

Removing these process inefficiencies – or project bottlenecks – is central to the kanban framework. To identify these bottlenecks and increase transparency and collaboration, the entire project is illustrated on a kanban board.

Kanban boards visually depict:

Tasks that are completedTasks that are currently being performed.Future tasks.

This simple approach to defining projects means that external stakeholders or new team members can quickly get up to speed. Many businesses utilize physical kanban boards while those in software development use virtual boards. This facilities better collaboration and increases accessibility from multiple locations.

Four core principles of the kanban framework

Kanban principles are based on:

An emphasis on small and gradual changes to the existing workflow.Limiting existing tasks. Here, the team must not take on too much work such that the project is negatively affected.Respect for existing roles and responsibilities. The kanban framework improves efficiency in established systems. It does not require that businesses change their operations or culture.Leadership. Traditional project management practices stipulate that a project manager must sign off on every task, no matter how menial. However, the kanban framework affords whoever is working on a task the freedom to make their own decisions. This creates a culture of iterative improvement and creates the next generation of leaders.



Implementing the Kanban framework

To apply kanban principles to almost any scenario, kanban management consultant David J. Anderson identified six core practices:

Visualize the workflow. This begins by creating a kanban board with columns for the three types of tasks mentioned in the introduction. For each type, kanban cards representing specific work items should be assigned. Cards should be moved from column to column as work on them progresses.Limit tasks that are currently being performed by setting constraints. This helps avoid multitasking and subsequent process inefficiencies. Manage flow, or the movement of work items through each step of the process. Many businesses make the mistake of micro-managing staff to keep them constantly busy. But the kanban framework simply focuses on moving the work through the process as quickly and efficiently as possible.Make management policies explicit. Members of the project team must understand what they are trying to achieve.Collect feedback. Kanban boards should have a column assigned for daily feedback – whether that be from staff or customers. This creates agile feedback loops that encourage knowledge transfer between key stakeholders.Collaborative improvement. With a deeper understanding of the project and potential bottlenecks, organizations using the kanban framework have a collective understanding of problems that need addressing. Working toward the same goal, they also share a collective vision of future success.



Key takeaways



The kanban framework is an illustrative approach to project or product development with a focus on removing bottlenecks.The kanban framework analyses project tasks according to whether they are completed, currently being performed, or assigned to a future date. This enables project team members to visualize the workflow and minimize multitasking to prevent bottlenecks.The kanban framework is suitable for most industries and does not require that a business change its culture or management practices. The framework also empowers those carrying out the tasks to make important strategic decisions.

Read Next: Agile, DevOps, DevSecOps, Scrum, Lean, Sprint.

Main Guides:

Business ModelsBusiness StrategyMarketing StrategyBusiness Model InnovationPlatform Business ModelsNetwork Effects In A NutshellDigital Business Models

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Scrum vs. Agile

Agile is a methodology focused on lightweight software development cycles, with fast releases, iterations, and continuous improvements; Scrum is an adaptation of Agile but for achieving business objectives, through a set of rules and a team organized according to the Agile methodology principles. Therefore, Scrum is a business process built on top of Agile, a method originally built for software development.

[image error]Scrum is a methodology co-created by Ken Schwaber and Jeff Sutherland for effective team collaboration on complex products. Scrum was primarily thought for software development projects to deliver new software capability every 2-4 weeks. It is a sub-group of agile also used in project management to improve startups’ productivity.



[image error]Agile started as a lightweight development method compared to heavyweight software development, which is the core paradigm of the previous decades of software development. By 2001 the Manifesto for Agile Software Development was born as a set of principles that defined the new paradigm for software development as a continuous iteration. This would also influence the way of doing business.

Read Next: Agile, DevOps, Scrum, Lean.

Main Guides:

Business ModelsBusiness StrategyMarketing StrategyBusiness Model InnovationPlatform Business ModelsNetwork Effects In A NutshellDigital Business Models

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Agile vs. Sprint

Agile started as a lightweight development method compared to heavyweight software development, which is the core paradigm of the previous decades of software development. A design sprint is a five-day process where a critical business question needs to be addressed via product development or prototyping. Therefore, a design sprint might be part of a wider application of the agile methodology.

[image error]Agile started as a lightweight development method compared to heavyweight software development, which is the core paradigm of the previous decades of software development. By 2001 the Manifesto for Agile Software Development was born as a set of principles that defined the new paradigm for software development as a continuous iteration. This would also influence the way of doing business.



[image error]A design sprint is a proven five-day process where critical business questions are answered through speedy design and prototyping, focusing on the end-user. A design sprint starts with a weekly challenge that should finish with a prototype, test at the end, and therefore a lesson learned to be iterated.

Read Next: Agile, DevOps, DevSecOps, Scrum, Lean, Sprint.

Main Guides:

Business ModelsBusiness StrategyMarketing StrategyBusiness Model InnovationPlatform Business ModelsNetwork Effects In A NutshellDigital Business Models

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Agile vs DevOps

Agile is a methodology focused on lightweight software development cycles, with fast releases, iterations, and continuous improvements; DevOps is an organizational function that combines and integrates development and operations. In short, DevOps might help operationally to execute an agile methodology, but DevOps might also use other methods, even though Agile is among the most used in software development.

[image error]Agile started as a lightweight development method compared to heavyweight software development, which is the core paradigm of the previous decades of software development. By 2001 the Manifesto for Agile Software Development was born as a set of principles that defined the new paradigm for software development as a continuous iteration. This would also influence the way of doing business.



[image error]DevOps refers to a series of practices performed to perform automated software development processes. It is a conjugation of the term “development” and “operations” to emphasize how functions integrate across IT teams. DevOps strategies promote seamless building, testing, and deployment of products. It aims to bridge a gap between development and operations teams to streamline the development altogether.

Read Next: Agile, DevOps.

Main Guides:

Business ModelsBusiness StrategyMarketing StrategyBusiness Model InnovationPlatform Business ModelsNetwork Effects In A NutshellDigital Business Models

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History of Amazon

Surviving the dot-com bubble

Since its inception in 1994, and its IPO in 1997, going to the 2000 dot.com bubble Amazon was not a profitable company. Indeed, as Amazon established itself as one of the strongest online brands, and the strongest bookstore online, already by 1996-1997, it quickly expanded to offer more and more, from DVD to any other item imaginable. That sort of expansion was driven to gain as quickly as possible market shares of, at the time, embryonic e-commerce market. Thus, Amazon lost money, year after year.  Yet, the company still managed to generate positive cash flows, thanks to its positive cash conversion cycles and exponential revenue growth, until the dot-com bubble kicked in.

As Amazon revenue growth slightly slowed down, its cash generation also declined and from $822 million at the bank, in 2000, Amazon ended up with $540 million at the bank by 2001, thus burning over $280 million in cash.

Amazon pre-dot-com bubble

While at the time Amazon had already expanded in many categories and product types, it still didn’t think as a platform. Amazon was an incredibly successful e-commerce with a broad selection of items, low prices, discovery, the 1-Click technology, fulfillment, “look inside the book” feature, reviews, wish list and more. 

As we’ll see it would be only in 2001 that Amazon would start three core programs (Merchant@amazon.com Program, Merchant Program, Syndicated Stores Program), that would help Amazon gain substantial traction, with revenues moving from over $3.1 billion in 2001 to over $5.2 billion by 2003, and for the first time in its financial history (at least from its IPO) Amazon turned a profit and cash started to flow in again. 

The near death experience

During the 2000s with the explosion of the web, capital was flowing at a high rate. This was mostly a top-down approach where venture capitalists invested billions of dollars in companies hoping they would build something valuable. A simple idea coupled with a domain name was enough to spur excitement and inflated stock growth. 

To have an idea of how gloomy was the scenario. As the Guardian highlighted in June 2000, in an article entitled “Amazon.bomb:“

Analyst Ravi Suria highlighted Amazon‘s “weak balance sheet, poor working capital management, and massive negative operating cashflow – the financial characteristics that have driven innumerable retailers to disaster through history.” It was a day during which Amazon‘s shares lost 20% of their value, and 51m of them changed hands. A company worth about $40bn (£25bn) just before Christmas had ended the day worth $12bn (£7.5bn), and things did not improve during trading yesterday.

At those comments, Jeff Bezos replied at the time:

Three years ago our stock was $1.50 a share, today it’s $30-something. There have been many, many days when our stock has gone up 20% in a day” – that laugh again – “and if stocks can go up 20% in a day, they can go down 20% in a day. All internet stocks are volatile, including Amazon.com… we are nowhere near running out of cash, and we are not at all worried about it.

And he was right. Even though the company had burned a few hundred million in cash in 2001.

It had managed to get a long-term loan of over six hundred million back in 2000, right before the explosion of the dot-com bubble. Thus, guaranteeing enough cash to go through that bad period.

Indeed, as of 2001, Amazon still had over five hundred millions of cash sitting in its bank account. To understand how bad Amazon reputation might have been at the time (of course not all agreed with that), an article dated April 26, 2001, by Doug Casey, author of “Crisis Investing,” highlighted: 

I’ve said several times that Amazon is a cinch for bankruptcy, certainly Chapter 11 (a reorganization) and maybe even Chapter 7 (a liquidation), although I consider the latter a bit of a long shot.

Luck for sure played a key role. Amazon, like many other companies during the dot-com bubble, played with a very aggressive playbook skewed toward market domination and investing the whole resources brought back into the business for more aggressive growth and expansion. This became clear when, in 2000, Amazon found itself in a cash squeeze. The company was burning cash, and although one deal with AOL brought in an additional $100 million in cash as an investment into the company.

There was another event that saved Amazon from bankruptcy, and it happened a month before the dot-com crash. Amazon sold $672 million in convertible bonds to overseas investors and it did so at just the right time. Had Amazon waited just a bit longer it would have failed miserably.

Given the perfect timing of that capital raise, as the dot-com busted, investors also filed a class action against Amazon, that would be finally settled in 2005. It’s important to remark that many internet companies underwent lawsuits during that time, as the bubble burst, leaving off the table billions and billions of investors’ money. 

That near-death experience taught Amazon to rehaul its whole playbook. It wasn’t any longer just about aggressive growth and expansion for its own sake, with an aggressive financial model where it was all about cash flows, but Amazon started to become more nimble and also to come up with programs such as Amazon websites (third-party) and many other programs that would lead to the success of the company. 

Today Amazon praises itself as the most customer centric company on earth. 

To understand also the shift on how Amazon spent money also in terms of product/technological development below a fragment from the Amazon financials back in 2001:

Technology and content expense was $241 million, $269 million and $160 million for 2001, 2000 and 1999, respectively, representing 8%, 10% and 10% of net sales for the corresponding periods, respectively. The decline in absolute dollars spent during 2001 in comparison to the prior year primarily reflect our migration to a technology platform that utilizes a less-costly technology infrastructure, as well as improved expense management and general price reductions in most expense categories, including data and telecommunication services, due to market overcapacity. 

The paradigm shift

The turning point was 2001, after the dot-com bubble burst. Amazon realized it needed something to change its pace of growth. They stopped thinking in terms of a traditional business operating on the web and therefore using the web as a sales channel and they started to think of the web as a platform for business model change. 

Thus they started to think in terms of ecosystem, so how do we enable other businesses on top of our platform? From there Amazon started to experiment some key programs that would not only enable the transition toward becoming a platform (most items sold on Amazon would be third-party) but also to develop later in the 2000s the cloud infrastructure that would evolve into AWS, today the most valuable part of the business, which is giving rise to another phenomenon, that of the AI company.

Back in the 2000s, Amazon opened up to brands like Toysrus.com, Inc., Target Corporation, Circuit City Stores, Inc., the Borders Group, Waterstones, Expedia, Inc., Hotwire, National Leisure Group, Inc., Virgin Wines, and others which further amplified Amazon’s brand.

If you could buy something from Target on Amazon, you would trust its brand more easily.

In 2001, we began marketing three services for third-party sellers that are designed to provide catalog retailers, physical store retailers and manufacturers with cost-effective e-commerce solutions and to expand the selection on our Websites for the benefit of our customers:

The third-party seller strategy started to work. And it showed how Amazon was leveraging on a platform business model to enhance its brand and business.

The third-party seller services strategy revolved around three core ones:

Merchant@amazon.com Program: here third party seller could offer their products on Amazon, either in its online stores or in a co-branded store on the Amazon site, or both. And they could also fulfill those thorough products Amazon by paying the company a fixed fee. Companies like Target and Toysrus were part of it.Merchant Program: with which the third-party seller had its own URL and Amazon provide the option of providing fulfillment-related services on behalf of the third-party.Syndicated Stores Program: which represented third-party seller’s e-commerce websites were offering products available on Amazon, which product were fulfilled by Amazon and the company paid commission to syndicated store.



The experiments that lead to becoming a tech giant

Some of the technologies that helped Amazon become a successful e-commerce company in the first place were the “1-click patent” and by 1999 Amazon had also launched its seller marketplace, that used to be called zShops, where sellers could sell their used merchandise. 

While, the turning point came by 2003, when Amazon launched web hosting services, that would become AWS, in reality, the real turning point was in the 2000, when Amazon started to order their jumbled mess to offer third party to build their sites on top of Amazon, what was known at the time as Merchant.com.

As Tech Crunch reports:

What you may not know is that the roots for the idea of AWS  go back to the 2000 timeframe when Amazon was a far different company than it is today — simply an e-commerce company struggling with scale problems. Those issues forced the company to build some solid internal systems to deal with the hyper growth it was experiencing — and that laid the foundation for what would become AWS.

As explained in Amazon 2017 annual report:

It’s exciting to see Amazon Web Services, a $20 billion revenue run rate business, accelerate its already healthy growth. AWS has also accelerated its pace of innovation – especially in new areas such as machine learning and artificial intelligence, Internet of Things, and serverless computing. In 2017, AWS announced more than 1,400 significant services and features, including Amazon SageMaker, which radically changes the accessibility and ease of use for everyday developers to build sophisticated machine learning models. Tens of thousands of customers are also using a broad range of AWS machine learning services, with active users increasing more than 250 percent in the last year, spurred by the broad adoption of Amazon SageMaker. And in November, we held our sixth re:Invent conference with more than 40,000 attendees and over 60,000 streaming participants.

The Amazon’s mindset

As Jeff Bezos recounted back in 2006, “many of the important decisions we make at Amazon.com can be made with data. There is a right answer or a wrong answer, a better answer or a worse answer, and math tells us which is which. These are our favorite kinds of decisions.”

Indeed, opinion and judgment, in that case, mattered way more. As Jeff Bezos recounted in 2006:

As our shareholders know, we have made a decision to continuously and significantly lower prices for customers year after year as our efficiency and scale make it possible. This is an example of a very important decision that cannot be made in a math-based way. In fact, when we lower prices, we go against the math that we can do, which always says that the smart move is to raise prices. We have significant data related to price elasticity. With fair accuracy, we can predict that a price reduction of a certain percentage will result in an increase in units sold of a certain percentage. With rare exceptions, the volume increase in the short term is never enough to pay for the price decrease. However, our quantitative understanding of elasticity is short-term. We can estimate what a price reduction will do this week and this quarter. But we cannot numerically estimate the effect that consistently lowering prices will have on our business over five years or ten years or more. Our judgment is that relentlessly returning efficiency improvements and scale economies to customers in the form of lower prices creates a virtuous cycle that leads over the long term to a much larger dollar amount of free cash flow, and thereby to a much more valuable Amazon.com. We’ve made similar judgments around Free Super Saver Shipping and Amazon Prime, both of which are expensive in the short term and—we believe—important and valuable in the long term.

In particular, Jeff Bezos cited a paper called “The Structure of ‘Unstructured’ Decision Processes” published in 1976 by Henry Mintzberg, Duru Raisinghani, and Andre Theoret.

More, in particular, the paper highlighted how, when an institution made decisions, primarily based on data and math, that made them take efficient operating decisions. Yet, as long-term, strategic and “unstructured” (based on processes that have not been encountered in quite the same form and for which no predetermined and explicit set of ordered responses in the organization) decisions, might not rely on quantitative understanding, will get underestimated.

That happens, because decisions that can be taken on a quantitative basis can be measured, thus institutions but also companies and managers in the field focus too much on measurable analyses. Yet those decisions might be good for the short-term. They might prevent an organization from focusing on long-term, hard and strategic decisions. Amazon, a company that relied over and over again on quantitative analysis of things that could be measured, optimized and maximized. Also relied a lot on judgment, opinion, and human decision-making when it came to long-term, strategic decisions that could not be based on previous experience or scenarios, but needed to be tackled. This point is very important. In a world of management that focuses more and more on the quantifiable, and measurable. Getting data-driven might mean losing the strategic focus.

Amazon laid out the foundation of its decision-making process, based on few key principles, defined in 1997, in the first Shareholders letter:

We will continue to focus relentlessly on our customers.We will continue to make investment decisions in light of long-term market leadership considerations rather than short-term profitability considerations or short-term Wall Street reactions.We will continue to measure our programs and the effectiveness of our investments analytically, to jettison those that do not provide acceptable returns and to step up our investment in those that work best. We will continue to learn from both our successes and our failures.We will make bold rather than timid investment decisions where we see a sufficient probability of gaining market leadership advantages. Some of these investments will pay off, others will not, and we will have learned another valuable lesson in either case.



Amazon’s renewed business playbook

In the annual letter of 2001, Jeff Bezos highlighted:

When forced to choose between optimizing the appearance of our GAAP accounting and maximizing the present value of future cash flows, we’ll take the cash flows.

And he continued:

Why focus on cash flows? Because a share of stock is a share of a company’s future cash flows, and, as a result, cash flows more than any other single variable seem to do the best job of explaining a company’s stock price over the long term.

Therefore, even though Amazon did survive the dot-com bubble, the business model which would enable the company to make it through the first phase of scale-up was drafted around the beginning of the year 2000, right at the bottom of the dot-com bubble.

In short, even though Amazon emphasized so much on cash flows, during the dot-com, the company was burning a substantial amount of cash. And Amazon itself still saw the web as a distribution platform, rather than a business model enabler.

Therefore, Amazon‘s survival through that period was nonetheless due to a bit of lack. However, Jeff Bezos led Amazon through that period with vision and extreme passion, and he kept pushing the company to a new business model.

Any lessons Amazon learned during the dot-com bubble to find business model-market fit that we haven’t mentioned? Plain luck?



Customer ObsessionOwnershipInvent and SimplifyAre Right, A LotLearn and Be CuriousHire and Develop the BestInsist on the Highest StandardsThink BigBias for ActionFrugalityEarn TrustDive DeepHave Backbone; Disagree and CommitDeliver Results

More About Amazon:

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