The Customer-value Ecosystem 1.0

“The consumer is the most important part of the production line.” - W E Deming, founder of Total Quality Management (TQM).

Figure 1: The Customer-value Ecosystem. An overly simplified 10,000 feet model of the core Ecosystem of Customer-value. Each System has it’s own internal structures and hierarchic subsystems. At a high-level, this is how these 3 Systems are interrelated.

One of the most important assets a company can own is knowledge about it’s customers. This is arguably the root of it’s entire competitive advantage, and source of its continued relevance in the world.

Despite this axiom, according to the latest State of UX Report (2022, UserZoom), 45% of businesses surveyed do not integrate learnings from User Research into Product decisions. And 43% do not have a process to do so. This is concerning, given that any product can only effectively meet the needs of the market with an accurate institutionalised model of those needs. I use the term ‘institutionalised’ to represent the effective ‘internalisation’ of that model in each and every member of the delivery team.

In this article, I’ll outline a very simple model, that makes it easy to recognise the core priorities of a business, the issues that affect business viability, and to think about one’s own place within it.

A word of warning from the outset that, in order to demonstrate how the mechanics and dynamics of customer value are incorporated into the model, there are some places where I will state the obvious. This is with the intention to put each dynamic in its rightful place within the overall structure.

In this article, I’ll cover:

• The importance of customer-centricity
• What is the Customer-value Ecosystem?
• The 3 parts of the Ecosystem
• Key benefits of the model

Since the entire model anchors on the importance of the customer base, let’s begin by baselining there.

Importance of customer-centricity

We can understand the preeminent importance of seeking and modelling customer needs, if we liken it to walking into a dark room for the first time. Being able to look around, and thereby encoding environmental data into a visual channel is one of the ways a person might adapt to a new environment. Business activity is like movement around the room, and user research provides data about the room in which that business directs its activity. Generative research is the business equivalent to an organism using its senses. Sure, bumping into objects in the room builds some understanding of the immediate environment. But it’s slow.

Some sporadic user research is like turning on a torch, or spotlight: you can see further, but the narrowness of the view is still limiting to business activity. Strategic research, understanding the customer’s behaviour, in absence of the business offering, is like turning on the light in the room. The absolute space to play is much clearer, and easier to plan for. Importantly, the business performance is more predictable.

Now the business has good visibility of the room, what about when the internal structure changes? (i.e. people leave the business). That internalised knowledge is embodied in the team, but when the team changes, the data is lost. Losing experience and knowledge from the team is the business equivalent of a lobotomy. It costs a fortune, and effects downstream productivity (Narver & Slater, 1990). The body of institutionalised knowledge must be rebuilt. A Research Repository is one of the most vital, but often overlooked, assets a business has.

In fact, if businesses are competing against each other to deliver more value to customers than competitors, then its knowledge about those customers is the most valuable asset it can possibly possess. Not just the product-itself (which is a product of investment, and current understanding of customer needs), not revenue (which is a product of its efficacy), not profit (which is a product of its efficiency), but of customer insights, which is a product of the problem-space the business must remain relevant within. Products change, economic factors will fluctuate. Certainty about customers must be perennial — for any business, of every scale, at every maturity-stage.

Now let’s add the final component of the analogy. The room itself is changing — the sofas are rearranging, more tables are added, chairs are removed, windows are shifted. The structure and relationships in the room are changing, updating, also adapting. Under these conditions, keeping the lights on becomes all the more imperative. This is what customers are doing: they never stay still, or satisfied, for long.

The continuing importance of customer-centricity

The importance of being customer-centric is vey much well-established. There’s no real need to cover the same ground. However, the meaning of being truly customer-centric, in the way that your entire functional world revolves around their needs is not always well-practiced, nor applied. To paraphase a verse from the Tao Te Ching, it is known by all, but done by none (chapter 78). Or rather not so many as it should be.

The reason for this is that businesses are run by humans. And humans can be myopic in their perspective. As an individual professional with a business, it is sometimes difficult to get an accurate picture of the world outside. Outside you, outside your team, outside the business.

In some businesses departments may operate in information-silos. Each team focuses on their own goals, not having time to appreciate nor question the big picture. Some businesses end up focussing on ‘just shipping’ rather than shipping with intention, intending to learn. They are efficient without being effective. They fall prey to the threat of ‘Productivity without Purpose’, and the inevitable output without outcomes. This is perhaps because they prioritise business activity over customer activity. Change within their control without consideration of how their actions affect their customers’ world.

The most effective businesses make use of a different mental-model: one that maps the commercial environment in a more holistic way, that reconciles experts and professionals from across multiple fields of expertise. Despite numerous departmental capabilities (albeit Marketing, Design, Product, Business, Customer Services, Operations etc), the most common cause of breakdown between alignment is the failure to recognise how each fits within the ‘bigger picture’. Customer-centred businesses understand how an individual, a team and how different skill-sets work effectively together as a single system.

Moreover, widening the scope of that world-view is also crucial. It’s not enough to recognise the interdependence within the business, but also to model the outside world and how the business interacts with it’s environment.

The existential purpose of a business is to create change. Not for the people within the business, but for the customers it serves. And yet, as we saw earlier, 45% of businesses surveyed do not integrate learnings from User Research into Product decisions. One might question: what are these businesses basing their decisions on, if not upon the needs of their customers?

In practice, there’s often a considerable gulf between the market reality and the perception of that reality within a given business. If we were to poll our internal stakeholders about the problems customers face, and poll customers about the problems they face — would there be a 1:1 relationship? Hopefully, but if the evidence is believed, then likely not.

This is proven by research into why businesses, products and start-ups fail. The accuracy of the instititutional model the business has about its customers can truly make-or-break business and product success. Misunderstanding the market, or attempting to push something onto a market, is one of the most common reasons for product failure. 35–42% fail because of lack of a market-need (Statista / CB Insights, 2021). Product ideas cannot be shaped in one’s imagination (which is almost always flawed to some extent), but be born in the reality of the customer’s needs.

It’s easy to see where this problem comes from: there’s a deeply ingrained trade-off between value and delivery, because everything must be made gradually. The pressure on a business to deliver products are the impetus for Scrum methodology and Agile, but there’s always been a deep inefficiency in how ‘incrementalism’ or ‘constructivism’ builds products. This is because it’s anchored on the belief that we know nothing about the customer until we show them something. Studying change on the basis of incrementalism is a challenging and sometimes wasteful process.

So it seems there are a few important problems which can be observed in many modern businesses, which are common sources of failure. Some of them can be attributable to some common problem(s):

• Institutional misunderstanding of why any business exists (not just for Profit, which is a proof of value).
• Ambiguous relationships between the market and the customer, the business and the product, and the value created.
• Misalignments and fractures between departments about how value is created, and for whom.
• Assumption that business or product metrics represent customer value.
• An over-dependency on product incrementalism (building features) over strategic customer discovery (building knowledge of problems).

To overcome some of these institutional, contextual challenges, I propose a simple mental model. Intentionally designed to simplify the working relationship between all the parts. With this in mind, let me introduce ‘The Customer-value Ecosystem’.

What is the Customer-value Ecosystem?

The Customer-value Ecosystem is a simple structure that provides anchor for how value is created by activity, and how activity creates products. The eco-system is a 10,000 foot view on the interactions between the most important entities involved in providing customer value.

To overcome the common problems identified above, it captures the fullest possible and relevant problem-space in which a business functions, and outlines the types of data and relationships that occur between each aspect of the Customer-value Ecosystem.

In that, there are 3 systems which operate at a low-level of recursion. It helps to explain what Stocks are required from each System, what inputs, transformations and outputs are created from each Subsystem within the Ecosystem, and also explains some of the more strange phenomena that occurs from the results of this structure (like very successful businesses still having very unsuccessful products). Because it’s comprised of 3 Systems, I also refer to it as the 3 Systems Model (3SM).

Below is an illustrated example of the boundaries between each of the entities. Like all models, it treats complexity in a perfect case, as opposed to the world that is inherently imperfect.

The small brown circles represent individual customers. For the sake of simplicity (since it’s a conceptual model), I haven’t created hundreds of thousands of dots, but they should be taken as being representative of such.

Figure 2: A simplified demonstration of the complexity inherent in the relationships between markets, in the total population. This is the map of how entities aggregate into sets, or collectives.

I’ve then overlaid some boundaries. The outer imperfect shape groups them by total population. The total population represents society at large. Within society, we find clusters of people with related and similar jobs and attitudes, which we might define as ‘Markets’, and the variety of customers within them is ‘Market segments’. A market is simply a statistically significant collective of individual needs.

At the same time, we also have clusters of professionals known as ‘Companies’. These people represent the capabilities a business needs in order to compete with other Companies.

A Company is a System in it’s own right, with capabilities having relationships with other capabilities in order to create competitive advantage. ‘Teams’, who are cross-functional and are united within a group called a ‘Company’. These people exist to serve ‘Markets’. All companies that exist based upon similar themes and motivations, often serving the same or similar capabilities are defined as ‘Industries’, or ‘Sectors’. Those who share markets and customer segments are termed ‘competitors’. This picture defines a mental model of how businesses and markets function, and are related to each other.

What this model misses is that when a business is engaged in understanding its market, and is actively producing value for them via a Product, then there are actually 3 Systems we need to investigate. We also need to understand the relationships between each of those domains in terms of Input-Output.

Internal to a business, Researchers, Designers, Managers, Executives, Developers, Product Managers, all hold varying degrees of differences in their views of their work. But they all tend to operate within the same domain. The inputs they receive vary in relevance in comparison with the Consumer domain, and the Product domain, and therefore incongruities develop, causing mis-alignments within a business.

In the past, I’ve found that the 3SM is capable of reconciling the differences between all the players, roles, and stakeholders in the game, by providing a stable mental model. In Cybernetic terms, this represents an abstraction of the full reality, which is often referred to as an ‘Assembly’. The origin of the 3SM comes from the observation of 6 subsets of activity which happen between 3 discrete Systems: The Market, The Business, The Product.

The adaptive enterprise, or learning organisation

Like any living creature, the primary purpose of a business is to maintain it’s existence — to persist. It‘s primary purpose is not to return a profit to shareholders. It serves a market, which represents it’s source of income, it’s nourishment — much like a living creature. The business adapts to the needs of it’s environment. When market needs shift, so too must the ways in which a business provides value. Animals that fail to adapt to new conditions go extinct, much like businesses that do not adapt to customer needs. Market needs change, the what and how of products will inevitable change, but the business must persist. This was the core of Peter Senge’s seminal work: The Fifth Dimension (1990).

When Theodore Levitt described in ‘Marketing Myopia’ (1975, Harvard Business Review), the article often credited to have kick-started the jobs-to-be-done approach, that businesses tend to be “product-oriented rather than customer-oriented”, he was pointing out that professionals have a propensity to focus on their own activity, focus on the ‘thing’ rather than the ‘purpose’ of that ‘thing’. He used the example of railroad companies who went out of business because they falsely assumed they were in the business of trains, rather than the business of transport. They had mistaken the ‘product’ to be their business, not the change they manifested for their customers.

A business must study customers. Based upon that study, it produces a Product (or Products). As the Customer interacts with Product, the Product generates data (behavioural, or activity, data) — embedded, perceptual, attitudinal, psychographic about the interaction. The business interacts with product- and customer-data as inputs, and makes adjustments (or, ‘interventions’), based upon a known variable.

The 3 systems of the Ecosystem

These 3 domains have boundaries, and therefore they are considered as distinct, even if the challenges related to them are not distinct.

Let’s define them first:

1. Consumer System (System 1)
2. Inventor System (System 2)
3. Product System (System 3)

All three Systems might rightly be referred to as subsystems of the same system. But in order to mentally prioritise the 3 parts, I have sought to reinforce it by anchoring on 3 domains. This is intended to achieve a solid grounding, by means of what Developers call a ‘separation of concerns’.

This represents an effective mental model to provide solid boundaries between the 3 subsystems, even though the true relationship is more like a mesh or lattice-work of interrelatedness, and interdependency. Each of the 3 domains requires deep investigation to understand the other 2.

Let’s inspect each one in turn:

The Primary System (the Market)

This refers to the Consumer, or Market, System. Specifically, it identifies the person(s) who use what we build, and need it to achieve their goals. The primary, and by far the most important system, is the Consumer System.

If you were to remove the concept of ‘a businesses’ from the face of the Earth, System 1 would continue to exist, and have needs to be fulfilled. As I’ve discussed elsewhere, this is at the core and kernel of Capitalism, as expressed by the economist Adam Smith.

Within this System, we find details about the decision-making unit (Kotler, 2009) such as Users, Buyers, Gatekeepers etc, and their individual goals. Individuals are themselves ‘systems’, such that we must consider user goals, and actions at an individual level, even if we present them as ‘personas’ at an aggregated level. We also find macro-influences upon them, such as geo-political, socio-economic factors, which determine the interplay and relationships of these. Inputs to these systems include culture, context etc.

A system is defined as a set of interrelated parts. The structure of System 1 comprises:

1. A single person has a problem.
2. A single person is aware of the problem.
3. When that single person has money and inclination to pay for a solution, they are defined as a ‘customer’.
4. A common problem shared across many ‘customers’ is defined as a ‘market’ (Blank’s Market-types).
5. Customers are inter-related, and therefore form a single system.

This rudimentary logic defines the scope of System 1 in its entirety. It also helps to explain why businesses don’t solve any and all problems, only ones that emerge from point 3, even if the users are not the customers.

The environment represents the entire market, but the target market for a business is a subset of the whole market.

The output of this System is unmet needs, at a scale that defines a Market. Individual customers have every right to ‘hire’ any solution that they wish in a free market, and have every inclination to become accustomed to a solution over time. Depending upon the personality traits of the customer, it defines whether they would be likely to find innovative alternatives, or whether they remain satisfied and loyal (See Everett Rogers’ Diffusion of Innovations, 1956).

Let’s drill down into System 1. The fundamental unit is the customer. For the sake of simplicity, let’s assume that the customer is also the user. The customer has a Need to be solved, or to view from the inverse perspective: a goal. Therefore, we might consider the user as a Goal-directed Agent (GDA). This model allows us to recognise that a user is able to recognise when a solution will bring them closer to their goal. A GDA is defined by layers. Those layers define the probabilities of using a product. Those layers can also be used to understand similarities and differences between GDAs. Where close similarities in goals exist between GDAs, they can be considered as a unified whole (a ‘market’).

Figure 3: The Goal-directed Agent (GDA) — Zooming into some detail. This diagram is based upon the ‘Drifting Goals Loop’ (System Dynamics), HCD ISO 9241–210:2019, Hierarchical Task Analysis and Jobs-to-be-done, both derived from Perceptual Control Theory. Overlaying some Self-Determination Theory into the mix, as well as Bourdieu’s Theory of Cultural Capital.

Figure 4: HTA: Zooming further into protocols between Current State and Actions, per Hierarchical Task Analysis (HTA). It’s clear from this that there’s a strong correlation between a goal-state and behaviours. These are some of the complexities which exist within Fig. 3.

The distance between the GDAs current state and their desired goal represents the potential value produced by a solution. The distance between the desired goal and the delivered goal represents the volume of satisfaction and delight possible (per the Kano Model: for example, if a solutions surpasses the expectations set by the desired goal, then the customer will reach a state of ‘delight’ — ‘delight engineering’ is therefore possible with the right targeting and understanding of what conditions produce it).

Figure 4: A definition of the states observable in System 1, related to Goals.

There are 4 recursions in the customer/market system, as a network of connections:

• The customer, is a node within a segment;
• The segment, is a node within a market;
• The market, is the aggregate of all target segments;
• The total market, is the aggregate of all markets.

System 1 also takes interrelated input from exposure to sources of solutions (i.e. businesses / System 2), which perpetually raises the benchmark of expectations of customers within System 1.

Inputs:

• Exposure to ideas / Experiences
• Behaviour / Motivation / Will / Need / Habit / Default
• Social effects: Relationships and influences as part of a Decision-making unit (DMU)

Output:

• Decisions
• Actions
• Payoff / Results

The Secondary Domain (the business)

The purpose of a business is to maintain viability.

The mental model for this is the Company or Business. A business maintains a stock of capabilities (embodied as ‘employees’) who deliver value to System 1, often through its output, in the form of System 3 (which we’ll describe shortly).

The determinant properties of the System 2 are its raw materials (human and material resources) as well as its vision/strategy, and operational models (per Jay Galbraith). The human capital of a business aggregates the collected ingenuity, world-view, skills, competencies, biases of those who create any Product System. This is further broken down into Management teams, Design teams, Product teams, Marketing teams, Operations teams, Engineering teams etc. Each of these teams function, and provide competencies within their remit, across the business.

The unit of creativity — the source of innovation — is not one dimensional (an isolated individual’s thinking or a team per se) but rather an individual within a team within an organization over time. Each level of this dependent sociocultural-psychological hierarchy has a both–and relationship to its environment that makes its existence and development possible: The person is both an individual and a team member; the team is both a group of individuals and a unit in an organization. (John E Arnold, pp.49)

System 2 employs a range of capabilities to understand and track System 1, such as User Researchers. It also has teams which are devoted to ensuring the internal structure operates effectively, such as HR, Finance and Operations. These are System 2-centric competencies. Some capabilities straddle more than one focal point. The axis for a Product Manager, for example, is a focus on System 1, whilst effectively prioritising which resources of System 2 could be deployed to create the biggest benefit to System 1.

In a product-based business, the System 2 takes input initially from System 1, to deliver intervention on the tertiary. Then once the tertiary system exists, it should also take inputs from both primary and tertiary. The biggest risk is that it ceases to take input from User Research. Companies that prioritise their own data from the Tertiary system, tend to be unable to adapt to changes found in System 1. System 1 will always continue to function, whether or not System 2 leverages User Research to build a model of it.

Organisational design dictates success, such that the structure of the organisation (in a way that dictates WHERE information may flow, and in which directions), as well as the actual activity (the operation, which includes information sharing). These are strong determinants for how the Tertiary domain exists. This axiom is reflected in Conway’s Law.

Within System 2, we can observe a variety of skills necessary to output a Product. The majority of the demarcation of those skillsets are derived from the career-paths and traditional training found in academia, rather than being reflective of the needs of a business. For example, Software Engineers typically have a Computer Science background, Designers typically have a Graphic Design, Interaction Design , Psychology or HCI background. This is an example pattern rather than the rule. As a result, those who write code typically have been grouped with those who also write code. Those who move digital boxes around on a screen have been grouped with those who also move digital boxes around on a screen. The emergence of ‘full-stack’ programs have tended to represent those who have studied more than one skill to proficiency in that subject-matter. ‘Unicorn’ is the unuseful term used to refer to those who have studied elements from both or more fields.

Likewise, the standard operational models that exist reflect those groupings. Approaches to Software Development (such as Agile: Scrum, XP, Kanban, etc), have tended to ignore the design aspect of Product Development opting to integrate it later. This has led to attempts to reconcile the 2, from the product management or software side. Likewise, approaches to Digital Design have established their own models, such as Design Thinking, Double-diamond framework, Design Sprints etc. Attempts to reconcile double-diamond and software development practices have been found in the Triple-diamond, for example. All of these methods and frameworks are attempts by those within those fields to organise and make sense of the most effective practice.

And further, Product Managers (who traverse a number of fields), have developed User story mapping, Jobs-to-be-done, etc are all artefacts used by the Secondary system to model and institutionalise the inputs from the Primary System.

When professionals describe how the double-diamond works, or the DesignOps triple-diamond process integrates with Agile, then they are describing properties of the Secondary system. The purpose of this system is to efficiently deliver, using the combined competencies and ingenuity of the inventors within the business to create value for the customer (Primary) by delivering a product (Tertiary).

Taking Design specifically, when Alan Cooper (About Face 3, 2007), Hugh Dubberly and Paul Pangaro, describe their approaches to UX and Design delivery using Cybernetic terms, they are describing how cybernetics and engineering principles may be used to define the Design process found within the Secondary system. When DesignOps specialists are describing team structures, and data flows within them, then they’re also describing subsets within System 2, which commonly do not reflect the Operational Models of other teams, or even the Market (System 1). Most models consider some parts of these systems, but rarely their whole. These just some of the ranges of problems currently facing businesses.

What companies state that Big Data is important, by leveraging data that the business holds, they are referencing interaction between customer and business. They do not capture the complexity or the movement that his happening in the absence of the business. This is one of the fundamental biases inherent within it.

The collected efforts of all aspects of the Value-Delivery System across a business is found in the output. That output we might call System 3, or The tertiary system. There are 4 recursions in the business system:

• The employee, is a node within a team;
• The team, is a node within a business;
• The business, is a node within an industrial sector;
• The business generally represents an explicit and distinct boundary.

The structure of the relationships between these nodes may be used to identify blockers to, and predictors of, future success. This structure comes in many different forms.

Input:

• Customer insights
• User needs
• Business Strategy, Mission, Objectives

Throughput (Transputation):

• Translation to design/architecture in 5 dimensions
• Conversion to coded function

Output:

• Product
• Process
• Incentive

The Tertiary Domain (the product)

The thing we build, which acts as a single proxy for the expertise of the Inventor System (2). It might seem strange to relegate the thing we build as the 3rd part of the system, but this is because it exists as a consequence of the previous 2 systems. Therefore it has the most dependencies from the Primary and Secondary Systems for its effectiveness.

It is from the interaction between the User and the Product System that generates activity and data about satisfaction and outcomes. It is from the direct understanding of the User System that the Inventor System may determine how to shape the Product System. This understanding is further defined by a subset of people within the Inventor System called ‘Researchers’. The communication structure of the ‘Inventor System’ tends to provide the directional structure and territory for the structure of the Product System (Conway’s Law).

Figure 5: The 3D conceptual model of the sweet-spot. If success comes down to 3 factors, which is another way of viewing the Customer-value Ecosystem. For each of the factors, a binary is possible. The right/wrong idea (or solution), right/wrong team (or competencies/skills in a more abstract sense), and right/wrong market (as a compound of problem and people). It’s entirely possible for a business to have the wrong market, wrong idea and wrong team (resources). Only 1/8 of approaches will hit the sweet-spot of right market, right idea, right team, which correlates with the statistics around both product or business failure.

A successful product depends upon Strong Market, Clear Vision, Great Team. An institutional knowledge of that market, an accurate prediction about the new status-quo to solve that market need, and a culture that’s design to encourage product-market fit are essential components of success within this system.

The product-led leadership approach, a means of platforming businesses around their primary asset, is one of the ways in which a business may drive the cultural alignment between different competencies, and departments.

There is also the aspect that customers may not interact directly with a ‘business’ but via the medium of their product. In which case, the tangible interaction being measured is something separate from the system that produced it in the first place. This must also be conceptually represented in the manner shown in the model.

Since I started to share this model, some folks have mentioned that the product is a product of the business, and therefore part of System 2. This is pragmatically the case, since it must be by its nature. It doesn’t spontaneously come into existence. It is ‘produced’ and is the result of effort, skills, knowledge etc. However, it is separated to make a more moral statement, in reference to Levitt’s comments earlier — that businesses cease to exist when they assume the product is the business. Instead, the business must remain relevant within System 1. This is one of the key lessons from this model — that the needs of customers change, and therefore the products of businesses must change. A business might have any number of products over time, but all of them are for the intention of maximising relevance to System 1. This is why I have continued to separate System 3 from System 2.

Input:

• User activity / engagement

Throughput:

• Transputation of needs into outcomes, i.e. change in System 1.

Output:

• Analytics
• Revenue / Transaction
• Measurable capability or change in System 1

The 3 loops

There are 3 systems, each being an open system which adjusts to the conditions set within the other systems. They are therefore all relative to each other. Each feedback loop provides input and output between each System.

1. Knowledge capital: Inventor <> Customer (Interaction 1 & 2): The interactions between Systems 1 & 2. Researchers collect data from the customers, and share it with designers and PMs. The task of the researcher is to explore variety and patterns, and to capture it from System 1. The purpose of System 2 is to create, and maintain an accurate model of System 1. This is in the form of an Insights System.
2. Engagement capital: Product <> Customer (Interaction 3 & 4): The interactions between Systems 1 & 3. Customers experience the product, or about their own problems and challenges. Data is generated from the interaction between the customer and the digital product. This provides performance and diagnostic data. In some cases. Data from this generates the customer to internal experience modelling data.
3. Productive capital: Inventor <> Product (Interaction 5 & 6): The interactions between Systems 2 & 3. commonly called DesignOps. How delivery teams work together to create value. Delivery teams (the collective noun for Design, Development, and any other roles involved in physically creating the Product System), reconcile their learnings from System 2, in order to modify the performance of System 1. The aim of System 3 is to accurately improve and produce positive change in System 1 on the basis of feedback provided through System 2.

Using the 3SM to diagnose risks

All these relationships are bi-directional. Risks occur when any one of these bi-directional is unidirectional. For example, if a business prioritises only modelling data about the product (interaction 6), then it risks missing the signals when the market has changed it’s needs.

Good examples of companies who did this were Blockbuster video, and Nokia, as captured in Tricia Wang’s fantastic TED talk (The insights missing from Big Data, 2017). They prioritised data only from System 3. Their assumption was that System 3 data accurately told them about the changing circumstances in System 1. That assumption was disproved by their inability to survive (remain viable). As we saw, this is also a key criticism of Big Data, given that it reflects data about business or product interaction (Systems 1&2) and not the changing circumstances of System 1. Tricia Wang refers to using a combination of data about System 1 and System 3, as ‘Thick data’ (after Geertz). Thick data is Deep and Big Data combined. The 3SM is capable of demonstrating how and why this risk exists.

Another risk is when companies tend to prioritise efficiency data about the performance of System 2, over indicators of the change it creates for System 1. Improving the effectiveness of internal diagnostic metrics is good, but greatness can only happen when those metrics make an impact on Systems 1 & 3. For example,

Another risk occurs when metrics in System 2 do not mirror the value that System 1 expects. For example, not everything that can be measured is valuable. This common fault occurs when input and output metrics between the systems are in misalignment. For example,

Numerous other risks are observable depending upon the possible deficits that exist between the loops. If there are inbalances between using data from any one of these loops over another, then there will also be symptomatic issues that will occur within the business.

Scaling the model

The current discussion explains the nature of the 3SM as it applies to a single business, with a single target market, with a single product. When we consider some of the pluralities involved, wherein a portfolio of businesses is targeting a portfolio of markets, with a portfolio of products, when we encounter new challenges to the usefulness of the 3SM.

This plurality also is a network effect. It doesn’t expect the singular ownership, where a portfolio of businesses is owned by a single corporation. A collection of System 2s is more commonly called an ‘Industry’, representing the collected skills and competencies of similar businesses.

There is typically only one objective ‘market’, which means System 1 defines the environment for all businesses. The variety within the market is represented in the variety of industries, and businesses serving them. All the businesses within the same sector are said to compete with those businesses also within the space. The simplistic aim of the business is to attain ‘dominance’ over competitors. However, using a Cybernetic perspective, the aim is to attain viability — that is, to ensure its own survival. The ultimate aim is longevity. There is no predicate in this model that assumes that competition is bad, but a driver towards incentivising progress toward survival. In which case, collaborating with competitors, could also be a good way to achieve viability.

Return on effort in the form of money is the fuel. If we consider System 2 as a compound, and complex system involving human capital, directed wholly towards viability of the business, by addressing the needs of the market, then we have the basis for the Operating System of Capitalism. Because money is required to sustain the operation of the business, then financial performance is often used as a proof-proxy for the business’ ability to meet the needs of System 1.

Ultra-stability is a Cybernetic concept of system viability which means it’s able to sustain its function, even under unpredictable conditions.

• A company performs a ‘market pivot’, when it targets its existing product to a new System 1.
• A company performs a ‘product pivot’, when it creates a new product to its existing System 1.

This definition is therefore useful to capture how a business ensures it’s survival through adaptation.

Key benefits of the model

We have explored each of the facets of the model, taking a very brief overview of the mechanics of each System, as well as how they interact with eachother. Let’s now summarise the ways this model provides a useful world-view.

We have seen how each capability within a business represents activity that is needed for the Business System to be effective. And the Product System (3) only exists as a means to deliver change in System 1, and out of necessity, to sustain the survival of the Business System (2). And both Systems may only exist to create real, and positive advantage to part, or parts, of System 1. Hence the idea expounded by Andy Rachleff on coining the term product-market fit. In circumstances when they do not, then over time they degrade and cease to exist. The rate of decay is roughly equivalent to their continued ‘fitness’ with System 1.

This latter point cannot be overstated: The entirety of this 3 part System ONLY exists in order to affect change, and create a difference between two states of System 1. The true measure of change therefore is ultimately found in System 1 between the State A (before-product) and State B (after-product). The bigger the positive change, the greater the value. The volume or rate of change does not occur, nor is directly measurable, in business metrics. System 2 metrics can only be proxies for value found in System 1 in the form of adoption, engagement and value.

Figure 6: Value Leaps. Value isn’t defined by the incrementality of the product. It’s defined by the outcome for the user. In which case, the degree of change must be measured by distance of change between user-states. Product is made in increments (per the Henrik Kniberg cartoon), but it’s designed make leaps for the customer.

Sometimes internal stakeholders can have a misunderstanding of artefacts like ‘user stories’ or ‘job stories’. They become confused because their thinking is often anchored in either System 2 (how the business works, or how they’ve institutionally always operated), or System 3 (the culture of building products and features). These artefacts exist only to ensure that activity within System 2 and System 3 remain focussed on System 1. That activity does not become introspective, and that value created is strictly and ultimately for measured change in System 1. A good measure for a solid User Story, for example, is that it captures the circumstances of System 1 only.

In this case, the model I’ve presented here effectively generates the following key benefits:

• a latticework: provides key relationships between common ideas such as User Research, Agile, Product Development, Business success etc. As such the concepts used by various capabilities — such as Product teams (derived from Marty Cagan, Jeff Patton, Mike Cohn, Ken Schwaber, Henrik Kniberg, et al.) UX teams (derived from Don Norman, Jakob Nielsen, Jared Spool, Alan Cooper, et al.), Marketing & Advertising teams (derived from Philip Kotler, Peter Drucker, Simon Sinek, Seth Godin, et al.), Business/Innovation teams (derived from Steve Blank, Eric Ries, Jim Collins, Clayton Christensen, Tony Ulwick), and Systems Thinkers/Cyberneticians (derived from Stafford Beer, Gordon Pask, Donella Meadows), can all be reconciled and placed in their relative positions and relationships. Bodies of knowledge become complimentary to understanding the components of the 3SM.
• seeks salience: promotes a focus on the real creation of value by identifying the sources of that value.
• transcends departmental perspectives: Creates a shared model for those from different parts of a business to recognise the shared value of their own activity, lowering barriers of communication, overcoming artificial barriers of educational/training background, terminologies, values et al. Increasing shared vocabulary about where value is created, how and for what reasons.
• positively elevates mental-models of the customer/user: to predict and anticipate where value occurs, and how to leverage it. It provides solid focus on what successful businesses do, and why — to focus on the existential purpose of a company: to create positive change for it’s customers.
• Interdependence: A change in System 1 requires rapid changes in Systems 2 & 3, as well as advances within Systems 2 & 3 increase expectation-baselines within System 1 too. This is why these Systems comprise an Ecosystem, per Drucker (‘It is the customer who determines what a business is, what it produces, and whether it will prosper’, 1954).
• diagnosis and correction: provides the ability to diagnose organisational issues, within a team or business by providing the wider context for success. A business that puts too much emphasis on Systems 2 and 3, do so at the expense of emphasis on System 1. Businesses that do this, are liable to become obselete to the market.

Overall, this simple model of 3 important entities interacting with each other is a useful tool to recognise the system in which one works. Of course, each system is far more complex than a simple round circle, as shown here. This article is intended as a simplified overview of the System Dynamics taking place in innovation and business strategy. It shows the 3 levers a business has, and the capital it actually maintains (knowledge, engagement, productive).

The model is evolving and changing as more folks provide helpful feedback. Thank you to everyone who has provided thoughts and perspectives to me so far whilst drafting. The model is designed to capture the components, but not to chart a plan or path through it. Therefore, it’s a map of an abstract set of territories, and is intended to change over time.

I’ve personally found the model to be useful and powerful, that has enhanced cross-functional discussions with a shared mental-model of the territories we collectively explore. Perhaps you might find it useful too?

The above article is a personal work, and does not represent the views of my employer.

If you’re working on (or just interested in) any of the topics covered, please reach out and start a conversation. Help me learn. Connect with me on LinkedIn, Academia, Twitter, or Medium.

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Useful Reports and Whitepapers

Forrester: The UX Playbook for 2022, How to scale your Design organisation (2021).

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InVision: maturity model (2021). Product Trends 2021, Talent.

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UserZoom: state of ux 2018, 2019, 2020, 2021, 2022.

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UX Magazine: 2019, 2020, 2021, 2022.

UX Trends: State of UX 2022, 2021, 2020, 2019, 2018, 2017, 2016.