Concepts of Prioritization — Chapter 4

Chapter 4 — Understanding Product ecosystem

In the previous chapter, we discussed about how to estimate the impact of a feature enhancement which has a bearing on another feature. In this chapter, we go into the depth of estimating impact of those tasks which have no impact on their own but help survival or growth of other features. To understand this better, we need to understand what a product ecosystem means.

4.1 Introduction to Product ecosystem

4.2 Understanding the impact of ecosystem

4.3 Estimating impact of creating ecosystem interactions vis-a-vis Estimating ecosystem synergy of an interaction

4.4 Mathematical representation of ecosystem interaction impact estimation

4.1 Introduction to Product ecosystem

In a biological ecosystem, various organisms interact with each other and the environment in which they live to sustain themselves and grow. Similarly, in a product ecosystem, various products and services interact with each other and the environment in which they are used to provide value to users and grow the ecosystem.

Just like in a biological ecosystem, where the health and survival of one organism is dependent on the health and survival of others, in a product ecosystem, the success and impact of one product or service is dependent on the success and impact of others in the ecosystem. The different products and services in a product ecosystem can be thought of as different species in a biological ecosystem, and the interactions and dependencies between them can be thought of as the interactions and dependencies between different organisms in a biological ecosystem.

In both cases, the overall health and sustainability of the ecosystem is dependent on the health and sustainability of the individual components, and the success of one component can have a ripple effect on the success of others in the ecosystem.

We can categorize the components of a product ecosystem into two main types:

in a product ecosystem, the interactions between the different components are also crucial for the ecosystem to function as a self-sustaining system. For example, the components of a product ecosystem can be categorized as:

1. Functional components: Products and services: These are the main components of the ecosystem and can include both physical and digital products/services. They are analogous to the biotic components in a biological ecosystem.
2. Structural components: Platforms and technologies: These are the supporting components that enable the products and services to function and interact with each other. They can include software, hardware, communication protocols, and other technical infrastructure. They are analogous to the abiotic components in a biological ecosystem.

The interactions between these components can take many forms, such as data sharing, cross-promotion, and integration. For instance, products and services can leverage the technical infrastructure provided by platforms to enhance their functionality and reach a wider audience. Similarly, platforms can benefit from the network effects created by the products and services that use them. These interactions help to create a self-sustaining system where the success of one component feeds into the success of others, leading to overall growth and sustainability of the ecosystem.

Types of Interactions

1. Co-creation: Multiple components within the ecosystem come together to create a new product or service.
2. Cross-selling: Encouraging customers of one product to purchase a related product from within the same ecosystem.
3. Customer data sharing: Sharing customer data between components to better understand user behavior and improve the overall customer experience.
4. Platform integration: Integrating multiple components into a single platform to provide a seamless user experience.
5. API sharing: Sharing APIs (Application Programming Interfaces) between components to enable data exchange and interoperability.
6. Resource sharing: Sharing resources, such as storage or computing power, between components to improve efficiency and reduce costs.
7. Standardization: Creating common standards and protocols between components to improve interoperability and ease of use.
8. Feedback loops: Collecting feedback from users of one component to improve other components within the ecosystem.
9. Collaborative innovation: Encouraging collaboration and innovation between different components within the ecosystem to drive overall growth and success.
10. Upselling: Encouraging customers to purchase a more expensive or upgraded version of a product they already own
11. Referral programs: Incentivizing existing customers to refer new customers to a product or service
12. Shared user accounts: Allowing users to access multiple products or services with a single account login
13. Shared data sources: Sharing data between products or services to improve functionality or user experience
14. API integrations: Allowing products or services to integrate with each other’s APIs for seamless communication and data exchange
15. Platform extensions: Allowing third-party developers to build and integrate their own products or services on top of a platform or ecosystem.

4.2 Understanding the impact of ecosystem

In classical mechanics, an object in isolation, by definition, does not have any position or configuration with respect to anything else, and therefore cannot have potential energy.

Similarly, one can think of individual product’s impact as kinetic energy and when the products and services come together, an ecosystem possibility arises and the impact of the ecosystem as a whole is higher than the impact of individual products added together.

And just like the gravitational potential energy increases when two objects get closer together, the ecosystem value increases as the products are better integrated and are closer to each other.

Adding an interaction can increase the impact of individual products and also increase the impact of the ecosystem. For maintaining clear difference between product’s impact, non-product ecosystem’s impact, lets call the value of the second one as Ecosystem synergy.

For example, imagine someone who is thinking of buying a phone and is planning to buy a laptop later. If this someone is indifferent between an iPhone and a OnePlus phone, then they might be inclined to purchase an iPhone if they see value in a macbook as they would want to benefit from the ecosystem. Its a potential value addition for the user. This is a classic example of a ecosystem synergy.

Total Ecosystem Impact = Σ (Impact of Individual Products) + (Additional Impact from Interactions)

The last component is what we are calling as Ecosystem synergy

4.3 Estimating impact of creating ecosystem interactions vis-a-vis Estimating ecosystem synergy of an interaction

To get better at estimating the impact of an interaction, we need to understand how to measure the impact of an interaction

1. Identify the metrics: Start by identifying the metrics that are relevant for measuring the impact of the interaction. For example, if the interaction is between two products, the relevant metrics could be the number of users, revenue, or engagement of both the products
2. Collect baseline data: This is the singular most important step to measure impact of an interaction. Collect baseline data for each metric before the interaction is implemented. This data will serve as a reference point for measuring the impact of the interaction.
3. Define the impact model: Develop a mathematical model that represents how the interaction is expected to impact the relevant metrics. The model should take into account factors such as the size of the user base, the level of engagement, and the revenue generated.
4. Estimate the impact: Use the impact model to estimate the impact of the interaction on each metric. This can be done through simulations, statistical analysis, or other mathematical techniques.
5. Validate the results: Validate the results by comparing the estimated impact to the actual impact observed after the interaction is implemented. This can help refine the impact model and improve its accuracy for future interactions.

Overall, the key to estimating the impact of creating interactions in a product ecosystem is to have a clear understanding of the relevant metrics and a robust impact model that takes into account the complex interactions between the components.

4.3.1 Illustration of ecosystem interaction impact estimation

Let’s take the example of Apple’s ecosystem and focus on the impact of the “Handoff” feature. Apple Handoff is a feature that allows users to seamlessly transfer their work across Apple devices. For example, a user can start writing an email on their iPhone and then continue writing it on their MacBook without any interruption. Handoff works by using Bluetooth and Wi-Fi technology to establish a secure and direct connection between devices. When the user moves from one device to another, the Handoff feature detects the change and automatically transfers the relevant data to the new device. Here is how we can estimate the impact of handoff feature

1. Identify the metrics: The metrics could be the number of Handoff-enabled devices, the number of Handoff interactions per user per day, the overall engagement of users within the ecosystem, and the user retention rate.
2. Collect the baseline data: Apple could collect data from various sources such as device usage logs, app usage logs, and user surveys to understand the baseline of both products
3. Analyze the data and design the impact model: We now have to establish correlation between Handoff usage and overall engagement and retention rates. For example, they could use regression analysis to estimate the impact of Handoff usage on retention rates. Based on the analysis, Apple could create a hypothesis that the Handoff feature has a positive impact on user engagement and retention within the ecosystem.
4. Test the hypothesis: Apple could conduct an A/B test by disabling Handoff for a group of users and comparing their engagement and retention rates with those who still have access to Handoff.
5. Validate the results: Based on the A/B test results, Apple could confirm or reject the hypothesis and adjust their strategy accordingly. For example, if the test shows that Handoff has a significant impact on retention rates, Apple could prioritize further development of Handoff and promote its usage to enhance the user experience and engagement within the ecosystem.

4.4 Mathematical representation of ecosystem interaction impact estimation

Ecosystem synergy impact of creating an interaction I1 between two products A and B whose impacts are Ia and Ib is denoted as

ESI1 = k*Ia*Ib*(Sab²)

k is a constant denoting the ecosystem synergy factor. Sab denotes how well the two products are integrated. The more they are integrated, the higher Sab would be and higher impact of I1 would be. ESI1 is different from increase in individual impacts of products A and B

The ecosystem synergy factor represents the overall impact of the ecosystem on the interaction, and Sab denotes the level of integration between the two products, which can amplify or diminish the impact of the interaction.

4.4.1 Calculating k

Calculating k, the ecosystem synergy factor, involves considering various factors such as the degree of interdependence between products, the level of compatibility between their functionalities, and the overall impact of the ecosystem.

One possible mathematical model to calculate k is as follows:

k= f(α ,Ic, β,If,γ,Io)

where:

• α, β, and γ are weighting factors that determine the importance of each factor in the calculation of k.
• Ic represents the degree of interdependence between products in the ecosystem, can be measured as the ratio of the number of interactions between products to the total number of products.
• If represents the level of functional compatibility between products, can be measured as the ratio of the number of compatible functionalities to the total number of functionalities across all products.
• Io represents the overall impact of the ecosystem, can be measured as a composite score of the individual impact of each product.

The specific values of α, β, and γ would depend on the context and goals of the ecosystem, and may be determined through experimentation and analysis. The formula can be further refined or adjusted based on feedback and insights gained from observing the ecosystem’s performance over time.

For example, let’s say we have an ecosystem consisting of three products: Product A, Product B, and Product C. Product A has four functionalities, Product B has three functionalities, and Product C has five functionalities. There are a total of seven interactions between the products.

A sample k function could be

k = (1 + α * Ic) * (1 + β * If) * (1 + γ * Io)

To calculate k, let’s assume the following values for the weighting factors:

α = 0.4, β = 0.,3 γ = 0.3

We can calculate Ic as follows:

Ic = (number of interactions) / (total number of products) = 7 / 3 = 2.33

To calculate If, we need to determine the number of compatible functionalities between the products. Let’s assume that Product A and B have two compatible functionalities, Product A and C have one compatible functionality, and Product B and C have three compatible functionalities. Then:

If = (number of compatible functionalities) / (total number of functionalities) = (2 + 1 + 3) / (4 + 3 + 5) = 0.6

To calculate Io, we need to determine the individual impact of each product. Let’s assume that the impact of Product A, B, and C are 5, 3, and 7 respectively. Then:

Io = (sum of individual impacts) / (total number of products) = (5 + 3 + 7) / 3 = 5

Finally, we can plug these values into the formula for k:

k = (1 + α * Ic) * (1 + β * If) * (1 + γ * Io) = (1 + 0.4 * 2.33) * (1 + 0.3 * 0.6) * (1 + 0.3 * 5) = 4.57

This means that the ecosystem has a high degree of synergy, indicating that the interactions between the products are positively impacting the overall performance of the ecosystem.

4.4.2 Calculating Sab

Calculating Sab will depend on the specific characteristics and goals of the product ecosystem being analyzed. However, there are several factors that can be considered in determining the level of integration and complementarity between products.

Sab = f (w1, f, w2, c, w3, n)

Where:

• f is the frequency of interactions between the products A and B.
• c is a compatibility score that measures how well the functionalities of A and B work together.
• n is a complementarity score that measures how well A and B complement each other in terms of fulfilling customer needs.
• w1, w2, and w3 are weighting factors that reflect the relative importance of each parameter. These factors should be determined based on the specific characteristics of the ecosystem and the products involved.

To calculate the values of f, c, and n, we can use the following sub-formulas:

f = f (Ta, Tb, Na, Nb)

Where:

• Ta and Tb are the total number of interactions that A and B have with each other
• Na and Nb are the number of times A and B are used by the ecosystem or the stakeholder

c = f(d ,D)

Where:

• d is the distance between the functionalities of A and B in a multidimensional feature space.
• D is the maximum possible distance between any two functionalities in the same feature space.

n = f(Pa , Pb)

Where:

• Pa is the market share of product A in the relevant customer segment.
• Pb is the market share of product B in the relevant customer segment.

Once we have calculated the values of f, c, and n, we can plug them into the Sab formula and obtain the integration score for products A and B.

Below are few sample functions

Sab = w1f + w2c + w3n

f = (Ta/Na)*(Tb/Nb)

c = 1 -d/D

n = (Pa * Pb)⁰.5

Easter egg: How to think of building product ecosystems

Identify and list all stakeholders

1. Begin by identifying all the stakeholders in your product ecosystem. This should include buyers, sellers, and any other segments of users who interact with your product.
2. Now list down L2 stakeholders — who would be impacted by the L1 stakeholder. As you map out stakeholder interactions, identify any secondary stakeholders who may be impacted by the actions of primary stakeholders. For example, if you’re building a marketplace for handmade goods, a primary stakeholder might be a seller who lists their products on the site. A secondary stakeholder might be a shipping provider who is impacted by the seller’s shipping choices.
3. The more levels you go, the more depth your ecosystem would have

Map out stakeholder interactions

1. Once you’ve identified all stakeholders, start to map out how they interact with each other. This includes both direct interactions (e.g. buyers and sellers making transactions) as well as indirect interactions (e.g. how a change in one stakeholder’s behavior might affect another stakeholder’s experience).
2. Identify the journey of the users and how each action from stakeholders can alter this journey. As you map out stakeholder interactions, think about how each stakeholder’s actions impact the user journey. This means considering the end-to-end experience of the user, from initial awareness of the product to post-purchase follow-up. Map out each step of the user journey and consider how each stakeholder impacts that journey.
3. The more breadth of the journey you can cover, the wider your ecosystem would be

Consider the dimensions of your ecosystem

Your ecosystem map is essentially a user story map that includes multiple dimensions. Consider each active component of your product as a dimension and map out how it interacts with each stakeholder. This will help you understand the complexity of your ecosystem and identify areas for improvement.

Continuously refine and update your ecosystem map

Your ecosystem map should be a living document that you update and refine over time. As you learn more about stakeholder interactions and the user journey, you’ll likely need to make changes to the map. Make sure to review and update your ecosystem map regularly to ensure it accurately reflects your product and its stakeholders.

Exercise: If there are 4 types of stakeholders and 5 products, how many dimensions does a product ecosystem map contain?

Assuming that each product interacts with all four types of stakeholders, the product ecosystem map would contain 20 dimensions. This is because there would be a separate dimension for each unique combination of product and stakeholder type (i.e. 5 products x 4 stakeholder types = 20 dimensions). However, if some products do not interact with certain types of stakeholders, then the number of dimensions would be reduced accordingly.