Structural Causes of Ecosystem Challenges

When EcoMap studied hundreds of ecosystems across the world, the most curious of our observations was the fact that they all faced remarkably similar challenges. Whether we were mapping a tech community or a corporate network, there were three core challenges that impeded the development or change of ecosystem: silos, misalignment, and momentum.

While at first this was puzzling, it began to make sense once we understood that it was the structure of ecosystems that were the root of these challenges. Ecosystems, as we know, are complex networks made up of independent assets and the relationships between them. Because of this system structure, ecosystems are incredibly resilient: in most ecosystems, the disappearance of a single asset or relationship will not cause the entire ecosystem to collapse, because the other nodes and edges “hold” the system in place. For the same reason, ecosystems are resistant to change: moving an entire interconnected system in a certain direction is much harder than moving an individual asset in that direction.

At the same time, the same structure that makes ecosystems resistant to change can also make them incredibly powerful as tools of change. This is the premise of Ecosystem-Led Development, a paradigm for developing effective solutions to complex, systems-level problems. Ecosystem-Led Development principles can be used by Economic Developers, Community Builders, Entrepreneur Support Organizations, Corporate Executives, Nonprofit Leaders, and beyond. If you want to learn more about it, you can read the whitepaper here (entirely free!)

Three separate articles examine each of the three most common ecosystem challenges: silos, misalignment, and sustaining momentum. If you want to learn mostly about how to overcome those challenges, you may want to skip to each article (linked below).

However, if you want to understand why the structure of ecosystems leads to these challenges, there are some complex but important core concepts to understand: the directionality of ecosystems and individual assets, the influence of assets, and the influence of relationships. Fair warning - the next 3 sections are pretty abstract, but really fun to dive into if you are interested in ecosystems.

The Directionality of Ecosystems & Assets

Directionality, in the simplest sense, refers to the direction that a specific ecosystem or asset is headed in. The hard part of this definition is specifying what ‘direction’ refers to, because not only is the “desired direction” entirely situational, but for any given asset or ecosystem, there are numerous axis of change on which ‘directionality’ can be measured. While it sounds complicated, we’re just formally defining a concept most people are familiar with - progress towards goals. Let’s illustrate with some examples, starting with Asset Directionality.

Imagine ReVamp is a hypothetical startup (Organization) who sells refurbished household goods online. For simplicity, let’s say ReVamp has three goals: be profitable, refurbish as many items as possible, and create well-paying jobs in their ecosystem. These goals create three Axes of Change (plural of axis, not 🪓) -  profitability, volume refurbished, and jobs created lu

These axes are simply lines, with the left side indicating the “negative” state, and the right side indicating the “positive” state. On the Profitability axis, movement towards the left would indicate the company is moving away from its goal of being profitable - perhaps it is losing too much money on buying items, or its refurbish process isn’t scaling over time. Movement towards the right indicates that the company is moving towards its goal of profitability - perhaps it developed new technology that cuts down on refurbishing costs. Let’s assume Revamp did just develop some new technology, and they are “heading towards profitability”. On the Profitability axis of change, Revamp is moving in the right direction (if that counts as a pun, it was intended)

While this seems good, profitability is only one of their three goals. Let’s say the new technology only works with larger items, such as furniture, and as a result they process fewer items in total. On the Volume Refurbished axis of change, the “negative” direction is refurbishing fewer items, and the “positive” direction is refurbishing more items. All else held equal, with this new tech ReVamp is headed in the “wrong direction” on their second axis of change. Finally, let’s say this technology reduces their need for labor and they cut employees to account for that. On their Jobs Created axis of change, ReVamp would be moving in the “wrong” direction as well.

(Important Note: With ReVamp’s new technology, you wouldn’t say that ReVamp is “refurbishing fewer products”, because they are continuing to refurbish, so the rote volume of products refurbished doesn’t decrease. However, you might say they are headed towards refurbishing fewer products, because the new technology reduces the rate of production.)

What direction is ReVamp headed in? It depends on what you’re measuring. One could say that on ⅔ metrics they are headed in the wrong direction, but “profitability” might be more important to them, because if they can’t reach profitability, they will cease to exist, and then they refurnish non furniture and create no jobs. You can tell the direction on any given axis of change, but as a whole, the picture becomes less clear.

If we can’t get a clear measure of overall directionality on individual assets, why do we care about it? Because the directionality of the ecosystem on any given access of change is determined by the direction of its assets.

We’ll continue with our example to examine Ecosystem Directionality. Unlike with specific assets, which can and do have defined goals, ecosystems themselves don’t have goals, since ecosystems are not autonomous or sentient. Rather, an ecosystems goals, if they exist, tend to be set by agreement among key assets in the ecosystem, or by an ecosystem-building organization (there are typically multiple sets of goals, which may or may not be complementary - we’ll discuss that in ecosystem Misalignment).

Regardless of this nuance, let’s say ReVamp is in Baltimore’s Tech Ecosystem, and the goal in Baltimore’s Tech Ecosystem is to grow the ecosystem, measured by number of startups that exit (acquisition or IPO) and the number of jobs created. Like with individual assets, these goals create two axes of change: Exit Volume and Jobs Created.

Clearly, ReVamp is not contributing to the “jobs created” metric - in fact, they are deducting from it. ReVamp is headed in the opposite direction that the ecosystem wants to go in, which is towards more jobs created. But what about Exit Volume? On the Exit Volume axis of change, the left is fewer startups exiting and the right is more startups exiting. ReVamps increased profitability probably makes them more likely to exit, so in this sense, ReVamp is headed in the same direction that the ecosystem wants to go in.

The aggregate of the directionality of individual assets determines the directionality of the ecosystem on each axis of change that might exist. However, it’s not as simple as “averaging” all individual asset directions. That’s because different assets have different degrees of influence, and direction can be counteracted based on relationships. Let’s take a look at both.

Influence of Assets

Some ecosystem assets are more influential than others. It’s easier to rip the bandaid off with that statement than to try and soften it - at the end of the day, certain People, Organizations, and Resources hold more “sway” within an ecosystem than others. However, notice that we did not say some assets are more important than others. These concepts are different, and too often conflated. Moreover, the idea of influence is more nuanced:

Influence in an ecosystem can mean a lot of things: a larger organization has more influence over the number of jobs created than a smaller organization, a person in a political office has more control over how resources are used (or created) than an intern, and a high-profile accelerator program has more influence over media attention paid to an ecosystem than a small local one. However, influence is relative to specific axis of change. A large organization may have more influence on the Jobs Created axis, but it might be so boring that it has zero influence on the Media Attention axis.

On any specific axis of change, assets with greater influence have a greater impact on the directionality of the ecosystem on that axis.

In some cases, this concept is straightforward. In a given ecosystem, let’s say there are only 3 Organizations: Aorg, Borg, and Corg. Aorg created 100 jobs, Borg cut 50 jobs, and Corg created 5 jobs. On the Jobs Created axis of change, Aorg was the most influential - even with Borgs 50 losses,  the net job gain is still 55 jobs, largely because of Aorg (although Corg contributed, it wasn’t very influential)

In other circumstances, influence is not as easy to measure. This typically occurs when progress (or lack of progress) on the Axis of Change is hard to quantify. On the “Number of Startups Exiting” axis of change, you can’t measure directionality just by the sheer number of startups that exit, because that indicates a point in time value rather than a trend.

Directionality refers to a trend, not a measurement. An ecosystem can have 5 startups exit, but if a high volume of startups begin to shut down because of lack of access to capital, then the ecosystem is likely headed in the wrongdirection on the “Startups Exiting” axis of change, even though the sum of startups that have exited have increased. In cases where progress along the Axis of Change is either qualitative, or it is measured by a variety of metrics, the best way to come up with a single metric to measure progress is by creating an Aggregated Measurement. This topic is discussed more in depth on page 37 of the Ecosystem-Led Development white paper.

So far, we’ve established that all assets in an ecosystem are moving along a variety of Axes of Change that are specific to their individual goals, and the directionality of an ecosystem on a given axis of change is determined by the direction of a all the assets moving along that axis, weighted by their degree of influence in the ecosystem. However, there is one more factor that needs to be considered when determining the overall directionality of an ecosystem on specific types of axis of change: the relationships between assets.

Influence of Relationships

Relationships in an ecosystem are the bonds that tie assets together, either in an informal or a formal way (If you haven’t read the article on Relationships: The Edges of an Ecosystem, you may want to pause and read that one first, since this concept relies heavily on the concepts presented in there).

For any given axis of change, there are certain types and categories of relationships between assets that will influence how the assets’ directionality affects the ecosystem’s directionality. For other types & categories of relationships, the relationship will have little to no influence on how the asset’s directionality impacts the ecosystem’s directionality. Sometimes, the relationship is directly influential, ****and other times, the relationship is indirectly influential. Sometimes, the impact on directionality is positive, and other times it is negative.

To understand this, we’ll need an example. Let’s continue with our “Jobs Created” axis of change. An asset contributes positively to the ecosystem’s direction of change if it creates more jobs, and it contributes negatively to the ecosystem’s direct of change if it creates fewer jobs. We’ll look at how different relationships could impact directionality, using two organization assets as examples - EcoMap and EcoSnap. For the sake of this example, EcoSnap is a very diverse organization offering many services.

Relationship 1: EcoMap and EcoSnap are marketing partners (promote eachother’s content)

• EcoMap creating more jobs is unlikely to influence EcoSnap’s creation of new jobs through the mechanism of this relationship
• This type of relationship has no influence on this axis of change, because of the nature of the relationship

Relationship 2: EcoMap purchases flyer design services from EcoSnap

• EcoMap creating more jobs is also unlikely to influence EcoSnap’s creation of new jobs through this relationship, because EcoMap adding team members likely doesn’t increase our demand for flyer designs
• This type of relationship has no influence on this axis of change, because the mechanism of directionality for each asset does not translate over this type of relationship

Relationship 3: EcoMap purchases employee benefits from EcoSnap

• EcoMap creating more jobs may influence EcoSnap’s creation of new jobs through this relationship, because EcoMap’s increase in team members means more revenue to EcoSnap, which they may use to increase the number of jobs at EcoSnap
• This type of relationship has an indirect influence on this axis of change, because the direction of one asset has an indirect (and here, not guaranteed) influence on the asset of another along this axis of change

Relationship 4: EcoMap has a 1-1 hiring agreement with EcoSnap (for every employee EcoMap hires, EcoSnap must hire an employee as well)

• EcoMap creating more jobs will influence EcoSnap creating more jobs
• This type of relationship has a direct influence on this axis of change, in a positive direction

Relationship 5: EcoMap and EcoSnap are competitors who hire from the same, limited pool of low-volume machine-learning AI talent and these are the only jobs they each hire for

• EcoMap creating more jobs will influence EcoSnap’s creation of jobs, because of EcoMap hires someone, then EcoSnap cannot hire that person
• This type of relationship has a direct influence on this axis of change, in a negative direction

We know that Relationships 4 & 5 are a bit ridiculous, but the point is the same - the impact that EcoMap’s creation of jobs has on EcoSnap’s creation of jobs depends on the nature of the relationship between them.

Here’s the whammy conclusion: The impact of one asset’s directionality on another asset’s directionality (and therefore the direction of the ecosystem as a whole) depends on whether or not the axis of change can be influenced by the type of relationship between them; then whether it is directly or indirectly influenced; and finally whether it is positively or negatively influenced.

There are a variety of rules that can be applied to determine which categories and types of relationships will have an impact based on the type of axis of change, but those mechanisms are far beyond the scope of this article. In general, the best way to understand this phenomena is on a case-by-case basis, and the important thing to know is that there are some cases where the relationships between assets will influence the direction of an ecosystem, beyond the directionality of the assets independently.

Phew - if you made it this far, a pat on the back! Now, when you read the articles about common challenges within ecosystems, you’ll better understand why these challenges arise. Let’s hop to them, starting with Silos.

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