Network Chain — Infomediary, Edge Interactions, and Data+ Network Effects


In my latest post, I introduced the idea of a “Network Chain.” After writing that post, I came across John Hagel’s most recent post (a must read), which energized me to buy (via Amazon) a twenty-year-old book called Net Worth. While ordering the book, I couldn’t stop myself from adding The Only Sustainable Edge to my cart. If you’re like me and want to explore the core of business thinking, these two books must be part of your intellectual arsenal.


I spent the past two months exploring the knowledge embedded within these two treasures and decided to extract a few gems (teaching and learned lessons) to enrich the Network Chain. To do so I obtained John’s blessing (via Twitter).


Into the enrichment process


Enrichment starts by performing a complex genome engineering, by extracting genes from Net Worth (Infomediary) and The Only Sustainable Edge, along with conducting a slight modification to their DNA’s configuration and then inserting the altered DNAs into our host organism (James Currier’s Network Effect’s Map). The insertion will target a site-specific location known as the Data Network Effect. Note: You must pilgrimage to Currier’s temple to reinforce your entrepreneurship’s spirit with high-quality and actionable knowledge.



Net Worth introduced the Infomediary concept as a full-fledged revolutionary business model. Here, I will try to present a lighter version of Infomediary as a function/profession. In the coming decade, Infomediary will resemble the form of apps backed by intelligent algorithms — thanks to the interplay between the biotech revolution and technological revolution. Although such Algorithmic Infomediary (“AIn”) is not the mandate of this post, below is a glimpse of how this might look like (AIn in hypothetical action).


Hypothetical Example — Kindle+


Kindle+ will be empowered with Algorithmic Infomediary, supported with advanced facial recognition software, which can trace your eyes along with every single paragraph, line, and word, and record your facial expressions as well as detect and analyze the movement of every tiny tissue beneath your skin. The AIn can detect the nerve impulses and muscle contractions affecting the size of your pupil with every line you read.


The AIn will provide you with a detailed analysis in an absolute percentage of your understanding based on the level of your emotional and intellectual engagement with the book. The AIn can then reproduce the book (e.g., with only the paragraphs that scored above 80% of passionate engagement.) Next time, when Amazon recommends a book, you will not have a choice but to buy it, since the recommendation will be derived from your inner and impartial emotions.


Amazon’s AIn will redefine the notion “like-minded.” You will be matched with an accurate percentage. For example, you can choose to be matched with someone who read the same book and scored 87% rather than 85% on the like-minded dashboard. I will stop here, but if you want to be enlightened about the future, read the 21 Lessons for the 21 Century by Yuval Harari.


In “Network Chain,” I wanted to draw the attention that in the core of every network effect, there is a vibrant network chain with a uniquely chained (DNA) configuration between the network’s features. With the above genome engineering, I am hoping to introduce a new (mutated) network effect — DATA+ Network Effects — by editing such a configuration. The added plus on the word (i.e., DATA+) resembles the introduction “Infomediary as a function/profession.”


DATA+ Network Effects generates a virtuous cycle of relevant, up-to-date, personalized, and curated data (choices and solutions). The Infomediary will be empowered with a wealth of actionable information that will enable him/her to zero-in between supply and demand.



Data Network Effects, as defined in the NFX’s Network Effects Manual, happens “when a product’s value increases with more data, and when additional usage of that product yields data.”


Data+ Network Effects, as I humbly envision it, occurs when the core value unit, core interaction, and edge interaction can be leveraged with additional relevant data via the help of a trusted Infomediary, and when additional usage of the core value unit and additional curated interactions (core and edge) yields additional relevant data that can unlock untapped potentials.


In economic terms, the Data Network Effect can reduce the cost of core interaction, allowing the value chain to squeeze an existing margin. While the Data+ Network Effects reduces the cost of interactions associated with both core and edge, at the same time, it leverages the chances of materializing untapped potential within future interactions, enabling the value chain to proliferate the emerging margins. If you wish to know more about the core value unit and core interaction, click on this post by Sangeet Paul Choudary.



An essential distinction between both interactions (i.e., core and edge) is that the core interaction is about a current job to be done, whereas the edge interaction is a serendipitous opportunity that might result from future interactions within a relevant ecosystem or the intersection between ecosystems.


The Only Sustainable Edge seeded and nurtured (in my brain) the edge interaction’s thinking within the context of platform thinking. The edge interaction that I am introducing here differs slightly from John’s theory on one front. John theory is based on a vital fundamental: opportunities rest within edges, and to excavate such opportunities, you need to experiment within these edges to avoid invoking your (corporate) immune system. The more an edge proves itself, the more resources (from your value chain) must be mobilized to support it, and when the edge becomes dominant enough, it might be your future core. On the other hand, my humble view regarding edge interaction is taking place within the network chain (i.e., experimentation within the edge of the network chain and not the value chain). This does not require the redeployment of proprietary resources (only orchestrating the ecosystems’ resources), and at the same time, it is very distanced from the immune system within the value chain.


The mandate of the edge interaction within the network chain is not to transfer the capabilities of the existing core into a new reality (i.e., not to replace a core with a new edge). The direct mandate of the edge interaction is to create new channels that can enhance the totality of our experiences. These edges might lead the relevant parties to create a new standalone reality.


On the surface, enhancing the totality of our experience in the platform era might look like this. An example of this is me traveling on a short vacation.



In other words, the invisible touch-points between these platform-based businesses can be viewed as the digital DNA of the totality of our experiences.



Enhancing the totality of our experiences in terms of stronger connectivity and efficient movement between these touchpoints is just a surface-level understanding. What I learned from Net Worth illuminated my thinking to enrich the Network Chain on a more profound level. Thanks to John, I learned that to enrich the totality of experiences, we must explore underneath such surface-level act of efficient connectivity between adjacent jobs to be done. If we truly want to enrich the totality of our experiences, we must understand and select the distinct businesses that nurture such adjacent jobs to be done along with the fundamental economic drivers underneath each of them (i.e., scale, speed, scope.)


Let us collide the above concepts into the below examples (i.e., Network Chain, Infomediary, Edge Interaction, and Data+ Network Effects.)



The above illustration resembles me performing three different jobs to be done (being a producer of values) by using the services of three different platforms that provide me with three different services that are underpinned by three different economic rationales and by leveraging their different network effects types.



The beauty of the edge interaction concept is that a platform can initiate multiple edges as experimentation in order to allow its users to interact within multiple ecosystems.



The ability to align different adjacent jobs to be done by leveraging their DATA+ Network Effects is the key differentiator in determining (1) which edges to maintain and (2) which edges to shut down.


Once a platform built a robust alignment between adjacent jobs to be done, the next step is to reinforce the connectivity between these edges (collaborative edges): I call it “Leveraged Edges” by introducing John Hagel’s Infomediary concept (the genetically modified gene).



Tightly integrated leveraged edges placed within collaborative edges and surrounded by Data+ Network Effects can help us to move faster and smarter: the integration between different jobs to be done can formulate an enriched set of experiences as a force of movable flow of knowledge creation, by obliterating the notional boundaries between the intersecting ecosystems.


When the totality experiences, which yield from participating within different platforms, get aligned and congruent with the right economic rationales as well as the right network effects, the distance between you and your objectives diminishes.


Below is a simple illustration to help in visualizing how the Data+ Network Effects can spark and amplify multiple virtuous cycles.



I will stop here, but I promise you that I will consolidate all the above stated concepts along with my previous post “Network Chain” into my upcoming post as one comprehensive example.


While I was ending this post, I received an email from Audible an Amazon company. Please look at the below screenshot: yes, it is happening (the seeds of Infomediary), not exactly as theorized by John Hagel, but this is just the beginning.



One more thing, if you doubt the rationale behind the platform-based businesses being able to operate within a boundary-less ecosystems, I invite you to play this video: Dropbox recent evolvement — coordination with other applications and businesses.


A special thanks to John Hagel, James Currier, John Seely Brown (co-author, The Only Sustainable Edge), and Marc Singer (co-author of Net Worth).

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