We hear [data](https://inleo.io/@leoglossary/leoglossary-data) is the new [oil](https://inleo.io/@leoglossary/leoglossary-oil).


This is not exactly accurate but it does paint a close enough picture to work from.  It is from this point that we can start to follow the process that is unfolding before our eyes and where it might go.


The flywheel is a topic of discussion since [digital](https://inleo.io/@leoglossary/leoglossary-digital) platforms are so valuable.  Nothing epitomizes this better than [Amazon](https://inleo.io/@leoglossary/leoglossary-amazon-company).  It is the best example of a [company](https://inleo.io/@leoglossary/leoglossary-company-business) that, over the course of a few decades kept expanding the flywheel.  This now shows up in the company numbers.


Of course, Amazon, like most other entities of this nature, rely heavily on data.  They are able to generate, filter, and apply it.  Here is where the oil analogy requires some "cleaning up".  More data is simply not the answer.  To be effective, it has to be clean along with aptly applied.


A lot is written and discussed about how data can help companies kick off a flywheel.  However, what about data itself as a flywheel?


This is what we will dive into with this article.

https://cbi-blog.s3.amazonaws.com/blog/wp-content/uploads/2017/06/cb-insights-data-technology.png

<center> [Source](https://www.cbinsights.com/research/team-blog/data-network-effects/) </center>


# The Data Flywheel Is Important For Web3


To start the conversation, it is best to reframe data. 


Instead of looking at it as a component that allows for the creation or better management of products, perhaps it is best to look at data as its own product.


By reframing it in this manner, we can then start to apply some of the same principles of network [science](https://inleo.io/@leoglossary/leoglossary-science) to data as everything else.  Here is where we could [gain](https://inleo.io/@leoglossary/leoglossary-gain) valuable insight into the strategies that are going to be employed.


Web3 opens up news doors for the entire [world](https://inleo.io/@leoglossary/leoglossary-world).  From a data perspective, the most valuable innovation is the removing of friction.  Here is where we see the first major insight when reframed.


What would happen if we looked at a company and realize it removed many areas of friction regarding its product?  Perhaps it was able to eliminate many steps from the supply chain while also simplifying [manufacturing](https://inleo.io/@leoglossary/leoglossary-manufacturing).  In addition, it developed a completely new distribution model that got the products in the hands of [customers](https://inleo.io/@leoglossary/leoglossary-customer) in half the time.


If we had a company like this, it would be the darling of [Wall Street](https://inleo.io/@leoglossary/leoglossary-wall-street).  It is likely that the competitors in that industry would simply be overwhelmed.  


That is exactly what Web3 does.  By replacing the client-server architecture, a major point of friction is eliminated.  Certainly, [applications](https://inleo.io/@leoglossary/leoglossary-application) will still have this to a large degree with much of the data but a fair portion finds it way to [blockchain](https://inleo.io/@leoglossary/blockchain).


Here is the point where we can see the potential for massive [power](https://inleo.io/@leoglossary/leoglossary-power) gains.  When it comes to [Web 2.0](https://inleo.io/@leoglossary/leoglossary-web-2-0), there is no comparison.  At the moment, Web 2.0 is light years ahead.  The fact it had a couple decades of data generation certainly helps.


That said, we have to look at the [layers](https://inleo.io/@leoglossary/leoglossary-layer-insurance) of friction.  Just like the financial system, we see a host of [intermediaries](https://inleo.io/@leoglossary/leoglossary-intermediaries-financial), all who restrict the [flow](https://inleo.io/@leoglossary/leoglossary-flow) of data.


Web3 solves this.


## Customer-Centric


One of the main premises of [Jeff Bezos](https://inleo.io/@leoglossary/leoglossary-jeff-bezos) strategy with Amazon is to be customer-centric.  That is the core of the flywheel that was created.


Everything is structured to drive value to customers.  This is achieved in many different ways but it becomes evident when one looks at the different facets of the [business](https://inleo.io/@leoglossary/leoglossary-business).


What is data tied to Web3 follows a similar pattern?


Instead of dealing with one company, we are dealing with a significant portion of the [Internet](https://inleo.io/@leoglossary/leoglossary-internet).  The customers, in this instance, would be any stakeholder in a platform that uses said data.  That gets to be a rather large number.


The design of Web 3 means that most things undertaken feed more value into the data.  This could be new compression techniques, faster communication systems, more versatile [databases](https://inleo.io/@leoglossary/leoglossary-database), or massive expansion of [smart contracts](https://inleo.io/@leoglossary/leoglossary-smart-contract) running operations.


Like Amazon, each builds upon itself.  We could think of this as a large digital platform, with each incremental step in value spread to all participants.


We each new addition, let's call it a division, the value derived is fed into the data-centric [economy](https://inleo.io/@leoglossary/leoglossary-economy).  Of course, data not only has to be generated, it requires being cleaned up, sorted, and put in useful form.  As this happens, it multiplies since we are dealing with open architecture.


## AI Driven


Most flywheels incorporate the idea of [artificial intelligence](https://inleo.io/@leoglossary/leoglossary-artificial-intelligence) driving it.  


Using Amazon, we can see the many ways that it uses [algorithms](https://inleo.io/@leoglossary/leoglossary-algorithm) and [machine learning](https://inleo.io/@leoglossary/leoglossary-machine-learning) models to cater to its users.  This applies across the entire [ecosystem](https://inleo.io/@leoglossary/leoglossary-ecosystem-digital).


Something interesting is starting to arise.


With the introduction of [chatbots](https://inleo.io/@leoglossary/leoglossary-chatbot) and other forms of generative learning, we are see the example of where the data is operating on its own flywheel.  These products are taking off and, if we look at them collectively, we see massive gains happening in a rather short period of time.


Of course, for the most part, we are dealing with closed systems.  The corporate concept is heavily in play with massive company's using their might.  Fortunately, the [open source](https://inleo.io/@leoglossary/leoglossary-open-source) community is growing, offering the potential it will outpace any of the corporate giants.


The advantage the open source has is a lack of friction.  Anyone can enter with the idea of creating a model to cater to individual needs.  This means a lot more innovation is taking place in this realm.  [ChatGPT](https://inleo.io/@leoglossary/leoglossary-chatgpt) might be able to answer some legal questions but it will not rival a bot that was trained specifically on the laws and legal practices in a particular province or state.


What part does Web3 play into this?


At this point, not very much since it is hard to find.  However, over time, as the data grows in this realm, it will be accessed repeatedly.  


This has huge implication if we consider the fact that we are racing even deeper into the information economy.  That is what a large portion of the developed economies are built upon.  It will only increase as sensors are placed into everything and algorithms start to parse the data, charting specific courses of action.


The data flywheel means that we can expect serious [economic](https://inleo.io/@leoglossary/leoglossary-economic) growth to occur.  Obviously, this is following the [trend](https://inleo.io/@leoglossary/leoglossary-trend-finance) that we saw with some companies, especially those in the [technology](https://inleo.io/@leoglossary/leoglossary-technology) realm.


It is an exponentiality that we are referring to.


With Web3, we can easily see how data reproduces.  To start, the open nature means it is repurposed.  Here is the first major change.  Anyone can take the same data and reuse it.  With Facebook's database, only Meta has access unless they decide to [sell](https://inleo.io/@leoglossary/leoglossary-sell) the data to someone else.


Another fact is that, as data is created and processed, more is generated.  A report on the data pulled from a blockchain that is posted on the blockchain ends up providing more data.


This then shows up across a number of interfaces, each which is free to utilize the data as it sees fit. 


Rinse and repeat.


When enough pieces are in place, we could see a flywheel effect kicking off with data.  It is, after all, a product itself these days.


____


<center> [What Is Hive](https://inleo.io/@leoglossary/leoglossary-what-is-hive) </center>






Posted Using [InLeo Alpha](https://inleo.io/@taskmaster4450/the-data-flywheel-and-the-importance-for-web3)