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How to Make Good Money from Your Company’s Data?



Here are some inspirational ways to make good money from your company’s data to enhance revenue

You can make good money from your company’s data as they have more information than they know what to do once they begin strategically storing, evaluating, and acting on insights from data. The simple solution that many businesses have discovered is to sell it and benefit their company data exclusively.

The 4th industrial revolution’s primary raw material is data, and to make money from data has grown significantly as business potential. Although data has always naturally developed as a byproduct of economic and commercial activity. 90% of all Internet data has been created. Only the so-called FAANG corporations (Facebook, Apple, Amazon, Netflix, and Google) were in a position to benefit from the enormous volumes of data gathered for more than ten years. Data is the main product and the foundation of these businesses’ value proposition, thus they moved rapidly to invest in AI teams, servers, networks, and other things.


Four inspirational ways to make money from your company’s data-

1. Educating yourself about Data Usage: Knowing what data you already have is the first step in learning how to use it. Make a list of all of your business operations to identify those that are organically producing data. What information does the business record and log? What do we not log, and why? What data are we discarding that we ought to be preserving? Once you have an inventory of your data, educate yourself on data utilization by observing how other businesses store and utilize data of a similar nature to enhance their operational processes.

How, for instance, are quality control records used by other businesses? Do they create machine learning algorithms to determine the most effective sales pitches and then educate their representatives accordingly? What about data on the logistics and supply chain? Are other businesses use that data to develop optimization tools that more efficiently route inventory?

2. Copy & Paste Methodology: Check out how the newest digital firms are making use of data once you have an understanding of how businesses are using it. These businesses can assist leaders in understanding how those who use data as their primary business are monetizing it, providing a cheat sheet for data usage.

To learn more about the innovations taking place in these businesses, think about entering into proof-of-concept contracts with seed-stage entrepreneurs or establishing data-sharing agreements with them. Sponsor corporate hackathons to identify data-centric AI solutions for your ongoing operational difficulties and to draw in IT talent.

To find out about the newest products and cutting-edge concepts, browse the news sources that company owners and developer influencers read, such as Hacker News and ML Substacks.

See whether you can apply these applications to your company by taking a look at them. Consider ways to exploit disruptive technologies for your company’s purposes rather than ignoring them.

3. Buy, do not Build: SaaS solutions currently exist for many of the issues that occur in collecting and managing data. Large organizations frequently develop their own data management solutions, which results in clumsy, slow infrastructure that doesn’t advance with other technology. Additionally, when new businesses try to develop these tools internally, they extend their time to market and run the danger of losing their first-mover advantage.

 Avoid deluding yourself into believing that your use case is so unique that it necessitates a unique internal infrastructure. Building in-house data infrastructure tools take months, it costs money to maintain them, and the outcomes are frequently inferior to those of a product that is currently available on the market.

When it’s feasible, you should purchase rather than create the tools needed to organize and handle data. Don’t rebuild the tools in-house if they are not essential to your firm. The creation of your machine learning model will be slowed down as a result, and that is the final output that will help you stay competitive and save money.

4. Start building your data channel: Large-scale data collection inside routine business operations can assist businesses in starting to create a structural data moat that can be leveraged for higher-value-generating activities. The data gives you a competitive edge because eventually, this moat can grow to be too broad for rival businesses to traverse.

Consider the tale of Rockefeller and the waste products from crude oil. The majority of refinery owners considered the wasteful byproducts of turning crude oil into kerosene and threw them away. However, Rockefeller recognized its worth and gathered the paraffin wax and petroleum jelly to sell to candle makers and medical supply businesses, respectively.

Be like Rockefeller. Save your data so you can later sell it. Just because it isn’t currently your main product doesn’t mean you should disregard it as a useless byproduct.

The post How to Make Good Money from Your Company’s Data? appeared first on Analytics Insight.

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