Strategies for Monetizing Data 2022 and Beyond

Strategies for Monetizing Data 2022 and Beyond

The Data Revolution is here and it has brought with itself a plethora of opportunities for Telco’s and operators to tap. One of the brightest opportunities in Telco is currently present in the monetization of data. With B2B and B2C data needs reaching all time high levels, the monetization strategies for this year and the period to come need to be both seamless and flawless. Seamless in the sense that offers should be incorporated for use across multiple platforms, and flawless in the sense that there should be no room for error now.

With 2022 almost halfway through, it is time that we talked about the data monetization strategies for this year and how they would still be impacting the process beyond this year.

In this article, we take a look at strategies for monetizing data. These strategies will ensure that data is monetized and improved for future purposes. The data monetization techniques you use here can be incorporated in the corporate world.

Data Monetization Strategies for 2022

The need for data is more than it ever was before. Authentic researchers have reported that the market size for the amount of data is on the rise and will soon reach an unprecedented stage of glory. The market size of data is set to exceed 180 zettabytes by the end of 2025, which is an insane growth curve considering that the size in 2015 was less than 10 zettabytes, to be exact.

What this age of data has meant is that the data culture for every organization needs to be revamped. Almost any company now has the potential to be a data company and eventually help in catapulting this data revolution forward. In research conducted recently on the niche of Big Data and Analytics, more than 85 per cent of all respondents interviewed reported that their specific firms have started the initiatives towards a data driven culture. But, when asked about success in achieving the culture, only 37 per cent were able to reply in the affirmative. The results from this strategy can be interpreted to define the direction we are headed to.

Internal Strategies for Data Monetization

A key protagonist in this move towards data monetization and efficiency are the Chief Data Officers in every organization. These Chief Data Officers have the responsibility for drafting the data culture for their respective organizations. When asked about the role of the Data Officers, 49 per cent of all people interviewed believed that they could lead the initiative forward.

According to Jeremy Radar the key point in achieving a futuristic data model that can monetize your data is to rethink your data strategy. A perfect example of this could be the RELX group, which revitalized its data strategy through the use of a 4-step model.

  • Deep understanding of customers
  • Leading content and data sets
  • Sophisticated Analysis
  • Power data management technology

Other than taking inspiration from the growth model of others, internal steps for data monetization can be achieved through this 3-step approach mentioned in Eckerson Report. Once you have realized the need for these 3-steps, you can move on to achieving them;

  1. Deliver Concrete Data Analytics: Employees within your organizations need to be presented with effective data analytics to help them optimize processes, make better decisions and reduce costs.
  2. Enrich Existing Products: Organizations can make the move internally by enriching their existing products with the use of data analytics and customer retention methods.
  3. Sell Data Products: The data products can eventually be sold off to customers to create a whole new product line or portfolio generating revenue.

What is needed for Succeeding at Data Monetization?

To succeed at achieving an extensive data monetization model, organizations need to do the following;

  • Vision: The company’s vision is set by executives who share the vision of correctly monetizing data and can allocate all resources include time, trusted workforce and energy towards execution.
  • Team: Data monetization can be done only through a close-knit bond between data architects, product manager, application developers, analytics specialists and marketing and sales professionals for turning data into dollars.
  • Data: For data to be monetized, it not only needs to be voluminous in size and nature but also has to be clean and consistent.
  • Analytics: Analytics provide the eventual meaning to the data through summarizations, models, calculations and categorizations. Data is way more valuable once it is analyzed.
  • Processes: Data should go through development processes to be tailored according to market preferences.
  • Delivery: The delivery system should be flawless as it has the responsibility of distributing the analytics to users.

Data Monetization While Going Into the Future

With our expected data creation and consumption expected to increase in the future there is no reason why we shouldn’t be incorporating strategies as of now. The problem in the future for data management and monetization would arise regarding the handling of data that is coming in from our use of IoT. Smart homes and smart cars are at an increase as they provide feasibility to the users, but the amount of data being transferred in these systems of the future is insane.

We can gauge the high impact of data from smart cars by evaluating Intel’s acquisition of Mobileye NV, which makes sensors and cameras for smarter cars and autonomous vehicles. The average autonomous car has the ability to generate roughly around 4 terabytes of data on a daily basis. This amount is equivalent to the data being generated by 3,000 people in a day. Intel’s data monetization strategies for the future would now be focused on utilizing these services and data analytics to create value for the customer. An estimate from a source puts the value of data created and collected by all cars to be valued around $450 – $750 billion by the end of 2030.

The Future of Data Strategies for Organizations Dealing With Large Data Figures

With data numbers expected to go above what we have currently the ideal example for the future would be that of a company looking to form a strategy with large data figures. An industry the figures could be applicable for is the health industry. Precision car is something patients have started opting for, but the process still lags far behind in efficiency. Healthcare institutions can implement the All-in-One-Day Goal that would prioritize things from the Patient to the Doctor through the use of effective technology.

Patients could get precision care in one day and would be assigned precision medicine from the doctor based on results from their tissue image analysis. The doctors would then recommend them the best treatment option based on data coming from across institutions. All of this would phase out within 1 day and would eventually enable the all-in-one-day goal through mutual cooperation and augmentation from technology.

Challenges and Solutions

The challenges that could plague this method and its applicability are;

  • Size: Raw data sets can be too large and impractical to share.
  • Speed: Critical treatments and diagnosis can usually take more than a couple of weeks
  • Secure Sharing: Patient privacy is difficult to protect
  • Scalability: Genomic sequencing outpaces the capabilities of current architectures

Conclusion to Strategies for Monetizing Data 2022 and Beyond

The solution to this problem lies in Federated Cloud Orchestration and Acceleration of Imaging Workflows. This would increase runtime and keep data stacked at institutions and hospitals. However, the need for data monetization is what would streamline the process and make the giant leap into the future more streamlined and coherent. Contact us for Strategies for Monetizing Data 2022 and Beyond.

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