Identifying Technologies That Make Data a Critical Organizational Asset

Identifying Technologies That Make Data a Critical Organizational Asset

Hey there! Data is becoming an increasingly valuable asset for companies in today’s digitally-driven world. Organizations across all industries are realizing the power of data in providing actionable and data-driven insights to improve decision-making, unlock new revenue opportunities, and gain a competitive edge.

But harnessing the true potential of data requires identifying and leveraging the right technologies that can capture, process, analyze and help make sense of colossal amounts of data. When combined together, technologies such as machine learning, cloud computing, blockchain and the Internet of Things can transform disjointed data into one of the most critical assets for an organization’s success.

Let’s take a closer look at these key technologies and how they converge to make data a pivotal organizational asset.

The Role of Data as an Organizational Asset

Data allows organizations to base strategies and decisions on hard facts rather than hunches. With data analytics, companies can identify profitable business areas, understand customer pain points, optimize operations and processes, minimize risks, and detect market trends and opportunities faster than competitors.

In today’s uncertain economic environments, data-driven organizations are 25% more profitable than competitors as they can predict changes in demand, adapt quickly to market disruptions, and allocate resources optimally.

But data is also a vulnerable asset. If customer data gets hacked or critical business data is lost, it can cost companies millions in lost revenue opportunities and recovery costs. Implementing robust data security and governance practices is key to realizing the value of data.

Key Technologies Making Data More Valuable

Machine Learning and AI

Machine learning and artificial intelligence help uncover patterns, correlations and insights within massive, fast-moving and unstructured data that is impossible for humans to analyze manually.

By processing billions of data points across documents, images, videos, and transactional data, machine learning models can automate essential business processes, personalize customer experiences, and improve decision accuracy by up to 50%.

For example, AI is helping Unilever analyze real-time social media data across over 5 million customer touch points to understand changing customer preferences and rapidly launch new products and services. Amazon uses machine learning across its retail, supply chain and logistics operations to deliver relevant product recommendations, optimize inventory levels, and enable faster deliveries to customers.

The convergence of greater computing power, the availability of big data, and progress in machine learning algorithms means AI adoption will grow at an accelerated pace – delivering over $500 billion in productivity improvements by 2024.

Cloud Computing

The cloud allows businesses to store and access massive amounts of data securely from anywhere. Cloud’s scalable infrastructure eliminates the need for expensive on-premise data centers and enables real-time collaboration across teams and geographies.

Pharmaceutical company Medable uses cloud computing to analyze terabytes of decentralized clinical trial data in real-time, speeding up new drug development. The flexible infrastructure ensures swift deployment of new algorithms as research needs change.

With public cloud computing spend expected to grow at 16% annually over the next few years, the cloud will be an instrumental foundation for rapidly unlocking value from data.


Blockchain establishes trust in data sharing across a business network through decentralization, transparency and encryption. All participants in a blockchain network can view transactions but unauthorized changes are almost impossible as manipulation would require altering records across several distributed servers simultaneously.

Walmart used blockchain to improve food traceability, enable quicker food recalls and reduce annual tracing costs by $20 million in just two years. Customers can also scan products to trace origins down to the farm source.

As an immutable record of asset and transaction data flows, blockchain data integrity capabilities ensure critical business data remains secure. This is fueling rapid growth in global blockchain spend which IDC predicts will reach nearly $18 billion by 2024.

Internet of Things (IoT)

The Internet of Things (IoT) allows physical devices to communicate real-time performance data and alerts that can help optimize business processes or inform new products and services.

From tracking vehicle fleets, to monitoring the flow of materials in factories, to improving energy efficiency in buildings, the IoT market is accelerating exponentially – Mordor Intelligence puts the growth at around 26% CAGR with over 30 billion active device connections globally by 2025.

By merging IoT data with transactional and operational data, organizations can enhance visibility across supply chains, predict failures in advance, and design better customer experiences.

Benefits of Combining These Technologies

While each technology has immense potential individually, combining AI, cloud, blockchain and IoT amplifies the value exponentially:

IoT provides the streams of real-time data that cloud computing and data warehousing architecture cost-effectively store and scale. Sophisticated AI algorithms then derive critical insights from the voluminous data. And blockchain establishes robust data provenance across ecosystems.

Together, these technologies unlock transformational organizational capabilities:

  • Accurately anticipate emerging risks – analyze thousands of weak signals across news feeds, financial reports and production databases using NLP algorithms to model and predict risk likelihood.
  • Personalize end-to-end CX rapidly – collect and centralize real-time behavioral data from web, mobile, IoT devices; leverage recommendation engines to predict needs and preference changes; customize interactions accordingly.
  • Continuously optimize supply chain – apply prescriptive analytics models to transactional data, logistics data and external signals from weather or traffic feeds to dynamically reroute shipments in cost and time-efficient routes.
  • Co-innovate with partners securely – share confidential design specifications with hardware and software partners to collaborate on connected products leveraging blockchain’s tamper-proof data sharing capabilities.

How Does AI Technology Contribute to Data as a Critical Organizational Asset?

AI technology plays a crucial role in transforming data into a valuable organizational asset. By employing advanced analytics and automation, AI wealth creation blueprint can help businesses gain valuable insights and make data-driven decisions. This, in turn, enhances operational efficiency and drives innovation, giving organizations a competitive edge in the market.

Critical Capabilities Required

Realizing the full potential of data requires four key capabilities:

First, build strong data literacy skills across the organization – from executives setting data strategies to frontline staff collecting and acting on insights.

Next, implement agile development workflows to translate emerging insights into new features and products faster.

Then, put change management practices in place as AI/ML will redefine job scopes. Reskill employees and augment capabilities to enable human-machine collaboration.

Finally, secure executive sponsorship and data leadership to define and fund data priorities while also governing through ethical frameworks.

Key Recommendations and Conclusion

The message is clear – data underpins organizational success in the digital age. To stay competitive, companies must urgently identify and adopt technologies that help manage data growth while simultaneously maximizing its value.

Leverage cloud economics to store swelling data volumes cost-effectively. Implement AI/ML data pipelines to drive efficiency through automation and analytics. Utilize blockchain to enable trusted data sharing with partners. And blend in IoT data flows to optimize decisions and innovate intelligently.

Just as critical – invest in continuous capability building to develop, monitor and govern data-driven technologies responsibly.

By combining, analyzing and strategically acting on data, companies can unlock transformational value – from boosting productivity to making processes leaner to informing new revenue models. The possibilities are endless.

The future will be defined by organizations who recognize data as the most valuable digital asset and actively adopt technologies that amplify its potential. The time to act is now!

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