What is data, and what makes it valuable? 

We frequently hear about how data volume is growing massively. Data has a value, but what does it take to realize this value?

Technology is advancing at breakneck speed as social and economic activities are increasingly taking place on the Internet. At the same time, advances in digital technology continue to reduce the cost of collecting, storing and processing data. The result is enormous volumes of data generated at an ever-increasing pace.  

The value of data

When discussing the value of a product or service, we usually think of its transaction value if sold in a market. However, we need to think differently about the value of data. Usually, value doesn’t exist in the data itself, but in how it is leveraged as an input factor for optimization, renewal and innovation. Thus, the value of data is measured by the financial or operational gains businesses achieve from utilizing it. As an input factor in production, data is used to provide better information and a more robust basis of decision-making for a more efficient allocation of resources. 

Data forms a basis for innovation and growth in several ways

Enhanced business insights from data analytics can provide a basis for innovation and growth in several areas, both in new companies being founded and individual companies or entire sectors being transformed. We have already seen quite a few examples of how digitalization drastically changes our everyday lives, and this change happens quickly!

Optimize your organizational operations

Using data to realize value by optimizing existing business operations is typically step number one in creating value from data. This may include making the organizational model more efficient, implementing more streamlined lines of communication, and elevating the quality of products and services.

Six mechanisms have been identified that – through intelligence and insights from collected data – contribute to improving organizational operations and add value to society. Those six mechanisms are:  

• Customer knowledge
• Value chain management
• Quality management
• Risk management
• Results management
• Fraud prevention

Achieve organizational renewal

Access to and utilization of data can impact an organization’s ability to renew itself. By renewal, I mean applying new methodologies, such as developing a new organizational structure, new communication channels, or new products and services. 

While optimization provides a more or less immediate impact in terms of increased productivity, renewal is key to keeping the business relevant and ensuring the realization of gains in the long term.

Create powerful business partnerships

Overlapping sectors are a current megatrend, driven by the rise of digitalization and the rise of data. Often, data from one sector is just as useful in another. This brings about new and efficient partnerships or causes subefficient companies to be outmaneuvered by better-positioned companies from other sectors.

From data to wisdom – The DIKW Pyramid (Data, Information, Knowledge, Wisdom)

The traditional DIKW Pyramid is a hierarchical pyramid where data sits at the bottom and wisdom at the top. This seems logical, but it is also one of the main criticisms against the model. Therefore, a fifth layer has been added, the semantic metadata, to describe the meaning of the data entities. This layer is essential when it comes to data governance and understanding of the meaning of the data. 

Illustration: DIKW Pyramid extended with semantic metadata layer (Epistematica.com) 

Data starts creating value when you can make stronger decisions based on it. This means that having large, many or comprehensive datasets is not sufficient. They need to be interconnected, nurtured, made available and put to work. Data from different sources is fundamental to a significant part of the value creation taking place in large and small businesses. 

Data comprises all types of digitally stored information, such as transactions, time series, map data, positional data, journals, captured experiential data, real-time data that, for instance, shows the live location of ships, containers, cars, and so on. Data is structured, semi-structured and, increasingly, unstructured. Most data needs to be acquired and processed with a goal and context in mind, making it information. Data gets its meaning after processing with a purpose, an end goal and a business process in mind.

When you have a business process or a goal served by data, information, content and insights, you have to trust your data. Data needs to be qualitative, accurate, complete, timeless and fit for purpose. It also needs to be managed, protected and respected. 

Data can be garbage or not fit for purpose due to human errors, for instance in manual data entry or capturing data, flaws in the systems used to capture the data, corrupted data, and so on.

It takes a robust infrastructure and expert knowledge of ICT architecture to design a system based on current best practices.

By successfully using data as a basis for decision-making, you can create value by optimizing and redesigning existing business models and giving rise to new ones. This is what the term ‘data-driven company’ really means. Data-driven companies can attest to higher productivity, better, simpler and/or less costly products and services, and higher ROI.