Data has become a primary asset for businesses today. Consequently, the survival of a business in our data-driven environment is highly dependent on the ability to have total control over data storage, extraction, and manipulation.
As businesses continue being bombarded with vast volumes of data, datafication has become a big trend that provides a solution to turn data into quantifiable, usable, and actionable information.
What is Datafication?
The term datafication was coined by Kenneth Cukier and Victor Mayer-Schöenberger in 2013 when they explained it as the transformation of social actions into quantifiable data.
Today, much data is collected at the point of contact with any technology device. Aside from data such as text, images, and numbers, there are logins, passwords, device activity logs, clicks, interaction times, and more. Datafication helps translate all of these human activities into data, which is then repackaged in a form that offers value.
In business, datafication means converting every activity of a business model into actionable data. This has been enabled by a rise in technologies such as artificial intelligence, machine learning, big data analytics, and predictive analytics.
It’s worth noting that datafication is not the same as digitization. While datafication is about taking all aspects of life and turning them into a data format, digitization involves converting analog content, such as images and text, to a digital format.
Examples of Datafication in Real Life
There are various ways datafication has been applied in real life, including:
- Social media platforms – a lot of data is found on social platforms through profile updates, preferences, reactions, comments, and posts. Such information is used for customer profiling.
- Ad personalization – tech giants such as Facebook, Google, Apple, and Amazon are already using collected data in their storage to personalize their ads and target potential customers.
- In customer relationship management – data collected through language and tone in emails, social media, and phone calls are used to understand customer needs and wants as well as buying behavior and personalities.
- Human resources – HR uses data obtained from social media or mobile apps to discover characteristics and personalities when looking for potential employees. They also use the data to assess employee productivity. This means that it may no longer be necessary to take personality tests, as the collected data can be analyzed to check if a person matches the company culture and role for which he applies.
- Insurance and banking – understanding the risk profile of a customer applying for insurance or a loan, as the data is used to assess the client’s trustworthiness.
Datafication for Competitive Advantage
With the above use cases, it is evident that businesses can leverage datafication to help improve operations, thereby increasing productivity and revenue.
For instance, collecting real-time customer feedback can help improve products and services. Additionally, it becomes easy to determine and predict sales by analyzing data from social platforms such as Facebook, Instagram, and Twitter.
The information collected from social media, emails, and other digital platforms is then used to create personalized campaigns, effectively targeting the most interested audience.
How Businesses Can Implement Datafication
Any trending technology that presents benefits to a business comes at a cost. Luckily, cloud computing eases datafication for businesses as they don’t have to worry about acquiring necessary hardware and software. With readily available software as a service (SaaS) or platform as a service (PaaS) technologies, businesses need only to define the goal they want to achieve with the data collected.
The main concern of a business remains the proper implementation of datafication. To begin with, it is best to ensure that the right technology – such as mobile devices, voice assistants, wearables, and IoT – is used.
Next is to use appropriate platforms. Using the right platform will help effectively extract data that a business needs. Such platforms should also analyze massive amounts of data and produce reports that enhance decision-making.
Another critical factor is to have a centralized repository where all authorized people in the organization can access the data.
Finally, it’s crucial to have skilled professionals in data infrastructure, data management, and data analytics to evaluate and manage the data. This could either be an in-house team or outsourced.
Businesses that wish to remain relevant must consider datafication as part of their digital strategies. However, as datafication enters digital transformation, its successful implementation will require attention to data protection through adhering to legal requirements, technical measures such as access control, and best business practices.
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