As the volume and prevalence of data grows exponentially every year, you wouldn’t be at fault for noticing the term “datafication” popping up more and more in popular discussion. According to stats, 328.77 million terabytes of data are generated every day. That’s in a single day. And it’s a mind-boggling volume of datasets exchanging across servers, platforms, businesses, and people.
Data is playing an ever-increasing role in both our personal lives and how we engage as businesses and consumers. It makes sense that the concept of datafication is capturing public attention, especially for businesses.
Data is the single most valuable business resource in the 21st century. It can govern everything, from operational improvements to productivity enhancements, to ongoing sales and revenue growth. But how does data enable this? To understand, we need to examine datafication more closely.
What is Datafication?
Datafication is the act of transforming tasks, processes, and behaviors into data. It’s a technological trend that turns actions into quantifiable, measurable data that can be used for tracking in real time, analytics, and insight.
Within a business context, it refers to turning key operational areas and processes into data for performance measurement, analysis, forecasting, and improvements. Datafication uses the latest technologies and software tools like AI, machine learning, IoT, analytics programs, and data platforms like CRM systems to turn every aspect of a business into a stream of generated, aggregated data. From here, the sky’s the limit when it comes to development opportunities that datafication can power for businesses.
The History of Datafication and its Industry Growth
Although the term “datafication” seems fairly recent thanks to its spike in digital discussion spaces, it was actually coined back in 2013. Kenneth Cukier and Viktor Mayer-Schonberger are credited with coming up with the term in their book “Big Data: A Revolution That Will Transform How We Live, Work and Think”.
In their book, they discuss the rising prevalence and importance of big data in our everyday lives, its value, applications, and use cases, as well as its potential risks for misuse. Aside from the anecdotal experiences we all share that come from big data’s usage in our everyday lives (think Youtube’s suggested videos, recommended products and services on Amazon, and GPS-enabled mapping), the research backs this up.
According to Statista, global data generation is expected to grow to more than 180 zettabytes by 2025, with data storage capacity also projected to grow at a CAGR of 19.2% between 2020 and 2025.
How Datafication Benefits Businesses
So how does datafication benefit businesses? Datafication helps businesses become fully data-driven enterprises, using insights from data to guide every decision, strategy, and operation.
By utilizing datafication, businesses can make smarter decisions, optimize their workflows, enhance their customer experience and drive customer loyalty and retention, develop high-value products and services, and drive greater net revenue.
We see datafication in action every day, when we log into our social media platforms to view curated content based on our engagement data and use our mobile devices, exchanging data to use apps and services. Datafication has virtually unlimited use cases across every industry.
Within the retail sector, datafication can enhance just about every process, from customer relationship management to marketing and sales, to service and support. Through data collection and analysis, retailers can create personalized shopping experiences, tailored marketing campaigns, unique product recommendations, and case-by-case support solutions via their mobile phones, chatbots, and other platforms.
They can create a completely personalized customer experience for every stage of the customer journey using data like browsing history, previous purchases, click-through rates on prior campaigns, and demographic data.
Financial institutions can utilize datafication to evaluate a client’s credit history as well as their risk appetite when it comes to investment decisions, developing a risk taking profile that they can use as a base for tailoring their service offerings.
Datafication can even benefit human resources and recruiting. Through datafication, recruitment agencies and businesses can replace personality tests with collected data of the applicant for screening and conducting criminal background checks as part of the hiring process.
But, with all the benefits that come with datafication, it also comes with risks and challenges for effective, ethical management of users’ data.
The Ethical Concerns of Datafication
The core concern of businesses leveraging datafication at scale is privacy and security, namely the privacy and security of users’ data. It goes without saying that for datafication to work, organizations need to collect vast amounts of data from customers.
Organizations collecting data need to ensure they’re not breaching any consumer privacy policies doing so. It’s essential to implement ethical data collection practices, centered around user consent and full transparency regarding where and how consumers’ personal data is being collected, how it’s being used, and where it’s being stored. This is crucial to prevent any unethical collection and use of personal information without a user’s knowledge and consent.
Security is another key concern of datafication. Collecting, storing, and analyzing massive volumes of data can leave businesses vulnerable to data breaches, hacks, and theft without proper security measures put in place. This could include implementing access controls, encryption processes, network monitoring and testing, and creating data backups in the event of a server failure.
When developing a strategy for data collection, privacy, and security, there are 7 best practices to use as a guide:
- Minimization – only collect data that is relevant and necessary for your datafication purposes.
- Anonymization – Remove or conceal personal identifiers within the data to prevent it from being linked back to users.
- Transparency – be transparent about what data you want to collect and why. Explain how it’s being used and who (and, most importantly who won’t) have access to it.
- Consent – obtain clear, explicit consent from consumers and users to collect and use their data before doing so. Make sure you have a digital record of their consent in your database.
- Security – implement necessary security measures, protocols, and emergency backup plans to protect consumers’ data and prevent it from unauthorized access and misuse.
- Governance – develop clear governance procedures to ensure your organization complies with all relevant data privacy and security laws and regulation policies.
- Ethics – constantly reevaluate how you’re collecting user data to ensure they’re legal and ethical (they don’t mislead users in any way) and respect user privacy, especially as data protection laws and regulations update.
Invisibly is committed to adding value to the digital ecosystem
At Invisibly, we’re committed to building a more connected digital ecosystem through the ethical exchange of data. Invisibly connects businesses with the user data they’re looking for. Users who sign up actively share their consented data in exchange for access to premium brand rewards.
Partnering with Invisibly gives you access to a wider, more diverse net of user data that you can use to drive organizational growth and innovation.
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