What Is Datafication and How Can It Impact Your Business?


Twenty-first century businesses are evolving at an increasingly rapid rate, and the main catalyst for this evolution is advancing technology, with data as a key focal point.

Not only is data important for most businesses to operate and compete, it’s becoming absolutely essential. And the exponential growth of data that’s occurring is staggering. By 2020, roughly 1.7 megabytes of new information will be created every second for every human being on the planet.

This massive rise in data is being primarily being spurred by IoT, the widespread use of mobile devices, BYOD policies and the affordability of sensors.

So, how can you use all of this information to your advantage? One specific way that companies can improve their decision-making and optimize operations is through the use of datafication. Here’s what you need to know to reap the benefits for your business.

What Is Datafication?

The term ‘datafication’ was first coined by Kenneth Neil Cukier and Viktor Mayer-Schoenberger in a 2013 essay in Foreign Affairs. They used it to describe the practice of taking aspects of the world that have never previously been quantified and rendering them into data.  

At its core, datafication is the practice of turning numerous aspects of life into data and transforming it in order to create value.

In a business context, this involves an organization using tools, technologies and processes to extract data and ultimately improve its overall objectives.  

Why Is It Important?

Businesses across nearly all industries can use datafication to improve critical processes. Once processes have been converted into data, they can be fully tracked, monitored and ultimately optimized.

This enables organizations to operate with greater efficiency, increase productivity and improve their bottom line.

On the micro level, this aids in day-to-day tasks and allows a company to make the most of its resources. On the macro level, it provides the opportunity for a company to enhance its strategies, streamline existing processes and rise to the forefront of its industry.

You could make the argument that organizations that effectively utilize datafication have a decided advantage over those that do not – and you would be right. That playing field is by no means level.

A Wide Range of Applications

What makes datafication so powerful is that it can be used for a nearly infinite number of purposes across a multitude of industries, such as healthcare, HR, finance and insurance.

Here are a few areas where datafication can have an impact:

  • User experience – Media/entertainment companies like YouTube and Netflix can offer customized recommendations based on what users have previously viewed.
    • Banking – Financial institutions can leverage data to assess a person’s trustworthiness and risk level when applying for a loan.
    • Hiring and recruiting – Companies can replace personality tests with datafication to fully assess a candidate’s behavior, working style, personality type, etc.
  • Commercial real estate – Data can be used to gain a more comprehensive understanding of various locations to determine the ideal location to open a store.
  • Retail – Companies can extract data from a customer’s previous purchase history, social media accounts, mobile phone location, inventory information, etc. and amalgamate it in order to send relevant promotional materials.

The possibilities are virtually endless.

How Datafication Can Impact Your Business

When leveraged correctly, datafication can revolutionize your business by streamlining and improving processes that may have been previously inconceivable.

By turning what may seem like mundane daily interactions into data, you can transform your business into a hyper-efficient, data-driven enterprise.

Here’s a look at some practical ways that companies have used datafication in the past.

Increasing Retention Without Increasing Overall Pay

One unnamed company was alarmed at their turnover rate and was struggling to retain their top employees. So, they chose to datafy HR and had their engineering team unearth pertinent information related to employee retention.

What they found was that mid-performing employees were willing to stay at their jobs even if their pay was cut to nearly 90 percent of compensation averages. However, the majority of top-performers would leave if their compensation wasn’t well above average.

They used this information to modify their compensation structure and shift some of the money they were using to compensate mid-performers to top-performers. In turn, they were able to reduce turnover without increasing overall pay.

And what organization couldn’t benefit from increasing employee retention? Research has found that it typically costs employers the equivalent of six to nine months of an employee’s salary to replace them.

Understanding What Makes a Great Salesperson

There are numerous factors that determine how adept someone is at selling goods or services. A few years ago, IBM went on a mission to identify these key traits so they would be in a better position to make hiring decisions.

They analyzed and assessed 40 million job applicants, workers and managers in hopes of gaining a deeper insight. What they found through comparing surveys and tests was that emotional courage – stepping out of one’s comfort zone and being persistent – was the most vital characteristic for success.

They determined that this was even more important than having an extroverted, outgoing personality. From there, IBM used this data to optimize their recruiting and hiring and were ultimately able to find top-tier salespeople.    

How to Datafy Your Business

Now for the million dollar question. How do you datafy your business?

A great place to start is to implement IoT into operations as much as possible. This includes things like mobile devices, voice assistants, Bluetooth beacons, and wearables. Anything that’s embedded with sensors, software or network connectivity allows you to capture data and store it for future decision-making.  

This shouldn’t be a problem considering that there were nearly 8.4 billion connected things in 2017, with this number predicted to grow to more than 20.4 billion by 2020. The more connected devices you have, the more data you can generate.

Use the Right Platform

You can also generate a wealth of data by using a data extraction platform like Import.io. This is ideal for generating non-traditional web data for research, and for converting a massive volume of data found online into structured, machine readable data.

You can do everything from monitoring competitor pricing to obtaining up-to-the-minute analyses of industry trends. In turn, you can use this information to enhance your organization’s decision-making and business processes.

Create a Centralized Repository

The impact of data is marginalized when siloed. In order to fully capitalize on it, you must develop a digital infrastructure where the data you generate accumulates in a centralized repository.

The term “data lake,” a storage repository that holds a massive volume of raw data in its native format until it’s needed, best describes this concept.

Keep in mind that you won’t typically use 100 percent of your data right away. But having the ability to easily store it so you can utilize it later on is critical.

The Future of Data

A data explosion has occurred in the 21st century. Research has found that more data was created in the past two years than throughout all of prior history combined.

The sheer amount of data that now exists is mind-boggling. But what’s interesting is that only a tiny fraction (roughly 0.5 percent) of the world’s data is actually analyzed. This presents a tremendous opportunity for today’s businesses. The data is out there and for the taking. It’s simply a matter of knowing how to access and analyze it.

In many ways, datafication represents the future of data. By converting the more subtle aspects of human behavior and daily interactions into meaningful data, organizations are in a position to flourish and thrive.

Sign up for Import.io and start getting data for your datafication efforts.