Social media marketing, business automation, recommendation system, enterprise resource planning systems… Sounds familiar, doesn’t it? Perhaps, for you, it is associated with some stuff related to tech giants like Google, Facebook, Amazon or such. If it’s so – then you are quite right, since the terms I have provided above are, actually, keys to success for every modern business whose ambition is to stand out amongst its competitors. But how and when did these terms arrive in modern business’ vocabulary? The answer to ‘when’ is quite recent, and to ‘how’ – is due to datafication, which I will discuss in more detail below.
Nowadays, datafication is a general practice for businesses, and those organizations that can leverage most effectively and innovatively eventually evolve into such tech giants, like Amazon, which dominates the contemporary retail market. Amazon achieved its heights just by innovatively utilizing datafication, more specifically, due to developing a cutting-edge recommendation system, i.e., by suggesting to its customers the goods which are most relevant to them, thereby enhancing the overall shopping experience and by leveraging social media marketing techniques (Kumari, 2021). Let’s discuss datafication more deeply and try to figure out why it is the main reason for success for every modern business.
What is Datafication?
Datafication is a contemporary trend in today’s technological world. Coined roughly in 2013, it implies splitting every single concept, social or natural phenomenon, and each process that takes place in people’s lives into a systematized and quantifiable form of data, which can later be used for a variety of purposes, including classification, analysis, or labelling among others (Batten, n.d.).
Datafication is empowered by the Internet and technology, which have quickly developed into quite common and widely used tools, the coverage of which spreads onto all areas of people’s lives ranging from local grocery stores to large global businesses (Just & Latzer, 2017). Businesses are interested in actively applying cutting-edge practices that derive from datafication to boost their revenues and discover new opportunities and directions of growth.
Datafication is a huge leap forward in the modern approach to business and business communication, and when properly applied, it is the key to success in modern conditions.
How Does It Go with Real-World Problems?
One of the most significant and valuable assets of datafication is in systematizing and organizing complex things (Flew, 2021). For instance, figuring out how to systematize the company’s customer feedback and tracing its main trends may seem tricky. It implies organizing the customers’ responses, tracing their mood and satisfaction, and making objective conclusions.
The problem mentioned above cannot be effectively solved through traditional polling or other techniques since it would be too time-consuming and an outdated approach. Contrastingly, datafication provides an efficient framework, thereby implying the following steps to address this issue (Batten, n.d.):
- represent every single customer’s response as an entity within a certain storage – a database;
- organize and store customers’ feedback;
- figure out main criteria and distinguishing features;
- draw conclusions based on the comparison and evaluation of these features
These steps illustrate the general paradigm of how datafication is utilized to manage various tasks. Its nature is to split complex and multifaceted things into separate, universal entities with traceable and quantifiable parameters (Flew, 2021).
Data As a Game-Changer in Business
Nowadays, humans have access to amounts of data larger than ever before. For instance, in the early 2000s, only a quarter of information was represented in digital format, but in 2013, digital data substituted every other format of the information, leaving only two percent of data to be non-digital (Cukier & Mayer-Schoenberger, 2013). Such domination of digital data opens a new room for businesses to discover opportunities.
Within this framework, everything may be represented as data: rain patterns, heartbeat, university lectures and news reports, among other things. Technically, there are no constraints to datafication, meaning everything may be categorized and classified.
Consequently, organizations have unlimited access to all kinds of information and actively utilize cutting-edge techniques to analyze it. The contemporary big data technologies, which are continually being developed, were formed by the growing quantity of data. Airswift bar chart below implies that big data are particularly relevant for modern businesses.
Source: Airswift. (2022). What is datafication and why it is the future of business. https://www.airswift.com/blog/datafication
The benefits businesses can draw from collecting and analyzing data are not limited to being able to observe and trace trends. In fact, all innovative data manipulation approaches, including social media marketing and ads targeting, workspace management, performance tracking etc. derived from datafication!
It’s hard to immediately understand the extent of how datafication changed the rules in contemporary business. In fact, data have become the most valuable asset in terms of strategic business management and the business itself. This can be proved by the revenues gained by those organizations that “datafy” their business in the above chart.
What makes datafication notable and exclusive is the value it gives to data, differentiating them from a simple piece of paper or a couple of bytes on a floppy disk. With datafication, as has been stated above, data became a valuable asset which may be utilized in a wide variety of ways.
One of the most commonly used and effective datafication derivatives is targeting, a shift in the commonly accepted paradigm of marketing and promotion (Kus & Efremov, 2018). With its help, organizations can trace their potential customers’ interests by analyzing their open-access personal information, subscriptions in social media and search queries, and present them with the offers that are most likely to be of interest to them.
This way, the organizations shift from common annoying ads broadcast to everyone regardless of choice. Instead, they target the most interested audiences, who are much more likely to buy their products (Airswift, 2022).
Datafication has paved the way for business automation, which is another key concept in today’s business. Its goal is to prevent the employees from performing repetitive and routine tasks, thereby putting more effort into critical and extraordinary problems.
Due to business automation, the automated system may simply replace the most common tasks, such as running marketing activities autonomously, performing financial reporting and accounting, or even automating the sales process.
Digital Hiring and Marketing
Another breakthrough in business caused by datafication is the revolution in the hiring process. Instead of time-consuming and demanding hiring and interviewing routines, modern hiring is data-oriented. Similar things happen with digital marketing since the exponential growth of digital data being transferred makes digital marketing the only type of promotion suitable in today’s world (Kus & Efremov, 2018).
Nowadays, the applications the company receives for their vacancy are, in fact, pieces of data containing the most valuable and relevant traits of applicants. Thus, companies can create a more structured and universal blueprint of the “perfect candidate” they are looking for and simply compare every applicant to it.
Both parties to the hiring process are satisfied under this paradigm: the candidates are aware of what the company expects of them, and the employer receives reliable and consistent data on the candidates.
If properly treated, big data may play a key role in winning the competitive advantage for businesses. As datafication implies compressing almost everything inside handy entities with only their most important features highlighted, organizations can “datafy” the most important things. More importantly, companies can quickly retrieve valuable insights from data, making them the field leader.
With datafication, tracing main trends among the customer demand and sentiment, predicting future trends and changes on the market, and automating complex and time-consuming tasks go to a completely different level.
Challenges and Concerns of Datafication
Obviously, the implementation of such a powerful and popular technical approach may have certain risks for businesses. Organizations should be aware of them since their awareness and ability to minimize them determine their chance to succeed in the volatile contemporary market.
The following issues may arise for business when it considers datafication:
- High cost of third-party platforms, which serve as data storage;
- Confidence and reliability concerns when giving sensitive data to third parties;
- Compliance and diligence of the staff;
- Significant reliance of decision-makers on technical expertise of data analysis staff;
- High volatility of technologies in data analysis domain;
- Expensive hardware and software equipment required to work with enormous amounts of data quickly;
Each of the points deserves to be covered in more detail.
First and foremost, companies should think of someplace to store their data. Nowadays, many companies provide data storage services (Platform-as-a-service or Server-as-a-service), so businesses don’t need to purchase any physical hardware since their data will be stored in the cloud (Airswift, 2022).
This approach has some shortcomings. Such services are costly, so businesses should carefully assess their financial capabilities. Another downside is the security issue since some companies may hesitate to provide their data to someone else because it may contain sensitive insights.
With datafication, the compliance and proper expertise of the employees also become a major concern. According to Crawford (2021), most people hesitate to give the collection of data to third parties. When letting data play a key role, the organization must be confident in its staff’s compliance and absence of malicious intent.
Another crucial thing to understand is that datasets are often represented as basic Excel or plaintext files, with numerous rows representing certain parameters and millions of records (IBM, 2021). The true value of big data cannot be discovered just by looking through the records and struggling to trace regularities.
Instead, it is the responsibility of trained professionals—data analysts—who have the technical skills for handling massive amounts of data to deal with big data and truly extract its value for businesses. Organizations must be responsible in their approach to the search for qualified specialists because massive data are useless without accurate and effective analysis.
However, data analysts can’t get by on their technical knowledge alone. Truly skilled professionals should also be able to use the tools and join multiple platforms required for working with big data. Businesses should be prepared to take their time to recruit highly excellent data analysts and to reward them handsomely for their efforts because these experts may be difficult to find and are expected to be paid well.
The field of data analysis is constantly changing and evolving. Those who are the first to create and adopt innovations in their practices win the game, and data analysis is no exception. Since time is the most valuable resource for businesses, data analysts should keep up with technological developments to quickly adopt cutting-edge techniques when processing large pieces of data.
The necessity of data analysis gives rise to another notable issue: the cost of adopting costly hardware and software. Datasets have grown to such sizes, which could not be imagined back in the 1980s (Crawford, 2021). Therefore, companies should care about proper memory allocation in their hardware to analyze massive datasets (IBM, 2021). No ordinary laptop or desktop would be enough for it, so the companies should be ready to afford costly hardware, which would make working with millions of records simple.
Still, the mentioned issues, which arise with “datafying” the business, do not outweigh the benefits brought by datafication. Nonetheless, the outlined concerns should be treated with great responsibility since the preparedness to face and mitigate these issues determines the success of the modern digitalized business.
With both advantages and disadvantages of datafication, we may figure out whether this phenomenon is good or not for today’s business. Using an example of Amazon, the answer to this question becomes obvious, and I tried to give you better reasoning. The final answer to this question is yes, it is good and even necessary, and here is why.
All the disadvantages I have outlined above have a common feature. By nature, they are not supposed to happen suddenly, so they should rather be called risks, not issues. A major concern of customer privacy should be properly communicated by businesses to assure customers that their data will be used responsibly. Consequently, organizations can prepare their response to these risks and be ready to mitigate them.
However, the advantages are the consequences of abiding by the rules imposed by datafication. In fact, datafication is a demand of modern times, so, at the end of the day, every single organization will “datafy” its business, so the question is only about the extent of datafication.
Additionally, businesses may use companies like Amazon as their role models by mimicking their best practices and trying to build on top of them.
Organizations may extract the maximum possible benefits from “datafying” their operations with proper preparation and a well-planned strategy. The need to digitalize and “datafy” business activity is imposed by today’s reality when the process of purchasing goods and providing services becomes more simplified.
The proper approach to digitalization attracts customers and paves the path to wider audiences since people are likely to accept new, simplified, reconsidered approaches and experiences. Datafication is the main phenomenon which transformed the informational technology industry and global business into what we all know now.
Airswift. (2022). What is datafication and why it is the future of business. https://www.airswift.com/blog/datafication
Batten, E. (n.d.). Datafication will transform your business. BairesDevBlog. https://www.bairesdev.com/blog/datafication-will-transform-your-business/
Crawford, K. (2021). The atlas of AI: Power, politics, and the planetary costs of artificial intelligence. Yale University Press.
Cukier, K., & Mayer-Schoenberger, V. (2013). The rise of big data: How it’s changing the way we think about the world. Foreign Affairs, 92(3), 28–40. http://www.jstor.org/stable/23526834
Flew, T. (2021). Regulating platforms. Polity.
IBM. (2021). The basics of business automation. https://www.ibm.com/cloud/blog/basics-of-business-automation
Just, N., & Latzer, M. (2017). Governance by algorithms: reality construction by algorithmic selection on the Internet. Media, Culture, & Society, 39(2), 238-258. https://doi.org/10.1177/0163443716643157
Kumari, R. (2021, Mar. 10). 10 companies that use big data. AnalyticSteps. https://www.analyticssteps.com/blogs/companies-uses-big-data
Kus, O., & Efremov L. (2018). Digital marketing and big data: Crossing paths in the age of digital transformation. In A. G. Pedja (Ed.), Linking business and communication from a sparkle to a flame (pp. 127-140). DOBA Business School.