Since I am a consultant, I frequently meet with clients and the first meeting is always the most important. Therefore, I have a habit of predicting the questions clients will ask to prepare myself for the meeting. Lately, predicting the questions has become a little easier.
Below are the most frequently asked questions :
1. What is digital transformation (DT)?
2. What is the relationship between DT and technologies such as artificial intelligence (AI) and big data?
3. What should our company (client’s company) do?
You can find the answer to the first question in the first and second articles of ‘Understanding Digital Transformation’ about the movie The Matrix and Cypher’s steak. Today, I will go over the second question ‘What is the relationship between DT and technologies?’
I stated that the answer to the first question ‘What is digital transformation?’ as 'transforming a substance into information.'
Then I assume two questions will pop up in your mind:
1. “I vaguely understand what digital transformation is but after going through the explanation, it seems digital transformation already existed in the past and the transition process has been underway. Then why has the concept became so important lately all of the sudden and is frequently covered on the media?”
2. “New technologies, especially AI and big data, are always mentioned when discussing about digital transformation. But, Why?”
Exploring the answers to these questions will lead to the answer to the second question above ‘What is the relationship between DT and technologies?’
Back in the days when I was in college, the only way to generate data was to input it in the computer. Most of the data was of stereotypical form, either code or text. Now, most people use smart phones and create text, images, and video clips data anytime, anywhere. Therefore, the amount of data created by people has skyrocketed. Moreover, countless number of sensors and devices are endlessly generating data, thanks to IoT. Nowadays, more than four sources churn out an incomparable volume of data.
In the past, the conversion of substances to information gradually increased, thus showing a linear growth of data. Thanks to mobile devices and IoT, data grew exponentially to an unexpected degree. As a result, the existing methods and systems could not handle the processing of massive volume of accumulated data.
Such accumulated data are what we call 'big data’ and people needed a new technology to store and process big data.
Cloud has risen as the solution to handle big data. Cloud is consisted with two key technologies, which are server virtualization and distributed processing. Server virtualization connects individual servers in parallel using software to function as one server, thus storing increased data exponentially. In addition, distributed processing enables the CPU, the parallelly connected servers’ brain, to distribute the processing workload. Based on the following two technologies, people solved urgent problems to deal with big data. Soon after, people realized that it is possible to earn money with cloud technologies. This led to the creation of a new business model.
Twenty years ago, only companies of certain sizes were able to introduce information systems because establishing such systems required a considerable amount of cost and more than a dozen employees to operate them. So introducing Enterprise Resource Planning (ERP), a representative information system at the time, even affected the stock prices of the company. This trend changed with the emergence of the “cloud service” business model.
Companies that used cloud technologies at the initial phase soon realized being able to freely connect and separate several servers meant that they could purchase many servers and storage, develop a service, and then sell it to companies or people. This business model is “cloud service.”
Information systems are not the exclusive property of large companies anymore. Anyone, including small- and mid-sized companies, start-ups, and even small merchants, can easily use such systems. The result? An increase in data volume, which was already explosive thanks to mobile devices and IoT, was further accelerated. Only rather large companies generated data in the past, but now almost all companies and individuals are creating data. With the introduction of cloud service, data grew even more explosively.
As data volume grew further, it was difficult to process big data even with the cloud’s distributed processing technology. People needed new technology again and this time, Artificial Intelligence (AI) was a solution. AI has interesting features. It requires quality input, such as big data to work well. When fed quality data and trained, AI creates a logic for data processing, faster than humans. This will again lead to an increase in data. What’s more, AI analyzes data, which will further grow data. Big data will become “bigger,” and the quality and quantity of input fed to AI will improve. This will affect the starting point of the cycle. As data can be utilized in various methods and areas, mobile devices and IoT will be applied to a broader range of areas, encouraging more companies to adopt cloud services. This again will lead to the growth of data.
Now a complete cycle has been made. This cycle is called the “digital transformation cycle” or simply “DT Cycle.” Below are five key technologies that play a crucial part in this cycle that spell out as I’m ABC with their first letters.
I : IoT
M : mobile
A : Artificial Intelligence
B : Big data
C : Cloud
Once a cycle is created, it adds momentum to the changes created by the cycle. Recently, COVID-19 significantly fueled the process, with contact-free technologies accelerating the cycle.
Today, we looked at DT and related key technologies – AI, big data, and cloud. Next time, let’s answer the last remaining question – what should our company do?
Written by Hojai Joo, a Senior Consultant of Samsung SDS