Start the digital transformation, and face the fear!
World War I is considered the greatest tragedy of the 20th century. Large-scale warfare destroyed cities, crippled economies, and humanity crumbled in the face of senseless violence. Wars emerge from the interweaving interests of multiple parties, making it difficult for a single nation or group to prevent them. Similarly, ending a war that has already begun becomes even more challenging when the threads of interest have become hopelessly tangled in the complex web of circumstances
However, there is a hidden reason behind the expedited end of the difficult armistice, the First World War: the Spanish flu. How did the Spanish flu hasten the end of the war? It is possible that the flu spread among soldiers during their combat operations, prompting the leaders of the warring nations to hastily negotiate a peace treaty. This raises the question: which is more destructive, war or a large-scale pandemic?
Seattle police in the U. S. with masks in 1918 while the Spanish flu was prevalent. It is a relatively recent phenomenon to feel uncomfortable wearing a mask under the pretext of personal freedom. / Wikimedia
Even without needing to answer this question, COVID-19 has significantly altered the familiar order we used to know. Economic shocks aside, the shift to contactless interactions has become an essential standard in our social relationships. As a result, the task of digitally transforming customer engagement and service distribution methods has become the top priority for all businesses. The coronavirus is acting as a ‘biological’ catalyst, promoting a transformation in the economic structure toward businesses that combine online and offline elements.
A McKinsey Consulting Firm innovation executive outlined three criteria for assessing the success of digital transformation in an interview. These criteria include financial performance through digital conversion, strengthening employee capabilities, and the sustainability of these outcomes. Among the companies attempting digital transformation, less than 30% manage to meet these criteria.
He identified the biggest cause of failure as the “pilot project trap.” Pilot projects are used to denote experimental attempts to verify long-term possibilities. These projects are meant to set the direction for ongoing tasks and identify areas of improvement early on. Therefore, it is not appropriate to assume that the tasks after the pilot project will automatically succeed or fail based solely on the results of the pilot project itself.
Two Yoo Project Sugar Man
The producer of the JTBC variety show “Sugar Man” commented, “The pilot failed.” However, after airing regularly, viewership ratings increased, and the show successfully gained attention.
For example, let’s reconsider the case of an employee from a subsidiary of Group A, who received training from Elice and developed a map for rental car accident locations. If Group A had simply rewarded and widely publicized this employee within the company, they might have easily fallen into the pilot project trap. However, Group A used this case as a steppingstone to expand company-wide training in basic coding and data utilization. Instead of stopping at what seemed like a success, they made choices and took action to sustain this momentum.
This comprehensive approach to digital conversion across the organization has been quite commonly discussed since last year. SK Group launched the integrated internal education platform called “MySUNI” in January. Employees can develop basic skills for utilizing AI and acquire the abilities necessary for digital conversion through this platform. The company is also implementing a system where training hours are reflected in performance evaluations. Similarly, Hana Financial Group established a separate entity called “Hana Finance TI” to lead digital and data-based strategies within the group, focusing on initiatives such as building a financial cloud platform.
Organizations undertaking enterprise-wide digital conversion must be prepared to endure cost and cultural risks affecting the entire organization. Even so, large corporations opt for company-wide digital conversion instead of relatively safer and predictable selective talent acquisition. What could be the reason for this? One reason is likely wanting to avoid the pilot project trap, but the main reason lies in the recognition that the experiences, skills, and existing domain knowledge accumulated by the organization’s members are more important.
Let’s say you are the strategic planning manager for D-Mart, the second-largest retail chain in the country. With an upcoming long weekend, you aim to secure a competitive advantage by identifying underperforming branches of your competitor, F-Mart. You plan to achieve this by diversifying product offerings and offering discounts. However, how can you find stores with low sales?
Up until now, estimations have been made by compiling publicly available data or relying on interviews with store managers. But what if you could directly count the visitors to nearby competitor stores? An idea strikes you. What if you use satellite images of the parking lots and employ object recognition algorithms to count the cars in these images? By doing so, you wouldn’t rely on secondary information but instead directly obtain the desired data.
Operation screen of the photo analysis algorithm that detects and shows empty parking areas with satellite images./阿里云
I described it as occurring in someone’s mind, but in reality, such an approach involves a synergy of various skills at the team level. It requires a chemical combination of information, human resources, and technology.
It isn’t easy to fill in new specialized talents in an existing organization. While the expertise of newly added professionals can enhance technological aspects, organizational decisions stem not only from good ideas and efficiency but also from the cultural interactions among members. This makes where the starting point for digital transformation should be more obvious: from within the existing members.
Existing members already have significant experience and the information needed to solve problems. Based on this, tools can be brought in from outside as needed. In fact, the most important part of data utilization is the process of designing plans and preprocessing data to suit them. This is something that only people with domain knowledge related to the data can do. If this work goes wrong, no amount of good tools can be used afterward to guarantee the value of the results (analysis data that underlies the organization’s judgment and execution).
Harvard Business Review’s Digital Transformation Feature, which was published last week, summarized the digital transformation with one sentence: “What matters is talent, not technology.” Therefore, digital transformation that utilizes data to solve problems starts with basic training that supports the perspectives and capabilities of existing members. Naturally, for practical effects, it is recommended that all members, not just decision-makers or digital dedicated teams, proceed. Currently, the content and direction of the training can be summarized into the following three parts:
Learning About Data Utilization Cases
Exploring digital transformation perspectives and perceptions is the purpose of case analysis./ Needpix
The purpose of examining cases where digital conversion has been attempted or is being attempted within business operations and organizations is not to analyze those cases or apply them directly to one’s own situation. The goal of this case-based learning is to explore different perspectives on one’s own organization or business nature from the standpoint of digital transformation. Reading the previous four articles in this series might be sufficient for this case-based learning.
Using Digital Tools for Basic LearningAnalyzing President Trump’s tweets
It is possible to understand the tool conceptually, but in order to utilize it, it is essential to actually carry out basic practice.
The next step is to identify and learn how to use the latest tools in data application. Currently, there is a fairly large gap when it comes to knowing how to use the latest tools. These can be understood to some extent by looking at types and concepts. But using it likely requires some professional competence. To learn how to use them, eventually, basic coding is necessary. Currently, the purpose of basic coding is not to learn how to use the tool perfectly, but to secure the minimum understanding necessary to outsource tool utilization. It would be ideal if everyone in the organization could handle machine learning models, but it isn’t necessary.
However, understanding machine learning conceptually is not enough to gain the insights necessary for practical applications. To understand what the code entails, how it operates within specific interfaces, and who possesses such expertise, foundational learning is essential.
Practice Utilizing Your DataStudents who participated in Elice’s AI education training are evaluating the usability of image processing algorithms. Collaboration is essential when it comes to data utilization and analysis.
The next step is to apply what you have learned. Previously, the importance of domain knowledge was emphasized To demonstrate existing knowledge and capabilities, domain knowledge-based data will be used rather than examples provided in the learning process. A team-level approach can be useful at this time. I’m not trying to state the obvious by saying that collaboration is important. Collaboration becomes a cumbersome process if the awareness of the problem is not shared. Individuals within the same team who share a common problem and are motivated to solve it together create synergy.
In short, with a basis of existing knowledge and experience, if awareness of the problem is shared through work structure and newly learned skills are supported, your organization has entered the gateway to digital transformation.
When the first electric light was installed on the Gyeongbokgung Palace grounds in 1887, hundreds of people gathered near the palace out of surprise and curiosity. Then, the cool water from the steam engine that had been supplying electricity flowed back into the pond in the palace, causing fish to die in droves At that time, there was a rumor that in the country, fish would boil, and the country would collapse. This is because there was more fear that existing life might be threatened by the new technology than interest in its utility.
The competitive system sometimes pushes out competing parties, but it also becomes a driving force for each other to grow in the process. If you clearly recognize the great stem and dynamics of change and can overcome the fear, there is every opportunity to respond to change through electric lights and steam engines.
A crisis can also be an opportunity for change and make things look different./ Wallpaper Flare
Depending on how it is handled. The post-COVID era can be a crisis or an opportunity. The meaning of developing the ability to write a line of code and process a line of data is to provide opportunities for the market and our society on their own. The overall digital transformation of organizational culture and corporate performance strategies is a choice for the survival of the organization they belong to, but in the long run, it is also about changing the societal and communal ecosystem to which the company belongs.
There is no reason to have a grand sense of duty. However, I and the implementation of digital transformation can send a clear message to others in this society. The fact is that digital conversion in the post-COVID era is just beginning, and it’s up to everyone who joins the change to create the outcome.
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