What are the roles of the DT organization and the IT organization?

   Companies of a certain size and above have IT organizations. It is called by various names such as information planning team, information strategy team, IT strategy team, IT planning team, computing team, and IT innovation team, and the tasks performed are very diverse as follows.

- Hardware: server, storage, etc.
- Software: O/S, WAS, DB, etc.
- Network: firewall, hub, etc.
- Security: PC security, document security, network security, etc.
- Application field: ERP and other business systems
- Help desk: PC, consumables, troubleshooting, etc.
- etc

   IT people are doing a lot. As the company's support organization, we have a lot of work to do and provide end-to-end solutions to a variety of issues. My partner is in these IT organizations, a role that is not easy to play well and sometimes even painful.

   But one day, an organization called Digital Transformation started to appear. They are called DT Promotion Team, DT Team, DT Lab, DT Core Team, DT Strategy Team, etc., but people within the organization are very confused. What is the difference between an IT organization and a DT organization? What is their R&R? I am confused even after hearing the explanation of the role, and the people who later drew the organization chart are also confused.

   Many organizations start similarly by creating DT organizations. The IT organization is simply reduced to an organization that manages infrastructure such as H/W and S/W, and the rest of the work is sent to the DT organization. Traditional IT organizations have people who are IT savvy. However, DT organizations are primarily made up of non-IT personnel who are business professionals. The company decided that because DT is business relevant, it is better for business professionals to understand the data and innovate on their own.

   But IT is not that easy. IT projects have their own methodology, and there are many things to consider, such as project management plans and maintenance after project completion. It is not easy for business experts to keep up with unfamiliar IT fields such as IT human resources management, partner management, vendor selection, S/W, H/W selection, etc.

   As a result, problems such as removing IT personnel from projects led by the DT organization or reducing the role of IT began to arise. There are many problems such as data interface with various systems, completeness of requirements, and maintenance. Project timelines continue to lengthen, costs increase, and quality is not high.

   IT organizations constantly talk about fixing these problems because they are expected, but DT organizations often misunderstand that IT is interfering with them. The DT organization cannot understand the story the IT organization is telling until the problem actually occurs. DT organizations sometimes cover up problems because they don't want to admit failure. Postponing bomb disposal into the future is very risky.

 

 

     If, after trial and error, it is determined that this should not be done, an IT staff member is assigned to the DT organization. Ultimately, IT organizations will be left with minimal infrastructure management staff. When key people from IT organizations join the DT organization, the distinction between traditional IT and DT organizations becomes blurred. When non-IT personnel become part leaders and leaders of DT organizations, they are forced to go through trial and error until they understand IT. In this process, the company and its members suffer unnecessary pain. The company created a DT organization to innovate the company, but ironically, it encounters an unexpected disruption. Looking at these things, I often think that DT is not digital transformation, but 'IT in the name of DT'. Indeed, many people understand DT as IT-based innovation.

       Data analysis is a very strong emphasis in DT organizations. It is to provide big data or artificial intelligence training to excellent field personnel so that they can directly analyze data and produce results. But even this is not easy. Even if they have expertise in each field, AI/big data is a completely different field, so you need to know IT to properly analyze it.

       We are currently in the process of going through this trial and error. This process seems to be a worldwide phenomenon, not just in Korea. Gartner describes the most desirable organizations as 'Fusion Teams'. It is a mix of people with domain knowledge in the field, data analysts, and existing IT personnel (developers, infrastructure experts, DBAs, etc.) to form an organization and do the work. It looks similar to the agile methodology, but there is a way to organize it into a TF organization where experts in each task gather, or to create a separate organization altogether.

       Heartbreakingly, I expect this chaotic transition period to continue for at least another 2-3 years.

       In the next part, we will explain smart factory and digital transformation.

 

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