In 2017, a personal endeavor to assist my mother’s company in transitioning to a digital monitoring system unveiled a broader mission: the digital transformation of traditional industries, such as Retail, E-commerce, Catering, Manufacturing. While Silicon Valley startups are often lauded for their innovative prowess, traditional industries, especially in developing countries, remain in the shadows of the digital age.
Digital transformation, while promising efficiency and modernization, poses challenges that can inadvertently affect the workforce and market dynamics. It’s imperative to approach this transformation with a holistic understanding, ensuring benefits for businesses without compromising the livelihoods of their employees.
How did the journey start?
The intention for digital transformation originated from an opportunity back in 2017. My mom’s company sought to improve their storage efficiency by introducing a digital monitoring system. As a CS major student, I began assisting her in understanding how solutions were implemented and tried to adjust their equipment to better support their work. My motivation with digital transformation is solely to improve the efficiency of traditional industries using information technologies, as they have lagged significantly behind the trends compared to companies in the Internet industry. Over the years, I’ve interviewed experts from various disciplines, including E-commerce, retail, food, and service, aiming to learn more and take more action in promoting digital transformation.
What is Digital Transformation to me?
The digital transformation I have abstracted includes three stages: automation, digitization, and intelligence. Automation is the ability to automate, mechanize, and produce on a large scale the traditional production process, which is the basis for introducing intelligent decision-making. Digitization, based on automation, is further divided into business digitization and management digitization, both of which support each other. Business digitization, based on mechanization, organizes the procurement, production, storage, logistics, sales, and other business links in a digital manner, establishes a complete database, formulates standard workflows, and has a more precise understanding of the market, consumers, and the company itself. Management digitization, while digitizing the business, cultivates the concept of data governance within the company, improves digital work capabilities, and adjusts workflows and structures when necessary. Intelligence aims to assist decision-making systems based on new tools such as artificial intelligence after obtaining multi-dimensional, large-volume data, such as warehouse replenishment forecasts, channel sales forecasts, and precise consumer demand forecasts.
According to my current understanding and research, the vast majority of industries are still exploring digitization. This is a deeper and wider river than expected. Some companies stop halfway and no longer go further. They seem to have completed digitization, but they are still using manual methods to analyze and summarize data, and there is no dedicated data management system.
Where should I start with?
Let’s start from thinking about Data Governance. A major challenge for current companies undergoing digital transformation is the obstruction of data flow and a weak data governance structure. This problem often arises from outdated systems, separate data storage in different departments, and a lack of a clear plan for managing and using data. Additionally, employees often lack the skills needed to manage complex data systems. These issues lead to inefficiencies and hinder the company’s ability to adapt and stay competitive in a fast-evolving digital world. I believe that the essence of data flow blockages is the uncertainty in data structure. This arises because, prior to advancing digitalization, there was no unified data standard across various sectors. To demonstrate how to address the common issues of data flow blockages and the importance of a unified data standard, I am using an example of the manufacturing enterprise’s SAP system to highlight the challenges and potential solutions.
Acquiring systems from various companies is a common and preferred solution for modern companies to establish their data backbones. But an inevitable consequence is lacking effective integration and data communication, leading to a plethora of derivative problems. Each third-party company has its own understanding of the segment they are responsible for, and each interfacing sub-department has its own comprehension of its business. However, communication between third parties, as well as between departments, is not smooth. A single phenomenon or issue can be reflected through multiple indicators. Although they can corroborate each other, this leads to a situation where, during digitalization, different third parties or company departments might use different terms or logic to describe the same indicator. Taking a manufacturing enterprise’s SAP system that I’m familiar with as an example: their entire SAP system is custom-developed. Whenever different individuals are responsible for the development of each financial segment, it results in poor interoperability between departments. Often, the same financial indicator has different calculation logic in different segments, leading to unnecessary errors and inaccuracies. Extending this issue to the company’s entire SAP system follows the same logic. The underlying logic of each SAP subsystem should be consistent; otherwise, there will be a situation where each system speaks its own language.
In reality, the design of data flow and the SAP system should be quite intuitive. I believe:
- There needs to be a core indicator. This indicator should run through various stages of production and sales, representing a product. Typically, it’s the product’s SKU.
- Centered on this indicator, organize other data indicators from various departments surrounding it and determine the data format and dimensions.
- Based on the core indicator, establish data templates for each stage and test the data flow efficiency for each stage using these templates.
- After fully understanding the data, construct a comprehensive data system for various company segments and ensure its continuity.
What can I achieve specifically via digital transformation?
One obvious outcome that digital transformation can bring is a more solid production design, more trustworthy analysis, optimized organization regulation. Enhanced data analytics procedure would a great illustration. There are details beyond imagination that can be reached and integrated into traditional data analytics with the help of digital transformation and a proper data governance structure.
Data analysis typically refers to a broad range, from basic Excel to data dashboards, to artificial intelligence and even intelligent decision-making. Traditional Customer Relationship Management (CRM) is more about managing relationships with B, C, G. However, with the popularity of e-commerce and online sales, especially in terms of data analysis and governance, CRM is more equated with membership management. It is about analyzing membership data to achieve refined operations of existing resources and further tapping into the value of the existing market. As the scale of the enterprise grows or market competition intensifies, the increasing cost of acquiring customers will inevitably lead companies to turn to the existing market to find new growth points.
The purpose of the membership system in marketing, as I understand it, is as follows:
- Increase average order value/repeat purchase frequency/total consumption.
- Create a sense of premium between members and non-members, and among different membership levels.
- Enhance customer loyalty and satisfaction, strengthen brand influence, and reinforce word-of-mouth.
Some of the structures that back this up typically include:
- Collection of member data:
- Basic data (personal information such as name, address, contact details, etc.)
- Consumption data (details of each transaction)
- Membership data
- Establishment of the membership system:
- Sophisticated Level system
- Points system
- VIP system
- Implementation of touchpoint marketing:
- Based on various information, provide exclusive marketing activities to members who meet certain criteria at specific times, places, and conditions, achieving refined operations and conversions.
- Record the feedback of each member to marketing touchpoints.
- Design, iterate, and evaluate the marketing strategy based on data.
Is this matter entirely beneficial without any drawbacks?
I believed I had accumulated enough knowledge to embark on such a journey until I encountered Ivan’s speech “To Hell with Good Intentions”. It triggered deep reflection on my motivations of digital transformation. I’ve envisioned transformation on a grand scale but haven’t delved into the lives of the numerous employees potentially impacted by my “solutions”. It’s well-known that traditional industries are tied to labor-intensive workloads, especially in developing countries. Digital transformation, in essence, aims to reshape working relationships and introduce more efficient workflows or automations that reduce the demand for human labor. Yet, I’ve seldom considered the potential job losses that many might face, jobs upon which they and their families rely. Moreover, digital transformation, with its heightened efficiency and productivity, could produce goods faster than ever, potentially diminishing their market value. This could, in turn, impact the profits of material suppliers.
I hope to further promote and deepen digitization, develop the needs and scenarios of intelligence in traditional industries, and hope to help more traditional industry companies enjoy the benefits of technology in the new era and further improve production efficiency. Digital transformation is not a one-size-fits-all solution. While it offers immense potential for traditional industries, it’s crucial to approach it with a nuanced understanding, ensuring that the march towards a digital future is inclusive and considerate of all stakeholders. As we stand on the tide of this new era, let’s pledge to harness technology’s power responsibly, creating a future that’s efficient yet compassionate.