An Industry Agnostic Perspective of Digitalization
Having worked with a few companies that cater to diverse verticals, I was able to witness how each organization adopted new technologies to improve many aspects of their organizational workflows. First, my main focus revolved around researching electric cars and how to best position them in global markets. Following which, I moved toward the more traditional automotive industry, and worked in China, developing and creating digital services, and evaluating various IT technologies. Eventually, the journey of finding an industry that stands to benefit greatly from digitalization led me to DB Schenker, a logistics and supply chain company, which participates in a very dynamic and engaging marketplace. Currently, I leverage my experience—of over ten years—as a research analyst, an ideator at Daimler AG, and an entrepreneur to help organizations in the APAC region seamlessly embrace digital technology to drive innovation.
Industry Leaders and Innovation
Data analytics play an important role in digitalization as it maintains the ability to bring about significant change in an organization and maximizes productivity. However, I have come to realize that it is less about simply acquiring new technology and more on how to leverage it. There will be IT professionals who can help you best utilize digitalized products and overcome several challenges. Nevertheless, the leadership team must also manage expectations internally and ensure that their employees are aware of the changes to come. With these amendments in place, leaders must be able to strategize and trigger the right processes that promise innovation. Lastly, I would advise starting new projects that involve the latest technology with a well-planned proof of concept (POC), scope, and design. Consequently, in the end, it is about understanding and utilizing digitalization to empower your organization; and industry leaders must always think ahead in that regard.
"Leaders must be able to strategize and trigger the right processes that promise innovation"
To me the word “catalyst” usually signifies deeper meaning than intended. It leads my thoughts immediately toward something that rapidly produces positive change. And of the many technologies available in the market, a popular and justified opinion is that machine learning (ML) and artificial intelligence (AI) are huge game changers. These technologies help companies to leverage data not only to create reports, but predict future outcomes and prepare strategies for favorable outcomes. It can also be applied in many areas of business operations, which truly takes precedence in today’s digitally-driven, hyper-connected world. At the current pace of development, AI and ML will become just as ubiquitous as the Microsoft Office suite of products for everyday enterprise functions.
A Word of Advice for Future Entrepreneurs
Having been an entrepreneur myself, I learnt about the inevitability of the threats an organization may face. This led me to exhaust many avenues in trying to avoid and tackle such problems via risk management techniques and solutions. While this is effective and safe, in the end, I learnt that sometimes you simply have to embrace risk. The main goal is to stay motivated throughout the duration of the project because sometimes your safety nets may fail. By the time my PhD in Engineering was complete, I understood something very simple in theory but difficult in application: you will have nothing to support your efforts until a project is successfully completed. Overall, an entrepreneur needs to be flexible and malleable. Learn from each encounter and do not shy away from new challenges.
Concerning technology, it is mission critical to choose the best products in your respective markets and construct a comprehensive POC. Within the first 10 seconds of viewing a presentation, clients must be able to understand your company’s offering and its benefits. Overly detailed POCs can lead to confusion or imply that the product is too complicated to implement and employ. The use case should be easily understood in the first instance.
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