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Maneuvering a New Supply Chain Learning Curve

  • Gary A. Smith
May/June 2017

For thousands of years, technology evolved at a snail’s pace. Generation after generation lived essentially as their parents did, and, when innovation did occur, the rate of adoption depended on the speed of your horse. However, since the beginning of the Industrial Revolution, we have jumped from a technology curve that was somewhat linear in nature to one that is on an exponential upswing.

Moore’s Law refers to a 1965 observation made by Intel cofounder Gordon Moore. He noted that the number of transistors per square inch on integrated circuits had doubled every year since their invention and predicted the trend would continue. Although the pace has slowed a bit as of late, the number of transistors per square inch today does tend to double approximately every 18 months. This has been a major factor in technology change of the last half century, paving the way for the iPhone, 3D printing, advances in renewable energy, cloud computing, big data, self-driving vehicles, and LED lighting—all of which have transformed our lives. In many ways, science fiction has become science fact.

But there is a downside. Some of these advances are creating issues because the rate of technological change exceeds the rate at which we can absorb, understand, and accept it. It’s difficult enough to keep up with the new lexicon of terms and concepts in supply chain; the technology behind them is another matter entirely. Furthermore, countless workers feel left behind as many jobs are eliminated while significant need is established for employees with all new skill sets.

Disruptive technologies require a workforce that adapts to new processes, ways of learning, and training systems. To that end, following are some key considerations supply chain management professionals should incorporate into their work and lives:

• Data analysis and database development skills are essential. Additionally, it is no longer acceptable simply to build a database and hand it off to your boss. Managers need more than data; they require advisors who can provide rapid, accurate analysis of the facts using logical, reasoned arguments and insightful opinions and interpretations of the available information.

  • Critical thinking is vital to data analysis. This capability enables people to gain knowledge by asking questions and breaking down complex problems into smaller, more manageable pieces. This process also has the effect of taking emotions out of a situation, making it possible to focus on the issues rather than feelings or personalities. The components of critical thinking include abstraction, systems thinking, experimentation, and collaboration.
  • Abstraction is the ability to discover patterns and meanings in data. It often is used in technology transfer, in which a particular concept or tool from one industry is applied to another for positive outcomes.
  • Systems thinking involves viewing issues in terms of how they relate to an entire system rather than just one area or function and relying on the fact that the good of the many outweighs the good of the few.
  • Many complex problems will require experimentation in order to find the best solution. This may include testing via trial and error, feasibility studies, or the implementation of pilot programs. The key is keeping in mind that it is OK to fail, as failure is a key part of the learning process. Through this process, people learn to think differently and possibly even change their conclusions when confronted with new conditions or evidence. Without experimentation, change and progress are impossible.
  • Collaboration involves working with others toward a common goal. It requires team building and facilitation skills as well as the ability to effectively communicate. Collaboration helps break down silos and develop effective end-to-end processes.

To succeed in an age of exponential change, exponential learning is required, as what you know will become what gets you ahead. The future belongs to those who can maneuver flexibly, swiftly, and boldly along this new learning curve.

Gary A. Smith, CFPIM, CSCP, CLTD, is vice president of the division of supply logistics for New York City Transit. He may be contacted at gary.smith@nyct.com.

This article was prepared by the author, acting in his personal capacity. The views and opinions expressed in this article are the author's own and do not constitute, nor necessarily reflect, a statement of official policy or position of the author’s employer.

To comment on this article, send a message to feedback@apics.org.

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