There is a saying that if you see one port, you have seen them all. Others will say, if you see one port, you have only seen one port. I would add when you see one port, you see one port for that day, as traffic patterns can change quite a bit. That was the issue here, as several presenters discussed the lower traffic in the port was the result decline after a surge of cargo moved to Britain prior to the last Brexit deadline.
After a great introductory presentation, we drove around the port, which handles a lot of autos! We first toured the facilities in the morning, while it rained, only to see it clear up later that day.
The question of Brexit remained a constant topic. The Port of Zeebrugge is a major gateway between Europe and the United Kingdom. Traffic through Zeebrugge remains integrated into supply chains for British retailers, even to the point of handling larger trucks, which are allowed in the UK, but not in the EU.
It was a great visit, hearing the presenters talk about importing fresh fruit, how interdependent the UK was for EU firms stocking their shelves, and how the port itself developed. (There is a lot of rail in Zeebrugee. They can build European block trains at the port.)
It was a great visit, but at the end of a long day, sometimes you are just ready to take the bus back!
There is the old nursery rhyme about how a kingdom is lost because a horseshoe falls off. The poem refers to paying attention to little things that can make a difference, as the casual relationship of minor things failing can evolve into major problems (the Space Shuttle Colombia is but one of many examples). While one could argue its importance on military logistics or other more mundane tasks (such as learning the basics when mastering any skill), the same logic could be applied to not only the development of data but to data applications.
In the age of “Big Data”, we see where more information can provide insights that were unavailable just five years ago. The use of Artificial Intelligence and Machine Learning will transform how we collect, manage and process data, providing insights that will assist researchers and decision makers. However, the casual relationships between collecting/using data with any unintended consequences remain.
For example, one could argue that I represent three people: a physical me who eats, sleeps and walks around, while there is a legal me, who signs legal documents and has financial interests. There is an emerging digital me, where I live and work in a virtual world. My information is collected, processed, and analyzed, as I become “a product” sold to others. In many ways, the data collected from millions of digital actions are creating better horseshoe nails for business, governments and others, but will this lead us to lose the kingdom of our individualism?
As a researcher, I have often heard people lament, “We studied this in the past and nothing was done”, or “Why are we not using this approach”, or some variation concerning the fact that data and information are not being used after the being developed, purchased, or studied. The question is that we think, using our crystal ball, we have built a masterpiece, and wonder why people don’t adopt our insights. We often forget that this “knowledge” could be slow to be adopted by others for many reasons.
Failure of adoption:
The first is simply the WHY? Sometimes when doing research we understand more about the question that the person who needs the answer. So while we prepare our work, we forget our client will only use what they can understand with some level of confidence. How often have we seen a more senior person misspeak based on information not properly summarized for them?
Secondly, there remains the ever consuming “tyranny of the urgent”, in that the research is needed in a timely manner, but the research is not needed beyond the “now”. The reasons can vary from staff turnover, policy change, new leadership, the findings were not what was expected, to a thousand different reasons. Furthermore, data is perishable, something that is often forgotten by the researcher, but not the client.
Thirdly, the experts may not agree with your opinions. My wife is a fan of Downton Abbey, and during season 3, Sybil Branson died after childbirth. The tragedy was there were two doctors arguing over her treatment, and the older doctor stated to the other doctor he is to not interfere. In many ways, we can find people with good intentions failing to achieve an expected outcome because they are using older models from the past. They remain uncommitted to learn, and without the application of new information, their working knowledge could, and does, fail, in providing actionable insights, or even providing the wrong information. Presenting this expert with new information may only lead them to become more entrenched to their position.
Finally, our research may not actually answer the question being asked!
For the research community, the ghost of people not adopting our great ideas haunts the adoption of our “great efforts”. But we must understand what the client may do with the research once it has been delivered, which may depend upon how we communicate before, during and after the research process!