The Next Step for the Fishing Industry: Data Analytics
August 1, 2018
The amount of respect I hold for the tradition and craft of the fishing industry is only surpassed by the humility I feel for being able to work in an environment that benefits from countless years of knowledge. By the same token, a majority of companies within the fishing industry treat their employees like family and still uphold the mantra that an unrelenting work ethic is a means to success. I want nothing more than to see the continued success of this industry and her fisheries, but despite being the son of a career crabber I was not gifted with the same back or stamina as my father.
One way that I can best contribute to our mutual success is by introducing the importance of analytics. Whether you are aware of the importance of analytics or have no idea what the term means, I hope I can convince you that developing analytic solutions is the next big step we as an industry should take. If you don't think the implementation of data analytics is important, bear with me, because it is, and it is the future, and we are one of the last industries to adopt data driven business models.
Pound for pound the value of data is comparable to that of oil; in fact drilling for data has created the tycoons of tomorrow. If you find this hard to believe, look at the empires of Facebook and Amazon. Jeff Bezos, the CEO of Amazon at the time of this article is worth more than $100 billion, and it is because of data.
How could this be? How could data prove so useful to a company like Amazon? One of the ways Amazon is able to exploit data to its advantage is to harvest user preference data and suggest items to that user based on that historical data. This is how Amazon knows which type of fishing rod you like, or what type of romance novels you enjoy. And, I am aware that the term analytics and data analytics are used interchangeably, but the important thing to understand is that when referring to analytics we are discussing the "analysis of data" or "what we can learn from an analysis of data." Implementations of data are endless, but we as an industry have been slow to adopt the tools used to portray accurate representations of our data, in large part because we don't know what we don't know.
I would never suggest how or where fishing will be good to one of my company's captains; I have no idea how to operate a commercial fishing vessel, but imagine that I could show a captain a dashboard with historical data from the past 10 years displayed on a digital map. With this map the captains are able to select each point that they fished from this dataset, during specific seasons. The map is fed info on fish size, catch per unit efforts, and the amount of bycatch for said tow. The captains can filter this data by area, trip, year, or whatever preference they think will give them the most valuable info.
In the same dashboard, imagine being able to see the monetary value associated with each trip during a specific season, or the value of the area they are currently operating. What about the grade of roe being produced by that same area in the last ten years? With a dashboard like this you are able to see how much money you made from a single tow and you can accurately measure the monetary difference from one tow to the next. Think of how this could affect the decision making process while fishing.
A majority of the time a tool like the dashboard I referenced will reaffirm what most fishermen already know from years of knowledge, but what about the times a captain can learn something he didn't know?
The type of information you could serve your company's decision makers is only limited to a person's imagination. Having actionable data on hand is precisely how companies like Amazon enjoy their current success, and if you still aren't convinced that data analytics should hold a more commanding role in the fishing industry you should remember, Amazon started by selling books on the internet while we pull fish out of the water in often inclement weather. I am pretty sure we can all agree which one sounds more difficult. The complexity of our industry is exactly why I suggest that companies who embrace a culture of data will find themselves at a huge advantage in the years to come.
I will reiterate that where data exists, the only limitation to gaining insight is a person's imagination. When my company decided to cut their pollock factory trawler in half, add sixty feet, a new main engine, a new fishmeal plant and a new factory you can be sure that data played and continues to play a big role in the success of this endeavor.
Hard work, planning, and excellent decision-making were at the forefront of this project but as I said before, data helped drive the decision process. This happens to have been the way I could contribute. For instance, I created a dashboard for our chief engineers that harvests log book information pertaining to main engine data. The dashboard displays graphs and readings regarding optimal engine performance, which can be filtered for certain conditions and specific electrical load parameters. If you do not have the technical "know-how" to produce a product of this nature, there are companies that can provide this service for you. ioCurrents is a company catering to the maritime and fishing industry that can provide fleet data pertaining to generator and engine performance, fuel efficiency and much more. Even better, ioCurrents has predictive models that are able to alert you should a component within your main engine be operating at subpar levels, allowing you to avoid unforeseen mechanical issues. This should not be seen as an exhaustive list of their capabilities but should demonstrate the fact that the tools are there for you to have a competitive edge whether you have the technical capabilities or not.
Sometimes the answers we seek within data are not always there. More often than not, a failure in your quest for answers within will often yield surprising results in areas you could have never imagined. I tried to determine the correlation between moisture content and protein in a specific product using a statistical programming language and failed miserably based on the available data, but in that exploration we were able to learn of multiple other relationships in the factory that we were unaware of, allowing us the opportunity to pursue more efficient means.
Just having data visualization in front of you illustrating trends within your data is a monumental step forward that a majority of us are lacking. You should rarely move into a project with the assumption that the answers will be straightforward, and it was a valuable lesson on the importance of being narrow minded which led to my results being skewed.
At this point I can imagine that anyone reading this who works for a smaller fishing company or even a single boat company is wondering how he could stand to benefit from adopting analytics into his business model. Big or small, the size of your operation could benefit from what I am discussing.
If your goal is to make more money while ensuring sustainability by having the ability to make the most informed decisions possible, analytics is the answer. Deciding whether to cut overhead or even increase spending to avoid higher costs in the future is exactly what analytics can help with. As I mentioned, there are companies and individuals who are capable of helping you achieve your data-oriented goals and who are willing to show you solutions to questions you weren't even aware that you had. Even if your company is too small to necessitate full time individuals in this capacity there are avenues to reach a culture of data, and if your company is "big" and you find yourself with little to no people with the technical skill to offer data solutions then you are not capitalizing on an incredible asset.
Miles is an avid data enthusiast looking for simple solutions in complex data. When he isn't working on analytic projects for Aleutian Spray Fisheries you can find him posting insightful content on LinkedIn.