What is your data acquisition strategy?
Ship owners and ship operators face increasing regulatory and competitive pressure to monitor and improve many operational areas, stressing the need for a coherent and flexible data acquisition strategy.
1. What are your business objectives?
Defining an effective data acquisition strategy starts with a clear understanding of your business objectives.
Focusing on concrete goals will simplify your initial efforts while you discover and refine your requirements.
2. What data do you need?
Taking the time to understand what data can best capture your business workflows, events and processes is key to building a cost-effective data acquisition solution.
Once you know what questions you are trying to answer, you can focus on the information that will make a difference.
3. How will it be captured?
Accuracy, frequency, latency and cost are some of the attributes to look out for when picking a data acquisition solution. Being able to retain the raw data is also important to ensure you are not limited by past decisions as your needs evolve.
Although automated data capture from onboard sensors can provide accurate high-frequency data, it might not be able to capture every aspect of your operations; human input often remains necessary.
4. How will it be processed?
Data preparation is as important as data acquisition. After all, what is the point of acquiring all this data if it cannot be used by your tools?
Building a mental model of how the data flows down your data analysis pipeline helps ensuring your requirements will be met at each step of the way.
5. Is it future-proof?
As your business faces new challenges, you will have new questions to answer.
Will your data acquisition solution be flexible enough to accommodate the business world of tomorrow and allow you to pursue the opportunities you identify?
6. Is it impacting your decision-making process?
Data mining is an iterative process with better decisions as the outcome. If you find your decision-making process unchanged despite investing in data acquisition and data mining, you might want to revisit your data analysis pipeline and find out where it is letting you down.