What do you do if you need to make strategic decisions as a Marine Engineer using data and analytics?

Onces. Wise man said "if you can collect and analysis data ,you can predict future " with this modern technology plus AI . Give us tools for analysis the data on emission , fuel consumption , efficiency, frequency etc . With these we can plan in advance and our future way to green ships , imo have already working on this with IIXI , CII ,SEEMP .which is taking ship to green shipping

Great first step, but we should not forget to also get a timeline of the human elements associated with the event (s) in question as they are not always captured in available data.

- Gather relevant data from various sources, including sensors, monitoring systems, and historical records. - Utilize statistical analysis and data visualization techniques to identify trends, patterns, and insights. - Extract actionable insights from data analysis to inform strategic decision-making processes.

Some popular tools that aid in data analysis and making comparisons include MS Excel, Python, SPSS. To improve accuracy of the analysis, the data collection must be very deliberate and tailored towards the goal at hand. For instance, to analyze vibration effects on an engine, vibration sensors are connected on horizontal, vertical and axial directions of the engine to collect appropriate vibration speeds across all parts of the engine.

This is pretty often to happen. Nowadays, we used to use a wide range of softwares, in order to help us and streamline work. Whatever is the type of ship, she will always have some kind of electronic devices to collect information and data for further analysis. We need to be familiar with the equipments and also have experience in order to do a good job. Always be in constant learning, new technologies. Acting this way we will be in constant development of our skills, and certainly we will know how to do it, in a better way.

Decision models will depend on the data being cleaned and the predicted outcome from the analysis. One important thing to have in mind is the final consumer of this information to determine what model will best explain to them the information to be processed. Simple or complex.

Once again great advice. We should always include the commercial impacts of the decisions. Whether actual or perceived the impacts of an “engineering” decision should always be tempered with a thorough understanding of the commercial impacts.

- Develop decision models and algorithms based on data-driven insights to support strategic decision-making. - Utilize techniques such as predictive modeling, optimization, and simulation to evaluate alternative courses of action. - Incorporate relevant variables and uncertainties into decision models to enhance accuracy and reliability.

I agree with this step but would add that the risks that need to be evaluated reach beyond the scope of the recommendation. Yes people, environment and assets are a minimum, but we should not forget reputational, client impacts and commercial viability.

- Conduct comprehensive risk assessments to identify potential threats, vulnerabilities, and opportunities associated with strategic decisions. - Utilize probabilistic modeling and scenario analysis to quantify and prioritize risks, considering both likelihood and impact. - Develop risk mitigation strategies and contingency plans to address identified risks and uncertainties.

To aid proper risk assessment of your modeled data, the following steps can be followed. 1. Identify potential hazards. 2. Assess consequences of each hazard. 3. Evaluate likelihood of occurrence. 4. Review existing control measures. 5. Identify gaps in control measures. 6. Evaluate overall risk exposure. 7. Prioritize risk reduction measures. 8. Clarify responsibilities for risk management. 9. Establish monitoring and review processes. 10. Develop contingency plans and emergency procedures. These will give you a greater control and mastery of the situation at hand.

- Foster collaboration and knowledge sharing among multidisciplinary teams to leverage diverse expertise and perspectives. - Engage stakeholders and subject matter experts in strategic decision-making processes, soliciting input and feedback throughout the decision-making lifecycle. - Utilize collaborative decision-making techniques, such as brainstorming sessions and workshops, to facilitate consensus-building and alignment.

- Develop and prioritize actionable solutions based on data-driven insights and strategic objectives. - Create implementation plans with clear objectives, timelines, and responsibilities to ensure effective execution of strategic decisions. - Monitor and evaluate the performance of implemented solutions, adjusting strategies as needed based on real-time data and feedback.

- Cultivate a culture of continuous learning and improvement within the organization, encouraging ongoing experimentation and innovation. - Invest in training and professional development opportunities to enhance data literacy and analytical skills across the workforce. - Stay abreast of emerging technologies and best practices in data analytics and strategic decision-making to remain competitive in the marine engineering industry.

As marine engineering professionals, integrating advanced analytics, simulation, condition monitoring, integrated data, remote sensing, and collaborative approaches can greatly enhance our situational analysis capabilities. Let's leverage these tools and techniques to drive informed decision-making, optimize operations, and ensure the success of our maritime endeavors. Together, we can navigate the challenges of the seas with confidence and innovation.

- Ensure data quality and integrity by implementing robust data governance practices and validation procedures. - Foster transparency and accountability in decision-making processes, communicating rationale and outcomes effectively to stakeholders. - Balance quantitative analysis with qualitative insights and contextual knowledge to make well-informed and holistic strategic decisions.