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How can data analytics improve communication of OR model results to stakeholders?

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Operations research (OR) is a discipline that applies mathematical and analytical methods to solve complex problems and optimize decision making. OR models can help organizations improve efficiency, reduce costs, increase productivity, and achieve strategic goals. However, OR models can also be challenging to communicate to stakeholders, especially those who are not familiar with the technical details, assumptions, and limitations of the models. How can data analytics improve communication of OR model results to stakeholders? In this article, we will explore some ways that data analytics can help OR practitioners present and explain their model results in a clear, concise, and compelling way.

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1 Data visualization

One of the most effective ways to communicate OR model results is to use data visualization. Data visualization is the process of transforming data into graphical or interactive forms that can reveal patterns, trends, relationships, and insights. Data visualization can help stakeholders understand the problem, the solution, and the impact of the OR model. Data visualization can also help OR practitioners highlight the key findings, compare different scenarios, and show the trade-offs and uncertainties of the model. Data visualization tools, such as Tableau, Power BI, or R, can help OR practitioners create and customize data visualizations that suit their audience and purpose.

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Harsh Shah

Senior Azure Data Engineer | 3x Certified in Azure Data Engineering, Power BI, and Fabric Analytics | Expert in Azure Data Factory, Databricks, Synapse and Azure DevOps | Active Reliability Clearance
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Data analytics can play a crucial role in improving the communication of Operations Research (OR) model results to stakeholders. Use data visualization techniques to present complex OR model results in a clear and intuitive manner. Implement real-time reporting features that enable stakeholders to access the most up-to-date information. Use data analytics to perform scenario analysis, allowing stakeholders to evaluate different scenarios and understand the potential outcomes of various decisions. Integrate predictive analytics to forecast future trends and outcomes, providing stakeholders with insights into potential future scenarios.

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2 Data storytelling

Another way to communicate OR model results is to use data storytelling. Data storytelling is the art and science of using data, narrative, and context to convey a message or persuade an action. Data storytelling can help OR practitioners connect with their stakeholders on an emotional and rational level, and explain the logic, relevance, and value of the OR model. Data storytelling can also help OR practitioners structure and simplify their presentation, and use metaphors, analogies, and examples to illustrate their points. Data storytelling tools, such as Storytelling with Data, Datawrapper, or Infogram, can help OR practitioners craft and share data stories that engage and influence their stakeholders.

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Harsh Shah

Senior Azure Data Engineer | 3x Certified in Azure Data Engineering, Power BI, and Fabric Analytics | Expert in Azure Data Factory, Databricks, Synapse and Azure DevOps | Active Reliability Clearance
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Data storytelling is a powerful technique that involves presenting data and analytical results in the form of a narrative to convey insights and make the information more compelling and understandable to stakeholders Provide context to the OR model results by framing them within a broader business or real-world context. Help stakeholders understand why the analysis was conducted and what impact it has on the organization. Use anecdotes, real-world examples, and case studies to humanize the data. Connect the numbers to the experiences and challenges faced by individuals or departments within the organization. Highlight the challenges addressed by the OR model and how the proposed solutions can positively impact the organization.

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Vasiliy Zamolotov

Manager (ex-SAS, ex-Accenture) | Operations Research | Data Science Lead
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This is a critical part of connecting complex mathematical problems with business problems and communicating results to stakeholders. Starting from people in the workplace who participate in the process that was modeled, ending with project sponsors and top management. It is very important to present the solution as a business story in order to speak the same language with business knowledge holders.

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3 Data literacy

A third way to communicate OR model results is to improve data literacy. Data literacy is the ability to read, understand, analyze, and communicate with data. Data literacy can help stakeholders appreciate the benefits and limitations of the OR model, and ask relevant and critical questions. Data literacy can also help OR practitioners establish trust and credibility with their stakeholders, and foster a culture of data-driven decision making. Data literacy tools, such as Qlik Sense, DataCamp, or Coursera, can help OR practitioners and stakeholders develop and enhance their data skills and knowledge.

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Harsh Shah

Senior Azure Data Engineer | 3x Certified in Azure Data Engineering, Power BI, and Fabric Analytics | Expert in Azure Data Factory, Databricks, Synapse and Azure DevOps | Active Reliability Clearance
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Data literacy is crucial for effective communication of Operations Research (OR) model results to stakeholders. When stakeholders possess a good level of data literacy, they are better equipped to understand, interpret, and make informed decisions based on the information presented. By promoting data literacy among stakeholders, organizations can bridge the communication gap between data analysts and decision-makers, leading to more informed and effective use of OR model results in strategic decision-making processes.

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4 Data feedback

A fourth way to communicate OR model results is to solicit and incorporate data feedback. Data feedback is the process of collecting and using input from stakeholders to improve the quality, accuracy, and usefulness of the OR model. Data feedback can help OR practitioners validate and refine their model assumptions, parameters, and outputs, and address any gaps, errors, or biases in the data. Data feedback can also help OR practitioners involve and empower their stakeholders, and create a collaborative and iterative learning process. Data feedback tools, such as Google Forms, SurveyMonkey, or Qualtrics, can help OR practitioners design and conduct data surveys, polls, or interviews with their stakeholders.

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5 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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How can data analytics improve communication of OR model results to stakeholders?

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1 Data visualization

2 Data storytelling

3 Data literacy

4 Data feedback

5 Here’s what else to consider

Operations Research

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How can data analytics improve communication of OR model results to stakeholders?

1

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3

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5

1 Data visualization

2 Data storytelling

3 Data literacy

4 Data feedback

5 Here’s what else to consider

Operations Research

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