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What are some of the advanced data analysis techniques and methods that you apply for operational planning?

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Operational planning is the process of defining, organizing, and executing the activities and resources needed to achieve specific goals and objectives. Data analysis is an essential component of operational planning, as it helps to identify problems, opportunities, trends, and patterns that can inform decision-making and action. However, not all data analysis techniques and methods are equally effective or appropriate for different operational planning scenarios. In this article, you will learn about some of the advanced data analysis techniques and methods that you can apply for operational planning, and how they can help you improve your performance, efficiency, and outcomes.

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Kevin Vega

Cyber Operations Manager | Army Veteran

1 Predictive analytics

Predictive analytics is the use of statistical models, machine learning, and artificial intelligence to analyze historical and current data and generate predictions about future events, behaviors, or outcomes. Predictive analytics can help you with operational planning by enabling you to forecast demand, optimize inventory, allocate resources, prevent failures, reduce risks, and enhance customer satisfaction. For example, you can use predictive analytics to estimate how much product you will need to produce or order based on past sales, seasonal trends, and market conditions, and adjust your production or procurement accordingly. You can also use predictive analytics to identify potential issues or failures in your equipment or processes, and take preventive measures to avoid downtime or losses.

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Kevin Vega

Cyber Operations Manager | Army Veteran
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When employing this method, it's easy to focus on the analysis and assessments, but fail to include others in that process. Even if you are a one-person analysis section, it's beneficial to bring in other minds from other functions to get a holistic view of all the data. It is never recommended to plan in a pipeline apart from other departments.

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2 Prescriptive analytics

Prescriptive analytics is the use of optimization, simulation, and decision analysis techniques to generate recommendations or actions that can help you achieve your desired goals or objectives. Prescriptive analytics can help you with operational planning by enabling you to evaluate different scenarios, trade-offs, and alternatives, and choose the best course of action based on your constraints, preferences, and criteria. For example, you can use prescriptive analytics to determine the optimal mix of products or services to offer based on your customer segments, profitability, and capacity. You can also use prescriptive analytics to design the most efficient routes, schedules, or assignments for your delivery or service operations based on your resources, costs, and deadlines.

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Kevin Vega

Cyber Operations Manager | Army Veteran
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One of the main ways we helped everyone get on the same page with this was "Battle Drills". These were flow charts for different scenarios that included actions, decisions, and information-sharing responsibilities for each section of the Operations Center. We deliberately spent time practicing each drill multiple times. This did ingrain the muscle memory for what needed to be done in each section. One way you can enhance everyone's capabilities is to switch roles during the practice so that anyone in that section can fill in if an individual is unavailable.

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3 Text analytics

Text analytics is the use of natural language processing, sentiment analysis, and text mining techniques to extract, analyze, and interpret information from unstructured text data, such as customer reviews, feedback, emails, social media posts, or documents. Text analytics can help you with operational planning by enabling you to understand the needs, preferences, opinions, and emotions of your customers, stakeholders, or employees, and use that insight to improve your products, services, processes, or communication. For example, you can use text analytics to identify the most common complaints or praises from your customers, and use that feedback to enhance your quality, features, or customer service. You can also use text analytics to monitor the sentiment or tone of your online reputation, and use that information to adjust your marketing, branding, or public relations strategies.

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4 Data visualization

Data visualization is the use of graphical tools, such as charts, graphs, maps, or dashboards, to present, explore, and communicate data in a visual and interactive way. Data visualization can help you with operational planning by enabling you to see patterns, trends, outliers, or correlations in your data that might otherwise be hidden or difficult to comprehend. Data visualization can also help you to share your findings, insights, or recommendations with your audience in a clear and engaging way. For example, you can use data visualization to display your key performance indicators, such as sales, revenue, or customer satisfaction, and track your progress towards your goals or targets. You can also use data visualization to compare your performance with your competitors, benchmarks, or industry standards, and identify your strengths, weaknesses, or opportunities.

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Kevin Vega

Cyber Operations Manager | Army Veteran
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The key factor for data visualization is to "know your audience". Data is a tool that helps drive the decision-making process. So the data that's presented needs to help drive that and inform decision-makers. Also, there should be an emphasis on the Recommendations portion because the information is only useful when it drives a decision. When the recommendation is presented, it should also be presented in a way that your audience can understand. In the organization or industry vernacular.

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5 Data governance

Data governance is the set of policies, standards, roles, and processes that ensure the quality, security, availability, and usability of your data throughout its lifecycle. Data governance can help you with operational planning by enabling you to manage your data assets effectively and efficiently, and ensure that they are aligned with your strategic goals and objectives. Data governance can also help you to comply with legal, ethical, or regulatory requirements, and avoid data breaches, errors, or misuse. For example, you can use data governance to define who can access, modify, or share your data, and under what conditions. You can also use data governance to establish how your data is collected, stored, processed, or deleted, and ensure that it is accurate, consistent, and reliable.

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6 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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Ufuoma Uwejeyan

General Manager @ Sage Grey Technologies Limited | Strategic Finance Leader| Driving Revenue Growth & Operational Excellence | Expertise in Fintech, Payments & E-commerce | Championing Women in Tech
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Contingency planning is also important. So as to know how to move forward at all times. We most always get to our desired goal.

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What are some of the advanced data analysis techniques and methods that you apply for operational planning?

1

2

3

4

5

6

1 Predictive analytics

2 Prescriptive analytics

3 Text analytics

4 Data visualization

5 Data governance

6 Here’s what else to consider

Operational Planning

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What are some of the advanced data analysis techniques and methods that you apply for operational planning?

1

2

3

4

5

6

1 Predictive analytics

2 Prescriptive analytics

3 Text analytics

4 Data visualization

5 Data governance

6 Here’s what else to consider

Operational Planning

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