What's the best way to prioritize data questions in food manufacturing?

1 What are data questions?

Data questions can help you understand your food manufacturing processes, products, customers, markets, and competitors. For instance, you may want to know how to reduce waste and improve efficiency in your production line, what the most profitable and popular products in your portfolio are, how to increase customer satisfaction and loyalty, and what the emerging trends and opportunities in your industry are. Collecting, analyzing, and interpreting data can provide answers to these queries.

2 Why prioritize data questions?

Prioritizing data questions is essential for any food manufacturing business, as it helps you focus on the most urgent and important problems or challenges, identify the most valuable and actionable insights or opportunities, and align your data strategy with your business strategy and objectives. This way, you can avoid wasting time and money on irrelevant or low-priority data questions.

3 How to prioritize data questions?

Prioritizing data questions in food manufacturing can be done using a scoring system based on three criteria: impact, feasibility, and alignment. To do this, first score the data question from 1 (low) to 5 (high) for each criterion. Impact measures how much answering the question will improve performance, quality, or profitability; feasibility considers the availability, quality, and reliability of data sources and the tools needed to analyze them; alignment evaluates how well the question aligns with goals, vision, or values. Add up the scores for each data question and rank them from highest to lowest. A spreadsheet or matrix can be used to compare and visualize these data questions. The higher the score, the higher the priority.

4 How to use your prioritized data questions?

Once you have your prioritized list of data questions, you can use it to guide your data collection, analysis, and interpretation activities. For instance, allocating your data resources and budget according to the priority level of each data question, defining the scope, timeline, and deliverables of each data project or task based on the priority level of each data question, communicating your data priorities and expectations to stakeholders, team members, or partners, and monitoring and evaluating your data results and outcomes based on the priority level of each data question can help you make the most out of your data.

5 How to update your prioritized data questions?

Your data priorities are not fixed. They can change over time as your food manufacturing business evolves, your data sources and capabilities improve, or your market and customer needs shift. Therefore, you should review and update your prioritized list of data questions regularly, at least once a quarter or whenever there is a significant change in your business environment. You can use the same scoring system to reassess your data questions and adjust their priority level accordingly.

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?