Why are you collecting the data?
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What data do you need?
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How will the data look?
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Equally important is the strategy for data capture. How do you ensure that our data collection process is efficient, accurate, and minimally disruptive? Who is involved in this process, and is their user experience taken into consideration? Is an understanding of the physical environment they will be navigating woven into strategy and toolset? Engaging with those who collect and provide the data ensures that the process is user-friendly, and that the data collected is of high quality.
These questions should be realistic, comprehensive, and facilitate the required level of detail—leading to valuable data insights that manifest as operational efficiencies. This process also helps identify where the data may be logically sourced from, ensuring the right data is collected from appropriate sources.
This clarity also facilitates proper project management to mobilize acquisition resources and allocate data processing, post-processing, and storage resources—ensuring the collected data is optimally handled after collection.
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How do you get the data?
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As you formulate your questions, it’s equally important to envision what good data looks like. Are you seeking quantitative data that provides numerical insights, or qualitative data that offers deeper contextual understanding? Should the data be structured, fitting neatly into predefined categories, or unstructured, capturing the richness of natural language and multimedia? Good data is accurate, reliable, and relevant. It should be comprehensive enough to answer your questions thoroughly yet specific enough to be actionable. By defining these characteristics, you set clear expectations for the data aimed to collect.
Here's a great opportunity for some upfront quality assurance. Determine the form of which the data to answer our questions will take. Not every question will have the same data format, but establishing consistencies and eliminating opportunities for messy entries begins here.
After understanding the purpose of your data journey, you can decipher what data is needed for successful deliverables. A set of questions will determine these points and values. Workshopping these questions requires the attention and collaboration of all involved initiative stakeholder groups because their input ensures that the right questions are asked.
Simply put, what is the purpose of the initiative? This is possibly the most important question. It sets the stage for structuring an optimal marriage of strategy and solution for specific results. A united understanding of the initiative's purpose prevents falling short of the requirements for success and allows for the possibility of additional value to be extracted.
The success of your data journey hinges on the strategies and solutions employed for data capture. What is the best tool or mechanism for capturing the data you need? Is it a survey, a sensor, a database, or perhaps a combination of the three? The choice of tool should align with the type of data you are collecting and the questions you are seeking to answer.