Data Analysis & Reporting

Reporting: The process of organizing data into informational summaries in order to monitor how different areas of a business are performing.

Analysis: The process of exploring data and reports in order to extract meaningful insights, which can be used to better understand and improve business performance.

 Data Analysis and Reporting

The manner in which data is analyzed and reported will largely have to be tailored to the specific circumstance or organization. Overall, it will be necessary to tailor the analysis and reporting methods by the type of data as well as to the intended audience. Managers are usually more interested in the “big picture” information while not being particularly interested in the level of technical detail However, regardless of the level of detail, the analysis should always portray results that can be translated into action.

 

How Data Analysis Helps You Find Answers

Data analysis is the process of examining data with the goal of answering a business question that supports decision-making. An analysis can reveal powerful insights if you are able to uncover why something is happening and what you can do about it.

 

Here are some key steps to building an analysis that helps uncover insights:

  1. Gathering data

The first step to be able to go through with the data analysis is to collect the data to begin with, software such as CRM could be a great help in gathering the data you need from your customers to be able to start your analysis.

 

  1. Start with Specific Questions.

Before you dig into your data, write down what questions need to be answered to achieve your goal. The more pointed the question, the more valuable and actionable the answer will be. For example, instead of asking, “How can my sales reps improve performance?”, you need to ask something like this: “Where in the sales pipeline are my higher performers spending their time vs. lower performers?”

 

  1. Categorizing the data

It would always be much easier to categorize the data you collect to be able to match the questions you’ve asked, once you’ve managed to categorize the data, you’ll be able to view it in a much simpler form that would make it easier for you to analyze.

 

  1. Identify Data Sources.

When you start with a detailed question, you are able to pinpoint the data needed to formulate an answer from that question. Using the example above, you can determine that you’ll need sales pipeline data, specifically time allocation by each rep within each stage of the pipeline.

 

  1. Interpret Results.

Data analysis still requires you to make a conclusion about your findings. As you find interesting facts or patterns and put them in context to your business question, you’ll want to test your conclusion by asking yourself, “Does the data answer my question and defend against any objections?

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