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Management Reporting

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Reporting to upper management

It is now time to consider how data should be reported to upper management. To begin with, there are a number of ways to report your insights and findings. Some of these include:

  • Real-time access for management
  • Regular updates
  • Comprehensive reporting at specified points throughout the year
  • Exception reporting
  • So-what analysis

What are upper management really looking for in order to make decisions quickly? Well, they want access to real-time tools that you can use to help them to make decisions on a daily or even an hourly basis. You may also need to have weekly meetings or conference calls. You need to specify comprehensive reporting at specific times. Moreover, there needs to be that combination of real-time reporting versus bulk batch reporting to come up with different layers of insights. These all drive different decision-making processes.

You also need to have exception reporting because, while there will always be regular analysis, you need to think about the more exceptional incidents. For example, if anything you need to determine how an exception will be handled if it arises.

So-what analysis

‘So-what’ analysis can be useful to stress test the impact and value of your recommendations and insights against common perceptions in the business. This is basically when you look at your results or your recommendations and you think “So what?”. What is the implication of the analysis to the business?

Best practices

Some of the best practices for reporting data to upper management include:

  • Distil the high impact findings, insights, and actions into a presentation or document.
  • Keep it simple.
  • Make it visually appealing.
  • Have both high-level and detailed reports to hand.
  • Include both quantitative and qualitative results.

However, be mindful of what not to report to upper management. Here are some suggestions:

  • Don't dwell on the details.
  • Guide the analysis, interpret the data for them, and provide insights.
  • Use words and charts to describe results for non-analysts.
  • Choose the most important data for them. You don’t have to give them everything!
  • Remember that sometimes less is more.
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Jack Preston

Jack Preston is a Data Scientist working within marketing analytics, with a particular focus on strategic customer loyalty. Jack has experience working in both small-scale startups and large corporates, including dunnhumby and Notonthehighstreet. He also holds an MSc in Business Analytics from UCL where he graduated with distinction.


Jack Preston
Skills Expert

This short course covers the principles of analytics and demonstrates techniques and useful tools that you can use to develop and refine your knowledge of data analytics.

You will learn:

  • The fundamentals of data, collecting data, and processing data, including best practices, techniques, and challenges
  • The principles of web analytics, the benefits and limitations of Google Analytics, terminology for reporting, and the legalities around consent and data privacy
  • The concepts of Big Data, the processes around data, including mining, scraping, cleansing, and de-duping, and the various languages and programs for testing your data
  • The importance of AI, Machine Learning, analysis types, the value of testing hypotheses, and forecasting based on the data available
  • How best to report and present data findings to management and the different tools available to you

Approximate learning time: 3 hours