Challenges in engineering writing

Writing for clients and other nontechnical audiences

One of the main challenges in engineering writing is that you are trying to convey technical information to people who may not understand the technical detail, but will still need to make important decisions based on it.

The key tip therefore is to keep your audience in mind when writing:

  • Make sure your language is clear.
  • Explain your findings. Make sure that the implications and conclusion are clear at every stage (eg the model showed an increase over time; this means that additional inputs will be needed to maintain the same production rate).
  • Show your reasoning. Say explicitly what you have concluded and why. Make sure there is a direct line between the aims of the project, what the results were and what you recommend (eg the model shows that the automatic pump reduces energy use by 23%; automating the pump process will therefore reduce your costs).
  • Do not get lost in detail. When a project has produced a wealth of data, it can be tempting to present it all in your report and discuss every twist and turn. But this can be confusing for your readers. Think about the key points of your story and how the data relate to your conclusion. Only include the main pieces of data in the body of your report, and keep the rest in an appendix.
  • Include assumptions. For clients to make good decisions, they must know all the implications of your work. Make sure you include your assumptions, and limits in their validity, so your client will have an accurate understanding of the meaning of the results.

Note that showing full reasoning or listing assumptions can sometimes be at odds with clarity and brevity. You can find ways around this, such as moving details to an appendix, or including summary or key points boxes.

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Ensuring accuracy

Engineering research and reports are usually designed to have real-world application. Accuracy is therefore paramount, to ensure that the application of the work is as safe as possible and performs as it was intended.

Do not overstate your findings. For example, if a positive result is not certain, include accurate estimates of the likelihood of success, and any caveats to achievement. Describe clearly the potential risks and benefits of any action, along with any risk and error estimates.

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