Despite best efforts, scientific software often has to deal with a dazzling array of different file types, however, few are ubiquitous across science as the Excel spreadsheet. Whether it's project planning or report building, Excel spreadsheets are often the first port of call for bench scientists looking to store and share all kinds of scientific information.

As software developers, a single question is obvious: why?

Excel is not fast, it's not particularly easy to learn or use. It's labour intensive to get data in and out, major incompatibilities exist between versions and sharing up to date information is a pain. At first glance this seems to fly in the face of many of the central tenets of scientific software: openness, compatibility, ease of use, and real-time performance.

The key is flexibility, which gives Excel the (almost unique) ability to keep pace with the rate of change in scientific fields.

• Instant feedback
  Updates to data and their layout are realised immediately.
  
  
• Flexible modeling
  Fields of a modeled domain can be manipulated in a few clicks. Entirely new attributes and "models" are quick and easy to add.
  
  
• No penalty to change
  Making these changes is not only possible, it is positively encouraged, thanks to undo, versioning and autosaving.
  
  
• Extensible
  Functions and macros allow additional value to be added to data quickly.

The baked-in flexibility of a spreadsheet provides a very quick, iterative approach to data design and analysis, with the added benefit that you can print out those numbers and scribble on them. Scientists love to scribble.

For those working on 'real' software, it might be easy to bite our thumbs at spreadsheets and their creators; instead we should be proclaiming our love for them, and keep their patterns for rapid change at the front of our minds.