I have just looked at a range of general/basic open source statistics programs. Some had extensive lists of tests available. Some had attractive output. And some made it easy to edit or import data. But I couldn’t help feeling your typical business analyst, school student, or medical/social sciences researcher with rusty statistics skills would feel quite daunted by the offerings I experimented with. Which got me thinking about the different use cases for general purpose statistics/analysis/reporting applications.
So what should the focus be when designing SOFA Statistics and what messages should be communicated and to whom?
Here are some messages that could be made by a statistics/analysis/reporting application:
- candy – beautiful output, attractive website, splashscreen, dialogs etc
- comfort – easy interface, lots of help at appropriate level
- communication - stats are well explained e.g. difference between mean and median
- correctness - stats you can trust, transparent, verifiable, certified by experts
- community – help is available for whatever level you are at (school homework, business results, advanced stats, integration with Office suites etc)
- credibility – backed by a real company, going to be here for the long run, reference group has an impressive membership with good coverage, people have appropriate qualifications etc
- continuity/compatibility – no need to abandon existing data to start getting benefits of new system. Has special “Help for users of [popular stats program name here]” etc.
- code – using the right software, the coolest programming tricks etc
- cheap – no money and little time required to use
- customisability – can make work with other systems, can integrate with other systems, can automate processes
And lining these messages up with potential groups they might appeal to:
- schoolkids – cheap, comfort, communication, community, and candy
- teachers – cheap (students can use it), comfort, communication (educational), community (start sharing stats teaching resources while they are at it), correctness
- university students (social sciences etc) – cheap, communication, community, correctness (so they’ll be allowed to use it)
- university students (statistics – starting off) – same as social science students
- statisticians (academic, professional) – correctness (paramount), credibility, continuity, customisability (can extend for special needs), cheap (they already have licenses for other products, plus they may want clients to do preliminary analyses using a free product they know themselves)
- business analysts – continuity/compatibility (must work with Excel, Word, mainstream web browsers etc), candy (produce lots of reports that managers like to look at and show others), comfort, communication (may be very rusty on stats skills), credibility (a must-have for this group), customisability (want to be able to automate processes e.g. reports), community (where people show them how to automate things, tricks to get problems solved etc)
- social science researchers – credible (so they can publish based on the data), candy, continuity/compatibility (so they can fall back on an established stats program if there is a problem or if SOFA can’t do something they need), comfort (may be good at social sciences but not computers/programming etc)
- school administrators – cheap, customisable (for their curriculum)
- business integrators – customisable, code (developers become more important and they care about code), cheap (so they can make their profit too), compatibility (with all the systems, input and output, they want to integrate with), credibility (can they make deals with you, will you be around in 5 years time?)
- geeks/developers/coders – code
Of course, having a message is one thing – delivering on it is another. But it is important to have a clear sense of a project’s priorities and a clear message to take to different groups.