Salutary reminder to all that eye watering data visualisation, visual data discovery galore, self-service analytics and the lure of the IoT & Big Data Analytics can all crumble to dust.
Too often BI & Analytics projects do not start by asking the right questions. What will we do differently as a result of this project and will it make a big difference?
Will the cultural DNA of the organisation encourage people to use the results or will they spend the whole time arguing about who has the right data?
Will the small project that received rapturous applause scale across the whole organisation, across geographic boundaries and business units?
And if we can make better decisions can we also execute better decisions.
The uncomfortable truth is that we must start to optimize the results we can actually achieve rather than the results we can theoretically achieve. These two standards can be quite divergent in the world of big data. Instead of focusing solely on the power of the analytics themselves, also require that the process will meet other, more pragmatic goals as well. If your solution won’t scale, or your corporate systems can’t make use of the results, or your people will refuse to use the results, then all the theoretical value in the world will yield nothing in practice.