Getting starting with analytics isn’t just about getting the right tools in place – a change of mindset is also needed, according to Gartner.
If changes are made then success with Big Data projects could be reduced. The research firm predicts that 60% of Big Data projects through 2017 will fail to go beyond piloting and experimentation, and will be abandoned.
The firm has identified four best practices that leaders in BI and analytics can use in order to get analytics initiatives off the ground.
First of all it is necessary to choose a business problem that offers an initial win. This means that they need to work with business leaders in order to identify problems to tackle.
The outcomes of this should be reviewed to identify the decisions that could provide either the biggest impact or the quickest payback.
Secondly, the firm advises to use outsourcing and to buy packaged apps when you are lacking in advanced analytics expertise. Building advanced analytics capabilities yourself can be a slow process, so outsourcing can lead to quicker wins.
The third idea that is advised is to identify the stakeholders in your organisation that need to be convinced of the value of advanced analytics. It is necessary to have a business case that demonstrates the value of the project.
Having the stakeholders’ on-side can be difficult to achieve, however, it is necessary to get their support as they can derail a project.
The fourth and final suggestion is to decide whether you want to build the skills and tools internally. The firm say’s that businesses that achieve best-in-class advanced analytics solutions typically do some through a build strategy.
Building these skills and tools internally though isn’t often the best way to start. Gartner, says: "It makes sense for an organisation to build advanced analytics internally if (a) analytics is a critical differentiator in its industry or if the area is of strategic importance.
"(b) A high level of agility and granularity of control is required, and (c) there are many opportunities across the organisation to apply analytics in multiple use cases or lines of business."
Those that do decide to build must have core business skills, IT skills and data science and quantitative skills.