The challenges of enterprise analytics are well publicised. McKinsey, Gartner and others regularly post the latest gloomy statistics on analytics programme outcomes. All the pundits agree that only a tiny percentage (fewer than 10%!) of big data analytics and digital transformation programmes succeed. 

But why do so many fail to flourish? The same pundits will offer you their “top 10” reasons. However, in our experience, these largely boil down to the same key underlying factor: culture.

To succeed in analytics, it’s about developing the people, processes and practices that allow analytics needs to take root and grow within your organisation. As 4IR takes shape, this is becoming all the more critical for survival, let alone growth.

It’s easy to get fixated on the technology, because it is the shiny thing. But the purpose is greater!

On the face of it, the culture of analytics can appear very much about a technology. But big data technologies are mature; there are solutions available for all manner of problems. Technology is like Bruce Lee’s “finger pointing a way to the moon.” If you concentrate on it, “you will miss all that heavenly glory!” The real challenge is building the culture and training your team(s) that will use the technology to point your company in the right direction. Do it right, and they will support and train each other to keep you on course for many years to come.

Every organisation has its own ecosystem, its own governance, its own history and its own style. The range of technology, both commercial and open source, can appear overwhelming. Every organisation must follow its own path to adapt the technology to its culture, and vice versa. The challenge is similar; the solution infinitely varied. 

For example, some organisations have teams of highly numerate specialists who are well placed to adopt data science tools and skillsets and apply them in their domain (for example your actuaries, biochemists, engineers, or R&D scientists). Other organisations will rely on their BI divisions to grow into their data science capability, and will often need even more help with up-skilling and introducing new technology. On the IT side, some organisations have wholly outsourced, while others have some degree of in-house with varying levels of support for new technology.

We are technology agnostic, but we do advocate open source technologies, simply because they are rooted in the kind of culture, ecosystem, and practices that support analytical success. Open source embodies precisely the kind of exploratory, experimental attitude, but with a rigorous, governed support framework. It is exactly this that you need to replicate: a flourishing creative hub that self-energises, but whose output is regulated (dare I say governed?) to match the needs, and style, of your organisation. There is give-and-take here, and an organisation can (and arguably should) evolve to adapt to analytics. But this takes time, and while it is ongoing, it is important to allow the analytics culture to grow….

If you are challenged with embedding analytics in your organisation, then turn to experts who live and breathe it with passion. We are passionate about putting data to work, using algorithms from the very simple and linear, to the cutting edge and complex non-linear. We like exploring and discovering, and helping you to do the same. 

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