Understanding and addressing the Big Data challenge
Starting out on the Big Data journey is daunting for any organisation. And there are plenty of distractions that can lead you astray along the way.
While data can be applied to address many business needs, prioritising where to start can be one of the biggest challenges, says Craig Saunders of Xerox. As experience is gained with particular big-data-driven services or capabilities however, usually specific business needs emerge as being of particular importance or urgency.
In succeeding with individual Big Data projects, organisations will recognise the top issues relevant to their business; arrive at a deeper level of understanding and control of them.
Break down silos
Successful exploitation of Big Data calls for silos to be broken, and this is a major task. Customers are demanding a single view of services, with interaction mechanisms and information flows on their terms, personalised to their needs.
On the flip side, organisations understand that to respond effectively to this demand, they need to have a single view of the customer.
While integrated and personalised services are emerging at a fast pace, the reality often is that the joined-up view presented by businesses to customers tends to hide a mess of legacy structures, processes and technologies that are complex to bridge.
When it comes to data, it can sometimes take large organisations weeks, even months, to figure out who owns the relevant data sets, and which internal and external partners touch or affect each element.
Make no mistake, silo-breaking is a huge task requiring significant investment and changes in attitude and working culture.
While this is particularly true for ‘non-digital’ organisations, ‘digital natives’ are not completely immune to the problem of silos — especially if their business has grown rapidly. A fast rate of expansion may have led to the creation of silos if there have not been clear and rigorous processes from the start to prevent this.
The sheer size of the task, together with the rapid pace of change within the field of big data, makes it challenging for large enterprises to have a wholesale, top-down strategy for Big Data. The risk and return of such a strategy is often difficult to quantify, and successful implementation requires time and a methodical and consistent approach.
This is not easy in a fast moving environment. There are plenty of misleading trails to follow. There is also a tension between the wish to rationalise, integrate and centralise, and the wish to encourage agility by letting everyone get on and move fast to capture more business opportunity.
However I actually find it encouraging that Big Data throws up so many challenges on so many fronts. It shows that the real challenge is awareness, understanding and planning. For all the attention its receiving, Big Data analytics is no different from any other technology, market opportunity or strategic constraint. The basic business rules of understanding the landscape, having the right strategy, hiring the right talent and making use of the right strategic partners still apply.
Understand how data can serve you
The challenges are at least as much about culture and people as about technology. Successful strategies — yours and those of your partners — will focus as much on people, processes, and what you are trying to achieve for your customers, as on data warehousing and analytics techniques.
Whether you are just starting on the journey or are already well on the way down the road, if you feel in any way overwhelmed or tempted to follow that trail of breadcrumbs, I would simply say: be encouraged to get help. It’s readily available at every level; you don’t have to go through expensive learning curves when others have been there before you.
Few are ‘going it alone’ in the Big Data world – there’s an ever-growing ecosystem of companies coming together to understand how their data can serve them, and their customers, better.
The author of this blog is Craig Saunders, director — analytics resource centre, Xerox Consulting and Analytics