Five things you need to do to operationalise big data

Five things you need to do to operationalise big data

Posted on October 6, 2015 by TheStorageChap in Big Data and Analytics

Big data’s been on every large organisations to-do list for a few years now. We hear a lot from companies that have a real appetite to get programmes moving but haven’t found a way to weave big data analytics into their organisational fabric. How do you operationalise big data ?

Evolving any organisation down a path of change this significant is a big challenge, and whilst it’s impossible to provide a formula that works every time, there are five things I see companies doing that have managed to make the transition. I’ll be discussing these further at the upcoming Chief Data Officer Forum Europe this month, so I’d be interested to hear your views on these, and others, you’ve experienced.

  1. Appoint / identify a board level sponsor for the analytics programme (CDO, CFO, CIO, CEO) – it doesn’t matter where they sit in the lines of business, but senior buy-in is necessary to drive support from the wider organisation and to place someone in a position to influence and evangelise that change. It can sometimes help if they’re not in an operational function (i.e. IT) so it can be perceived as a strategic change programme led by the business rather than an IT project being foisted on the management. Strategic CIOs, of course, will be able to sidestep this.
  2. Eliminate the infrastructure challenge. For big data to be part of the fabric, ‘computer says no’ can’t be a feature of your IT experience. Data lakes that allow for near real-time analytics to be conducted without the need for a time consuming or costly data ingestion process will help deliver returns sooner rather than later.
  3. Work with your applications teams to enable apps for easy data sharing. Not every piece of data you might want to interrogate or draw upon is easily accessible. It’s vital to unlock the data you need from applications that don’t naturally make data available.
  4. Identify or create a team of data analysts or data scientists, as needed. They’ll consult into the business on specific problems. But, also, crucially, they need to have the freedom to spend time exploring data in and around the business to derive unexpected insights.
  5.  Package and promote the outputs of each project. Strategic initiatives – especially significant ones that require a shift from the ‘business as usual’ methods – need strong internal champions and promotional support. It’s vital that the change that’s being effected has enduring impact, and isn’t just a flash in the pan. The service, insights and capabilities of the analytics programme need to be evident and well measured to demonstrate the potential of the technology.

If you have any other thoughts, I’d love to hear them in the comments.