The Value is in the Answers, not the Data
Beyond all the hype and discussions, adoption of big data is simply inevitable. The number of successful case studies continues to expand, supporting the industry’s sentiment that when companies embrace data and analytics in their operations, from customer services to operations, they can deliver productivity and profit gains. Broadly speaking, the business outcomes we’ve seen of Big Data will deliver; improved operational efficiency; improved customer intimacy; generate new business/monetisation and improve risk management.
Easy, right? Not exactly.
Big Data should be a commitment for companies. Big Data projects demand management commitment, clear direction and money to be successful. Initial efforts should be focused on two points
- Get management commitment – Build an inclusive plan. It may sound obvious, but a good strategic plan highlights the critical decisions that must be made: whether to focus on high margins, faster growth, improved customer experience etc. The next step is synchronising your initial focus area with investments in the right tools, analytics, infrastructure and skills that will ultimately create the business value you are seeking. If management, IT and data scientists have a common ‘plan’ to work from, they will have a better chance of delivering better business outcomes.
- Big Data capabilities – By understanding the plan and the prioritised initiatives, the Big Data owners are in a much better position to choose the internal and external data sources, infrastructure, analytic models and importantly the skills required to exploit this potential. This step is critical. Help the Data Scientist to help you. Your Big Data capabilities will have a direct impact on the time, effort and eventual outcomes that a Data Scientist has to deliver. I’m not advocating spending millions. Big Data architectures typically start small but then grow with number of queries, departments and strategic questions it draws in. In most cases your existing data warehouse is supplemented with a Big Data architecture that will be significantly more cost effective to acquire initially and run in the future.
Quoting one of the large financial services companies in the UK, ‘Just start’. They realised their adoption of Big Data was inevitable – the increase in their data volume was just too big and too expensive to be managed by the traditional monolithic data warehouses. They were thinking big and started small, and now they’ve grown to a critical mass that can support the organisation as a whole.
I realise what I say is not necessarily easy. Building an inclusive plan is fraught with complexities and politics, and competition for IT budget is ever present. However once you compare the cost of Big Data vs. its conventional counterparts (even just expanding your existing Data Warehouse) and what additional capabilities it offers you will realise why I say the adoption is inevitable.
Think big and start small.