Guest blog by Tim Seears, Chief Technology Officer, Big Data Partnership as part of Big Data Week
(Originally featured on TechUK)
Implementing a Big Data programme is an investment, one which will take the time to realise fully a return, but that should not mean you invest for a long time before getting anything back. Structure a programme that aims to deliver short-term value as quickly as possible, and demonstrate value to stakeholders. This is vital to maintain momentum and commitment – and budget. Ensure the programme roadmap includes future vision and aspiration for the longer term, even if you don’t plan to implement those use cases yet. Your architects will thank you for it later, and you will save cost.
Many projects can also rot on the vine if they don’t remain agile. It is a reality of the world that requirements and use cases can, and will, change. Given the strategic importance most organisations place on their Big Data programmes, they cannot afford to ignore this reality. Structure and operate your projects to follow agile principles: both within individual development projects, and at the broader programme level. You can take this as far as keeping your use case roadmap agile, and keeping your data architecture agile.
By expecting and structuring a programme to be responsive to change, you can capitalise on new opportunities as and when they occur. These may come from changes in:
> The technology ecosystem (which are frequent)
> The user requirements (which are inevitable) or
> External market/environment (which represent the highest value, if you can exploit them).
> Modern agile data architectures and Big Data solutions are ideally suited to capitalise on the rapid pace of change, if you structure a programme and projects appropriately to embrace it.
It also remains important to demonstrate tangible business value early, and often. Many historic large-scale IT programmes have failed from lack of proof of value early enough in the process. A Big Data implementation is not immune to these traditional challenges, just because it uses the latest favourite technology. Structure your programme in a way that ensures it is use case-led, not technology led. Expose business value early, iterate and build on it rapidly to show incremental value. This can be achieved through careful structuring and prioritisation of the use case roadmap, and setting out to prove business value as well as technology functionality.
Remember, a Big Data implementation is often in reality a programme of business change, as well as a technology programme. Big Data practices can unlock insight hidden deep within your data, which often challenge the understanding an organisation may have of its users, customers, or the environment. That is, after all, the real value and the point. Prime your business stakeholders to embrace the integration of the new insights that will emerge from your Big Data programme. Be prepared to help pro-actively them change their business processes to adopt the new insight and to become data-led in every line of business. This will allow full and complete realisation of the business value possible from a Big Data implementation, and install an open philosophy across the organisation.
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