With vast amounts of ever richer data being stored in the world, it has never been more important to have a well-planned, cohesive strategy for gathering, storing and using data to inform, guide and grow your business.
Whilst there is enormous potential benefit from implementing the right strategy, getting it wrong presents a number of risks. A bad strategy will frustrate, misinform and, more often than not, mean time is spent on trying to find information rather than using it to inform and provide insights.
There are many potential pitfalls when it comes to implementing a data strategy. Here are our top three, based on our experience at CSL:
Trying to boil the ocean. Projects are often too ambitious in their initial scope. One company we worked with had a data project that was due to take 5 years – before even starting on delivering any analytics. Business requirements change constantly, so a 5-year project is doomed to failure from the outset. To get around this, look at the whole requirement and then break it down into smaller deliverables. This allows the project to deliver fast value, whilst being able to grow over time and evolve with requirements.
One size fits all. We have seen many projects where the desired outcome is to create a standard solution across the business. These projects usually fail because there is simply too much variation in the data and requirements across functional and geographical areas. If the project comes to completion, it normally delivers a solution that doesn’t really fit anyone. The best way around this is to have a comprehensive data solution which can be used to deliver tailored outputs according to requirements. One effective way to avoid falling into this trap is to create local data marts to meet specific requirements. The data marts can then supply summarized/aggregated data to a central repository for global or organisational analytics.
Ill-defined requirements. It is critical to define your systems and requirements with consistent metrics, making sure these continue to be right as the project progresses. During a consultancy period with one client, there was a key metric that was discussed often. When we drilled into this, it turned out that different departments were calculating this metric in different ways. This metric was then being discussed across the organisation without people realising that they were not talking about the same thing. This problem can be avoided by scrupulous planning and creation of a detailed common data model and dictionary. The involvement of a third party in the process can often help in terms of providing an objective viewpoint.
There is no escaping the fact that designing and delivering an effective data strategy is a complicated and time-consuming business. However, the benefits to the business when it is implemented well are enormous.
If you would like to dicuss further, contact us on email@example.com or call 01483 528302