While much of the discussion about information management centres on things that are new and exciting, it is easy to neglect some of the basic principles that the profession has learnt over the last decade. Here are just five things that I think are among the most important to consider if your project is to be a success.
First, use a standard project plan. MIKE2.0 has been available for some years now and provides a work breakdown structure which is comprehensive. Such an approach allows you to involve contractors and multiple service providers without being locked into anyone’s proprietary method.
Second, use data models that have been published. There are many of them around ranging from low cost publications by authors such as Len Silverston through to enterprise models provided by the major software vendors. Even the most expensive model is typically much cheaper than the labour cost that it can save.
Third, borrow from Don Rumsfeld: “There are known knowns. These are things we know that we know. There are known unknowns. That is to say, there are things that we know we don’t know. But there are also unknown unknowns. There are things we don’t know we don’t know.” The data warehouse is trying to manage the complexity of the entire business. You can’t possibly know everything and hence requirements analysis should focus on the fundamental principles of the organisation and those things that are hard to undo later.
Fourth, the foundation of tomorrow’s enterprise data warehouse is unlikely to be today’s tactical solution. Avoid the temptation to make the first iteration self-funding, the organisation has to be prepared to make an investment otherwise there are always cheaper short term solutions.
Finally, ask yourself whether your organisation is really as unique as your stakeholders think it is. One of the most common reasons given for the use of unusual architectures or data models that don’t borrow from published materials is that the business is unique. Everyone is looking for a point of differentiation but that doesn’t mean that you shouldn’t adopt standards where possible. It is unlikely that the use of an unusual data warehouse architecture is going to enable a store to sell more toothpaste. That same store, might, however, gain a real edge by combining consumer and supplier data in a new and novel way building on existing approaches to modelling the data.