1.

Project size and development methodology

Because they are intended to serve multiple areas of the business, financial data warehouses are, by nature, large projects.

Businesses that invest upwards of USD10 million in the development process typically aim to create a strategic reporting platform that is sufficiently flexible to support a wide variety of requirements for sales, risk and compliance teams.

…60 percent of the projects surveyed were late, over budget, missing key features or cancelled altogether.

However, the latest research from the Standish Group indicates that outcomes are seldom positive. In fact, large projects were found to have success probability of only 40 percent; the remaining 60 percent of the projects surveyed were late, over budget, missing key features or cancelled altogether. For development projects within the financial services sector, the outlook is gloomier still; just seven percent of such projects succeeded.

The popularity of agile development methodologies is booming, and such approaches might appear to offer an attractive way to improve the chances of your development project succeeding. Can breaking up a large project into smaller, iterative stages help financial services organizations to cut through the complexity and improve their chances of success? The answer seems to be “no”.

Unlike reporting solutions for industries such as retail—in which getting closer and closer to a working system with each new iteration is an acceptable compromise to shorten the development cycle—the financial services sector demands complete accuracy 100 percent of the time. Compliance teams, for example, cannot work with ballpark figures, and new investment decisions must be made using precise data.

It is perhaps unsurprising, then, that Standish Group’s research indicates that agile methodologies only improve outcomes on small-scale, low-complexity development projects. For large development projects with exacting requirements for accuracy, the success rates still hover around the 40 percent mark, regardless of whether agile or waterfall methodologies were employed.

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Whitepaper
Five things you must know before you build a financial data warehouse

Exploring the risks and opportunities of a do-it-yourself approach.