It is a mistake to think that your data has to be complete and clean for you to push ahead with analytics. You will leave on the table significant savings and insights that could be realized even from imperfect and provisional models or conclusions based on partial or not-fully-scrubbed data. For example, if you did not more than study the distribution of timekeepers who bill time to you from the five firms you use the most, that will be progress.
Lawyers like completeness and tidiness, but neither is a feature of complex data. Resist the conservative reins! This idea came from the Deloitte Review (undated) at page 16. Data is never perfect, so it is better to get your hands dirty and work with what you have than to delay, spend money, grow frustrated and perhaps never learn anything. Plunging in will help you figure out better what to collect and how to collect it.