Many asset managers consider their business to be data rich but knowledge poor. The key reasons for this challenge are missing, incomplete and/or duplicate data records as well as poor quality data in attribute fields. Decision makers, unsurprisingly, have a lack of confidence in asset data and as a result find it difficult to leverage the data and create value in the business. The challenge becomes even more difficult as many organisations wrestle to close historic data gaps but continue to create future data gaps with capital programs that don’t provide timely, complete and accurate data as new assets added to the portfolio. This presentation provides simple and effective suggestions to close existing data gaps and future proof your data model using asset management readiness specifications.