Our previous blog looked at the issue of disconnected data for Sports Organisations. For commercial success, it’s necessary to have accurate data, and to have it all in one place, to provide a reliable understanding of every aspect of the organisation. Having all data in one place is central to data strategy which gets results. But what does a data strategy look like?
Data Quality lifecycle
The data quality lifecycle shows the key stages of a great data quality strategy. Capture and Validate is the entry stage where data entering your system needs a gatekeeper, which only lets the good stuff through. Cleanse and Enrich deal with existing data’s inaccuracies and add valuable data to it. Analyse and Acquire are the processes of gaining insight from data and adding to it according to the insight you’ve acquired.
Traversing the Data quality challenge
Think of your lifecycle like this. You’re a mountaineer ascending Everest. Your summit is data quality and data management, which fuels successful marketing and strong partner relationships.
Each time you move forward the ice causes you to slip and you’re set back. The slippery surface is human error and data decay. These need constant management, or you’ll continually be slipping, making mistakes and suffering inefficiency.
Our data tools and technology are the mountain equipment; the crampons and the ice pick that keep you moving toward your goal. Each time you move forward you’re in a better, smarter position to traverse towards the summit. Commercial success.
To get your organisation stuck into data strategy, follow the lifecycle, putting the tools in place and continuing to develop and progress over time. It’s not a one off process, but a lifestyle change. The old adage in marketing remains true in data quality management; test, test and retest. This is the only way to understand what works and to take action about what doesn’t. Making your commercial database as profitable as possible will come through continual analysis and action.
Download our latest White Paper: The Marketers’ Ultimate Guide to Data Quality