Just because data defects aren’t immediately apparent, doesn’t mean you don’t have a data quality problem. It’s true that there is no easy way to measure or value it, but imagine if your biggest competitor went into receivership, which is their assets would you like to get your hands on? Nine times out of ten, it’s their customer database. Surely that gives it a value? And if that’s true, why do so many companies neglect their data?
Data quality isn’t just about the savings made by avoiding mistakes; it’s about the success derived when you make a good business decisions based on accurate information. Getting a grip on dirty data and breaking the cycle of corruption and correction will ensure you:
- Make better-informed business decisions
- Improve profitability
- Dramatically improve response rates
- Generate increased sales
- Retain customers for longer
It’s actually not that hard to take control of data quality – step one is to get out of denial and admit that there’s a data quality problem and you’re halfway to solving it.
Its not even a big task if you apply the right tools. Software currently available on the market makes it simple to reference, cross-match and de-duplicate to deliver trusted data and information in the right place at the right time. It’s not even a resource-hungry or highly skilled task if you use the right software tools.
Why not take the seven step Data Quality program?
- Get out of denial and own up to the fact there is a data quality problem
- Get executive buy in; data quality is a business problem not a Marketing or IT problem
- Assess where the greatest damage is being done to identify where fixing the problems will generate the greatest return
- Look at what can be achieved tactically within each data silo to improve data quality
- Identify the defective business processes which often create a cycle of “correction and corruption”
- Research data quality improvement tools which will help solve the critical problems identified
- Work diligently to first identify, then correct and prevent the dirty data defects which damage the effectiveness of CRM systems deployed in your organisation