Poor data entry by employees is the number one culprit when it comes to flaws in customer data. That is why we have developed iDQ ™ as a solution for you that will save time and money while ensuring a high quality of data in your CRM system and customer master data hub. But even if you ensure your customer data quality during data capture, there will still be a need for ongoing maintenance and quality assurance.
A world of big reference data
Reference Data is a term often used either instead of Master Data or as related to Master Data. Reference data is those data defined and initially maintained outside a single enterprise. Examples from the customer master data realm are a country list, a list of states in a given country or postal code tables for countries around the world.
The trend is that enterprises seek to benefit from having reference data in more depth than those often modest populated lists mentioned above. In the customer master data realm such reference data may be core data about:
- Addresses being every single valid address typically within a given country.
- Business entities being every single business entity occupying an address in a given country.
- Consumers (or Citizens) being every single person living on an address in a given country.
There is often no single source of truth for such data.
Combining effective business processes and data quality
Exploiting these big reference data sources directly in business processes where customer master data is entered and utilized helps a lot in the quest for getting better data quality.
Getting the best and most relevant reference data within your home country isn’t easy. Getting it done for international reference data is a daunting task.
At the same time you often want to view these big reference data sources along with what you already have registered in internal customer master data repositories.
Add to that the rise of social networks, the new source of customer master data you have to mashup with traditional sources.
iDQ is your companion in getting data quality right the first time by exploiting the wealth of global reference data and at the same time getting more efficient business processes with huge time saving in data entry and investigation processes.