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Ask for dates instead of number of years

When you are doing any kind of data acquisition, (for example- generating a lead from a prospect, admitting a patient through an admission form, getting a customer to fill-up application form for your product), always try to ask for dates instead of tenure.
 
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When you are doing any kind of data acquisition, (for example- generating a sales lead from a prospect, admitting a patient through an admission form, getting a customer to fill-up application form for your product), always try to ask for dates instead of tenure. Some examples are:

  • Date of birth instead of age in years.
  • Year and month of moving in current residence, instead of number of years/months in current residence.
  • The year/month of joining the current job instead of number of years/months in the current job.

Sometimes a customer may not be able to remember the exact date or even the exact month related to a given event. However the same issue stays if you are asking for a tenure.

The reason is that the tenure stays as a static information which may not change with time (though some systems have a way to constantly change the tenure -for example incrementing age by 1 at year-end processing of the systems) in most of the cases. Therefore this information becomes stale as well as misleading. This problem becomes more acute with legacy/old systems. Apart from bad analysis, it may also lead to wrong customer segmentation and positioning of your product. For example, you may create new products assuming that 80% of your customers belong to "young generation", where as some of them might be older, while your system show their age, which was recorded some years back.


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Relevant Links to this page
Principles & Rules → Data Quality is a subject of business ownership and not of IT-ownership → Principles & Rules → Don't create a hype on Data Quality Program. → Principles & Rules → Sponsor for a Data Quality Program → Practice Techniques → Business Case for Data Quality → Principles & Rules → Data Quality is not Perfect Quality → Principles & Rules → Engage the Vendors in Data Quality Program → Practice Techniques → How to get more data along with Sales leads → Principles & Rules → How to Maximize the effectiveness of Data Stewardship → Practice Techniques → Field Tips Series#1- Data Mapping and Assessment → Principles & Rules → Data Management Standards for Data Entities will be a mix of collaboration and top-down → Principles & Rules → Data Management standards for data entities are not only for IT systems → Principles & Rules → Cascade your standards and guidelines to business partners and Vendors → Principles & Rules → Data quality assurance and control guidelines are no-brainer. Publish one immediately and evolve thereafter. → 
 
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Relevant links to this page
Data Quality is a subject of business ownership and not of IT-ownership
Don't create a hype on Data Quality Program.
Sponsor for a Data Quality Program
Business Case for Data Quality
Data Quality is not Perfect Quality
Engage the Vendors in Data Quality Program
How to get more data along with Sales leads
How to Maximize the effectiveness of Data Stewardship
Field Tips Series#1- Data Mapping and Assessment
Data Management Standards for Data Entities will be a mix of collaboration and top-down
Data Management standards for data entities are not only for IT systems
Cascade your standards and guidelines to business partners and Vendors
Data quality assurance and control guidelines are no-brainer. Publish one immediately and evolve thereafter.
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