September 15, 2015
In 1996, a sheep named Dolly made world headlines as the first animal cloned in a laboratory. At the time I was a graduate student in Molecular Biology and had a decent grasp of the massive complexity involved in such a momentous task. A year later, Little Caesar’s pizza released a humorous television commercial spoofing this event, with a group of scientists gathered in a viewing chamber while one of them simply pressed a large “CLONE” button, causing a sheep in the next room to suddenly multiply into two sheep.
Now, many years later, I wish the idea behind that commercial weren’t so comical. As a pricer who likes to get deep into data, there is nothing more frustrating than bad data – and nothing I want more than a “CLEAN” button with which to magically make the data completely accurate and trustworthy.
Alas, like the truth behind cloning Dolly, arriving at good data is often a lengthy, complicated, and even expensive process that can involve teams of people and months or even years of time. It’s almost never as simple as pulling some data field from an existing table somewhere. Painfully so, in fact.
However, just as Dolly was successfully created in a lab, clean data can truly exist in your data warehouse. The most important thing a company can do to ensure this happens is to have a clear and coherent data strategy that is agreed upon by all members involved. Some examples of topics that should be included in your strategy are:
- Who owns the data?
- Where is the data stored?
- What is the process for correcting data errors?
- Who determines what data is needed in the first place?
- What is the process for ensuring that the data makes sense?
If you find yourself without answers to the above questions, consider attending the Professional Pricing Society Fall Conference, where a day-long workshop will be given on “5 Steps to Improve Your Data & Enable Powerful Pricing Decisions”. This workshop will not give you a magic “CLEAN” button, but it will provide you with a solid backbone for creating a data strategy at your company, leading to better, cleaner, and more trustworthy data.