Often in internal discussions at New Canvas Advising (NCA), the conversation is rich and multi-layered as Hannah talks through applying scientific principles to practical business realities. Very often, I think, “this would make a great blog”, but then time presses on and we forget the moment or idea. I decided to transcribe snippets of conversation and offer them as “mini-blogs” along with related articles from other sources. Below is an excerpt from a recent conversation about data and reveals NCA’s philosophy of the use of data and analytics to support business endeavors. We welcome you to join our conversation and share in the comments your own key insights into the ubiquitous topic of data!
"All data is not created equal.
All data is not information.
All statistics are not meaningful analysis.
People can be persuaded based on their own personal opinions, biases and personal experiences that inform long-held beliefs.
Data is shaped by many things: business need, financial position of an organization, operating model, and the rhythm of business.
What the data reveals depends on how starkly you want to look at the data measured against how serious you are about change. It is reflective of the business, but not independent of the business.
Data doesn’t objectively materialize. It is imagined and designed for purposeful exploration of a specific area requiring some form of research. From that perspective comes questions. I ask a series of questions that reflect a thought I have in my mind that is based on a hypothesis and then requires scientific inquiry.
Data doesn’t come independent of questions. It doesn’t exist independent of the construct from which the questions are being asked. If you have an optical illusion, if your lens is bent or colored, then your optical illusion will distract what you are seeing and your data will not convert into information. It will just be a loose collection of data points.
Data is a precious commodity that needs to be treated with respect and needs to be based on situational context. I look at data with any given client – that data is different from each individual client. Now, $1million is indisputably $1million, so one could say it is not different. But $1 million to one client is very different from another in terms of revenue structure, tax liability and employees.
Data ($1 million) informs a completely different set of questions between clients so thus the data is different.
I don’t think of it as data and analytics. You have data and from there you do analytics, then add in the third element which is information and how information is discerned is based on the business you’re working with."