The Harvard Business Journal published a great article about data management from an upcoming book called, “Keeping Up with the Quants,” by Thomas Davenport. The main premise of the article is that many businesses have shown that they are not comfortable with data, and as a result they make bad decisions. “Companies need general managers who can partner effectively with “quants” to ensure that their work yields better strategic and tactical decisions.”
How do managers and other decision makers get what they need from those that perform the complicated quantitative analysis? The first step is to become a good data consumer, because although the quants know the numbers, “most lack sufficient knowledge to identify hypotheses and relevant variables and to know when the ground beneath an organization is shifting.”
“Your job as a data consumer—to generate hypotheses and determine whether results and recommendations make sense in a changing business environment—is therefore critically important.” The Harvard Business Journal highlighted six steps for accomplishing this goal:
1. Recognize the problem or question
2. Review previous findings
3. Model the solution and select the variables
4. Collect the data
5. Analyze the data
6. Present and act on the results
In addition to these data management steps, the author had a few other useful pieces of advice. First, if you didn’t cover statistics in college, or if you’ve just forgotten, do something to ensure you understand how to interpret numbers. “You need to understand the process for making analytical decisions, including when you should step in as a consumer, and you must recognize that every analytical model is built on assumptions that producers ought to explain and defend.”
Second, the source of your data makes a big difference! Find someone who understands how you think, because “quants and the consumers of their data get much better results if they form deep, trusting ties that allow them to exchange information and ideas freely.”
For more on using data management to make data a benefit, not a burden, read this post…