Data is and will be around us and it is increasing at an astonishing rate. In the such business environment, what should business managers do? I do no think every manager should have an analytics skill at the same level as a data scientist because it is almost impossible. However, I do think every manager should communicate with data scientists and make better decisions by using output from their data analysis. Sometimes this kind of manager is called "analytic savvy manager". Let us consider what "analytic savvy manager"should know.
1. What kind of data is available to us?
Business managers should know what kind of data is available for their business analysis. Some of them are free and others are not. Some of them are in companies or private and others are public. Some of them are structured and others are not. It is noted that data which are available is increasing in terms of volume and variety. Data is a starting point of analysis, however, data scientists may not know specific fields of business in detail. It is business managers that know what data is available to businesses. Recently data gathering services have provided us a lot of data for free. I recommend you to look at "Quandl" to find public data. It is easy to use and provides a lot of public data for free. Strong recommendation!
2. What kind of analysis method can be applied?
Business managers do not need to memorize formulas of each analysis method. I recommend business managers to understand simple linear regression and logistic regression and get the big picture about how the statistical models work. Once you are familiar with two methods, you can understand other complex statistical models with ease because fundamental structures are not so different among methods. Statistical models enable us to understand what big data means without loss of information. In addition to that, I also recommend business managers to keep in touch with the progress of machine learning, especially deep learning. This method has great performances and is expected to be used in a lot of business field such as natural language processing. It may change the landscape of businesses going forward.
3. How can output from analysis be used to make better decisions?
This is critically important to make a better decision. Output of data analysis should be in aligned with business needs to make decisions. Data scientist can guarantee whether numbers of the output are accurate in terms of calculations. However, they can not guarantee whether it is relevant and useful to make better decisions. Therefore business managers should communicate with data scientist during the process of data analysis and make the output of analysis relevant to business decisions. It is the goal of data analysis.
I do not think these points above are difficult to understand for business managers even though they do not have a quantitative analytic background. If you are getting familiar with these points above, it would make you different from others at the age of big data.
Do you want to be "Analytic savvy manager"?