Welcome to Brilliance@Work, a series of profiles about stellar collaboration professionals and their best practices at work. Throughout May, we’ll feature Marketing Analytics & Data Science experts.
Camille P. Schuster, Ph.D. is Professor, Marketing, for the College of Business Administration at California State University San Marcos and President of Global Collaborations Inc. She’s also a presenter at the Marketing Analytics & Data Science Conference on June 8-10, 2016 in San Francisco, California.
As a preview to her presentation “Playing Detective with Data,” Camille shares insights on how the questions you ask while analyzing the data are critical for successful business outcomes.
Peggy L. Bieniek, ABC: How should organizations innovate and improve the way they use data in their business operations?
Camille P. Schuster, Ph.D.: All organizations have a tremendous amount of data available to them including consumer information, heavy users vs. light users, average purchase size vs. large purchase, number of purchases per week or month or quarter, feedback forms, on time payment data, social media data, contact information, and more.
How to use it depends upon the business question. Analyzing data for the sake of analyzing is not particularly helpful. Start with the business question, analyze the data you have, determine whether it is cost effective to obtain other data you would like to have, and move forward.
PB: What is the role of data in data analysis?
CS: Data is the raw material that can be used to solve problems. The data itself includes numbers or words (if analyzing text) to be transformed into a standard format for comparison and manipulation purposes. When the comparisons and manipulations are complete, then you have information.
The most valuable skill of all is the ability to interpret what the information means and how it can be used to solve a problem. All three steps are critical for success and require different skill sets.
Preparing and cleaning the data to make it usable for use in specific software requires one set of skills. Knowing which tools are needed to perform what calculations requires a different set of skills. Being able to understand the data and what calculations were formed to be able to interpret the results and make recommendations to solve business problems requires another set of skills. Understanding each of the steps and the interaction between the steps is essential.
PB: What are the attributes of a successful system for reliable data analysis?
CS: The attributes of a successful system include:
- Knowing the questions that need to be answered
- Determining whether you have data that can answer those questions or can get that data
- Having people with the skills to perform the necessary steps
- Having the appropriate hardware and software for the analyses you need to do
PB: What will people gain from attending your conference presentation?
CS: My presentation will demonstrate how the questions you ask influence your results and understanding of the situation which, in turn, will change your business recommendations.
Want to hear more from Camille? Join us at the Marketing Analytics & Data Science Conference. Learn, network and share best practices with the most influential leaders in data science and analytics. Stay connected at #MADSCONF.