Data Analytics: What’s Your Plan? (You Should Have One)
Welcome to the first in a series of articles on Data Analytics. Why a series? Because this is a topic that is a bit larger than one article and to do it justice requires a few more words and broad strokes.
Big data. Data mining. Data analytics. Data science. It seems that every day there are more articles on the importance of data analysis and big data and the like, including this one (ironically). The reality of the situation is that there is gold in those hills of data, and if it is found, it could be worth your time and effort to dig out. But the question is not “Is there value?” No, the question is “How can I discover the value?”
The answer to that question lies in the answer to many other questions about you, your organization, and the data you can access and mine. The world is changing all around you, faster and faster each day, and regardless of belief, knowing if and how your organization should change could mean the difference between success and failure.
I offer the following (this series of articles) as a framework to use to consider data analytics in your organization, for yourself, your department, and your company. It all starts with a single step on the path, and with each subsequent step, you will be that much closer to better information to make better decisions.
After all, the purpose of data analytics is to discover useful information that suggests conclusions to support [better] decision making. That sounds good to me. Read on if you agree.
Step 1: Decide to Begin; Commit to Analytics
This seems like an obvious beginning, but ultimately this is where we start with any endeavor. The purpose of data analytics, better data and information for better decisions, is something we strive for on a daily basis. The challenge is that (1) we aren’t always clear on the purpose of our analysis and (2) we aren’t always clear on the process of our analysis. Intuitive analysis and general analytics can be helpful at times, but sometimes the quality of more informal analysis leaves something to be desired, mainly rigor. If we are deciding where to eat lunch, we can do a lighter analysis (who likes pizza?). If we are deciding what new area of the country to invest marketing dollars, more thoroughness and objectivity is probably recommended.
This first step is needed to set a mental benchmark, a new starting point, while declaring that new analysis will have a bit more rigor and exactitude. We don’t need to move to a super-formal structured, documented process, but we should move toward a process that is better defined. One of the great ironies of this day and age is the contrast between enjoying the benefits of a complex technological society and disliking the structure required to enjoy the functional benefits of such complexity. Everyone loves their smartphone and its magic, but who likes learning and dealing with settings? Advanced functionality requires advanced investment.
And so, Step 1: Commit to Analytics. Decide to go into the undiscovered country of performance metrics, data supported decisions, balanced scorecards, and the like. Look around at how you make decisions today, accept them for what they are (both good and “could be better”), and ask yourself: “How can we change how we analyze and make decisions better?”
After you commit to improvement, then we can take the next step on the path.
Stay tuned for the next article in this Data Analytics series. If you have any questions, please contact Samuel BowerCraft, MISA, CISA, Senior Manager in the Internal Audit and Management Consulting Group at McKonly & Asbury at sbowercraft@macpas.com.
