Goal: Use Big Data to Predict Business Trends

Big Data is a hot topic. Heck, there’s a Harvard Business Review category dedicated to articles strictly about the “problem” of Big Data. But at ASQ, we like to think of Big Data as an opportunity rather than a problem. With all of the data that your website can collect, it’s hard to imagine a scenario where your business goals cannot be completely data-driven. However, there may be some sources of data you are not considering.

We like to lump them into two groups: internal variable data (you’re probably considering) and external variable data (maybe you’re not considering).

Some examples of internal variable data include: calls, revenue, jobs, cost and marketing (including traditional, digital and social – unpaid or paid). These are things that you consider to directly impact your business. And while you are right, they may not paint the whole picture. That’s where external variable data comes in. Some examples of external variables include: weather, stock prices, consumer confidence, material prices for your products, shipping costs, or anything else you might think indirectly impacts your sales.

Shall we use a metaphor? All right then. Think of your business like a map. The question you want to answer is “where are we going?” The answers lie in where you’ve been, where you are now and the prediction for the future. Big Data can help answer all of these independent questions, which allows us to predict where you’re going. Just how is this accomplished? Well, first we connect the dots among your disparate data sources. Whether or not its an automated or manual process, we are able to layer your data sources and make them searchable. This gives us the “where you’ve been” picture. Often times, companies are collecting data across tons of platforms and they’re all housed in different places. Creating a program to access all of your data and pull them together is called custom database development.

Now we are ready to assess the “where are we now” and “where are we going” pieces of the map. To do this, we compile + organize the historical data along with the other relevant external data variables, layering the information so that it is easier to access and analyze. Next we create a statistical model to predict trends for the future that influence your business. We are then able to manipulate factors in that model to determine how much it will impact your bottom line, thus the ability to find where your business can run on optimal efficiency. It is not enough to consider the internal variables, but to also include things that impact consumer decisions also.

So why do we need to work with Big Data in this way?

Aside from the obvious positives already mentioned, database management creates ways to communicate with every level of professional in your company. Take, for instance, reporting. Analysts, management and clients need to look at the data in various levels of depth, and the database creates the opportunity to do that automatically and seamlessly. Additionally, different people pulling reports from different data sources can often lead to human error. Automating reports ensures better accuracy and more seamless trending over time, which leads to better models and predictive analysis.

Big Data does not have to “bury” your company, as some have claimed it will. It is possible to aggregate + act upon it for optimal business efficiency based on a seemingly-endless number of factors. The question is now not Where are we going? but How soon can we get there?

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