NEWS

In the words of W. Edwards Deming, “Without data you’re just a person with an opinion.” Some refer to Deming as one of the founding fathers of quality.

The real drivers of an organization are of course its people and data can only take an organization so far. But, there is no question that data analytics are necessary to make the best informed business decisions to take advantage of opportunities. Analytics establish a clear performance baseline and track trends based on actions taken over time. Through the use of predictive analytics you may determine which metrics are actionable insights.

Descriptive and Predictive Analytics

To understand predictive analytics, it helps to understand descriptive analytics. Descriptive analytics are everything from last quarter revenues to current customer satisfaction numbers. Descriptive analytics focuses on what has happened and does not provide clear path for action.

But predictive analytics focus is on the future. Instead, they recommend optimal next steps to drive desired outcomes. With predictive analytics, you will see which actions will make the biggest impact and can prioritize activities.

Clean Data

Analytics are not optimal until the data is clean. There are huge volumes of data that may flood businesses every day. Focus should be on quality over quantity. If data is to be of service to an organization, data needs to be useful. It should provide opportunities for strategic insight and support data-driven decisions. This is where the quality of data comes into play.

Quality data is clean. Data cleansing is the process of correcting or removing corrupt or inaccurate records. It refers to identifying incomplete, inaccurate or irrelevant data and then replacing, modifying or deleting the dirty or coarse data.

Clean data gives confidence that the metrics are sound. Current applications can predict failures or defects before they get to the consumer in the early stages of manufacturing. The goal is early intervention for better outcomes and to provide genuine insights to the people who influence customer perceptions the most: your front-line team.

Take Charge

Data has been collected, analyzed and future trends have been predicted. Now it is time for recommendations for action – prescriptive analytics.

Referred to as the third phase of analytic capabilities, prescriptive analytics utilizes mathematical and computational sciences. It goes beyond predicting future outcomes by also suggesting actions to benefit from the predictions and shows the implications of each action.

According to Deloitte, advanced analytics is expected to grow globally from $136 billion just a few years ago to $232 billion in 2021, attaining an 11.3% compound annual growth rate.