By Gil Nizri

The greatest risk an organization can take today is to not become data-driven.

Some companies count on intuition, which can be wrong. Other companies hoard data or draw false conclusions from it. Predictive analytics, in contrast, provides decision makers with the ability to make data-driven decisions based on solid facts and reasoning.

Let’s break this down further: Intuition is the ability to understand something immediately, without the need for conscious reasoning. In many cases, a person having intuitive insight in unable to explain in detail the reasoning behind his decision. That is what differentiates intuition from knowledge.

When you run a company, you are called upon to make thousands of decisions every day about any and every facet of the business. Some of these decisions are “easy,” meaning either you have seen them before or they have only a few parameters that truly influence them and you can therefore quickly examine the parameters and make a decision for success.

How many parameters can a human mind simultaneously process? Very few. Therefore, when it comes to those decisions with multiple or competing parameters, things can get complicated.

All organizations today collect data … lots and lots of data.

Data is generated and stored from nearly every one of a company’s interactions with customers, suppliers, distributors and others. Each data point could or could not have relevance and influence on future decisions. Making decisions that are not data-driven (or that are based on false interpretations of this data) puts your company at risk. If this is done too often, the company could falter.

Most companies still rely on reporting and BI analysis. There is nothing inherently wrong with BI. However, while it can describe in detail what happened, it has very little if any impact on the ability to determine future action.

Let me explain: BI basically tells you that sales decreased by 80 percent last quarter. That is good to know. You are now aware there is a problem.

Now what? The next step is using predictive analytics, the most powerful tool for making data-driven decisions that could impact the future of your company. The next step is taking the knowledge you gained from BI and predicting what you should do next.
An example:

ACME-L4U is a loan company handling dozens of requests for loans per day. It employs five full-time underwriters. ACME-L4U is expanding to online loans and their new e-Loan division is now generating 500 loan requests per day. How should the company address this growth? Should it hire 50 new underwriters to examine and respond yes or no to these requests.

Clearly, hiring so many new people would cut heavily into company profits. Rather, a predictive analytics model can determine if a potential customer is likely to default on his/her loan and provide a data-driven score for every potential borrower. The automation is easy and accurate (not based on intuition). More loans get written and the company’s bottom line grows with little risk.

Are you leveraging predictive analytics in your company? If you are interested in knowing how you can up-skill your BI team to deliver accurate, data-driven decisions for your company, request a DMway demo.