The gap between Analytics and your CEO
As we live in a global information society, all companies and organizations have more access to data which are practical and usable and as a consequence the need for applying Data Mining techniques is imperative. These techniques though are based on sophisticated analytical methods and algorithms and as a result there is sometimes a gap between the organization’s ability to understand these Data Mining techniques and its ability to apply them to business needs.
We could easily state the question “How can the organization’s CEO, CFO or any Business Manager who maybe does not have strong mathematical and statistical background use analytical reports or insights resulted from the application of Data Mining techniques?” This is a serious business and management issue and is actually what we talk about, the gap between the application and the understanding of Analytics.
It is an undeniable fact that if we make the analytical results more simplified and more understandable then we can empower and help the decision makers to take better and less risky business decisions. Well, seeing this problem into more detail we could say that this gap widens when the Data Experts/ Scientists do not understand the whole organization’s business and the upper level management executives do not understand the analytical reports and results. Acting towards the direction of minimizing the gap between Analytics and Decision Making the writer’s opinion is that organizations must deal with this issue both from the Data Experts and the Managers side.
From the Data Experts side there are many tasks that could be done in order to make Analytics more usable by the upper management executives. First of all the organization must ensure that all the data needed for dealing with the organization’s business pains are available, centralized and easily available and accesible by the Data Experts. Then the organization must educate the Data Experts on the whole organization’s Business. Analytics professionals have to understand the business issues and have to have the ability to see behind the numbers and interpret the results from a business point of view. Furthermore organizations have to invest in new technologies including hardware infrastructure and software in order to improve the performance of the data processes and the quality of the extracted data during the data production step.
From the Managers side, in other words from the deployment part of the analytical data lifecycle, managers have to become well informed and perceptive of Analytics. They have to work towards the direction of understanding the analytical results and reports and they also have to become more proficient about data and the ways of analyzing them.
In conclusion, since we live in a global information society and as more and more organizations look to analyze their datasets which are rapidly increasing, Data Mining becomes increasingly critical to Data Scientists and its applications continuously add value to every organization. As a consequence in order for an organization to be or remain competitive and innovative in the global market this gap between Data Experts and Decision Makers has to shorten ensuring the organization’s understanding of Analytics in both the data production and data consumption step.