Business Analytics has evolved a lot. Business Analytics was designed for addressing the need for deriving intelligence out of data‘, which is nowadays referred to affectionately by many as the crude oil’ or gold ore’ of modern times. Business Analytics synergizes the strengths of various sciences including data mining, knowledge discovery, machine learning, pattern recognition, statistics, neurocomputing, and artificial intelligence. However, the world is still in a state of the perfect synchronization of Business Analytics and human expertise “ Business Analytics cannot exist alone without human participation. The requirements have to be defined and the logic has to be structured by human beings for the Business Analytics juggernaut to roll on.
Human participation is still indispensable in Business Analytics.
Business Analytics can highlight only what is better or worse in the given dataset; humans have to set the logic. Business Analytics can only minimize the time needed for segregating or slotting the data in the dashboards and allow time for humans to analyze the data trends. Definitely, technology solutions have taken over the part of dissecting and categorizing data so that humans can use their time more efficiently to seek insights. But the human participation is still inevitable.
For instance, Social Media is monitored in real-time to get the unbiased opinion of the customers and public at large about your company’s brand and that of your competitors. By thus monitoring the verbose online conversations, company leadership can decipher what is on the mind of the customers and also the general public and use the qualified data to drive decisions in the organization. Business Analytics allows filtering out promising leads from the clutter and noise “ the algorithms pick on high-quality information. However, still analytics only helps to recognize patterns “ selecting the features that ultimately reveal the patterns, analyzing the patterns, and arriving at a decision is still the responsibility of human beings.
The most celebrated success of Business Analytics is that while human teams can take months to collate and recognize patterns in the data and make predictions, Business Analytics reveals the same patterns in a matter of hours. The further process to make meaningful decisions is of course the part to be played by human beings.
Prevalent Examples:
Following are some of the widely acclaimed examples where Business Analytics is put to good use through human participation:
#1 Recently, in Canada, the state law enforcement machinery teamed with data scientists and developed a system, which sources information from GPS data, emergency line calls and emails, building security-logs, and police-officer activity records. By building algorithms for deriving meaningful patterns out of this holistic information, the law enforcement machinery sought to reduce the time lag for addressing the crime and the idle time of the police-officers.
#2 Similarly, in the USA small sensors either implanted or strapped to out-patients for continuous monitoring of their health help predict the likelihood of their sickness episode so that timely corrective actions could be taken. Though the logic and the parameters for the individual patient have to be defined by the doctor and the decision for imparting the right corrective medical procedure immediately has also to be taken by the doctor.
Thus in this age and date, machine learning and human intervention have to be balanced out for leveraging the maximum output from Business Analytics. Just having Big Data and Business Analytics is useless without a human mind to find the practical application. The algorithms have to be continuously tweaked to get valid results. Agreed that we have machine learning systems that are self-learning compliant, still, humans are required for implementing the right decision. Such bimodal managers, who are well versed with functional knowledge as well as for analytics, are very important to the business. The analytics tools though important are secondary.
Today, we have the technology; we just need the human push to make an organization truly data-driven. Thought leadership is of paramount importance. By way of human participation, organizations today need bimodal managers, who can get behind the scene, understand the machinery in the organization vis-Ã -vis technology in the wider landscape, and drive the change and transformation. Business Analytics does provide low latency and high throughput. However, tailoring the Business Analytics to suit the organization’s needs is the job of the bimodal manager “ the human participation element in Business Analytics. Truly, a bimodal manager will be the most sought-after person in the age and era of smart cities and smart nations.
