Enhancing Strategic Decision of Business with Data Analytics
Dr. Somarata Guha Chakraborty, Associate Professor, IQ City United World School of Business, Kolkata The strategic decision making at business level has been revolutionized with the help of tons of data. It is not a new thing that starting from demand forecasting, purchase decision, inventory management, supply chain, operations, pricing, and customer relationship etc. application of Data Analytics is omnipresent in all aspects of business. But when we are talking about strategy it is somehow different. Strategy development is something that provides an integrated roadmap to develop some bold choices that will create some competitive advantage for the organization. The strategy development manager assumed to have some proficiency that facilitates the adoption of intuitive strategic decisions like creative thinking, abstract thinking skills, the ability to analyze context, and not just facts. Twenty or thirty years ago experience and gut instincts of human beings were the central processor of business decision making but unfortunately it was too human and human brains are inflicted with many cognitive biases which impact the decision making in a predictable way. But after the evolution of Data Analytics, it transforms the decision intelligence framework. It is a known fact that top level decision making in a business primarily focuses on strategic Choices which ultimately lead to resource allocation. There are many ways where Analytics can help immensely in this aspect. Artificial Intelligence & Machine Learning facilitates capturing the real time as well as historical relevant trends based on impulses in the form of news alerts, competitor’s reaction, investment data and other inputs. Decision makers can utilize the data for setting their strategic moves according to the outcome. AI can work as complementary to the traditional methods in identifying the granular or the non obvious areas of growth. Again, detecting and minimizing the stochastic element through analysis of thousands historical data about the strategic moves and the performance of other companies which finally help in examining the likelihood of success of any strategy before allocation of resources. The contribution of artificial intelligence to economic growth may be three or more times higher by 2030 than it is over the next five years and it may be claimed that the use of Data Analytics can create a performance gap between early adopters to slow adopters or non adopters(McKinsey Global Institutes Research). For the laggards the factors are hindering like lack of technical expertise for practical implementation of Data Analytics and lack of knowledge about its potential from the business stakeholders perspective. So it is the need of the hour to invest in developing the platform as well as production scale solutions for data analytics so that the investors and stakeholders will gain more confidence and start relying more on it for driving their critical business decisions.