The integration of machine learning in formulation of business strategies has been identified as a cornerstone for the success of the organisation. Machine learning has emerged has one of the major transformative tool in the field of modern business environment. The rapidly evolving world of technology has increased the dependency on artificial intelligence (AI) and machine learning (ML). The dependency has boosted and guided the business for strategic decisions, improving the overall automation and efficiency, helping firms gain indispensable insights with enhancement of enhancing customer engagement and operational performance. The evolution in technology has created opportunities for transforming business strategies. The acceptance of AI and ML is conceptualizing and automating the repetitive tasks of the businesses helping identification of core business strategies. The incorporation of machine learning in businesses are not just for the sake of trend but it has been recognized as strategic necessity for businesses for continuous evolution of performance over the moving time frame.
The application of machine learning has been witnessed across various industries namely healthcare, automotive, energy, finance and among others, aiming to reshape the business models, fostering innovations and financial growth. The adaption of machine learning has identified majorly four areas namely improved predictive insights, enhanced customer experiences, operational efficiency and informed strategic planning which has ameliorate the business strategies. The variation and adaption in the strategic thinking and planning has increased the ease of business doing increasing the market potential of startup programs. The concept of automation of business process is not new for the world, but machine learning driven automation has increased the business yield unprecedentedly. Machine learning has identified 5 key areas which are:
- Improved Decision Making
- Increased efficiency
- Enhanced Customer experience
- Predictive Maintenance
- Fraud detection
Machine learning helps in overall reorganization of different patterns that lies within the large set of data, which sometime get ignored by humans, helping firms gain more insights about the prevailing competitive advantages or edge. Every aspects of business which are important in framing strategies can be formulated with the use of machine learning and one such field where machine learning adaption has shown pragmatic and efficacious outcomes are marketing and finance. The marketing teams have observed considerable improvements with automation of marketing tasks with beneficial chatbots interactions under customer service with real-time customer queries resolutions. The need of self-driven marketing tasks has grown exponentially in recent years with generation and availability of big data which are crucial for formulation of marketing strategies. Not only marketing, but a significant improvement has been observed in the domains of human resources, operations, and strategic management. It is helping financial domain in identification of risks and frauds, optimization of budgets and automation of auditing and algorithmic trading. The area of human resource management and operations & supply chain management has identified streamline functions of machine learning in talent acquisition & resume screening, employee performance analysis, employee behavior analysis, minimization in recruitment biases, warehouse automation, route optimization, predictive maintenance and quality control & defect detection. With the adoption of machine learning at different domains of businesses, the real-time analysis of data helps firms respond quickly to negative feedback and improve their customer service. The optimization of price through machine learning improves pricing strategies for products and services, helping find companies understand the demand situation with its alignment in accordance with company’s goals and objectives. The evaluation of business strategies through price optimization techniques helps evaluation of sales promotions with right price estimation of products for the potential customers.
While there are thousands of positive aspects of machine learning, there are certain challenges too that needs to be addressed while adopting machine learning technology in businesses. The major concerns being identified are data privacy and security issues, algorithm biasness and requirement of highly skilled personnel for development and interpretation of new technology. Also, business firms are required to increase their share of investment in the segment of data quality assurance and governance to ensure accuracy and reliability of machine learning insights for development of numerous business strategies.
In the fast paced technological changing era, machine learning stand out as game-changer in the field of business strategy and analysis, with immense potential of automated decision making processes for various business across industries. The professionals who are embracing machine learning tools are better equipped to deal with modern day business landscape complexities. But, it is essential to adopt machine learning technologies under the stated ethical considerations with commitment towards human welfare and business growth. The coming years of business will revolve around machine learning and artificial intelligence, evolving and presenting various presenting new opportunities and challenges for business analysis professionals. Thus, it is indispensable and imperative to adopt effectively the evolving technologies to be at the forefront of driving innovation and success in their organizations.
Blog By:
Ms. Giti Vatsa
Assistant Professor
Biyani Girls College