Young Leaders Programme (YLP)
Management Development Institute ,GurgaonOpen For Admission
The pandemic sent shockwaves across various industry verticals, disrupting all possible processes and systems. Right from supply chain to daily operations to customer engagement, every aspect of business almost raced to adapt to the 'new normal. One of the greatest aspects of business that went through a tumultuous time was demand forecasting. The existing traditional methods of forecasting could hardly forecast the rapidly changing market and as a result, innumerable companies were forced to shut shop. With the uncertainty looming large on the market, the industries across the globe were almost forced to invest in machine learning to:
· Track demand sensing forecast vis-à-vis baseline forecast
· Estimate the impact of Covid on the overall supply chain
· Track change in consumer behaviour
According to a report published by Fortune Business Insights, the global market size of machine learning witnessed a traction of 36.2% in 2020 in comparison to 2019-2020. Furthermore, the market is projected to clock in a staggering USD 152.24 billion in 2028 from just USD 15.50 billion in 2021. This sudden adoption of machine learning can be attributed to the key benefits it has been delivering in business not only during pre-covid times but also during the first and second onslaught of Covid-19. Let’s take a look.
Key Benefits of Machine Learning in Demand Forecasting
1 Accuracy in demand planning-The economic impact of inaccuracy is huge, and the efficacy of machine learning has already been validated. Machine learning leverages high-performing algorithms for data processing thereby, producing results more effective than traditional demand forecasting.
2 Absorb a tremendous volume of varied data and generate mission-critical insights- Machine learning enables the absorption of a great volume of varied data at a startling velocity thereby, improving the forecasting at SKU level comprising of four pillars-Time series member, case ID, transaction amount, and date.
3. Update data in real-time and re-route supply chain processes around it- Machine learning forecasting leverages superior algorithms to constantly update the 'demand forecasts' in real-time. This helps in aligning the product, customer, pricing, and promotions with great efficiency.
4 Accelerate the data processing mechanism- The modern machine learning architecture facilitates optimized use of memory storage and propelling the forecasting mechanisms to lightning speed. This enables the decision-makers to make well-informed investments for superior data processing.
From the above discussion, it can be safely concluded that machine learning is one of the key requisites for executives today. As a result, executive education has witnessed a significant proliferation in academic courses tailored to offer a holistic and working knowledge of Analytics. Amongst a milieu of courses on analytics, the Executive Programme on Business Analytics (EPBA) offered by IIM Calcutta in collaboration with Hughes stands out for its all-encompassing curriculum on Business Analytics. The course curriculum has been designed to deliver data-driven competitive strategies to outthink competitors in the market.
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