Operations Analytics - NMIMS SOLVED ASSIGNMENTS June 2026

 

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Operations Analytics

Jun 2026 Examination

 

 

 

Q1. A manufacturing company must allocate limited resources between producing two products, X and Y, in order to maximize total profit using prescriptive analytics. 1. Product X provides a profit of Rs.1,700 per unit, while Y gives Rs.2,100 per unit. 2. Production of X requires 6 hours of machine time and 4 units of raw material per unit; Y requires 8 hours of machine time and 3 units of raw material per unit. 3. The constraints are: (i) maximum available machine time per week: 260 hours; (ii) raw material available per week: 140 units; (iii) due to contractual obligations, at least 8 units of X and at least 6 units of Y must be produced weekly; (iv) company policy mandates that the combined weekly production not exceed 30 units due to logistics. 4. Suppose the supplier gives a proposal to increase raw material supply by 20% if the company pays an extra Rs.300 per additional unit of raw material. Using prescriptive analytics principles (and appropriate linear programming and shadow price concepts), determine the optimal production quantities, and analytically evaluate whether accepting the supplier's offer will increase or decrease total profit, explicitly identifying the new profit and interpreting the value of the resource constraint changes. (10 Marks)

Ans 1.

Introduction

Prescriptive analytics helps businesses make the best possible decision by combining data, constraints, and objectives. It does not just predict what will happen. It tells you exactly what action to take to achieve the best outcome. Linear Programming (LP) is one of the most powerful tools in prescriptive analytics. It finds the best way to use limited resources to maximize profit or minimize cost. Shadow price is another important concept in LP analysis. It tells us how much the objective function value changes when a constrained resource increases by one uni

 

Q2 (A). A retail company uses the basic Exponential Smoothing method to forecast weekly demand for a key product. For the first week of the month, the forecasted demand was 500 units, but the actual demand observed was 550 units. The company uses a smoothing constant (alpha) of 0.3. a) Calculate the forecasted demand for Week 2 using the exponential smoothing formula. Show your step-by-step calculation. (3 Marks) b) If the actual demand for Week 2 turns out to be 520 units, what will be the forecasted demand for Week 3? (2 Marks) (5 Marks)

Ans 2(A).

Introduction

Exponential smoothing is a demand forecasting method that gives more weight to recent data and less weight to older data. It adjusts the previous forecast based on how wrong it was. The smoothing constant alpha controls this adjustment. A value close to 1 makes the forecast very reactive to recent changes. A value close to 0 keeps the forecast more stable.

Theory: Formula

 

Q2 (B). Sipkart, a major Indian e-commerce retailer, has leveraged sophisticated inventory optimization techniques to expand rapidly across the country while maintaining high service quality. Recently, however, Sipkart noticed that during major festivals, certain high-demand products experience frequent stockouts, despite increasing overall inventory levels. The management is concerned about the escalating costs of holding excess inventory and the reputational risk of running out of bestsellers. They are debating whether to invest further in demand forecasting algorithms or to increase safety stock across key categories. Critically evaluate Sipkart's current approach to handling festival demand surges and recommend whether prioritizing advanced demand forecasting or simply increasing safety stock would be more effective for optimizing inventory during peak periods. Justify your answer by weighing the costs, risks, and operational implications for a rapidly scaling retailer. (5 Marks)

Ans 2(B).

Introduction

Sipkart is facing a problem that is very common among fast-growing e-commerce retailers. Stockouts during festivals hurt revenue and damage customer trust. At the same time, excess inventory across all categories raises holding costs significantly. The core question is whether better forecasting or more safety stock is the right solution. This depends on understanding why stockouts are

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