Demand Variability

Demand Variability refers to the fluctuations or changes in customer demand for a product or service over a specific period. This discrepancy can stem from various factors like seasonal trends, market dynamics, consumer behavior, or unexpected events on large and small scales.

It is a critical factor that businesses must consider when managing their supply chains. Managing variability enables better planning, minimizing underutilization or overutilization of resources, optimizing production schedules, and reducing waste. Companies can be more resilient against unexpected market shifts, reducing vulnerability to economic downturns or sudden changes in consumer behavior.

• Demand variability refers to the fluctuations in the quantity of a product or service that customers purchase over time.
• This variability can arise due to a number of different reasons, such as global disruptions, market dynamics, seasonal trends etc.
• Demand variability is a significant challenge for businesses because it can impact their operations, supply chain, and profitability.
• The common methods used to calculate demand variability are mean absolute deviation (MAD) and coefficient of variation.
• Demand forecasting, price discrimination, discounts, expanding the market and developing new products can reduce the variability in demand.

Demand variability in the supply chain refers to the fluctuations or inconsistencies in the demand for a product or service over a period of time. It describes the degree to which actual demand can deviate from forecasted or expected demand. Various factors, both internal and external to the business, can cause this variability.

Demand, itself, is not a simplified prospect and can be quite dynamic in nature. Demand may undergo seasonal changes depending on the nature of the market and the customers. Consumer preferences can change over time due to the introduction of new products or global and political events. An example is the change in the demand for medical equipment at the onset of a global pandemic. Recessions and economic downturns also play a major role in influencing demand variability. Identifying and analyzing the reasons for demand variability is a crucial step in eliminating their effect on business.

The common methods used to calculate demand variability are as follows:

Mean Absolute Deviation (MAD)

Mean Absolute Deviation (MAD) is the average of the absolute deviations of each demand point from the mean demand. It is calculated as follows:

MAD = (1/n) * Σ |Di - D̄|

Where:

• Di is the demand at the time i
• D̄ is the mean demand
• n is the number of demand periods

Coefficient of Variation (CV)

Coefficient of Variation (CV) formula is the ratio of the MAD to the mean demand. It is calculated as follows:

CV = MAD / D̄

CV is a dimensionless measure of demand variability, often expressed as a percentage. A higher CV indicates greater demand variability.

Let us look at the demand variability examples to understand the concept better:

Example #1

Suppose a retail store specializing in seasonal clothing faces significant demand fluctuations throughout the year. During peak seasons, such as the holiday period, demand for winter apparel skyrockets, while demand for summer clothing dwindles. To effectively manage this variability, the store implements a demand-driven inventory management system that dynamically replenishes inventory based on real-time sales data. This system enables the store to maintain adequate stock levels during peak periods and avoid excessive inventory during off-peak periods, optimizing overall inventory management efficiency.

To quantify the extent of demand variability for a particular winter jacket, the store employs MAD to calculate the average deviation of demand from the mean:

MAD = (1/n) * Σ |Di - D̄|

Where:

• Di: Demand for the item in week i
• D̄: Average weekly demand for the item
• n: Total number of weeks in the analysis period

Analyzing Demand Patterns

The store analyzes the demand pattern for the winter jacket over the past 12 weeks. The average weekly demand (D̄) is determined to be 100 units. The demand for the jacket during each week (Di) is as follows:

Calculating Absolute Deviations

The store calculates the absolute deviation (|Di - D̄|) for each week:

| Week | Demand (Di) | Average Demand (D̄) | Absolute Deviation (|Di - D̄|) |

|---|---|---|---|

| 1 | 80 | 100 | 20 |

| 2 | 90 | 100 | 10 |

| 3 | 120 | 100 | 20 |

| 4 | 110 | 100 | 10 |

| 5 | 100 | 100 | 0 |

| 6 | 90 | 100 | 10 |

| 7 | 80 | 100 | 20 |

| 8 | 70 | 100 | 30 |

| 9 | 130 | 100 | 30 |

| 10 | 120 | 100 | 20 |

| 11 | 110 | 100 | 10 |

| 12 | 100 | 100 | 0 |

Determining MAD

To calculate the MAD, the store sums the absolute deviations and divides by the number of weeks:

MAD = (1/n) * Σ |Di - D̄|

= (1/12) * 200

= 16.67

The MAD of 16.67 units indicates moderate demand variability for the winter jacket. This information empowers the store to make informed decisions regarding inventory levels, preventing stockouts during peak seasons and minimizing excess inventory during off-peak periods, thereby enhancing overall inventory management effectiveness.

Example #2

Apple's overall revenue was $81.8 billion in the third quarter of 2023, slightly above Wall Street estimates. iPhone sales were weaker than predicted, slipping 2.4% to $39.7 billion.

Apple executives admitted that the smartphone market was slowing down, particularly in the US. The company was reining in spending, but China was a bright spot, with strong sales of wearables and iPhones. Apple expected the year-over-year performance of the iPhone and services to improve in the current quarter, but the Mac and iPad divisions would decline.

Services revenue was a clear highlight, climbing 8.2% to $21.2 billion.

Here are some ways to reduce demand variability -

• Improving demand forecasting: By accurate demand forecasting, businesses can better plan for production and inventory levels, which can help to reduce stockouts and overstocks.
• Offering promotions and discounts: Promotions and discounts can be used to stimulate demand during periods of low demand and to reduce demand during periods of high demand.
• Implementing price discrimination: Price discrimination can be used to charge different prices to different customers based on their willingness to pay. This can help to smooth out demand by charging higher prices to customers who are less sensitive to price and lower prices to customers who are more sensitive to price.
• Developing new products and services: New products and services can help to attract new customers and increase demand for existing products and services.
• Expanding into new markets: Expanding into new markets can help to reduce demand variability by diversifying the customer base.

This article has been a guide to Demand Variability and its definition. Here, we explain the concept along with its examples and how to reduce it. You may also find some useful articles here -

• Demand Estimation
• Perfectly Inelastic Demand
• Demand-Side Economics