Demand Planning in India-Emerging Trends & Challenges

By Sastry, M. V. Hanumat | The Journal of Business Forecasting, Spring 2011 | Go to article overview

Demand Planning in India-Emerging Trends & Challenges


Sastry, M. V. Hanumat, The Journal of Business Forecasting


EXECUTIVE SUMMARY | This article discusses not only the challenges Indian businesses face in demand planning, but also ways to deal with them. Geographical diversity in terms of customs and traditions has a great impact on demand, which has to be properly managed.

Demand planning-forecasting and managing demandplays a vital role in managing a business in India. In recent years, almost all the major companies in various regions have shown healthy growth rates upward of 10% (See Table 1). But India, being a highly diversified nation with 28 states and varying purchasing behaviors, has its own challenges in managing demand. This article discusses unique challenges that Indian companies face when managing demand and the best way to deal with them.

In recent years, consumer demand i n I n d i a h a s t r a n s formed the recession-based conservatism into aggressive optimism. Many Indian companies have experienced im-pres sively healthy growth rates. Most of the demand is coming from consumers who recently experienced a surge in their discretionary income. Businesses can ramp up their growth further if they manage their demand effectively. In fact, most Indian companies have started to pay more and more attention to demand planning. Not only that, many ambitious Indian companies have even started to include the export component in their demand planning process.

DEMAND PLANNING

How to manage demand effectively depends on the country because the people in each country have different purchasing powers, consumer behaviors, and cultures. Knowing the unique challenges in India, we outline here a few critical points to be considered in implementing a successful demand planning process.

1. Demand planning an autonomous body;

2. Formal forecasting process;

3. Demographic diversity;

4. Forecasting assumptions;

5. Impact of promotion;

6. Performance measurement; and

7. Training.

DEMAND PLANNING BY AN AUTONOMOUS BODY

Sales forecasts in India are usually highly biased. Mostly, sales teams own the forecasting process. They bias the forecasts downward if sales quotas are based on them; otherwise, their numbers would be quite optimistic to ensure products are in stock when orders come in. In other cases, forecasts are prepared by the supply chain people, who have a bias of their own-they under-forecast if their performance is evaluated on the basis of inventory and over-forecast if they are evaluated on the basis of customer service. We also see companies making multiple forecasts, where each function prepares its own forecasts for its own use, making it difficult to align supply and demand. How can we align supply and demand if a sales plan is based on one set of numbers and a production plan on another? In a multiple forecast environment, even management won't know for sure which numbers to use.

These are the problems that many Indian organizations face. They can be managed effectively if demand planning is performed by an independent body. With that, demand planners will come up with forecast numbers that truly represent the market. In recent years, many Indian organizations have moved in that direction.

FORMAL FORECASTING PROCESS

It is not enough to just have a demand planning process; demand planning means demand forecasting and managing demand. For a robust demand forecasting process, it is important to have a formal forecasting process wherein a forecaster obtains input from various functions and then prepares statistical forecasts, which are then presented in the consensus meeting. Members of consensus team go over the numbers and then overlay judgment where necessary. Most organizations in India don't have a formal forecasting process in place. Forecasts are prepared in a very crude way with little or no application of statistical models. Data are not analyzed for outliers, structural changes, and/or seasonality.

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