How Does Demand Management and Forecasting Complement Supply Chain Logistics?

How much did you spend on the Big Billion Days last festive season? Wasn’t there another ‘Great Sale’ in January? Oh yeah, ‘The Great Republic Day Sale’ with discounts as high as 70%.

Well, India alone has an online shopper base of around 500-600 million shoppers, ranking second as per global rankings. 

But how on earth do businesses cater to such an extensive customer base? Even with the most ideal logistics channels and congestion-free roads, catering to such large orders would seem like a long shot. Well, we don’t seem to have that yet, so how did we manage it in India?

Through forecast and demand management! 

By analyzing data on customer purchase patterns and seasonality factors, companies expecting heavy sales volumes can easily pre-stock inventories according to geographic hotspots, plan operational layouts, etc., even before the sales start coming in.

So, what are forecasting and demand management in the supply chain? Read on to find out…

What is Demand Management in Supply Chain?

Supply chain demand planning or management is a strategic process employed by companies to synchronize their operations with consumer buying trends. While this sounds like a simple demand and supply activity, there’s more to it than meets the eye. 

Consider a scenario where a company affected by low sales volume halts its production or reduces its stock levels to cut losses. However, there’s a change in customer purchase patterns, and bulk orders start coming in. Due to the lack of predictive insights, the company ended up reducing its production, whereas it should have been bolstering them.

Moreover, you need a considerable amount of time to prepare for such seasons. For example, planning operations like logistics for shipping goods, marketing, and branding activities to leverage the seasonal trend, inventory management, hiring customer service and other personnel to deal with the high order volumes, and more.

Similarly, imagine if a company anticipated wrongly and overstocked its shelves, ran its manufacturing hubs at full throttle, and went on a hiring spree. The sales won’t come in, and the company would bear heavy production, logistics, storage, and wastage costs, all while generating negligible revenue – a total catastrophe.

Thus, successful demand management requires perfect forecasting and a meticulous chain of command that takes up ownership of different cogs in the supply chain. A small chink in the forecast and planning, and the entire business could fall down like dominoes.

That brings us to the next section, ‘What is demand forecasting, and how do we do it accurately?'

What is Demand Forecasting?

Demand forecasting is the process of leveraging predictive analytics to analyze historical data on customers’ purchase patterns, events, and actions taken on marketplace brand stores, websites, etc., to predict the demand for a product or service accurately.

E-commerce giants like Flipkart and Amazon also leverage predictive analytics models to determine sales probabilities and plan their operations accordingly.

For example, when you visit an e-commerce website, the predictive model stores data about the products you viewed, your purchase history, and other relevant information to make an educated prediction about the products that you are most likely to buy. 

Similarly, different customers exhibit different purchase patterns that are recorded in their respective personas. Accurate analysis of multiple customer personas over a period of time helps companies predict a surge or drop in sales and plan operations accordingly.

A very common example is the Big Billion Day Sale, which often starts in October and November and continues until New Year's. The idea is to tap into the festive sentiments, knowing that Diwali (Dhanteras), Christmas, and New Year’s are some festivals where people believe in buying and gifting. 

Having forecasted increased sales, businesses plan operations like marketing activities and heavy discount campaigns to amplify customer demand and simultaneously increase production and inventory stocks to meet them.

Additionally, there are multiple other benefits that one can gain from forecasting and demand management. We have discussed them in the section that follows.

Benefits of Supply Chain Demand Forecasting and Management

The most evident benefit of forecasting and demand management is an increase in sales and a reduction in operation costs. However, there are multiple operation-level benefits to planning in advance.

1. Determining Potential Risks or Opportunities

   Predictive models analyze historical data and external factors such as market trends, economic indicators, industry trends, and more. They use these variables to predict an impact on product demands and determine risks or even opportunities for the company to scale up.
   Some highly sophisticated algorithms can also incorporate customer reviews and feedback as a variable for predicting product demand. This further facilitates product development and planning of new launches.
   
   

2. Resource Allocation and Production Efficiency

   Demand forecasting lets you allocate resources like the staff at inventories or warehouses, install equipment at the manufacturing hubs, arrange logistics, and more.
   According to a survey by Gartner, companies using advanced analytics and demand forecasting in production planning achieved a 15% reduction in production costs and a 10% increase in overall efficiency.
   
   

3. Effective Brand Awareness via Marketing Ventures

   Insights on various customer personas and demographics help brands plan their marketing activities accordingly. Knowing how your customers perceive your brand/products helps you optimize your targeting.
   Moreover, building awareness or hype around a new launch needs time. You need to plan your social media outreach, create print media collaterals, create a buzz around your brand, and more.
   Knowing your launch dates beforehand gives you ample time to plan the perfect mega event.
   
   

4. Cost and Waste Reduction

   Do you remember the catastrophic example we discussed a few sections ago? The one where you predict wrong and end up with surplus goods without any outlet? Sophisticated forecasting and demand management help you turn that into loads of profit.
   Here’s a simple analogy – you know about the Bullwhip Effect, right? How a small fluctuation at the retail end sends major waves at the production level. The demand management process helps build supply chain responsiveness and alleviate the Bullwhip Effect.

   A study published in the International Journal of Physical Distribution & Logistics Management found that improved demand forecasting and communication reduced the bullwhip effect by up to 60%.
   
   

5. Enhancing Customer Service

   The customer is King – this won’t change anytime soon. While one happy experience might bring in 6 others, one bad experience, especially in this digital world, will be brought to the notice of 6000 others.

   
   So, keep them happy! Forecasting and managing demands help you know exactly what your customers want, and you can meet their needs even before they ask for it.

   
   

   That’s right! Remember those “Deals for you” and “You may also like” sections on Amazon? The relevance of these suggestions is thanks to their meticulous analysis of your purchase patterns in combination with other similar personas.

   
   

   Moreover, their sophisticated algorithms ensure the availability of popular products by restocking inventories as and when required.

What are the Types of Activities Involved in the Demand Management Process?

The demand management process comprises end-to-end planning, like collecting and reviewing historical data, leveraging AI-powered models to anticipate demand, planning supply chain responsiveness, and managing consumption demand to mitigate production challenges.

1. Reviewing Historical Data for Qualitative Analysis

   Customer behavior data could provide insights into how consumers perceive your products. Information on customer likes, dislikes, purchase history, etc., helps you plan your targeting campaigns accurately.
   
   

2. Evaluate Market Condition and Competitor Data

   Market and industry conditions play a pivotal role in determining consumption patterns. Analyze the industrial sector and learn about economic conditions, employment data, etc., to understand customer sentiments and plan your production and supply accordingly.

   
   For example, the recent recessions brought down employment rates and, thus, the general customer’s expendable income. Simply put, people would think twice or even thrice before making a purchase. Without the luxury of purchasing on a whim, retail stores might end up selling only essential commodities.
   
   

3. Leverage AI-powered Models for Data Analysis and Visualization

   AI-powered predictive models can analyze incredible loads of data at a time and visualize it in a manner perceivable to the general public. Better visualization streamlines the planning process, thereby improving operational efficiency.

   
   Moreover, AI models are better equipped for incorporating market fluctuations and trends in real time, thereby improving predictive accuracy.
   
   

4. Structure a Demand Plan

   Once you have the predictive market scenarios in place, you need to build a contingency plan that addresses all possible scenarios. This plan will help you mitigate probable supply and demand fluctuations and build a responsive supply chain that focuses on customer satisfaction and profitability.
   
   

5. Implement the Plan Across Supply Chain Touchpoints

   Well, the plan is only as good as its execution! Ensure that the demand plan is circulated to all POCs across supply chain touchpoints. Understanding probable scenarios could help them manage groundwork in a responsive and efficient manner.
   
   

6. Manage or Mitigate Consumption Demand

   Interestingly, brands hold a lot of influence over consumer behavior. For example, let’s take the well-known Apple Inc. If you noticed, they will often reduce the cost of older models when they launch a new one. While the loyalty the brand holds does not affect the new product launch, the lowered prices often influence consumers to make purchases. This further helps Apple clear up the existing inventory stocks.
   
   

   A similar example is with discount coupons or buy two get one offers. Consumers who weren’t even looking to buy a commodity ended up purchasing twice their requirement for fear of missing out on what seemed like a great deal.

   
   

   In other industries, brands can alter their production capacity in anticipation of seasonal trends. For example, a spokesperson for Mother Dairy recently disclosed to the Economic Times that they had to ramp up milk production during the recent festive season. Diwali, Christmas, and New Year’s, followed by the marriage season, saw an incredible hike in demand for milk.

At a Glance

In essence, the symbiotic relationship between demand management, forecasting, and supply chain logistics is the cornerstone of success for businesses navigating the complexities of the Indian market. With a colossal online shopper base and diverse festive seasons, companies must master the art of meeting consumer demands efficiently.

Demand management acts as a strategic guide, aligning operations with consumer buying trends, while accurate demand forecasting empowers businesses to plan for peaks and troughs in the market proactively. The benefits extend beyond mere sales boosts, touching upon risk determination, resource allocation efficiency, brand awareness, cost reduction, and enhanced customer service.

The demand management process, encompassing historical data review, market analysis, AI-powered modeling, demand planning, etc., highlights the comprehensive nature of this strategic approach. In a dynamic business landscape like India, where consumer preferences and market dynamics are in constant flux, the integration of demand management and forecasting emerges as a critical formula for business resilience, ensuring companies not only navigate challenges but thrive in the face of diverse and ever-changing market demands.