Verst Insights Blog

5 Strategies to Solve Demand Planning Problems

Written by Robert Runyon | August 31, 2018
In order for companies to improve how they respond to and manage demand, these companies must ensure that their forecasting, demand sensing and shaping, planning, and fulfillment capabilities are organized and coordinated to counter the shift in today's market demand.

Demand Planning & Management Overview

Demand management capabilities need to be strengthened, and there is a large need for many companies to do so. There is a big need today for companies to strengthen their demand management capabilities. Demand volatility and the lack of demand visibility are two of the top challenges that companies face in the supply chain.
 
A supply chain manager has to understand and investigate deep into the necessities of demand planning. The process all starts by looking into the suppliers of raw materials, manufacturers for products, warehousing associates, wholesalers or distributors to the retail stores. The key to success lies in being ready for the demand peaks and not losing revenue when there is not a demand. Innovation and growth will depend on a company's ability to quickly and effectively process and respond to demand.
 

Five Elements of Demand Management Strategy

The solution to this very complex problem is to not think of demand management in the traditional terms of demand planning and fulfillment. Companies need to create a comprehensive demand management strategy that also encompasses demand forecasting, sensing, and shaping. Here are the best practice recommendations for each of the five elements:
  1. Demand forecasting: Organizations should look at sales forecasts, marketing plans, and downstream deman data, not just the historical sales activity. Machine learning and pattern recognition can help complete not just look at the historical sales activity, but also with innovative signs, such as sales forecasts or marketing plans, and downstream demand data, such as retail point of sale or channel sales data. However, the data mentioned above is often incomplete, and pattern recognition and machine learning can help predict the missing values.
  2. Demand planning: Using more accurate and appropriate data, companies can increase the frequency of forecasts which will improve their demand planning. Sales and operations planning should look at multiple forecasts before deciding on a consensus demand plan. Mature demand planning processes will also provide models for segmented channels.
  3. Demand sensing: In today's economy, real-time "sensing" of demand has replaced demand forecasts that are based on rules in the B2C world because of online ordering. Companies are seeking to have a better visibility of the demand by looking at the indirect wholesale and distribution channels, allowing demand sensing to be applied to the industrial business-to-business market. The technologies associated with demand sensing are now including simulation and optimization strategies that allow companies help with midterm planning.
  4. Demand shaping: Demand shaping includes programs and capabilities such as price management, new product launches, and promotions to increase demand or profitability for products and services. Best practices involve synchronizing supply strategies with demand and product management decisions through processes like S&OP.
  5. Demand fulfillment: In order to meet the demand, companies must differentiate demand fulfillment processes to make accommodations for different products, customers, and channels. For example, certain defined segments or combinations may require certain models, while others will require a different fulfillment technique.

Every company has demand management capabilities scattered somewhere throughout their organization, but they are often distributed across multiple teams and roles. Companies need to design a platform what connects the capabilities to create a rational response to customer demand in order to become better at demand management.