How to do effective demand management?

What is demand management?

Demand management helps your organisation to tailor its capacity to meet variations in demand. It’s used to manage the level of demand, often using marketing or supply chain management strategies. Having successful demand management in place ensures that products or services reach the right people whenever and wherever they need it.

How does the demand management process work?

Demand management is made up of multiple activities that make the process work. The first thing to consider is the type of demand, independent or dependent.

Independent demand is influenced by the market conditions and is not related to any production decisions. Independent demand can be estimated and usually demonstrates a continuous and definable pattern. On the other hand, dependent demand can be forecast, and depends on product decisions.

There are four basic steps in the demand management process:

All these step’s act in coordination and, when done well, enables you to match supply with demand with minimal disruptions. It’s also important to check that through the process, you’re constantly trying to find new ways to reduce the variability in demand and to improve your organisations flexibility.

As you can see, successful demand management requires you to balance the whole area of the supply chain process. If some areas within the supply chain face challenges, this ripples down through the different areas within the supply chain.

Potential advantages of good demand management

To have a ‘good’ demand management process within your organisation, you must rely on the data being accurate. There’s also a need for collaborative demand forecasting. This is where firms reach a consensus, both internally and with their value chain partners on the expected level, timing, mix and location of demand. The data should form a common foundation for the wider departments including merchandising, logistics and budgeting processes. If all these vital things are followed, you should experience the following advantages:

What is supply chain forecasting?

Supply chain forecasting refers to the process of predicting demand, supply or pricing for a products in a particular industry. It looks at past data about product demand to help make decisions and leads to better supplier relationships and customer satisfaction.

Why is supply chain forecasting important?

Supply chain forecasting is crucial for organisations to accurately predict demand. The more accurate your forecasting is, the faster you’ll be able to fulfil orders and keep customers happy. Forecasting helps you to make informed decisions on production, inventory, pricing and resources, but also helps to avoid excess inventory which is costly. Any errors in forecasting can have consequences in the supply chain which can result in loss of sales and wasted resources.

What are the methods in supply chain forecasting?

There are two main methods for supply chain forecasting, and those are quantitative and qualitative.

Quantitative

There are two main methods for supply chain forecasting, and those are quantitative and qualitative.

• Moving average forecasting is based on historical averages but doesn’t allow for seasonality or trends.
• Exponential smoothing has an emphasis on recent data and is ideal for short-term forecasts
• Auto regressive integrate moving average is suitable for forecasting up to 18 months or less but is very time consuming
• Multiple aggregation prediction algorithm is designed for seasonality

Qualitative

This method relies on insights and expertise and experience of industry experts.

• Historical analogies predict sales based on existing products.
• Market research is the process of researching, surveying and interviewing a specific demographic.
• Internal insights are based on opinions of experience staff to inform predictions.

What makes supply chain forecasting difficult?

As organisations supply chains span the globe, this can make supply chain forecasting difficult. Things such as trade policies, currency changes and any political instability all affect accurate forecasting. Consumer behaviour also make forecasting difficult. Seasonal events and consumer preferences all fluctuate, so it’s important to monitor certain trends and be prepared, as well as looking at new products out there on the market. Another challenge is the reliance on data quality. Inaccurate data can lead to mis-leading forecasts, as well as being able to access historical data, so make sure to invest time and resources into this area.

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