The Evolution and Future of Demand Management

For the planners who are managing super-complex supply chains that include everything from your tiered suppliers, inventory to logistics and sales, the pressure has literally gone through the roof. Yes, we live in an era where demand drives supply.

But to not be able to understand or manage that demand, given the market volatility created by higher customer expectations and shorter fulfillment cycles, has created continuous ripples of chaos in the entire supply chain.

In the midst of such a situation where planners are desperately seeking back control, key questions around demand management that you need to ask yourself are:

Are we able to accurately anticipate and analyze demand to fulfill the requirements? If not, how do we get there?
Are we able to intuitively align inventory to match demand? If not, how do we avoid overstocking or understocking products?
Do we have thorough insight and understanding of existing production operations? If not, how to gain more visibility?
How flexible are our supply and demand plans to ensure extreme market conditions don’t impact the existing productivity? If not, how do we drive more agility?

In the quest to answer these questions lies the supply planner’s capability to rein back control over one’s supply chain operations. And enabling you to get to these answers in a more efficient and faster way are the AI-driven data and analytics capabilities rooted in strong demand management principles.

The Evolution of Demand Management Solutions to Meet Changing Needs

Demand management solutions have gone through a series of changes and evolved over a period of time. In fact, one of the significant areas where progress has been made is to provide the much needed flexibility so that demand solutions can evolve as the organization’s priorities change and the market evolves.

Many growing organizations have, over time, tweaked their demand management processes to ensure the following objectives are met:

Enhanced customer orientation and service delivery
Companies have realized that demand management has to incline towards seamless customer service. Therefore, a clear understanding of client needs and behaviors helps demand management align with better customer satisfaction and thus, boost sales.
Better forecasting accuracy
Demand management solutions need to have strong predictive analytics to provide key insights to optimize decisions for CSCOs. This helps them reliably execute supply chain management initiatives with accuracy.
Reduced operational costs
With better forecast accuracy, demand can be aligned with inventory investments and can therefore arrive at better stock levels to avoid overstocking or understocking. Demand management, therefore, can directly contribute towards cutting down day-to-day business running costs.
Better accountability of business actions
With clear demand management mechanisms in place, CSCOs can ensure better accountability of business initiatives and reduce the possibility of uncertainties and possible bottlenecks in the business strategy.
Effective end-to-end supply chain planning
Demand management can ensure the right balance is always maintained between supply and demand and this provides clear visibility across the value chain with synchronized efforts and better collaboration within the business units.

Demand Planning and Demand Management – Irreplaceable and not Interchangeable

Often used interchangeably but yet very different, demand management and demand planning are not the same from a supply chain perspective.

Though demand management is similar to demand planning as the core function of both processes attempt to balance supply and demand, however, in the larger scheme of things, demand management goes way beyond demand planning.

Demand planning involves forecasting future demand for a company’s products or services, based on historical data, market trends, and other factors.

The goal of demand planning is to create a more accurate and reliable forecast of future demand, which can then be used to inform production schedules, inventory levels, and other aspects of the supply chain.

Demand planning typically involves the use of statistical models and other analytical tools to project future demand and identify potential risks or opportunities.

Demand management, on the other hand, involves actively managing demand for a company’s products or services to ensure that supply can meet demand.

This may involve a range of strategies, such as adjusting prices, launching promotional campaigns, or offering incentives to customers who purchase in off-peak periods.

The goal of demand management is to balance supply and demand in a way that maximizes profitability and minimizes waste, while also maintaining high levels of customer satisfaction.

In summary, demand planning is focused on forecasting future demand, while demand management is focused on actively shaping and managing demand to optimize supply chain performance. Both approaches are important for companies to effectively manage their operations and meet customer needs.

Data-driven Demand Management and Planning for Holistic Supply Chain Excellence

It takes accurate data, a centralized, collaborative approach to operations, and tight inventory control to ensure continued customer satisfaction and healthy revenue. Accurate demand management can help you balance your stock levels while minimizing risk and still delivering on customer promises.

Unfortunately though, supply chain disruptions are expected to continue in 2023 and beyond. Lead times will remain long, and supply unreliable. In the midst of all that chaos, a great way for better control over demand management would be to start by accurately forecasting demand in the near-term.

A strong AI-powered demand tool can help predict future sales and effectively plan for new product launches and campaigns, factoring in seasonality and other variances while ensuring that your supply chain continuously meets demand.