Demand planning has long been known as the assurance process by which products and services will be available when needed — up to a year or more in advance. However, as supply chains have become more complex, and data and technology more sophisticated, demand planning can be so much more.

For starters, the data necessary for every decision in demand planning exists already. The art and science era of demand planning has given way to science due to the advancement of technology that can support Integrated Business Planning and the S&OP processes.

The key concept of using prescriptive analytics for demand planning is to optimize supply and demand simultaneously instead of solely matching supply to demand forecasts.

Here’s how that works.

Three Best Practice Steps for Demand Planning

Prescriptive analytics can take demand planning to new levels because of its what-if analysis abilities. Now, companies can look at demand options with considerations like resource allocation and financial objectives. This is powerful because what-if scenarios like “How are supply costs impacted when demand planning exceeds resources?” or “What substitute products could be manufactured to fulfill demand with available inventory?” can be validated with data responses.

Best practice advice to implement prescriptive analytics for demand planning includes:

1. Implement an Easy-to-Use, Scalable Analytics Solution
2. Utilize the Power of Analytics
3. Create an Effective Change Management Strategy

Implement a Scalable Analytics Solution

Because four out of five companies use spreadsheets for supply chain planning and over 75% of companies say their supply chain plans aren’t integrated with manufacturing, procurement or sales, the potential to scale analytics is missing.

The most successful organizations are integrating scalable enterprise solutions, offering companies the ability to:

• Analyze unlimited what-if scenarios simultaneously, not sequentially
• Identify opportunities across all aspects of the supply chain, including supply and demand
• Prescribe execution that optimizes both supply and demand

In turn, organizations rely on integrated data.

Utilize the Power of Analytics

Business intelligence tools continue to favor descriptive and predictive analytics. Unfortunately, these are two processes that limit companies on analyzing data to take action on ways to maximize profit while considering business constraints.

Questions like “What should be done?” or “What can we do to make ‘x’ happen?” are powerful when the responses are data-driven.

The most successful organizations are implementing prescriptive analytics into their demand planning. They are calculating forecasts AND translating those demand forecasts into actionable and feasible plans.

Create an Effective Change Management Strategy

Corporations are expanding the use of prescriptive analytics because of increased awareness around its transformational abilities. This climate of acceptance helps, but it is advised that a change to a data-driven culture begins at the top. Democratizing data and insights shift data support systems from silos to cross-functions within the organization.

The rewards of the change to seeking data-driven plans of action are high, and happen as more employees, including those outside of IT, gain access to easy-to-use business intelligence and analytics.

Demand Shaping in Near Real-Time

Within the realm of demand planning with prescriptive analytics is the ability to execute on-demand shaping in near real-time. This ability to quickly react is important when supply and demand become out of sync, which is inevitable with market dynamics. However, by looking at scenarios such as promotional programs, demand shaping actions can equalize the imbalance.

The objective is to identify the impact of different demand shaping strategies on the business, maximizing a combination of revenues, profit, and volume through:

• Pricing
• Promotions
• Specific customer deals

Prescriptive analytics is the advanced analytics tool that provides a solution to that long-standing issue “how do we best meet our demand while maintaining profitability?”…even when there are supply constraints or excess capacities.

With prescriptive analytics in place, companies can integrate demand planning as a subset of the S&OP process in addition to taking advanced actions with demand shaping.