Demand Planning & Forecasting

What is demand planning & forecasting?

Demand planning and forecasting is a set of business processes that involve predicting future demand and aligning production and distribution capabilities to meet that forecast. Involving a number of different business functions this requires the sharing of timely data, the accurate processing of that data, and agreement on joint business plans.
The process consists of three parts:

1. Demand forecasting: The art in the process for creating a statement of projected, unconstrained, demand for a product or service over time
2. Demand planning: The science involved in restricting (or increasing) a forecast to reflect known constraints and associated impacts of capacity (production or logistics) or changing priorities or the impact of external events
3. Demand management: The creativity involved in influencing the demand by the addition (or cancellation) of activity, the increasing or reducing of price, the rationing or allocation of stock, etc.
    

Increased investment in forecasting

Increased competition, more frequent new product introduction and shorter product life cycles have made forecasting increasingly complex.
Organisations have also become more complex in the last decade operating in a greater number of locations, business units and markets. Furthermore, unprecedented levels of economic uncertainty, affecting buying patterns and historical data, have added to this complexity.
Our research highlights that the need to improve service and reduce stockholding are the two biggest drivers to investment of resources in the forecasting and demand planning process.

Key demand planning challenges

According to IGD research, there are three main types of challenges faced by the industry in improving their forecast accuracy performance. These are:

• Poor communication including issues such as late communication of changes on promotion mechanics
• Inadequate internal collaboration and processes to manage business and customer requirements
• Knowledge gap caused by issues such as ‘no recognised forecasting tool/process’, ’promotional complexity (multiple promo-SKUs)’ and ’data integrity, e.g. multiple promotional SKUs for base product’

In addition to these challenges, there are organisational issues as well. For example, who does the responsibility of the forecast sit with? Is he/she also accountable for it? If not, is he/she empowered to influence or challenge the forecast?

The forecast cycle

IGD research highlights that a ‘typical’ process to the forecasting cycle (for short-term forecasts) includes the following steps:

Measuring forecast accuracy

The key to good forecasting is stability in the accuracy, as this will help set correct inventory levels, thus avoiding over-stocks and out-of-stocks. Where forecasts are consistently higher than the actual sales, inventory levels will rise; where forecasts are consistently lower than actual sales, the service levels issues will increase.
Forecast accuracy can be measured at multiple levels including at a SKU, customer or business level.

Benefits of measuring forecast accuracy:
The need to improve service and reduce stockholding has driven businesses to invest resources in the forecasting and demand planning process.
IGD research identified a number of key benefits from measuring forecast accuracy:

1. Service benefits – in addition to a ‘clear impact on customer service’, a formal demand planning process has helped companies to respond quicker to market related developments.
2. Cost benefits – these include lower waste, improved production accuracy, reduced stock holding and better capacity planning.
3. Revenue benefits – through stronger availability on-shelf, and ‘being closer to the business plan’.
4. Organisational benefits – such as better accountability, control over processes and a reduced level of ambiguity and improved internal collaboration.
    

Measurement calculations:
Absolute Forecast Accuracy

Forecast Bias

Collaboration is key

A lack of collaboration with trading partners is seen as a key frustration for suppliers in the demand planning process, and indicates that despite efforts to share information, this is not common practice across the industry, and is not sufficient on its own.

The way forward

Flexibility in responsiveness and the robustness of integrated business planning are important factors in delivering real-time demand-led supply chains, but companies need to take a more systematic approach to demand planning and forecasting. There is a need to strive for deeper collaborative supply chain practices - both within organisations and with trading partners - and so developing collaborative supply chain practices will drive business capability, optimise service levels, reduce wastage and maximise on-shelf availability.