Promotion Planning for Supply Chain Planning (part 1)

Promotion Planning

Trade promotions have always been murky water.  Manufacturers give millions of dollars annually to retailers in the form of slotting fees, sample and trial items, reverse logistics fees, new stores fees, introductory allowances, volume pricing discounts, and promotions to end-consumers.  This money is spent to drive bottom-line ROI, improve customer loyalty, build stronger sales channels, and execute market share strategies.  So, how can a manufacturer accurately determine the impact on the supply chain, and analyse the return on investment, before committing to a promotions event?  It all starts with a comprehensive promotion plan.

Promotion Planning success depends upon:

When embarking on a promotions planning exercise, there are several dimensions of the planning process that should be considered.


Retailers often see promotions through the lens of the consumer.  Their focus is on the products, being promoted for the duration of a  promotion.  Retail success is often measured by sales uplift, alone.  Manufacturers do not have this luxury, and need to think more laterally than a Retailer.  Manufacturers plan for full impact of a promotion, which also requires managing the unintended promotional impact, on the wider product portfolio, not only those items being directly promoted.

Manufacturers measure the potential cannibalisation of product sales from similar-use, non-promoted products.  For example, if a 1Kg packet of laundry detergent is promoted, it may reduce the demand for the 5 Kg pack of the same brand, which is not promoted.  There are many complex examples of product-cannibalisation.  Understanding the product-cannibalisation effect, requires analysing sales promotion history, and identifying correlating sales trends across different products.  It is rarely an obvious change in pack-size.

The ability to consider the halo-effect, where a non-promoted product is positively impacted by the sale of a promoted product, is also important.  If a paint manufacturer promotes a certain type of paint, then there may be increased demand for undercoat or sealer.  Halo-impact planning often affects distributors, more than manufacturers, as the halo product is often sourced elsewhere.  For example, a paint manufacturer promotes paint, and the paint-brush manufacturer incurs a demand spike.  Like product-cannibalisation, Impact of the halo effect may be predicted by analysing historical sales data, and performing correlation detection analysis.

Manufacturers understand the promotions impact on the full planning horizon, beyond the sell-in dates.  Promoted products often show reduced demand, for several sales days before and after promotion.  Manufacturers determine the self-cannibalisation behaviour of promoted products, that occur outside of the sell-in dates, and then factor it into the total demand plan. 

Failure to manage cannibalisation and halo effect impact, may lead to unforeseen demand signals in the non-promoted product range.  This causes unnecessary firefighting, by production and material planners, to meet service levels when they are busy executing a promotion.

On the flip side, the ability to accurately plan the full impact of a promotion has wide-reaching benefits that propagate through the supply chain.  Manufacturers with accurate visibility of promotions-impact, may plan production, procurement, warehouse and distribution capacities, as well as the additional labour required to manage the promotion.


Manufacturers do not measure promotion success by solely analysing the uplift quantity against the rebate or price reduction.  It is important to analyse the financial impact across the product portfolio, and across the planning horizon.  

The correct metric to measure promotions activity depends on the promotions strategy.  For new markets and new product launches, market share growth is important.  Financial stakeholders focus on revenue, sales budget achievement, and profitability.  For sales and marketing, promotions ROI is important.  Regardless of the metric, promotions performance is measured by comparing a baseline (no promotion) plan to a promoted plan.

Baseline plans are well defined using traditional demand planning techniques, such as statistical extrapolation and demand sensing.  However, many manufacturers struggle to easily generate a historical sales baseline.  The historical sales baseline is an important value to truly understand the promotions value-add.  It is also an important input to statistical and machine learning techniques to improve the accuracy of statistical forecasting and budgeting.  Advanced demand planning solutions offer a range of methods to solve this problem, such as pro-rating gross sales volumes against the baseline component of the demand plan.  This approach effectively negates the “intended promotions impact” from the gross sales values to automatically determine a historical sales baseline.  Many notorious supply chain disaster stories arise from a manufacturer’s inability to determine a historical sales baseline. This includes the infamous green Volvo saga, which led to increased production of an obsolete item.  This would not have happened if Volvo had projected future sales on a historical sales baseline instead of on gross sales.


Like all components of a supply chain plan, promotions plans must be as accurate as possible.  Practitioners often see promotions planning, as an art,  rather than as a science.  Which products will be impacted?  Precisely, what is the impact, and when will it occur?  Traditionally, this was done by guessing consumer response to a given incentive or message. 

Modern, super-connected supply chains provide more data, from more sources, more often to measure promotions behaviour.  If the data is the fuel, then analytics is the engine to convert consumer behaviour into accurate insights, of how a specific promotion will behave in the future.  The pattern matching and profile capabilities of machine learning algorithms are capable of generating a weekly profile of sales behaviour before, during, and after a promotion.  This includes promotional sales profiles, but also cannibalisation and halo effect sales profiles.  It is sensitive to the customer, the region, the event, and the type of promotion.


Modern digital supply chains move fast, and include promotions activities.  Agile planning requires strong connectivity and visibility, to ensure the plan may respond to unforeseen demand and supply signals.  Visibility requires a single promotion control-tower or active-dashboard experience where all promotions may be plotted against a timeline, allowing smart signalling to describe the status of the promotions landscape.  Promotions planners require a single dashboard experience to rapidly visualize;

  • Promotions by brand, promotion type, event, customer, or region.
  • Competitor promotional activity.
  • Risks and Alerts that impact supply or demand.
  • Analytics such as revenue, uplift, profit and return on investment.

In addition to the visualization of the landscape, the planner needs to be able to simulate and compare multiple promotions strategies to determine the most appropriate approach for the current plan.

Stay tuned, part 2 of promotion planning success next week.

Shaun Phillips
Shaun joined QAD DynaSys in 2017 and brings with him an extensive career in Supply Chain technology. As global product & market manager, Shaun is responsible for the strategic direction of the QAD DynaSys DSCP product as well as the go-to-market enablement and market development. Shaun has an international focus having started his career in Australia spending many years serving the APAC region. He then spent several years in Germany and since 2012 has called Paris home. Outside the office, Shaun often sneaks a shocking game of golf in between the adventures of raising two young boys. He is very passionate about Australian Rules football.