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Predict, plan, price - the value of integrated demand planning in retail

Forecasting, planning and pricing form the very essence of retailing: having the right product available at the right time at the right price is the holy trinity. Commercial and operational execution are in sync when these three elements are well-coordinated. Unfortunately, many retailers are far from successfully syncing supply and demand. A lack of coordination quickly hurts margins and negatively affects customer satisfaction and your success as a retailer. How to create the right interplay between these elements? The time has come to integrate demand planning with forecasting, supply planning and pricing.

Winter wonderland in The Netherlands: people ice skating over a frozen lake

To adequately connect demand, replenishment and pricing with each other is a difficult game to play. Mastering this relationship requires to overcome the inherent complexities of supply and demand planning along with the many challenges driven by the very nature of retail itself.

Let us explore some in more detail. 

Inherent complexity: demand forecasting  

Demand forecasting continues to capture the minds of many in the organization. Partially intuition, but mainly mathematics, the key variables are simple: volume and time. Add to that promotions, external factors (such as weather, trends, global events), macro-economic trends and competitor dynamics, and you see complexity emerge. However, finding the right forecasting methodology with the lowest forecast error, that’s where many retailers stop their forecasting efforts. And exactly that is where the game begins for the most dominant forces in the retailing landscape. 

Inherent complexity: supply planning  

Knowing demand is step one. But step two is to ensure stock availability at the right time at the right place. Supply planning and inventory management balance lead times, storage constraints, distribution constraints, batch sizes, and costs against the ability to serve the customer at the right time at the right place. Whereas this is an area to optimize quantitatively, many retailers take a ‘better safe than sorry’-approach to stock planning. This can result in an abundance of obsolete stock followed by excessive markdowns, ultimately resulting in significant margin impact. 


Inherent complexity: pricing  

Pricing is an art form, balancing multiple variables itself. Most of which sit in the behavioral domain of economics. Think about price elasticity: to what extent will demand increase for which price drop? Or psychological factors like odd-even prices (€4,95 vs. €5,00), product substitution, or seasonality (think about the price differences of skiing gear in-season vs. post-season). Non-behavioral factors also play a role. This could be for example how your price compares to competitors or what your competitive landscape looks like. And let’s not forget the minimum price the article needs to go for to make a profit. Pricing is an art, and a complex one. Yet pricing efforts are often simply driven by revenue targets, upping the prices by a certain percentage cross-category and hoping for the best. 

Complexity by ‘nature’: the unpredictability of Dutch winters 

Let’s look at an example. In the Netherlands, the anticipation of 'ijskoorts' or ice fever during winter is not only a source of communal excitement but also a strategic challenge for businesses. As temperatures drop and the prospect of frozen canals and lakes arises, local shops gear up for the expected surge in demand for winter-related products like ice skates, thermal wear, and hot beverages. However, the unpredictability of Dutch winters adds a layer of complexity to the equation. In some years, the much-anticipated 'ijskoorts' may not materialize due to milder weather conditions, leaving businesses with a significant inventory of winter gear and supplies. However, once the frost kicks in, demand nearly always exceeds supply, which paves the way for smart pricing strategies. Businesses must navigate the fine line between meeting customer expectations and maximising margins during 'ijskoorts' and mitigating potential margin loss when winter fails to deliver its icy spectacle. 

This example emphasizes the intricate dance between demand forecasting, pricing, and stock management in the face of unpredictable weather patterns. Complexity ‘by nature’. Once you also factor in the many challenges driven by the very nature of modern retailing itself, a seemingly unsolvable puzzle emerges: 

Demand forecasting, stock planning, and product pricing are intertwined and may cause opposite responses on each end of the spectrum. Adjustments to price will almost always affect demand and replenishment. Demand dynamics will always affect replenishment and pricing. And changes in supply planning may ultimately affect prices and demand in the form of markdowns or empty shelves. 


Added retail complexity: thousands of items and multiple variations  

Most European retailers often hold well over 10,000 SKUs. Things become even more complex when there is a parent-child relationship between a product and its characteristics, such as a t-shirt, in a certain color, in a certain size. Or think about product bundles comprising multiple individual SKUs which are combined and sold as one, such as a cordless drill with a drill bit set. This is where most retailers would apply the 80/20 rule and channel their focus on the roughly 20% of items that contribute most to revenue, skipping the remaining products that may eventually end up on the markdown shelves. 

Added retail complexity: multiple channels  

Retailing nowadays is a blend of online, physical stores, and sales through partners. Each with its own demand patterns, pricing characteristics and stock constraints. Price comparison, for example, is much more important in online sales than in physical stores. Whereas stock management is completely different – as a central warehouse can hold more items and item variations than a physical store. The added complexity of multiple channels is usually not considered and either left out of scope or is bundled together and viewed as being homogeneous.   

How can you manage this puzzle of complexities? Many retailers try reducing the scope by creatively connecting (or even automating) multiple exports from several systems with complex spreadsheets. While that may do the trick, it is incredibly time-consuming, prone to error and not at all scalable and flexible. A more holistic and modern approach is necessary to truly master the complex triangular optimisation of forecasting, planning and pricing.  

Man in sports shop looking at ski shoes

An integrated demand planning solution to combine forecasting, planning and pricing  

Integrated demand planning solutions have proven to be effective in supporting businesses with managing the combination of forecasting, (stock) planning and pricing. Compared to their traditional counterparts, digital solutions can handle more volume, more product characteristics, further planning horizons, product fade-out, multiple sales channels, can be implemented in terms of weeks rather than months, and often leverage AI and ML – for example to respond to market prices. 

Machine-based learning systems need ‘only' about 300 to 400 data points and two years of historical data to start predicting correctly. It can find patterns and connections that a human would not be able to. Integrated systems with advanced technology do depend, however, on the quality of data put in. As the adage goes: garbage in, garbage out. Finding the optimal balance therefore between human and machine interaction is key. In general, the best way to do it is putting the human in control, via exception-based management and letting the machine do all the repetitive tasks and complex calculations.  

Implementing integrated demand planning involves untangling a myriad of processes and systems that intertwine within a business. However, navigating this complexity to deploy a truly integrated form of integrated demand planning can unlock significant value. It can greatly increase your margins and enable an effective responsiveness to dynamic market conditions and seasonal fluctuations, such as ‘ijskoorts’. 

Hence, we are winter-wondering: where have your skates taken you so far on the journey of integrated demand planning? We are eager to take you through the possibilities and discuss your needs. Ready to join us on this ice-cool adventure? 


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