Random Demand Increase

In this scenario the objective is to determine if it is more economically beneficial to hold more stock in order to cope with random increase in demand or lose part of those sales and expect the overall system to adjust to this event. In reality, there are several reasons for relatively small and random increment in demand; for this case-study in particular, these are the main factors which increases or decreases demand:

 Weather is one of the most important factors influencing demand. In the case of chocolate sales

weather has a significant impact on a week-to-week basis: if cold the demand increases, whilst in warm weather the demand decreases greatly. For example, customers do not purchase chocolate in warm conditions but also if it is, for example, too rainy the high-street footfall is affected but the mail order sales are increased;

 Economic factors for example an increase in disposable income due to for example higher wages and

lower taxes;

 Advertising, media and social networks can increase brand exposure and loyalty to the goods and

therefore an increase demand;

 Expectations of future price increases;

 Examples of changes in other prices, the impact of prices increases of some products might mean that customers will transfer their purchase to another product;

 Non-planned product promotion or marketing as a reaction to a competitor offer;

 A change in the prices of related goods (complementary goods or substitutes²), for example the main competitors to chocolate gifting are flowers gifting, so an increase in flower prices might impact on chocolate gifting;

 Increase on the product exposure in the shelves (retail) or the homepage (web), or change in the

merchandising strategy;

 Speed of change in the marketplace, which means historical data is not necessarily a good predictor of

future demand;

 Shorter product lifecycles.

2A good that causes an increase in the demand for another good when its price increases is called a “substitute good”. A good that causes a decrease in the demand for another good when its price increases is called a “complementary good”.

From the scenarios presented leading to a demand increase, two scenarios will be studied:

(i) Press coverage and advertising leading to an increase in demand for the specific product line;

(ii) How another product line out of stock impacts on this line through product substitution, one of the aspects not considered so far.

Considering a 52 weeks’ time period (T = year), the demand has been manually changed during a period where demand is quite stable, meaning where no increase in demand was expected, as follows:

A. At week 38 the retail demand had a 66% increase on the same week last year (LFL = 66%) due to the fact that the product was displayed on the store windows following a press coverage on the Sunday Times.

B. At week 27 this product was used as a product replacement in the mail order chain after the seasonal version ran out, which meant that 800 extra units were sold.

These case-studies were analysed in two different scenarios:

(i) No changes to safety stock (determined in the GA optimisation in chapter 4).

(ii) Increase the safety stock (q was increased from 163 to 326 units in scenario A and q was increased from 342 to 682 units in scenario B, which corresponds to the average demand for the period).

The results are shown in Table 9.

52 weeks No changes to safety stock Increase the safety stock

Case Overall profit Backorders Overall profit Backorders Agent

A £386k 34 £381k 302 Retailer

B £378k 793 £375k 838 Mail Order

Table 9 Model output for increase on demand scenarios.

In scenario A, despite the 66% increase on the same period the previous year, the existing safety stock is almost enough to fulfil demand and manage the demand increase through the supply chain

without major out-of-stock situations (34 backorders) - this is true even without changing the production plan. In real life, within 8 weeks the manufacturing agent will to be able to re-establish the stock levels, therefore no backorders will exist therefore is no need to increase the safety stock. In these circumstances it isn’t surprise that increasing the safety stock will considerately affect the profitability.

In scenario B, the increase of demand corresponds to a period where there is already a natural uplift in demand therefore is not so easy to fulfil with extra product requirements causing an out-of-stock situation (793 units) so, even if the mail order safety stock is increased, it places further strain on the supply chain and interestingly increases the backorders affecting not only the profitability, as there are higher stock holding costs, but also a higher probability of more out-of-stocks in the longer term.

These results show that lower safety stocks levels mean higher profitability, despite the increase in out-of-stock situations. These results support Ketzenberg et al.’s (2000) conclusions, which demonstrated that excessive inventory levels impede profitability. Traditionally, lower inventories meant lower costs and lower service, but on the contrary, they proved that lost sales were lower than expected, with the lost sales of all the heuristics being minimal. In reality, another aspect to consider is that excessive inventory holding levels affects profitability through a less obvious route: by crowding out other categories of goods. A retailer with limited shelf space must face the trade-off of putting fewer categories out for sale against holding inventories of current products.