## 2 Fundamental Definitions and State of Research  
The literature review shows that there are about 30 basic methods that help to predict future sales, many of them with subtypes [1]. The purpose of demand planning is to improve decisions that affect demand accuracy [2]. Its main task is to calculate future demand, and it comprises the selection of a specific forecasting method and its parameters. The typical demand patterns are stationary, seasonal, trend, and sporadic [3]. Independent of the demand type, the bullwhip effect is a challenge in every supply chain due to the lack of transparency between stages. As a result, it is frequently difficult to forecast the final customer demand based on orders along the supply chain [4], and this causes an extreme fluctuation of stock at the beginning of the supply chain, creating many backorders alternating with large excess inventory [5]. To combat the bullwhip effect, there should be information sharing of consumer demand across the supply chain in order to allow each party to plan efficiently according to true demand information [6]. Collaborative forecasting and planning are the basis for capacity management through the supply chain. Capacity utilization, like stock levels and work in progress, is one of the degrees of freedom of planning and control in supply chains. An assessment of the necessary capacitive resources is a task in every planning period. Supply flexibility in medium- and short-term planning often requires long-term arrangements [5] such as investments in production capacity. To decide on investments properly, it is necessary to focus on the system limitations. A constraint can be the management of an organization, capacities along the supply chain, or market demand. In this context, the theory of constraints (TOC) provides a framework to deal with capacity management issues with five steps: identify the constraint, exploit the constraint, subordinate the rest of the system to the constraint before increasing capacity, then add new capacities and start other times by finding the capacity constraint [7]. There are four procedures, from short to long term, to adapt supply capacity to demand requirements. 1. Extra hours or reduction of hours: This approach is closely related to the \"additional shift\" process; it allows great flexibility and is used with the advantage of existing employees. 2. Additional shifts: This alternative allows dealing with short-term demand fluctuations. Extra costs and training depend on the demand fluctuation and staff availability. 3. External production: This is used to react to demand peaks; it results mainly in higher unit prices and has the risk of knowledge transfer. 4. Investments: This option requires good predictions of capacity needs, because, as capacity increases, fixed costs also increase. There are multiple customer implications of a lack of capacity, from delays to market share losses. The consequences of bottlenecks are as follows [8]:  
* Limited availability;
* Long delivery times with decreasing reliability;
* Constantly changing priorities and quantities;
* Errors and cancellations;
* High personal commitment of the employees involved in order processing;
* Additional expenditure due to extensive internal clarifications or the search for external alternative suppliers;
* Additional costs through partial and express deliveries, special shifts, and temporary employees;
* Individual decisions instead of overall optimum. If this condition remains over time, customer satisfaction decreases, and companies lose market share and sales potential. Investments are not immediate and, therefore, do not alleviate the bottleneck in the short term and have the risk of being oriented too much to short-term needs and an overcapacity situation developing in the long term [8]. As a consequence, key indicators for capacity-related decision-making should be defined taking into account that the final goal of each business activity is to increase the value of the company [9].