**3.1 Foundations of research on cognitive biases**

Tversky and Kahneman [5] were the first who questioned the assumption of rational human behavior and introduced the term of cognitive biases. They state that humans taking decisions systematically go wrong, especially in complex and uncertain environments. In further experiments, [14] deepens this research of the underlying factors and describes the cognitive processes of intuition and reasoning.

Stanovich and West [15] named these cognitive processes System I (intuition) and System II (reasoning). While System I acts automatically, fast, emotively, and effortlessly and is hardly controllable, System II operates relatively slowly, reflected, and effortful [15]. System I creates spontaneous impressions and persuasions, which form the basis for further decisions and actions of System II. Based on this two-system view, [14] claims that impressions are generated in System I and judgments are made in System II.

This fundamental research made clear that there are plenty of different cognitive biases that may affect human decision-making. Ref. [6] categorized these biases into six main categories:

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**Figure 3.**

*Lead time syndrome in PPC.*

*The Influence of Cognitive Biases in Production Planning and Control: Considering the Human…*

2.Statistical biases are the human tendency to over- or underestimate certain

3.Confidence biases act to increase a person's confidence in their prowess as a

4.Adjustment biases describe the human tendency to stick to the first available

5.Presentation biases influence humans in their decision-making by the way how

6.Situation biases describe the way how a person responds to the general decision

We take inspiration from a case study of the steel industry presented by [2]. The analyzed PPC process takes place within a R&D department of a German steel case company. To compete in the global steel market, a short time to market is crucial. Especially in the R&D department, production and analysis processes are hardly to plan, and it is one of the major challenges of production planners to fulfill the customer requested delivery date. Samples of new alloys have to pass sequences of different tests before they can be launched in the market. In the analyzed R&D process, the first orders for different steel samples are placed through external and internal customers. After estimating the planned lead time for several manufacturing and analysis processes, the orders get a due date. For the scheduling of the production orders, a custom-developed DSS is used. In total, a production system with 20 machines and 35 employees in 1 shift was analyzed over a period of 3 years (from 2011 to 2014, 1.023 orders were analyzed). On-site visits, expert interviews, and observation documents were the used research methods. To evaluate the key performance indicator (KPI) development in terms of due date reliability, inventory, and lead times, feedback data from 13 months based on 240 shop floor

**3.2 Case study: decreasing due date reliability at a German steel producer**

information or to a reference point when making decisions.

*DOI: http://dx.doi.org/10.5772/intechopen.89259*

information is being displayed.

statistical parameter.

decision-maker.

situation.

*3.2.1 Initial situation*

calendar days were analyzed.

1.Memory biases describe biases influencing the storage and the ability to remember information.

*The Influence of Cognitive Biases in Production Planning and Control: Considering the Human… DOI: http://dx.doi.org/10.5772/intechopen.89259*

