Final answer:
The concept discussed is 'garbage in, garbage out' (GIGO), which emphasizes that quality input is crucial for quality output in computer systems. Problems such as poor system design, inadequate follow-up evaluations, and errors in data analysis can result in poor outputs, affecting business operations and decision-making.
Step-by-step explanation:
The principle you’re referring to is often encapsulated in the phrase ‘garbage in, garbage out’ (GIGO). This concept highlights the importance of quality input in order to produce quality output. In the context of computer systems and data management, if there are errors in data entry, the resulting output from the information system will also be flawed. This is essentially a reflection of poor documentation practices, which can result in inadequate, unreliable, or erroneous output that affects decision-making and operations.
Poor system design decisions early in the development process can prevent the system from meeting customer needs effectively. Similarly, inadequate systems for long-term follow-up evaluations can compromise the integrity and utility of the system over time. Issues such as over-reliance on devices, as mentioned in FIGURE 8.7, can have severe impacts on business operations, customer satisfaction, and revenue if those devices or systems fail.
Mistakes in data analysis, such as sampling errors or nonsampling errors, also contribute to GIGO if they are not properly managed. In research, errors such as incorrect citations or inadequate distinction between original ideas and sourced content can mislead readers and invalidate the research.
To mitigate these risks, it's essential that systems are designed with precision and error-prevention in mind, and that users are trained to ensure accurate data entry. Furthermore, effective data management requires regular system evaluations and upgrades to maintain high standards of data integrity and functionality.