Decision-making process in busines

In any given market, the decision-making process is crucial to the company’s success. Unlike in the past, when decision-making was restricted to top management, information systems have enabled lower-level management to participate in the decision-making process by making information accessible to them (Laudon & Laudon, 2016). The case study investigates how information technology has reshaped the farming industry. It demonstrates how major agricultural corporations use data gathered from farmers to improve farming by lowering costs and increasing crop yield. Many farmers, on the other hand, have expressed concern about the amount of data that agricultural companies need (Laudon & Laudon, 2016). They are suspicious that the companies may use the information for individual gains rather than for the benefit of the companies. The case study seeks to answer the amount of data-driven planting that is beneficial to the farmers.

Discussion Questions

Response to Question 1

Global Positioning System(GPS): It is computerized system that guides tractors and combines used in the field. It gives instruction to the equipment on the exact amount of fertilizer to put in the grooves. GPS allows farmers to monitor the progress of such equipment remotely from their smartphones and computers.

Prescriptive farming: It involves analysis of data by the agricultural data companies which is collected from farmers in a given region regarding the soil condition, the trends of crop yield in the past years, field boundaries, seed performance as well as the type of soils (Laudon & Laudon, 2016). The company later sends back the information with recommendations to the farmer in digital form such that the farmer uploads the data in his computerized planting equipment. The planting equipment follows the given recommendation when at work.

FieldScript: It is a software that was developed by an agricultural company called Monsanto. The software analyses the information of a given region. The details analyzed include the amount of sunshine, shade, components of soil, genetic properties of the seeds as well as predicted climate. That way, the agricultural companies can give precise instructions to planting equipment (Laudon & Laudon, 2016).

Response to Question 2

Examples of operational intelligence in the case study is the delivery of the exact amount of fertilizer in the groove, identifying the areas that require much or less fertilizers in the field and the kind and quantity of fertilizer and seed for what part of the field (Laudon & Laudon, 2016).

Response to Question 3

Farmers use the information provided by prescriptive planting to determine the amount and the kind of fertilizer and seeds they will use for a given size of the field. (Laudon & Laudon, 2016). Prescriptive planting can support three decisions: structured, unstructured, or semi-structured (Laudon & Laudon, 2016). Structured decisions include the amount of fertilizer and seed to be used while unstructured decisions include the kind of seeds and fertilizers that they should use in a given field. Semi-Structured decisions include the weather forecasts and other factors that will assist in movement of the crop from planting to harvesting.

Response to Question 4

The technology is not likely to benefit small-scale farmers because of the cost of service and acquiring the planting equipment is very high, and the farmers will be receiving diminishing returns. However, it would be beneficial to the large-scale farmers because the profits they generate can set-off the cost of production (Laudon & Laudon, 2016). Information technology has had a positive impact on the agriculture sector as farmers who use it can manage their farming efficiently and effectively thus increasing the yield and profitability. It has helped reduce the use of harmful pesticide as the seed companies have developed genetically modified seeds and crops that resist insects as well as weed-killing sprays.

Conclusion

From the above analysis, it is evident that the agricultural companies such as Monsanto and Dupont are using data corrected from the farmers to develop technology software that allows farmers to work more efficiently and effectively. With the forms of technologies analyzed in the case study, farmers can make informed decisions, reduce farming costs, as well as increase profitability.

References

Laudon, K. C., & Laudon, J. P. (2016). Management Information Systems: Managing the Digital Firm (14th ed.). Boston, MA: Pearson Education

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