Big data is a computing term for the large data sets collected by organizations which are often efficiently analyzed computationally to reveal associations, trends, and patterns that help understand certain occurrences (Schlegel & Trent, 2015). Big data deals with large volumes of structured and unstructured data. Big data, therefore, offers organizations innovative ways to process information and gather enhanced insights and decision-making ( Gandomi & Haider, 2015 ). For instance, in logistics, big data might be used by a major trucking company to combine massive amounts of data from their fleet with sophisticated algorithms that will help the firm optimize its fleet operations.
When coming up with a supply chain strategy, organizations connect supply chain risk strategy to help inform them of the most efficient way to conduct business and build a foundation for risk management. Supply chain risk strategy deals with controlling supply chain complexities that facilitate the likelihood of risk ( Kilubi, 2016 ). These may include transfer, avoidance, and mitigation strategies employed by organizations to reduce the chances of the occurrence or risk. On the other hand, supply chain strategy development is the creation of effective means to facilitate the product and information flow among and between supply chain stages to maximize profitability in the organization ( Kilubi, 2016 ). Supply chain strategy conceptualizes a company’s long-term aspirations, broad policies, and constraints affecting the firm’s activities and action plan to meet desired goals.
Delegate your assignment to our experts and they will do the rest.
Risk management strategies are vital to supply chain strategies because they help inform participants of the risk issues they are likely to face. Organizations connect supply chain risk strategy with supply chain strategy development by forging critical linkages between the two (Schlegel & Trent, 2015). Companies do this by making risk assessment plans a mandatory part of the strategy development process. By doing this, firms embed risk assessment plans into an organization’s corporate culture (Schlegel & Trent, 2015). Moreover, they ensure that risk assessments do not bring major changes in the supply chain strategy development as they are part of the strategy development process. These actions ensure participants involved in the development of supply chain strategies have to consider risk issues and come up with risk aversion plans, thus connecting supply chain strategy development with supply chain risk strategy.
External intelligence quotient and external intelligence are components of strategic risk. External intelligence is a term used to describe the knowledge, information, and data from outside the organization (Schlegel & Trent, 2015). These may include regulatory and legal changes, supplier and competitor actions, customer expectations, macroeconomic changes, technological innovations, industry changes and trends, risk factors, labor force, and social trends. External intelligence helps organizations stay up to date on any changes and trends in the industry to avoid surprises that may negatively affect the firm’s profitability and growth (Schlegel & Trent, 2015). Closely related to the concept of external intelligence is EIQ, also known as the external intelligence quotient. The description of EIQ can be inferred from that of external intelligence. EIQ is defined as how well an organization amasses, analyzes, and acts upon the relevant external data, knowledge, and information (Schlegel & Trent, 2015). It is, therefore, a risk management concept that can help organizations mitigate risk in their supply chain and business strategies.
References
Gandomi, A., & Haider, M. (2015). Beyond the hype: Big data concepts, methods, and analytics. International journal of information management , 35 (2), 137-144. www.sciencedirect.com/science/article/pii/S0268401214001066
Kilubi, I. (2016). The strategies of supply chain risk management–a synthesis and classification. International Journal of Logistics Research and Applications , 19 (6), 604-629. www.researchgate.net/publication/301905632_The_strategies_of_supply_chain_risk_management_-_a_synthesis_and_classification
Schlegel, G. L., & Trent, R. J. (2015). Supply chain risk management: An emerging discipline . CRC Press .
