Using the Indicators and Warning Analysis Technique

Using the Indicators and Warning Analysis Technique

Indicators and Warning (I&W) analysis is a qualitative risk assessment approach that may be used to statistically analyze risk by identifying risk indicators and warnings. Indicators are early signals that a risk is about to occur, whereas warnings are more clear signals that a risk is likely to take place (Zhu & Liu, 2021). The following steps should be taken to quantitatively estimate risk using I&W analysis. The first one should be the identification of the risks for evaluation. In this step, operational, legal/compliance, technical, and reputational risks were identified in the Risk Assessment assignment. The second step relates to identifying the risk’s warning signs and indications. The four risks identified are as follows: warnings and indicators.

Risk	Warning	Indicator
Operational risk	Data breach	System outage
Legal/Compliance risk	Regulatory audits	Change in policy and regulation
Technical risk	Issues in product performance	Software bugs
Reputational risks	Negative backlash in social media	Negative publicity in media and news channels

Third, every indicator and warning is assigned a value, and the aggregate risk score for each risk is calculated. If an indication or warning is present, this value should indicate the chance of the risk occurring. The values are assigned on a scale of 1 to 10, with 1 representing the lowest probability and 10 representing the highest probability of occurring. The values of the indicators and warnings for the four identified risks are shown in the table below. The assigned values are based on a historical examination of Optimus.

Risk	Warning	Value	Indicator	Value	Overall Risk Score
Operational risk	Data breach	3	System outage	5	15
Legal/Compliance risk	Regulatory audits	4	Change in policy and regulation	3	12
Technical risk	Issues in product performance	8	Software bugs	7	56
Reputational risks	Negative backlash in social media	9	Negative publicity in media and news channels	1	9

First, operational risk, such as a system failure or data breach, can disrupt a company’s operations, potentially resulting in revenue loss and lower productivity. However, depending on the intensity and length of the outage or breach, the impact of these occurrences may vary. A rating of 3 for data breach and 5 for system outage suggests that these indicators predict operational risk relatively well. Second, on reputational risk, according to Ge et al. (2020), negative press coverage or social media reactions can affect a company’s brand, leading to a loss of confidence from consumers, workers, and investors. The magnitude of the bad publicity or reaction also influences the impact of these occurrences. A rating of 1 for unfavorable news coverage and 9 for negative social media backlash suggests that negative social media backlash is a better predictor of reputational risk. Third, technical risk, customer unhappiness, income loss, and higher support expenses can all result from software problems and product performance concerns. A result of 7 for software bugs and 8 for product performance concerns implies that these indicators forecast technical risk very well. Lastly, for legal/compliance risk, regulation changes or regulatory audits may entail considerable operational adjustments for a business. However, the magnitude of these occurrences is determined by the severity of the modifications or the audit results. A result of 3 for regulatory changes and 4 for regulatory audits implies that these variables predict legal/compliance risk considerably.

When the risks are prioritized based on their total risk score, the schedule above shows that technical risk is the greatest priority, followed by operational risks. Reputational and legal/compliance risks have minimal impact on the company and should be considered last. However, they should not be ignored completely. Thus, Optimus should pay attention to technical and operational risks to enhance its progress in the technology sector.

References

Ge, Y., Qiu, J., Liu, Z., Gu, W., & Xu, L. (2020). Beyond negative and positive: Exploring the effects of emotions in social media during the stock market crash. Information processing & management, 57(4), 102218.

Zhu, Z., & Liu, N. (2021). Early warning of financial risk based on K-means clustering algorithm. Complexity, 2021, 1-12.

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For this assignment, you are to quantitatively assess each of the four risks identified in the risk assessment assignment using the indicators and warning (I & W) analysis technique.
Demonstrate critical thinking skills in using quantitative analytics methods and techniques to identify and assess competitive risks. Perform a detailed quantitative risk assessment. You do not need to perform a detailed quantitative risk assessment.
Summarize the steps you would take, or have hypothetically taken, to determine quantitatively the potential impact and probability of the risk.
Prepare a two-page summary of how you quantitatively assessed the risk using the I & W analysis technique.
After selecting and quantitatively assessing your risk, you should again update and submit the RT & RP with the summarized high-level results of the quantitative assessment.
Submit the 2-page summary.