Week 4 Discussion: Financial Risks and Operational Risks
CO3: Differentiate risk among components including strategic, hazard, financial, and operations
Discussion Prompt:
Altman developed the Z-Score model to estimate the likelihood that a company will go bankrupt in the next few years. The model takes five financial ratios and plugs them into a formula. As a result, you receive your Z score.
If the company’s score is above 3.0, they are considered safe, whereas a company that scores below 1.8 means that bankruptcy may be coming shortly. An example of this would be Party City; from 2015- 2019, Party City’s Z score went from 1.4 to .54. Once the Pandemic hit in 2020, it shot down to -.13, and they could never recover.
At the beginning of the pandemic, restrictions were implemented that limited the gathering of people “parties,” which directly resulted in the loss of sales for Party City. Their market began to shrink with
major retailers expanding their decoration selections.
To add insult to injury, they added another problem with the helium shortage, which increased the price of helium. They filed for bankruptcy in January of 2023. Like Supplier risk, demand and process are two other risks that companies need to be aware of and be able to manage.
For example, two types of demand risks are Customer promotions and new product introductions. If a customer decides to promote a product without any planning or doesn’t have solid communication of its advertising with the supplier could lead to a significant delay in the production of the item creating a demand risk.
As for new product introduction, a company will produce a product that it believes will solve a problem for its customers; if proper research isn’t conducted and customer feedback isn’t taken into
consideration, the product could fail due to the product’s inability to solve a customer’s problem or the problem it is solving is so rare that the demand for it is limited.
Process risks, simplified, are risks that the company can manage internally. Two examples of this are Inventory and Equipment Failure.
An example of inventory is if a company provides a product that has a shelf life and that item expires, they are essentially throwing money away.
To mitigate this, a company can implement a stock monitoring system that ensures they deliver the items
well before the shelf-life expectancy date expires.
Equipment failure is self-explanatory; if a piece of equipment fails, it could not only lead to a loss in production but could potentially cause injury to an employer resulting in potential legal actions.
This can be mitigated by proper preventative maintenance, emphasizing operator safety, and adequately monitoring the equipment.
Utilizing the Z score to determine supplier selection and having the correct processes and procedures to mitigate demand and process risks are vital to a company’s success.
References
Schlegel, G. L., & Trent, R. J. (2014). Supply chain risk management: An emerging discipline. Taylor & Francis Group. Retrieved from: https://ebookcentral.proquest.com/lib/apus/reader.action? docID=1680353&ppg=153& 156
Movement, Q. ai-Powering a P. W. (n.d.). The Party Is Over: Party City Files For Chapter 11 Bankruptcy. Forbes. Retrieved April 25, 2023, from https://www.forbes.com/sites/qai/2023/01/23/the-party-is-over-party-city-files-for-chapter-11-
bankruptcy/?sh=77ddef2c740c
Altman Z-Score Chart and History 2015-2022 | DiscoverCI. (n.d.). PRTY | Altman Z-Score Chart and
History 2015-2022 | DiscoverCI https://www discoverci com/companies/PRTY/altman-z-score
The Z- Score combines a series of weighted ratios for public and private firms to predict financial bankruptcy. The Z- Score also provides a single score that can be used during the preliminary evaluation of potential suppliers.
It provides guidance regarding suppliers to keep or eliminate from the selection pool. And it gives a basis for tracking economic changes over time. (Schlegel & Trent, 2015) For example, in 2019, Francesca’s shook up its C-suite, hunted for a suitor, went on a cost-cutting mission, and planned to shift to a fast-fashion model.
Instead of working on a turnaround, the retailer spent much of 2020 issuing going concern warnings and permanently closing stores as the pandemic slammed its sales and roiled its plans.
Still, the pandemic wasn’t its only problem. The retailer, which runs smaller-than-average stores, had been struggling for a while as apparel sales growth ebbed and fewer consumers shopped at malls.
A day after its bankruptcy filing, the Nasdaq warned its stock would be delisted on Dec. 15, something Francesca’s wouldn’t appeal since its investors are taking it private.
TerraMar has committed to keeping at least 275 Francesca’s stores open out of the 558 it was running at its Chapter 11 filing after closing dozens in recent years. (Kim, Y., 2021) There are several examples of demand risk and process risk.
I chose two examples of demand risk: forecast errors and time delays. Forecast errors can be mitigated by basing demand planning on actual usage data vs. historical sales.
Distributors can leverage this usage data to optimize their distribution centers and to consign inventory at customer sites, reduce carrying costs and improve customer service.
Time delays could be mitigated by prioritizing planning and setting a strict schedule for when you would like products to be done.
Have meetings periodically to discuss where sections are with the consequences. I chose two examples of process risk information delays and systems. Information delays can be mitigated by communication down to the lowest level.
If a timeline has been adjusted or expectations have been altered, communicate with team members,
subcontractors, and third-party vendors so that the new timeline is clearly understood. All are in agreement to move forward with the revised plan.
Maintaining a well-informed, multidisciplinary, competent project team is vital to ensuring a positive outcome for all involved.
Systems can be mitigated by reducing batch sizes. Smaller workloads include less functionality, thus fewer potential flaws, each likely to have a minor impact on the system.
References:
Kim, Y., (2021) Retail Dive. https://www.retaildive.com/news/the-running-list-of-2020-
retailbankruptcies/571159/
Schlegel, G. L., & Trent, R. J. (2014). Supply chain risk management: An emerging discipline.
Taylor & Francis Group. Retrieved from: https://ebookcentral.proquest.com/lib/apus/reader.action?
docID=1680353&ppg=153& 156
https://kissflow.com/project/how-to-avoid-project-delays/
The Z-score is a statistical tool used to measure the financial health of a supplier by analyzing its financial statements. It is a formula that calculates the likelihood of a company going bankrupt within two years based on its financial ratios.
The Z-score considers five financial ratios, namely liquidity, profitability, leverage, activity, and solvency, and combines them into a single score.
The higher the Z-score, the better the financial health of the supplier. Generally, a Z-score above 2.99 indicates a low risk of bankruptcy, while a score below 1.8 suggests a high risk of bankruptcy.
Many supplier bankruptcies have occurred due to various reasons, such as poor management, economic recession, natural disasters, and unexpected changes in demand or supply.
For instance, in 2019, Forever 21, the US-based clothing retailer, filed for bankruptcy due to increased competition from online retailers, high rent costs, and declining foot traffic in malls.
Similarly, Toys R Us, the toy retailer, went bankrupt in 2017 due to the rise of e-commerce, high debt levels, and intense competition from Amazon and Walmart.
In some cases, there were red flags that indicated the possibility of supplier bankruptcy, but they were not noticed or ignored.
For example, in the case of Carillion, a UK-based construction company, that went bankrupt in 2018, it was revealed that the company had a high debt level, poor cash flow, and a flawed business model.
However, these warning signs were overlooked, and the company continued to operate until it was too
late.
Demand risk and process risk are two other types of supply chain risks that companies must manage. Demand risk refers to the uncertainty of customer demand, which can lead to stockouts, excess inventory, or lost sales.
Two examples of demand risk in Table 7.2 are new product introduction and seasonality. To mitigate the negative impact of new product introduction, companies can conduct market research to forecast demand, test the product with a small group of customers, or offer discounts to encourage early adoption.
Similarly, to manage seasonality, companies can use demand planning software, offer flexible work
arrangements to employees, or collaborate with suppliers to adjust production schedules.
Process risk refers to the risk of disruptions in the supply chain due to issues related to logistics, production, or quality control.
Two examples of process risk in Table 7.3 are supplier quality and production line failures. To mitigate the negative impact of supplier quality issues, companies can conduct supplier audits, set quality standards, or implement a supplier scorecard system.
Similarly, to manage the risk of production line failures, companies can conduct preventive maintenance, use backup production lines, or have a contingency plan in place. Supplier selection is critical in managing supply chain risk, and the Z-score is a useful tool to monitor the financial health of a supplier.
However, companies must also manage demand risk and process risk to ensure a resilient and agile supply chain. By identifying potential risks and implementing appropriate mitigation strategies, companies can minimize the negative impact of supply chain disruptions and ensure business continuity.
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