18 Dec Unit 10_MT497_Discussion response
13863Respond or elaborate to discussion post below:
As the VP of finance, I would be hesitant to approve a large research expense without clear quality expectations since there is no quality control manager in place. At a minimum, I would want product development to define clear quality standards around data security, privacy protection, system reliability, and customer support. For a “safe” phone, quality has to mean more than a promise. It needs measurable standards, testing results, and proof that customer data is actually protected. From a financial standpoint, if we cannot clearly define quality, we cannot accurately estimate costs or long term risk.
Understanding market segmentation would directly shape how strict those quality controls need to be. If the target customers are professionals like executives, healthcare workers, or legal professionals, the expectations for privacy and reliability would be much higher. That would justify stronger security features and higher development costs. If the market is everyday consumers who value privacy but are more price sensitive, quality controls may focus more on usability and basic protection. Knowing who the customer is helps align quality with what they are actually willing to pay for.
When it comes to using AI algorithms to control employees, I think companies need to be careful. AI can be useful for improving efficiency or supporting decision making, but when it crosses into constant monitoring, it can hurt trust and morale. Research shows that employees perform better when expectations are clear and they feel trusted rather than watched (Manning & Curtis, 2021).
I do not think AI control should be limited to only certain industries, but it should be used thoughtfully. A strong alternative, especially for remote employees, is results based management. Setting clear goals, tracking outcomes, and having regular check ins often works better than monitoring activity levels or screen time.
Overall, market segmentation research reduces decision making risk for the VP of finance by confirming there is a real demand for the product and clarifying how much customers value privacy. It helps prevent overinvesting in features the market does not want or underinvesting in quality where expectations are high. With solid research, financial decisions become more confident and less based on assumptions.
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