BUS 700 Week 4 Applying Critical Thinking Example

Questioning a Vendor's Promise and the Bank's Own Assumptions: Critical Thinking for a Doctoral Practitioner

[Student Name]

University of Phoenix

BUS/700: Introduction to Business Administration in Doctoral Study

Week 4 Assignment

[Instructor Name]

[Date]

The doctoral student, the bank, the vendor and all claims are composites written for a model paper.

Marcus Bell, a composite DBA student who directs retail operations at a regional Ohio bank, received a proposal from a technology vendor. The vendor's mobile banking app for small businesses, the proposal claims, raised digital adoption among business owners over 55 by 40 percent at a client bank and will do the same for Buckeye Valley. The contract would cost $1.2 million over three years. Executives are enthusiastic, and the bank has assumed for years that older customers resist technology. Critical thinking is not a refusal to believe; it is the discipline of spelling out what a claim depends on and then checking each piece. This paper applies critical thinking to the vendor's claim and to the bank's assumptions.

What Critical Thinking Involves

Critical thinking involves identifying the claim, the reasons and evidence offered, the assumptions linking them and alternative explanations, then judging whether the conclusion follows. It requires intellectual humility, applying the same scrutiny to one's own beliefs as to others'.

Mapping the Vendor's Argument

The claim is that the app will raise adoption by 40 percent. The evidence is a case study from one client bank. The implied reasoning is that because adoption rose after the app launched there, it will rise here. Unstated assumptions include that the client's customers resemble Buckeye Valley's and that the app caused the increase.

Evaluating the Evidence

The case study reports results from a single bank over one year. It does not describe how adoption was measured, whether other changes occurred at the same time, such as branch closures or fee changes, or whether similar banks without the app saw similar gains. The vendor produced the case study, a clear conflict of interest.

Heuristics and Biases

Tversky and Kahneman (1974) documented mental shortcuts that save effort but bend judgment in consistent directions. The 40 percent figure may serve as an anchor, shaping expectations even if adjusted downward. The vivid success story may trigger availability bias. Executives who already favor digital investment may seek confirming evidence, a form of confirmation bias.

Questioning the Bank's Assumptions

The bank assumes older customers resist technology because of age. Research on technology acceptance suggests otherwise: Davis (1989) reported that whether people judged a system helpful and simple to operate did more to explain its use than other factors, which implies that design and support may matter more than age. If so, the bank's problem may lie in how its current tools serve business customers rather than in customers themselves.

Problematization

Alvesson and Sandberg (2011) argued that researchers should generate questions by challenging assumptions underlying existing views rather than only filling gaps. Applied here, Marcus asks not only whether the app works but whether the framing of the problem, older customers as resistant, is correct.

Alternative Explanations

Several explanations could account for the client bank's 40 percent increase: branch closures forcing customers online, a fee for in-branch deposits, a pandemic-era shift, intensive staff coaching that accompanied the launch or growth from a very small base. Any of these could produce the result without the app being the cause, and several could operate together, making the app's own contribution impossible to separate from the case study alone.

What Would Count as Better Evidence

Stronger evidence would come from several client banks, comparisons with similar banks that did not adopt the app, clear definitions of adoption and independent analysis. Peer-reviewed research on similar tools would add further support, as would references from client banks that the vendor did not select.

The Cost of Being Wrong

Errors run in two directions. If the bank signs the contract and the app fails, it loses $1.2 million and three years of attention. If it rejects a tool that would have worked, it may lose small business customers as branches close. Critical thinking weighs both risks. Here, a short pilot costs little relative to either error and reduces uncertainty, which is why it is the better choice rather than a simple yes or no.

Asking Better Questions of Vendors

Marcus drafted questions for the vendor: how many clients have used the app with older business customers, what adoption looked like at banks that did not see gains, how adoption was defined and measured, what else changed at the client bank during the period and whether the vendor would share anonymized data for independent analysis. A vendor confident in its product should welcome such questions.

Critical Thinking About Numbers

Percentages can mislead. A 40 percent increase from 10 percent adoption is a rise to 14 percent, while a 40 percent increase from 50 percent is a rise to 70 percent. The case study did not report the starting level. Marcus learned to ask for absolute numbers, base rates and time periods before interpreting any percentage change.

Considering the Vendor's Perspective

Fairness requires acknowledging that the app may be good. The vendor has an interest in promoting it, but that does not make the claim false. Critical thinking asks for evidence proportional to the decision's stakes, not dismissal.

A Constructive Conclusion

The evidence is insufficient to justify a three-year contract based on the 40 percent claim. A better decision is a six-month pilot in two regions with branch closures, comparing adoption, usage and customer satisfaction with two similar regions using the bank's current app, with the vendor paid a pilot fee and an option to expand.

Designing the Pilot

The pilot will define adoption as at least two business transactions per month through the app, track results by age group and survey customers about usefulness and ease of use. Staff support will be the same in both groups, so differences can be attributed to the app.

Reflecting on Marcus's Own Biases

Marcus recognizes that his own enthusiasm for digital tools, and his belief that branch staff are irreplaceable, could bias how he reads pilot results. He will agree on success criteria with colleagues before the pilot begins and ask an analyst outside his team to review the data.

Sharing the Analysis With Executives

Presenting skepticism to enthusiastic executives requires care. Marcus framed his analysis as protecting a good idea from a weak test, not as opposition. He showed the alternative explanations, the missing baseline and the pilot design on one page, and he emphasized that a successful pilot would give the bank confidence to invest and a stronger negotiating position with the vendor.

Critical Thinking in Doctoral Work

The same habits, mapping arguments, evaluating evidence, questioning assumptions and considering alternatives, apply to reading research, framing problems and designing studies throughout the DBA.

Conclusion

Applying critical thinking to the vendor's claim revealed weak, self-interested evidence, cognitive biases that might lead the bank to accept it and an assumption about age that research questions. Rather than rejecting the app, Marcus recommends a controlled pilot that will produce evidence suited to the decision, demonstrating how critical thinking leads to better action.

References

Alvesson, M., & Sandberg, J. (2011). Generating research questions through problematization. Academy of Management Review, 36(2), 247-271. https://doi.org/10.5465/amr.2009.0188

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319-340. https://doi.org/10.2307/249008

Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185(4157), 1124-1131. https://doi.org/10.1126/science.185.4157.1124