ORG 726 Week 3 Technology Adoption and Resistance Example

Why Underwriters Kept Their Spreadsheets: Adoption Models and Resistance to an Insurer's Pricing Tool

[Student Name]

University of Phoenix

ORG/726: The Impact of Technology on Organizations

Week 3 Assignment

[Instructor Name]

[Date]

Prairie Shield Mutual, its systems, people and figures are composites written for a model paper.

Prairie Shield Mutual, the composite Midwestern insurer studied in earlier weeks, writes about $210 million a year in farm property and liability premiums. Pricing a farm policy has long depended on underwriters' judgment: they weigh buildings, equipment, livestock, crop storage and the farmer's loss history, often using personal spreadsheets built over years. Last year the company launched a pricing tool, built by its actuaries with a vendor, that uses predictive models and aerial imagery to recommend a premium. Leaders expected it to be used for nearly all new quotes within six months. Nine months after launch, it was used for 35 percent. This paper asks why.

The Usage Evidence

Use varied sharply by group. Underwriters with under five years of experience used the tool for 71 percent of their quotes; those with five to fifteen years for 38 percent; and the eleven senior underwriters, each with more than fifteen years, for 9 percent. Among quotes priced with the tool, underwriters changed its recommended premium by more than 10 percent in 44 percent of cases. Loss ratios on tool-priced policies in their first year were slightly better than on others, though the sample is small.

Individual Adoption Models

Davis (1989) proposed that two beliefs drive whether people intend to use a system: that it will help them do their work better and that learning it will not take much effort. He labeled these perceived usefulness and perceived ease of use. In his studies the first belief mattered more. Venkatesh et al. (2003) compared eight adoption models and combined them into a single model, UTAUT, in which expected gains in performance, expected effort, the views of important others and supportive conditions predict intention and use, moderated by gender, age, experience and voluntariness. Their model explained more variance in intention than the earlier models.

A survey of 64 underwriters, using items adapted from these models, found high ratings for ease of use and facilitating conditions but low ratings for performance expectancy among experienced underwriters, who doubted the tool priced farms better than they did. Social influence was mixed: underwriting managers had not said whether use was expected, and senior underwriters, whom others consult, were openly skeptical. These findings explain part of the pattern: experienced users doubted the tool's usefulness and received no clear signal that use mattered.

What Adoption Models Miss

Interviews with 20 underwriters added what the survey missed. Senior underwriters said the tool shifted pricing authority from them to the actuarial department, whose models they could not see or challenge. Their informal status, as the people others consult on difficult farms, rested on pricing judgment. Several said the tool undervalued risks it could not see from the air, such as poorly maintained grain dryers, a known fire hazard. Junior underwriters reported that when they used the tool's price, senior colleagues sometimes questioned it in front of them.

The tool did not only change how premiums were calculated; it changed who in the department was the expert.

Resistance as Politics

Markus (1983) studied resistance to a financial information system and compared three explanations: people-determined, where resistance stems from individuals' traits; system-determined, where it stems from flaws in the system; and interaction, where it stems from the interaction between the system and the context in which it is used, particularly the distribution of power. She found the interaction theory best explained the resistance she observed, because the system shifted power among groups. The pricing tool fits that account. It is not poorly designed in general, and senior underwriters are not simply resistant to change; the tool redistributes authority over pricing from underwriters to actuaries.

How Resistance Spread

Lapointe and Rivard (2005) studied resistance to clinical systems in hospitals and modeled it at several levels, in which individuals assess a system's initial conditions, such as their power and status, and the threats it poses, leading to resistance behaviors. When management responds poorly, individual resistance can converge into group resistance, and triggers can intensify it. At Prairie Shield, early complaints from senior underwriters about grain dryers and outbuildings went unanswered by the actuarial team for three months. During that time, senior underwriters' skepticism spread to mid-career colleagues who consult them, and use among that group fell from 52 to 38 percent. The resistance moved from individual to group level because the organization did not respond to legitimate concerns.

Comparing the Explanations

Each explanation accounts for part of the evidence. Adoption models explain why junior underwriters, who found the tool easy and had no pricing reputation to protect, used it most, and why unclear expectations let others opt out. The political account explains why use fell with seniority more steeply than doubts about usefulness alone would predict, and why senior underwriters criticized junior colleagues who used it. The multilevel model explains the timing: resistance spread after the complaints went unanswered. No single theory covers all of it, which supports combining individual and organizational levels.

Resistance as Information

Not all of the resistance is about status. The senior underwriters' complaints about hazards invisible from aerial images have merit; the actuaries later confirmed that the model did not include equipment maintenance factors. Treating resistance as information revealed a real limitation that, if ignored, could raise losses on farms with poorly maintained equipment.

Responses That Would Backfire

Two responses leaders were considering would probably make matters worse. Mandating use without addressing the model's blind spot would produce formal compliance with heavy overrides, a gap between formal and real use that institutional theorists call decoupling, and would confirm senior underwriters' view that the tool is imposed. Retraining underwriters on the tool's features would address ease of use, which survey results show is not the problem.

Measures of Success

Success will be judged by tool use across experience groups, the rate and direction of overrides, first-year loss ratios by pricing method and senior underwriters' participation in model reviews. A rise in use with stable or falling overrides would show the tool earning trust rather than compliance.

Recommendations

Address the design gap: add an underwriter inspection input for equipment and outbuilding condition, built with senior underwriters.

Share evidence: publish quarterly loss ratios for tool-priced and judgment-priced policies, so usefulness can be judged by results.

Redistribute authority: give a panel of senior underwriters a formal role in model review and in approving overrides above 10 percent.

Clarify expectations: managers will state that the tool should be used for all new quotes, with documented overrides allowed.

Respond quickly: commit to a two-week response to underwriter issues about the model.

Conclusion

The pricing tool's low use reflects more than individual attitudes. Adoption models explain experienced underwriters' doubts about usefulness and the lack of clear expectations. Political and multilevel theories of resistance explain how a shift in authority, combined with unanswered complaints, turned individual skepticism into group resistance, and part of that resistance pointed to a real flaw. A response that fixes the flaw, shares evidence and gives senior underwriters a role addresses the causes rather than the symptoms.

References

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

Lapointe, L., & Rivard, S. (2005). A multilevel model of resistance to information technology implementation. MIS Quarterly, 29(3), 461-491. https://doi.org/10.2307/25148692

Markus, M. L. (1983). Power, politics, and MIS implementation. Communications of the ACM, 26(6), 430-444. https://doi.org/10.1145/358141.358148

Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3), 425-478. https://doi.org/10.2307/30036540