GM541 Unit 4 Sensor Pilot Resistance Analysis Example

Resistance or Information? A Unit 4 Resistance Analysis of a Sensor-Driven Service Pilot

[Student Name]

Purdue University Global

GM541: Organizational Transformation and Change Leadership

Unit 4 Resistance Analysis

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[Date]

The refrigeration service firm, its technicians, its stores and every figure are composite and illustrative; the frameworks and studies cited are real.

The Pilot

For seven months, twenty-two technicians in Ardent Cold Service's north zone worked under condition-based scheduling. Sensors on 610 refrigeration systems in about 90 stores reported temperatures and compressor data to the monitoring room, and technicians were sent when the data showed a system drifting toward failure rather than on a fixed monthly visit. The project team expected scheduled visits to fall by about 40 percent.

Four behaviors troubled the project team: unscheduled visits to stores the system said were fine, disputes over sensor alerts, a union grievance and a persistent attachment among senior technicians to their old routes.

A Frame for Reading Resistance

Jeffrey Ford, Laurie Ford and Angelo D'Amelio argue that much of what gets called resistance is a name the leaders of a change give to behavior that surprised them, and that some of it is a reaction those same leaders set off through the way they built and explained the change. They suggest treating resistance as a source of information about the change itself (Ford et al., 2008). Sandy Kristin Piderit adds that people can welcome what a change is for while doubting how it was built, and that this mixed stance is common (Piderit, 2000). Each strand below is examined the same way: the behavior as the records show it, the project team's explanation, the technicians' explanation and what the evidence supports.

Strand 1: Shadow Visits

The behavior. Technicians made 212 visits to stores the system had not scheduled, usually during a nearby call, and logged the time as customer courtesy.

The project team's explanation. Habit, and technicians' reluctance to trust the system.

The technicians' explanation. Sensors measure temperatures and compressor run time but cannot see door gaskets that have torn, evaporator coils icing over or a stock clerk blocking airflow with pallets. Those problems are visible only in the store, and they often precede a failure by days.

What the evidence supports. Of the 212 shadow visits, technicians recorded a fix on 131. In 58 of those, the problem was a gasket, coil or airflow issue the sensors could not detect. The visits were filling a real gap in what the system could see.

Strand 2: Disputed Alerts

The behavior. Technicians disputed about a fifth of sensor alerts, telling the monitoring room that the alert was false.

The project team's explanation. Technicians do not yet understand the data.

The technicians' explanation. Alert thresholds were set using data from newer cases with electronic controllers. Older cases with mechanical expansion valves cycle differently and look abnormal to the system when they are working normally.

What the evidence supports. About 70 percent of disputed alerts came from systems more than twelve years old, which make up about a third of the zone's systems. The thresholds did not fit the older equipment. When the monitoring room reviewed a sample of thirty disputed alerts with the technicians involved, it agreed that twenty-one had been false, all but two on older cases.

Most of what the project team called resistance was technicians correcting a design that could not see gaskets, misread old valves and had never priced night work.

Strand 3: The Union Grievance

The behavior. The union local filed a grievance in month four over on-call assignments.

The project team's explanation. The union opposes the program.

The technicians' explanation. Under the old model, after-hours callbacks went to the route technician and were paid as overtime. Under condition-based scheduling, the monitoring room sent alerts at night to whichever technician was on call, and on-call pay had not been revised. Some technicians were dispatched three or four times a night for the same pay as a quiet night.

What the evidence supports. Night dispatches in the pilot zone rose by about 60 percent, because the system caught drifts earlier and sent someone to fix them before morning. Nobody had priced the extra night work.

Strand 4: Attachment to Routes

The behavior. Senior technicians continued to describe stores as "mine," asked to be sent to their former stores and in a few cases called store managers directly.

The project team's explanation. Unwillingness to give up control.

The technicians' explanation. Years of relationships with store managers and knowledge of specific equipment, which they believed customers valued.

What the evidence supports. This strand is different from the first three. It is not a design flaw; it is a real loss. Condition-based scheduling does reduce the role of the individual technician as the store's fixed point of contact, and the design cannot fully restore it. Shaul Oreg's research suggests that responses to change reflect both individual dispositions and the context of the change, including what people stand to lose (Oreg, 2006). For senior technicians, what they stand to lose is a professional identity built over decades.

What the Findings Mean for the Project

Three of the four strands point to fixable features of the design. The sensor package could add periodic in-person inspections for what sensors cannot see, perhaps a quarterly gasket and coil check, which would turn shadow visits into scheduled work. Alert thresholds could be calibrated separately for older systems, using technicians' knowledge of how those cases behave. And on-call pay could be revised to reflect the number of night dispatches. Each change would reduce what the project team has been calling resistance, because each addresses the reason behind it.

The fourth strand needs a different response. The firm cannot give senior technicians their routes back without abandoning the model. It can acknowledge the loss openly, ask senior technicians to serve as zone experts on the older equipment they know best and make their knowledge part of how alerts are reviewed.

Limits

Seven months in one zone may not represent the others, and technicians' own logs, which record the shadow visits, may be incomplete. The analysis relies partly on technicians' explanations, which may emphasize the reasons most favorable to them, though the equipment-age data and night-dispatch counts support their accounts.

Conclusion

What the project team called resistance in the pilot zone was mostly information. Shadow visits revealed problems sensors cannot see, disputed alerts revealed thresholds that do not fit older equipment and the grievance revealed unpriced night work. Attachment to routes reflects a real loss that design changes cannot remove but leadership can acknowledge.

References

Ford, J. D., Ford, L. W., & D'Amelio, A. (2008). Resistance to change: The rest of the story. Academy of Management Review, 33(2), 362-377. https://doi.org/10.5465/amr.2008.31193235

Oreg, S. (2006). Personality, context, and resistance to organizational change. European Journal of Work and Organizational Psychology, 15(1), 73-101. https://doi.org/10.1080/13594320500451247

Piderit, S. K. (2000). Rethinking resistance and recognizing ambivalence: A multidimensional view of attitudes toward an organizational change. Academy of Management Review, 25(4), 783-794. https://doi.org/10.5465/amr.2000.3707722