Unit I — Foundations of OB
1. Nature & Scope of OB
Organizational Behaviour studies how individuals, groups, and organizational structures interact to affect behaviour within firms, at three nested levels of analysis: individual, group, and organization. Managers use this lens to diagnose whether a performance problem originates in a person's ability/motivation, a team's dynamics, or systemic organizational design. Task performance (formal job duties), organizational citizenship behaviour (OCB, discretionary helpful acts), and counterproductive work behaviour (CWB, deliberate harmful acts) together determine organizational effectiveness.
- Individual level: ability, personality, perception, motivation, job attitudes
- Group level: team dynamics, communication, leadership, conflict, norms
- Organization level: structure, culture, HR policies, technology, environment
- Behavioural outcomes: task performance, OCB, CWB, turnover, absenteeism
- Effectiveness criteria: productivity, quality, employee well-being, adaptability
- Absenteeism rate — unplanned absence days divided by scheduled days, monthly
- Productivity index — units produced per labour hour versus standard, weekly
- OCB frequency — supervisor-rated helping/voice behaviours on a 5-point scale, quarterly
- CWB incidents — recorded disciplinary actions, theft, sabotage reports per quarter
- Employee turnover rate — voluntary exits divided by average headcount, annually
- Grievance count — formal complaints filed per 100 employees, monthly
Anand Auto Components, a 450-employee tier-2 manufacturing plant near Pune supplying gaskets to two major OEMs, has seen line productivity fall 14% over two quarters while absenteeism on the night shift has risen from 4% to 11%. The plant HR manager, Radhika Iyer, initially assumed the night-shift supervisor was simply a poor leader, but exit interviews reveal complaints about outdated machines, unclear shift rotation policies, and a new incentive scheme that inadvertently rewards individual output over team quality checks. Some workers privately blame a few colleagues for taking excessive breaks and slowing the line, while others say management never explains scheduling decisions. Radhika must decide whether the root cause lies with individuals, the shift team's dynamics, or the plant's broader systems before recommending a fix to the plant head.
Productivity decline
-14% over two quarters
Night-shift absenteeism
4% -> 11%
Machine downtime (night shift)
18% of shift hours
Incentive scheme
Rewards individual units, not team quality
Grievances filed (last quarter)
27, up from 9
Exit interview theme
Unclear rotation and scheduling policy (61% of exits)
AIndividual-level intervention: performance coaching and discipline
Target specific low-performing workers with coaching, warnings, or reassignment, treating this as an individual motivation/ability problem.
BGroup-level intervention: team-building and shift norms reset
Run facilitated sessions to rebuild shift-team cohesion, clarify roles, and reset norms around breaks and mutual accountability.
COrganization-level redesign: fix incentive scheme, machines, and scheduling transparency
Redesign the incentive scheme to reward team quality outcomes, invest in machine maintenance, and publish a transparent rotation policy.
DDiagnostic pilot: combine limited coaching with a structural audit before full rollout
Run a 6-week diagnostic on one line combining light-touch individual coaching, a team norms workshop, and data collection on machine/incentive effects before committing to a plant-wide fix.
AIndividual-level intervention: performance coaching and discipline
Strengths
- Fast, visible action
- Addresses genuine free-riders if they exist
Risks
- Ignores systemic incentive design flaw
- Risks scapegoating and morale damage if root cause is structural
BGroup-level intervention: team-building and shift norms reset
Strengths
- Improves communication and trust
- Can surface informal norms undermining quality
Risks
- Does not fix the incentive scheme driving individualistic behaviour
- Effects may fade without structural follow-through
COrganization-level redesign: fix incentive scheme, machines, and scheduling transparency
Strengths
- Addresses root systemic causes
- Signals fairness, likely to reduce grievances and turnover
Risks
- Higher cost and longer implementation time
- Requires plant-head and corporate sign-off
DDiagnostic pilot: combine limited coaching with a structural audit before full rollout
Strengths
- Evidence-based, reduces risk of wrong diagnosis
- Builds buy-in through visible experimentation
Risks
- Delays relief to a plant already losing productivity
- Requires disciplined measurement capability
Which level of analysis (individual, group, or organization) should Radhika prioritize first, and what specific action should she recommend to the plant head?
Target specific low-performing workers with coaching, warnings, or reassignment, treating this as an individual motivation/ability problem.
Strengths: Fast, visible action; Addresses genuine free-riders if they exist. Risks: Ignores systemic incentive design flaw; Risks scapegoating and morale damage if root cause is structural.
Run facilitated sessions to rebuild shift-team cohesion, clarify roles, and reset norms around breaks and mutual accountability.
Strengths: Improves communication and trust; Can surface informal norms undermining quality. Risks: Does not fix the incentive scheme driving individualistic behaviour; Effects may fade without structural follow-through.
Redesign the incentive scheme to reward team quality outcomes, invest in machine maintenance, and publish a transparent rotation policy.
Strengths: Addresses root systemic causes; Signals fairness, likely to reduce grievances and turnover. Risks: Higher cost and longer implementation time; Requires plant-head and corporate sign-off.
Run a 6-week diagnostic on one line combining light-touch individual coaching, a team norms workshop, and data collection on machine/incentive effects before committing to a plant-wide fix.
Strengths: Evidence-based, reduces risk of wrong diagnosis; Builds buy-in through visible experimentation. Risks: Delays relief to a plant already losing productivity; Requires disciplined measurement capability.
Set the weight of each criterion (1–5), then score every alternative (1–5). The matrix is a thinking aid, not a verdict.
| Criterion | Weight | A | B | C | D |
|---|---|---|---|---|---|
| Behavioural impact | |||||
| Employee acceptance | |||||
| Feasibility | |||||
| Cost (higher = more affordable) | |||||
| Risk containment | |||||
| Long-term sustainability |
With your current weights, alternative A scores highest. A matrix only reflects the weights you chose. Evidence, ethics, feasibility and the people affected still belong in your judgement — you decide.
OB theory suggests behaviour is jointly determined by person and situation (Lewin's B = f(P, E)); before attributing the productivity fall to individual failings, managers should rule out situational/systemic causes such as flawed incentive design, which is a classic case of rewarding the wrong behaviour. The evidence pattern here (falling productivity, rising absenteeism, an incentive scheme misaligned with quality, and grievances about policy transparency) points toward organizational-level and group-level causes rather than individual deficiency alone, so any credible answer should show a diagnostic sequence rather than jumping to blame.
- Short-term: choosing individual discipline without fixing incentives likely triggers further grievances and possible unionized pushback
- Short-term: a diagnostic pilot delays a company-wide fix but produces defensible data for the plant head
- Long-term: correcting the incentive scheme should realign OCB and reduce CWB such as corner-cutting on quality checks
- Long-term: transparent scheduling policy is likely to reduce absenteeism and turnover over 2-3 quarters
- Reputational: how this is handled affects trust in HR's fairness across the wider plant, not just the night shift
- How would you distinguish a genuine individual performance problem from a symptom of poor organizational design?
- What data would you want before concluding the incentive scheme, not the workers, is the primary cause?
- How might OCB and CWB be simultaneously present on the same shift, and what does that tell you?
- What risks does Radhika face if she acts only at the individual level to look decisive quickly?
Organizational Behaviour typically analyses phenomena at which three levels?
In the Anand Auto case, which piece of evidence most strongly suggests an organization-level (not purely individual) cause?
Given the mixed evidence of both individual complaints and systemic issues, what is the most defensible first step for Radhika?