1. Service Process Performance Management Robert D. Weaver r2w@psu.edu

2. Processes, Performance, & Incentives • The setting and the implications for service management • Examples • Current research & potential for applications • Example application projects • Bottomline – the potential R.D. Weaver

3. The setting Services provision involve complex processes • Not typically linear • Not typically based on fixed “production” rules • Performance results from • Human agent interaction • Human agent management of resources, other agents, & clients • Achievement of performance requires • Metrics to quantify and monitor • Incentives direct agents R.D. Weaver

4. The issue – How to manage performance? • Management of service processes is fundamentally different from manufacturing processes • Service processes • Involve “agents” • Agents are multifunctional and interactive • Agents are self-directive implying control is not direct • Agents embody “tacit” knowledge that is critical to performance • Process performance often depends on collaboration among agents R.D. Weaver

5. Service performance management Two steps • Define, implement, and monitor performance metrics of the service system • Overall system performance • Agent performance • Process performance • Design, implement, and monitor incentives that drive agent performance to achieve system goals R.D. Weaver

6. Step 1: Service process performance Salient features of service processes Role of agents Metrics for performance

7. Service systems are not linear Marketing & Sales Technical Service Outbound Logistics Production R.D. Weaver

8. Service process characteristics • Processes are fuzzy • Semi-autonomous human agents • Interact • Loosely follow rules that describe process ideals • Apply material and time inputs • Respond to continuum of problem settings • Agents “manage” subprocesses that compose a service system to deliver value R.D. Weaver

9. Service system configurations: Simple cases R.D. Weaver

10. Service system configurations R.D. Weaver

11. Service system configurations R.D. Weaver

12. Service system configurations R.D. Weaver

13. Role of agents in service system • Many agents • Agent have decision-making capacity • Agent goals affect decisions • Agent manage “sub” processes • Agents interact and are interdependent • Monitoring is costly and imperfect R.D. Weaver

14. Characteristics of agents within a service system • Directed by process rules • Capable of decision-making in response to change in problem setting • Guided by personal goals and resources that may include service system goals (alignment) • Influenced by incentives R.D. Weaver

15. Types of agent interaction • Asset service sharing • Tactical integration – joint modification of traditional silo operations to enhance collaborative performance • Strategic integration R.D. Weaver

16. Multi-agent service system R.D. Weaver

17. Example: Major League Baseball R.D. Weaver

18. What metrics for service performance? • Metrics are simply indicators of performance • Three types needed • Agent performance • Process performance • Service system performance • Performance must be defined by service system strategic goals and subsidiary objectives • Quantifiable measures of necessary conditions for performance levels acheivement. R.D. Weaver

19. Prerequisites for metrics • Observable • Verifiable • Low cost/value • High frequency • Leading indicators of service system goals R.D. Weaver

20. Examples of metrics • Efficiency of resource use • Fill rate, response delay, client revisions • Financials: typicals, cash-to-cash turn rates, R.D. Weaver

21. Example: Major League Baseball R.D. Weaver

22. Why performance metrics? • Monitoring for management • Gauging net benefits of agent configuration • Sharing net benefits through incentives • Monitoring for diagnostics • Identify opportunities for improvement • Identify bottlenecks, new problems • Establish opportunities for response • Metrics form basis for incentive design R.D. Weaver

23. Step 2: Incentive design Align agent & service system goals Manage agent performance

24. Alignment of goals • Incentives signal service system goals • Incentives encourage alignment • Salary level • Promotions • Bonuses (cash, options) R.D. Weaver

25. Need for managing agent performance • Agent autonomy creates bases for incentive design • Agent performance may be difficult monitor on a continuous basis • Agent potential (quality) difficult to measure • Agent performance varies across agents • Ultimately, agent performance reflects some voluntary human behavior ! R.D. Weaver

26. Potential of incentives • Differential incentives encourage productivity where pay-off will be greatest • Incentive package can induce agent to • Reveal “true” quality • Perform at potential • Incentive package design can align agent with service system goals • Incentive package design can be done at the system level R.D. Weaver

27. Nature of the beast Choose incentives conditional on metrics Dynamic, stochastic optimization of service system goals, given • Service system process • Agent autonomy and optimization R.D. Weaver

28. Potential pay-offs • Uniform incentives across heterogeneous agents fail to induce goal achievement • Differential incentive packages provide means of inducing agents to contribute to system performance R.D. Weaver

29. Service system process management Summary

30. Three stages of research • Service system mapping Characterize system processes, agents, and flows of effort that lead to delivery of service • Performance metric design Derive metrics from service system strategic goals and system structure • Incentive design R.D. Weaver