1. Government Regulation of Service Levels for Telephone Company Call Centres in Canada – Work in Progress – Armann Ingolfsson Samina Khandakar, Tarja Joro armann.ingolfsson@ualberta.ca School of Business, University of Alberta Edmonton! Workshop on Call Centers, Montreal, May 11, 2006

2. Motivation How should planning problems for call centres be posed? –Minimize cost, s.t. service level above a standard in every period –Minimize cost, s.t. aggregate service level above a standard Answer depends on the context For regulated public utilities, answer depends on the form of quality regulation

3. Related Literature Economics of quality regulation –Highly stylized game-theory models –Typical “firm’s problem:” Max profit = P(x, q) x – C(x, q), s.t. q ≥ MQS x = quantity, q = quality, P = price/unit, C = total cost Regulating telephone service quality –Institutional issues Little attention to operational issues – how to deliver a specific level of quality –In economic terms: what is the structure of C(x, q)?

4. Telus Sask Tel MTS Bell Aliant NorthWestTel Telephone Companies in Canada

5. The Regulator: CRTC Regulates telephone companies, broadcasters, cable service Timeline: –1876: Bell patents telephone –1893: Rate regulation starts –1968: CRTC formed –1982: Service quality regulation starts –1992: Long-distance competition –1993: Telecommunications act –1997: Local competition

6. How the Regulation Works Sixteen Quality-of-Service Indicators Each indicator has a pass/fail standard Companies self-report every three months Performance reported per month If below standard, firm must report monthly until standard met three months in a row Penalties decided on a case-by-case basis

7. Call Centre QoS Indicators 3 of 16 indicators are related to call centres: –Access to business office –Access to repair bureau –Access to directory assistance Standard: 80% answered in ≤ 20 seconds

8. Questions What does it cost to meet the standard? How does service level vary with time if standard is met at minimum cost? Influence of firm size –100 K – 20 M subscribers Influence of staffing method –Constant utilization staffing –Square root staffing What if the standard had to be met every hour?

9. Firms FirmSubscribers NorthWestTel110,000 SaskTel820,000 Telus9,618,000 Bell21,275,500

10. Assumptions Performance in hour t can be modeled as a stationary system: –M/M/s(t) (Erlang C), or –M/M/s(t)+M (Erlang A) Single employee type No scheduling issues No call volume forecast uncertainty

11. Notation  (i, t) = Arrival rate to company i in hour t = n(i)   (t) / 250 n(i) = # of subscribers for company i  = avg. # of calls per subscriber per year [0.5 – 2]  (t) = fraction of daily calls in hour t [Example from Green, Kolesar, and Soares (2002)]  = service rate [6 per hour] 1/  = avg. patience [= 1/  = 10 min.]

12. More Notation r(i, t) = (i, t) /  = Offered load for company i in hour t SL(i, t) = service level for company i in hour t = Pr{Delay ≤ 20 seconds, served} SL(i) = aggregate service level for company i = demand-weighted average service level

13. Staffing methods Constant percentage safety staffing: Square root safety staffing

14. Cost vs. size [Erlang C]

15. Cost vs. size [Erlang A]

16. Service Consistency vs. Size [Erlang C]

17. Service Consistency vs. Size [Erlang A]

18. Example: Northwesttel [Erlang A]

19. Example: Bell [Erlang A]

20. Conclusions Costlier for smaller firms to meet standards Performance may be far below standard at off- peak hours, if firms meet aggregate standard at minimum cost Incremental cost of meeting standard at all hours decreases with size Constant percentage less costly than square root safety staffing –[For Erlang C. Not clear yet with Erlang A]

21. Further Work Benchmark: minimum cost staffing Finish Erlang A analysis Compare to regulation in other countries –USA, Brazil

22. Discussion: Analysis Tools Erlang C: Queueing ToolPak (MS Excel function library) –Demonstrate Erlang A: 4CallCenters software How should we “package” our tools to maximize their use?

23. Discussion: Auditing Companies self report performance data How can/should companies be audited?

24. Discussion: Auditing Approach 1: Use models to check whether self-reported data is plausible Approach 2: “mystery callers” Approach 3: ?

25. Discussion: Auditing Brazil: companies report inputs (arrival rate, service rate, number of servers), regulator uses model to compute output (SL), compares to reported output How should this be done? –How often? –For what time interval? –Using what model? –When should action be taken?

26. Discussion: Data Reporting What data should regulated companies be required to report?

27. Discussion: Monitoring Manufacturing: SPC charts to monitor production processes Why not for call centers? Monitor: –Service times –Abandonment rates –Forecast errors –… What modifications are needed for using SPC charts in call centres?

28. Discussion: SL Constraints Aggregate vs. period-by-period Q: what’s the value of consistency? Customers react to perception – expectation Asymmetry: negative impact of not meeting expectations likely larger than positive impact of exceeding expectations

29. BACKUP SLIDES

30. Example: Northwesttel [Erlang C]

31. Example: Bell [Erlang C]

32. Cost of Constant SL [Erlang C]