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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.
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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 AlbertaEdmonton! Workshop on Call Centers, Montreal, May 11, 2006
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
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)?
Telephone Companies in Canada NorthWestTel Telus Sask Tel MTS Bell Aliant
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
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
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
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?
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
Notation l(i, t) = Arrival rate to company i in hour t = n(i) ab(t) / 250 n(i) = # of subscribers for company i a = avg. # of calls per subscriber per year [0.5 – 2] b(t) = fraction of daily calls in hour t [Example from Green, Kolesar, and Soares (2002)] m = service rate [6 per hour] 1/g = avg. patience [= 1/m = 10 min.]
More Notation r(i, t) = l(i, t) / m = 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
Staffing methods • Constant percentage safety staffing: • Square root safety staffing
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]
Further Work • Benchmark: minimum cost staffing • Finish Erlang A analysis • Compare to regulation in other countries • USA, Brazil
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?
Discussion: Auditing • Companies self report performance data • How can/should companies be audited?
Discussion: Auditing • Approach 1: Use models to check whether self-reported data is plausible • Approach 2: “mystery callers” • Approach 3: ?
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?
Discussion: Data Reporting • What data should regulated companies be required to report?
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?
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