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Matching and routing

Who should meet whom?

Becker (1973)

Gary S. Becker, "A Theory of Marriage: Part I," Journal of Political Economy 81, no. 4 (1973): 813–846. doi:10.1086/260084

What it found

When partners' traits are complements (each makes the other more productive), total output is highest with positive assortative matching: best with best. Shimer and Smith (2000, Econometrica 68(2): 343–370) show that search frictions can weaken this.

Why it matters

If a great rep is worth more on a great lead than on a poor one, pair them. Close rate × lead value is multiplicative, which is the definition of complements.

Read our explainer

Gale & Shapley (1962); Nobel 2012

David Gale and Lloyd S. Shapley, "College Admissions and the Stability of Marriage," American Mathematical Monthly 69, no. 1 (1962): 9–15. doi:10.1080/00029890.1962.11989827

What it found

The "deferred-acceptance procedure … always leads to a stable outcome." The side that makes the offers gets its best stable matching. Roth and Shapley won the 2012 Nobel "for the theory of stable allocations and the practice of market design."

Why it matters

Matching is a solved, designable problem, whether for territories, account assignment or routing, and design choices decide who comes out ahead.

Gans, Koole & Mandelbaum (2003)

Noah Gans, Ger Koole and Avishai Mandelbaum, "Telephone Call Centers: Tutorial, Review, and Research Prospects," Manufacturing & Service Operations Management 5, no. 2 (2003): 79–141. doi:10.1287/msom.5.2.79.16071

What it found

A review of call centers as systems where "the behavior of customers and employees is closely intertwined with physical performance measures," and where traditional queueing models are "fundamentally limited."

Why it matters

The base reference before challenging a speed-to-answer target.

Armony (2005)

Mor Armony, "Dynamic Routing in Large-Scale Service Systems with Heterogeneous Servers," Queueing Systems 51, no. 3–4 (2005): 287–329. doi:10.1007/s11134-005-3760-7

What it found

In large, busy systems where agents differ in speed, routing each caller to the fastest available agent first minimizes waiting.

Why it matters

Routing that's optimal for speed loads up the fastest agents. It optimizes waiting, not value.

Note. Summary drawn from a published review of this work.

Armony & Ward (2010)

Mor Armony and Amy R. Ward, "Fair Dynamic Routing in Large-Scale Heterogeneous-Server Systems," Operations Research 58, no. 3 (2010): 624–637. doi:10.1287/opre.1090.0777

What it found

"There is a natural trade-off between minimizing customer wait time and fairly dividing the workload among agents of different skill levels." Their policy "outperforms a common routing policy used in call centers (that routes to the agent that has been idle the longest)."

Why it matters

"longest idle" routing, the fairness default, has a measurable cost.

Mehrotra, Ross, Ryder & Zhou (2012)

Vijay Mehrotra, Kevin Ross, Geoff Ryder and Yong-Pin Zhou, "Routing to Manage Resolution and Waiting Time in Call Centers with Heterogeneous Servers," Manufacturing & Service Operations Management 14, no. 1 (2012): 66–81. doi:10.1287/msom.1110.0349

What it found

Agents "exhibit very different performance for the same call type." Simulations on a financial firm's data trace a trade-off curve: the best-resolution rule reached about 90.6% resolution with waits over 7 minutes, while a hybrid rule reached about 88.6% with about 18 seconds' wait.

Why it matters

The closest published evidence on routing by ability: it costs a little speed and buys better outcomes, and smart hybrid rules get most of both.

Note. A simulation on a real company's call data, not a live rollout.

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