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The purpose of this paper is to expand upon policy implications of a recent study assessing adolescent mental health service contact and subsequent depression.

Review of related evidence from academic and grey literature.

Studies assessing the role of mental health services in reducing mental disorder during adolescence are sparse, and even prevalence figures for adolescent mental disorders are out-of-date. Adolescent mental health service contact rates are shown to fall concurrent with budgetary decreases. School-based counselling is highlighted as an important source of help that may be at risk of being cut. Increased training of General Practitioners and school counsellors is needed to improve efficiency in specialist Child and Adolescent Mental Health Services (CAMHS).

Longitudinal studies of young people’s mental health should include mental health service usage and its relationship with subsequent mental health outcomes.

Funding cuts to CAMHS must be avoided, school-based counselling must be protected, and service referrers should be better trained.

This paper highlights the need for increased CAMHS data, sustained funding, and improved training for this vital service.

The purpose of this study is to understand the profit implications of analytics-driven centralized discriminatory pricing at the headquarter level compared with sales force price delegation in the purchase of an aftermarket good through an indirect retail channel with symmetric information.

Using individual-level loan application and approval data from a North American financial institution and segment-level customer risk as the price discrimination criterion for the firm, the authors develop a three-stage model that accounts for the salesperson’s price decision within the limits of the latitude provided by the firm; the firm’s decision to approve or not approve a sales application; and the customer’s decision to accept or reject a sales offer conditional on the firm’s approval. Next, the authors compare the profitability of this sales force price delegation model to that of a segment-level centralized pricing model where agent incentives and consumer prices are simultaneously optimized using a quasi-Newton nonlinear optimization algorithm (i.e. Broyden–Fletcher–Goldfarb–Shanno algorithm).

The results suggest that implementation of analytics-driven centralized discriminatory pricing and optimal sales force incentives leads to double-digit lifts in firm profits. Moreover, the authors find that the high-risk customer segment is less price-sensitive and firms, upon leveraging this segment’s willingness to pay, not only improve their bottom-line but also allow these marginalized customers with traditionally low approval rates access to loans. This points out the important customer welfare implications of the findings.

Substantively, to the best of the authors’ knowledge, this paper is the first to empirically investigate the profitability of analytics-driven segment-level (i.e. discriminatory) centralized pricing compared with sales force price delegation in indirect retail channels (i.e. where agents are external to the firm and have access to competitor products), taking into account the decisions of the three key stakeholders of the process, namely, the consumer, the salesperson and the firm and simultaneously optimizing sales commission and centralized consumer price.