At Your Service (Part 2)
To read Part 1 of this article, click here…
One of the most influential thinkers in this field is the practical and thoughtful Frederick Reichheld of Bain Consulting [Ref 1]. It was he who most clearly articulated the lifetime value of customers and the wisdom of investing most service cost in those of greatest long-term value. It was also he who first proposed the “Net Promoter Score” (NPS), defined as:
NPS = (% of customers actively advocating you as a provider they would recommend to others) – (% of customers who would advise others not to buy from you)
This score has been found to be strongly correlated with customer loyalty and with actual procurement decisions. As such it is a most useful top-level summary measure. Other, lower-level data is needed to interpret the influences upon the state. This is where the hierarchy introduced earlier in this article is also informative of contributory relationships to decide actions to amend service levels and costs.
For the purposes of valuation, it is useful to examine two classes: revenue generating and non-revenue generating services.
I consciously pay more for my broadband than the cheapest supplier. The reason is that my current ISP delivers a consistently well informed and effective fault resolution service. With their aid last year I resolved a major service outage that was traced to my firewall (outside their responsibility). The small monthly premium over the competition that I pay is of considerable incremental value to me. This sustains their ability to price at a premium. This is the means by which they fund the incremental costs of qualified, loyal staff and supporting infrastructure on which their competitors may spend less. It appeals to a segment of customers who value service quality, including me.
There is research [Ref 2] that supports the intuitive observation that those who pay most expect the highest levels of service. It is thus possible to establish a quantified relationship between the frequency and severity of issues and customer defection for various levels of price premium. Most intuitively accept the correlation from their own experience and avoid the costs of research.
Goodman, in the research cited, proposes a good customer service valuation approach. It accommodates the observation that most people experiencing bad service do not complain to the company, whilst still telling their contacts to avoid patronising the enterprise. With the Reichhard customer loyalty value and periodic data on numbers of complaints received, the company can calculate the periodic sales lost. He calls this the “Market Damage Model ™”. This is a quantified opportunity cost of less-than-perfect service. In the most sophisticated enterprises, the model can be applied differentially by customer segment to accommodate their varying customer lifetime values. Every company will have a residual level of customer loss and associated opportunity cost. It must decide how much to spend on each aspect of customer service to optimise overall profitability.
This is a rational, evidence-based approach that informs experimental investment and the allocation of resource. As such, it is one I find simple enough to be useful. It allows the analysis of the relative effect of measures to:
- Reduce the number and severity of problems and incidents
- Increase the percentage of customers who complain when they encounter an issue
- Increase the quality of outcomes when customers complain
And thus to make rational investment decisions regarding customer service. The approach is notably powerful when combined with the perspective of customer experience. There will, as in all investment decisions be elements of uncertainty regarding the magnitude of effect. These can frequently be minimised by experimentation.
Not all points of pain are of equivalent cost. In sourced services one of the greatest that I have encountered when supporting customers has been seen in transition project delivery. I was asked by one client to examine such a situation where the core question was “should I fire these clowns now or will they ever get their act together?”
In many IT and BPO services, there is a separation between the customer who commissions and funds a service and the service user. This is taken to extremes in organisations such as government where the link can be so marked that the commissioner entirely loses sight of it, especially where they do not get out much.
Service users in non-revenue generating situations may face little choice of other suppliers. They are frequently trained to have low expectations. This can be seen in examples such as an employee who can turn only to his internal IT department for connection to the corporate network. In some cases, vengeance is sweetly extracted through behaviour such as BYOD, departmental purchase of cloud services avoiding the IT department and lobbying for the CIO to be fired.
Such situations do not directly affect revenue. There are however internal costs including:
- Loss of user productivity
- Total costs of service provision (multiple call-backs, management escalation time)
- Work-around costs (e.g. departments hiring their own programmers for ITO and accountants for F&A)
These can be problematic to value, being characterised by many transactions each with a small value. In many cases the data indicates clearly which is the best course to take based on performance data without there being high initial confidence in the pecuniary value. That can be discovered having made the decision and monitoring the outcome. They are typically non-cashable, but can be material. The CIO who asked whether he should fire his service provider was spending as much as 60% of his own time in issue resolution, changing the priority of his staff each time a new issue came in.
The simple selection of either the most expensive or the cheapest options for customer service provision is not rational and is frequently sub-optimal. To deliver the best value requires an understanding of the lifetime value of customers and how their valuation of the various aspects of the service they receive affects their loyalty. Knowing this, selective investment and the diversion of funds from less influential areas, allows optimisation of service for value.
1. The Loyalty Effect, Frederick Reichheld. Harvard Business School Press 1996
2. Strategic Customer Service, John A. Goodman. Amacom 2009
This article was first published in Outsource #36 (Summer 2014).