Okay so you are ready to launch your customer experience and satisfaction initiative. Referencing my initial blog on this site, "The Customer Experience Big Tent," the first critical activity is taking the time to understand and implement meaningful customer metrics. You might be wondering why I even raise this somewhat self-evident topic. Self-evident yes, but there are some nuances. It all starts with a deep understanding and involvement with your customer... simply put you need to ask!
This planning activity is best framed by addressing two fundamental questions:
- What should we measure?
- How should we measure it?
1. What should we Measure: The biggest risk at this stage is launching a customer satisfaction program and a metrics structure that is internally-facing. The common response is "of course we know what to measure. After all we have been working with these customers for years"... wrong answer. To do this properly you need to have an outside-in mindset and internalize your custom's business. The service or product provider's perspective needs to morph. Metrics that are tracked and monitored need to reflect the real impact on the customer's business and processes. The only way to do this is to invite the key customer stakeholders to the table and mutually define these metrics with them. This discussion should cover three distinct components:
Metric Selection: Understand the "Critical to Quality" (CTQ's) drivers of your customer's business and jointly define what metrics should be included in the program. You must ask your customer's what measures are important to them and understand how they directly impact their business performance. Metrics outside of the core operations, quality, and cost areas that you might consider of tertiary importance, might in fact be very significant. Take for example paperwork accuracy and ease of processing (invoices, credit notes, warranty claims processing, etc) as some simple examples.
Customer Context: Define the chosen metric within the context of how it impacts your customer performance and process, not on how you conveniently like to track the measure. Let's take a simple example from relevant capital equipment industries where a services repair depot operation exists. Instead of measuring classic repair depot turn-around-time (TAT) from shop induction to shipment from the depot, one might instead calculate end to end TAT as time measured from shipment from the customer facility to the time the unit was received back at the same facility for re-installation into service (dock-to-dock).
Thresholds and Limits: Establish mutually agreed to Service level Agreements (SLA's) with clear thresholds of what constitutes good, neutral, and needs improvement performance.
2. How Should we Measure It: Do not forget about process variation measurement. Most customer-facing organizations measure their performance and impact to their customer's business based on average performance. While important, it is perhaps more relevant to measure and communicate your process variation. Of course customer's desire both world-class average performance that is repeatable (low standard deviation). However, best-in-class average performance with wide process variation is problematic. Take on-time delivery (OTD) as an example. Imagine you had industry leading (top 15 percentile) OTD metrics but:
- You missed a critical flight-line spare part component shipment date for a commercial airline resulting in the cancelation of a 747 and the need to reschedule 200+ passengers
- You missed a spare part shipment for a MRI device in need of repair in a major regional hospital resulting in patients being turned away for critical imaging tests
- You missed a spare part shipment to a semiconductor fab resulting in critical equipment downtime costing hundreds of thousands of dollars per hour of facility downtime
For all of upcoming meetings with these customers I suggest not leading with your industry leading average OTD charts. The bottom line is if you understand and can effectively communicate your process repeatability or variation then customer's can plan around this. They might for example stock a higher level of safety stock... more expensive, sure, but better than the impact and associated costs of the scenarios identified above.
This variation analysis doesn't need to a rigorous standard deviation exercise. Simply measuring and tracking some proxy for variation with mutually defined thresholds starts to get at the issue. For example, the number of times this month that a delivery date was missed.
Next up on this customer experience blog topic will be a discussion on the importance of Data Breadth & Reporting --- Providing interactive, intuitive, and accessible measurement, analysis, and reporting solutions that considers all cross functional data and sources.