A broken hand and a sympathetic soul: little lies, big data & the customer experience
I broke my hand in February which has resulted in eight long months of my body slowly repairing the surprisingly extensive damage to bone, tendons and ligaments. After weekly visits to the local hospital’s hand clinic, it recently became clear that one finger’s tendon problem was getting worse, not better, requiring review by a consultant.
The consultant’s appointment was yesterday. I was given an appointment slot and arrived on time, as always (I have a ‘thing’ about good time-keeping). Settling into my chair in the reception area I waited … and waited.
Three hours later, I was still waiting; with no-one managing my expectations - indeed - no-one around to even ask what was going on! Now, before you read on, I want you to know that this isn’t going to be a bash at, nor a plea to save the marvels of, the NHS. It is, however, going to be about impact, emotions, lies and big data.
Back to the waiting room: I was eventually called into a consulting room and seen by a weary-looking consultant who had been on-call since 1.30am. Sleep deprived and out of gas on the charm front, he inspected my hand, read the notes, and looked at me closely.
I watched him just as closely and could guess from his facial expressions that he was fast realising that I wasn’t the type of person who was going to accept his first option of ‘go away and see what happens’.
Instead, he sighed and recommended in a manner of curt irritation (and that’s me being generous in my wording) a steroid injection into the tendon running up the palm of my hand. Now, I’m a grown woman and used to dealing with ‘direct’ senior professionals, but this was hardly the warm encounter you expect to receive when you’re in a vulnerable position and in physical pain.
Bedside manner aside, the injection was administered within five minutes by the curt consultant himself, no messing around with another appointment, and I was dismissed.
Walking out of the consultation room I was met by a rather sheepish-looking nurse who asked me to fill in a ‘customer feedback form’. Squirming with awkwardness she said, “I know you were kept waiting and I’m sorry, but we couldn’t help it”. Her face was a mixture of pleading, embarrassment and tiredness. I took the pen and reviewed the small card giving me the usual tick-box range of 5 options from ‘Truly Appalling’ to ‘Absolutely Amazing’ (I paraphrase).
I thought about my customer experience of the morning: about the three-hour wait, about the non-existence of anyone managing my expectations, about the brusque consultant … and I lied. The plea in the eyes of the harassed nurse, the weary gaze of a tired consultant who, ultimately, gave effective treatment compelled my sympathetic emotions to override my rational thoughts.
I gave a high customer satisfaction rating. I lied.
Despite getting the treatment I needed, my overall experience was, to say the least: pretty poor. That lie is now going to go back into the data system and be analysed with feedback from other sympathetic souls, and nothing is going to change at the systemic level - all because I felt sympathy for the individual in the system.
What can we learn from this? Well-meaning lies screw big data, and well-meaning lies are told when confronted by the individual in the system.
If someone had asked me questions, listened to my nuanced replies, and carefully analysed those responses, then there may actually be a chance of understanding the important aspects of customer experience and customer journeys. Every interaction (or lack thereof) is weighed up by each customer – often out of awareness. Customers are human; our responses are a mixture of cognitive, emotional and social. Customer experiences and customer journeys need to have psychological understanding at the heart of analysis, not just totting up scores on a tick-box form.
If you’re serious about understanding your customer’s satisfaction levels, your staff need to be given the processes, training and time that enable them to identify the customer need and support that customer along their individual journey.
How do you understand your customer journey? What questions do you ask to make sure you’re not getting sympathetic lies that will only serve to screw your big data?