I recently overheard a conversation among three instructors about their university’s Blackboard learning management system. They were swapping stories of times when the system failed. One of them mentioned that one time during a particularly rocky period in the service’s history, he entered a large number of grades into the system only to find that they weren’t there the next day. As a result, he started keeping grades in a spreadsheet as a backup of sorts. The other two recalled times when the system would repeatedly fail mid-quiz for students. Even if the failures were due to their own errors, the point is that they lost trust in the system.
This got me thinking about “shadow systems.” Shadow systems are hardly new, people have been working around sanctioned IT systems since the first IT system was sanctioned. If a customer doesn’t like your system for whatever reason, they will find their own ways of doing things. This could be the person who brings their own printer in because the managed printer is too far away or the department that runs their own database server because the central database service costs too much. Even the TA who keeps grades in a spreadsheet in case Blackboard fails is running a shadow system, and even these trivial systems can have a large aggregate cost.
Because my IT service management class recently discussed service metrics, I considered how trust in a system might be measured. My ultimate conclusion: all your metrics are crap. Anything that’s worth measuring can’t be measured. At best, we have proxies.
Think about it. Does a student really care if the learning management system has five nines of uptime if that .001 is while she’s taking a quiz? Does the instructor care that 999,999 transactions complete successfully when his grade entry is the one that doesn’t?
We talk about “operational credibility” using service metrics, but do they really tell us what we want to know? What ultimately matters in preventing shadow systems is if the user trusts the service. How someone feels about a service is hard to quantify. Quantifying how a whole group feels about a service is even harder. Traditional service metrics are a proxy at their best. At their worst, they completely obscure what we really want to know: does the customer trust the system enough to use it?
There are a a whole host of factors that can affect a service’s credibility. Broadly speaking, I place them into four categories:
- Technical – Yes, the technical performance of a system does matter. It matters because it’s what you measure, because it’s what you can prove, and because it affects the other categories. The trick is to avoid thinking you’re done because you’ve taken care of technical credibility.
- Psychological – Perception is reality and how people perceive things is driven by the inner workings of the human mind. To a large degree, service providers have little control over the psychology of their customers. Perhaps the most important are of control is the proper management of expectations. Incident and problem response, as well as general communication, are also critical factors.
- Sociological – One disgruntled person is probably not going to build a very costly shadow system. A whole group of disgruntled people will rack up cost quickly. Some people don’t even know they hate something until the pitchfork brigade rolls along.
- Political – You can’t avoid politics. I debated including this in psychological or sociological, but I think it belongs by itself. If someone can keep some of their clout within the organization by liking or disliking a service, you can bet they will. I suspect political factors almost always work against credibility, and are often driven by short-sightedness or fear.
If I had the time and resources, I’d be interested in studying how various factors relate to customer trust in a service. It would be interesting to know, especially for services that don’t have a direct financial impact, what sort of requirements can be relaxed and still meet the level of credibility the customer requires. If you’re a graduate student studying service management, I present this challenge to you: find a derived value that can be tightly correlated to the perceived credibility of a service. I believe it can be done.