Nothing is perfect. Of course. All businesses strive for top performance, but mistakes do happen. It’s what happens after the mistake that matters. How good is your provider’s service recovery? How quickly do credits post to your account? How often do mistakes happen, and is there a pattern you can’t quite put your finger on? Maintaining a positive relationship with your provider is difficult if mistakes keep happening. It is crucial to understand the impact of these mistakes.
In addition to keeping track of everything, monitoring service recovery has unique features that present some challenges. The most important aspect of tracking mistakes is determining whether or not they are truly isolated events. Or, are they occurring as a result of some type of systemic problem. Is there some hidden detail or missing piece of information that would reveal a larger pattern? To be clear, we’re not interested in pointing fingers – we believe in just figuring out the problem and helping either you, your provider or both resolve it and move forward.
Unirithm understands the rigor involved with managing a managed program, as well as the frustrations that arise when things go sideways. In addition to keeping a log of service failures, we create service failure scenario models that help us predict when a mistake might happen, and we attempt to deploy measures that PREVENT the mistake from happening in the first place.
Unirithm employs machine learning to figure out if recurring service issues are isolated or systemic (or some place in between). By modeling your service and logistical structure, we become proactive in helping your program stay on track. Why react to mistakes when you could avoid them altogether?