CaseBank recently exhibited at the Field Service Medical conference in San Diego, CA, where there was a lot of buzz about M2M (machine to machine) and IoT (Internet of Things) technology. As a participant on the panel called “Driving Field Service Transformation through Connected Products,” we were pleased to contribute insights about collecting machine data and using it to improve the customer experience and remove human error from troubleshooting. During this panel it became clear that many companies are successfully collecting data from their machines but are now wrestling with putting the data they’ve collected to valuable use.
CaseBank helps service departments improve field support by leveraging the connectivity of these complex machines. Many companies have been hoping that remote support will reduce the number of times technicians are dispatched for basic repairs and adjustments however, as noted in a previous blog (Reduce Your Call-back Rate) equipment can be remotely repaired only about 10% of the time. Remote assistance—whereby product support centers diagnose the problem remotely and guides equipment operators through the repair—works only 25% of the time. That means 65% of the time OEMs still need to dispatch a technician, and once on site, technicians spend 40% of their time diagnosing the problem.
According to a recent Aberdeen report, “the connected machine enables field service teams to diagnose reasons for failure which leads to faster resolution.” (The Internet of Things: Connecting the Enterprise and the Customer , October, 2014). The report goes on to discuss how IoT can enable a company to connect all departments—product design, service and manufacturing—to the customer. While companies that embrace IoT and M2M can manufacture highly automated equipment, IoT and M2M don’t do much to address a major challenge for global companies: the challenge of technical expertise becoming “siloed” (i.e., technician expertise becomes concentrated in some areas but is inaccessible to others).
For maintenance and repairs to be executed with similar expertise around the world, better technology is needed to allow collaboration between field service teams so that troubleshooting and repair information can be shared. IoT and M2M is about collecting digital data from complex machines, but more is necessary to make use of that data and understand what it means for equipment performance and reliability. New combinations and correlations of diagnostic codes are constantly being discovered and once the secret of those fault codes has been exposed, it’s only by breaking down those technical siloes that critical information can be quickly distributed and acted upon. So, as companies begin to leverage the latest IoT technologies to collect data, putting that data into use is still a problem that most companies are struggling to solve. Better condition monitoring and better preventative maintenance will not be realized by collecting data but by applying the lessons gleaned from that data.
M2M and IoT connectivity is certainly helpful in terms of generating information about equipment performance in the field, but it is only part of the answer to increasing field service effectivity. Although IoT and M2M are opening up new opportunities for manufacturers, the sheer volume of data has actually complicated the service process (see previous blog post, Closed Loop SLM: A life preserver for those drowning in data). Some manufacturers admit that 80% of their equipment fault codes are ambiguous (i.e., they don’t indicate the actual source of the problem).
CaseBank software sifts through the data collected from machines in the field, and then shares any lessons learned with others to solve this problem; providing a comprehensive view of all the data and the ability to discern what’s relevant and what isn’t. When users can easily identify and troubleshoot equipment problems companies find that more issues are quickly recognized and solved, and technicians are dispatched only for critical issues.