Some of the largest vendors and OEMs on the planet were in agreement at the Axeda Conference in Boston this week – embedded devices will allow manufacturers to monitor their goods after sale, and in doing so, present a wide range of revenue opportunities that are just starting to become reality. New, M2M-driven revenue sources will resemble subscription sales more than the traditional movement of hard goods, and handling “Big Data” will be the key to making that happen.
“Overall, revenue from the sale of finished products is declining. Of course, manufacturing concerns can grow through mergers and acquisition, but that tends to be a temporary solution, and it really represents consolidation. What we’re seeing now is a true transformation in the most basic business models for manufacturing – providing real, organic growth through value-added services that bring a whole range of benefits,” said Mike Wendell, vice president of Industry Business Solutions with backbone software provider SAP (Walldorf, Germany).
In his keynote address, Wendell pointed out that manufacturers will increasingly look to gain revenues through subscriptions and metered usage, and according to Gartner, 35% of the Global 2000 companies that sell hard goods will generate 10% of their revenue from subscriptions by 2015. OEMs at the conference backed him up. The Infection Control Division of Danish medical equipment maker Getinge  (Getinge, Sweden) reports that fully 40% of the division’s total of $700 million in annual revenue now comes from recurring service delivery.
“When we started, we really didn’t know what the revenue impact would be, but now we’re on our third version of our web service, which is basically sold as a service-level agreement. The results have been spectacular. It’s possible to track our machines deployed anywhere in the world through the Axeda web-based platform, and our customers are happy to pay extra for service if they get more for their money through increased uptime and other efficiencies,” said Anders Buch, Getinge’s remote diagnostics manager.
According to Wendell and others, the key to realizing the benefits of subscription revenue will be handling – and effectively analyzing – the massive amounts of data that M2M deployments generate. To cite just two examples at the conference, Cisco (San Jose, CA) and SAP touted their FOG Computing architecture and Business Web SAAS respectively. Both are aimed at allowing enterprise firms handle “Big Data” – something that the typical enterprise is not accustomed to.
GE Jenbacher  (Jenbach, Austria), GE’s gas engine division, estimated that by analyzing big data and avoiding service technician dispatches, the company could see a 50% cost reduction. According to Audi Lucas, project manager at GE Jenbacher, a 2008 case study involving faulty bearings inside a generator shows that preemptive analysis of big data helps limit the downtime of engines. GE Jenbacher developed an algorithm to monitor certain data points associated with the faulty bearings. When a certain threshold was reached the system sent notifications displaying that the bearing was going to fail, and therefore could take preemptive steps in limiting the downtime of an engine. Instead of an engine standstill of six to eight weeks with a failed engine, predictive algorithm monitoring allowed for a pre-fail detection two weeks in advance, and gave the company time to schedule a dispatch to go out and replace the part.
M2M technology not only allows OEMs to put the right technician on the job quickly, but also to better warranty control, streamlined supply chains, better operational metrics, increased conditional awareness, and even better product designs, according to Wendell. “The U.S. Army recently surveyed the use of their Humvees to get a better idea of the field conditions for the vehicles – it was largely an M2M monitoring deployment. The result of the survey was that Humvees spend 90% of their time standing and idling while soldiers go about their tasks. Do you think this will influence future vehicle designs?” he said.