Do End Users and Service Providers Agree on the Trajectory of M2M?

Kathryn Weldon
Kathryn Weldon

Summary Bullets:

  • Every year at its Connexion conference in Boston, Axeda, a provider of cloud-based M2M application solutions, presents an ever-growing scale (now reaching nine levels) that measures the sophistication of M2M solutions, ranging from 1) unconnected to 2) connected, 3) serviceable, 4) intelligent, 5) optimized, 6) differentiated, 7) eco-friendly, 8) collaborative/socialized/multivendor, and 9) cross-industry solutions.  Each year, Axeda adds new levels.
  • Axeda also showcased several end users’ actual M2M deployments.  Where were they on this scale and can we deduce anything about the current trajectory of M2M from these real-world case studies?

End users at the Axeda Connexion conference included Getinge Group, which provides hospital systems, extended care and infection control.  In 2003, the company envisioned a system to provide a service for remote monitoring of its equipment, but it ran into technology and regulatory challenges along the way and had difficulty building a model that made the ROI self-evident.  Eventually, the company connected the end customer (hospital) though a web portal and smartphone app, offering a value prop of unprecedented knowledge via online troubleshooting, access to historical data and statistics for production planning, and real-time equipment status.  It was in production in 2011; as of 2012, it still found take-up slow among its customers, especially in low-cost labor countries that did not ‘get’ the value prop.  In the future, it plans to add data mining.  Overall, it took Getinge eight years to get to the ‘connected,’ ‘serviceable’ and ‘intelligent’ stages – essentially reaching level 4 (out of 9) on the Axeda model.

In another example, GE Gas Engines realized if it could save just 10% of its customers’ costs (in this case, savings were achievable due to more optimal fuel usage, productivity enhancements and CapEx reduction), the company could save a huge amount over time.  Over a 15-year life, these savings reached $30 million, $66 billion, $63 billion, $27 billion and $90 billion, respectively, for its aviation, healthcare, power, rail and oil and gas customers.  GE is also involved in asset and operations optimization, with a software center of excellence dealing with big data analytics.  GE is approximately at level 5 in the Axeda model (i.e., its M2M solution is ‘optimized’).

Diebold, a well-known equipment leasing company with a large base of ATM machines, was dealing with margin erosion and increasing competition and needed to change its business model to generate incremental revenue.  It saw a way to evolve (with a vision that involved stepping through the M2M levels up to connected, serviceable and intelligent solutions) through remote servicing of its ATM machines.  Remote software updates, product improvements and replacement of onsite maintenance have yielded increased the availability and uptime of its ATMs.  Over 50% of the ATM service base is now remotely managed, with a 25% reduction in on-site service calls.  It is essentially at level 4 or 5 of the model (‘intelligent’ and on the way to ‘optimized’).

Axeda’s model is useful for looking at the potential of M2M to change business processes, save money, enhance productivity and even generate new service revenues through entirely new lines of business.  It is clear, however, that most of today’s M2M deployments have just begun to live up to their eventual potential.  This shows a bit of a disconnect between the very optimistic positioning of the supplier ecosystem and what is actually being done in the real world.  We still have a long way to go, but we are getting there.

What do you think?

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