Capping IT Off

Capping IT Off

Opinions expressed on this blog reflect the writer’s views and not the position of the Capgemini Group

IoT and the Impact on Service Lifecycle Management

I recently read an article by ABI Research, [London, UK, April 28, 2014] that made this very interesting observation: “… revenues from maintenance analytics will total $9.1 billion this year. Following a CAGR of 22%, the market’s size will reach $24.7 billion in 2019, driven largely by adoption of predictive analytics and M2M [Machine to Machine] connectivity. While the more advanced forms of maintenance, predictive and prescriptive, still account for just 23% of this year’s market, at the end of the forecasting period they will collectively represent 60% of all revenues.”  That is some serious growth forecasts for a traditionally small piece of the aftermarket SLM market space.

Since the 1990’s the concept of servitization has seen significant growth in the manufacturing sector as product sales margins have declined while aftermarket service as a percentage of revenue and with higher margins has increased. The idea of offering unique product focused services and offerings beyond the traditional aftermarket warranty or extended warranty are seeing innovative approaches to market differentiation and customer demand.  This trend will continue to evolve and expand with the exponential growth of IoT and M2M data generation and collection.
Predictive analytics in maintenance is already an early winner of IoT technologies with the expanded use of sensors in products to monitor various product systems health. Though, health monitoring has been around for decades the breadth and amount of data is exploding with the internet and wireless connectivity.

The key words here being analytics and predictive.  To manage the copious amounts of data generated by sensors, the business will have to invest heavily in:
  • Big Data architectures and solid governance to manage data quality
  • Analytical tools that can handle millions of records with the ability to apply visualization and advanced predictive modeling techniques
  • Data science resources imbedded in the aftermarket maintenance and engineering domains to help the business expertise to make sense of the information being analyzed
  • Marketing and business groups that can take technical data and exploit new business opportunities
Where does your company stand in this space? Are you exploiting the data that is being generated by the IoT to its fullest or just scratching the surface? Are you innovating new aftermarket products and services to differentiate you from your competitors and make your products more supportable?

If you need help in answering these questions please feel free to contact me.

About the author

Peter White

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