Industrial IoT

Empower a Data-Driven Aftermarket & Improve Your Bottom Line

4 min readWhat is the aftermarket The “aftermarket” can generally be defined as a secondary [...]

4 min read

What is the aftermarket

The “aftermarket” can generally be defined as a secondary market that supplies accessories, spare parts, second-hand equipment and other goods or services used in repair and maintenance. Generally seen as a cost burden (or logistical mess), aftermarket services are often an underappreciated source of revenue. Stable and untied to external factors, if implemented correctly, they can help companies leverage existing customers at almost no cost.  For manufacturers, the one-time sale of equipment is only the tip of the iceberg, the real opportunity lies below, where aftermarket ‘servicing’ begins.

How does it relate to the IoT

Aftermarket services are not a new concept. Companies have been employing aftermarket services for years, in fact  49% of GE’s revenue come from the aftermarket alone. But with the IoT and the increase in connectivity,  products are not ‘just products’ anymore. They are services. Real-time monitoring shifts the focus from a ‘one time sale’ to an ‘ongoing relationship’. As a result, the market is no longer defined by the ‘ship and pray’ service model, where products are blindly delivered to the customer and post purchase servicing is reactive (after a customer complaint). With the right data strategy, product manufacturers can proactively deal with product issues, optimize maintenance schedules and reduce downtime.

In short, the aftermarket has three key benefits that traditional equipment sales do not:

  • Profitability: There is a shorter sales cycle when selling to existing customers, which reduces (or eliminates) the cost of acquisition. Additionally, after-sale services and parts offer manufacturers a margin three to five times larger than that of a one-time equipment sale
  • Customer satisfaction: The aftermarket is where manufacturers can build brand loyalty by offering customized services. In fact, an enhanced after-sale experience strongly correlates with returning customers and influences the perceived value of the company
  • Stable growth: The aftermarket is not volatile or cyclical and more importantly, it doesn’t depend on external factors such as economic stability (all equipment must be maintained and upgraded)

If done right and treated as a separate business segment with its own dedicated infrastructure and resources, the aftermarket will bring a long-term and stable stream of revenue.

When developing an aftermarket service, there are many things to consider. For instance:

  • Should it host services for the entire range of products or only a subset?
  • What kind of services should be offered?
  • Where should the service centers be?
  • What parts should be stored in the inventory at all times?
  • Etc..

How do IoT analytics enhance aftermarket services

Directing the aftermarket model – IoT Data Analytics are playing an important role in the aftermarkets. With insights derived from product data, manufacturers are able to completely restructure their aftermarket strategy.

They can understand how/when/where their products are being used, develop customer and product-centered metrics as well as monitor the performance of the equipment in real-time.

Product Usage Insights The real-time monitoring of product lifecycles empower manufacturers with insights into why and how products are being used. This enables usage based business models – usage-based warranties or ‘pay per use’ service packages, which are more predictable for servicing and less expensive to maintain. Moreover, product usage insights provide manufacturers with knowledge into feature usage – which features are used the most and which ones are simply discarded; helping both the R&D and aftermarket team.

Operational Efficiency – Manufacturers that know the when and where of their products can capture information such as location and time of usage. These are critical to structure the aftermarket product and geographical hierarchy – for instance, how to allocate spare parts across multiple service centers.

Predictive maintenance – With remote monitoring and asset health scores manufacturers have a real-time picture of equipment health (system failures and anomalies) and can anticipate maintenance and upgrades, as well as optimize truck rolls (servicing and replenishment of consumable goods).

At mnubo we work with a major communication company that is using data-driven insights to improve its aftermarket servicing. The data analytics provided by the SmartObjects platform helped the company significantly reduce truck rolls by implementing a more efficient servicing schedule based on customers needs.

Manufacturers can package these insights to furnish end user insights, providing them with a potential competitive edge. For example, the manufacturer of a connected agro application, will package some of these insights to power  added value to the farmers. In the case of commercial equipment, some of these insights are packaged and sent to the building operations and equipment dealers.

Interested in finding out how mnubo’s SmartObjects solution can enhance your aftermarket strategy, request a free consultation today!