How MPS providers can leverage an IoT maturity model

How MPS providers can leverage an IoT maturity model

September 23, 2019
Articles, Digital Transformation, Managed Print Services, Trends

Multi-function printers (MFP) have evolved into smart, intelligent, interconnected devices capable of interacting with multiple external systems. Managed Print Service (MPS) providers should exploit the wealth of data generated by smart MFPs to create new opportunities for innovation.

Smart MFPs are some of the oldest IoT devices on the network. Print manufacturers have long been using the data the devices and their inbuilt sensors generate to intelligently deliver remote and predictive maintenance. To date this has mainly been to optimise print device fleets and make recommendations to reduce wasteful printing.

As the print market continues to consolidate and devices become more commoditised, print manufacturers can differentiate themselves by delivering new services that go beyond the print infrastructure. In doing so they will deepen their relationships with customers and generate new revenue opportunities.

The connected and intelligent Smart MFP (Source: Quocirca)

Leveraging the IoT maturity model for MFPs

MPS providers should leverage an IoT maturity model, based on the following levels:

  1. Basic connectivity. Devices are connected and the data they generate is collected and stored
  2. Serviceability. Devices are remotely monitored and serviced. Once a product is connected its status can be monitored from anywhere. This can reduce field service engineer costs as well as making field service visits more effective. There are typically three main categories of servicing:
    • Corrective maintenance: basic monitoring enables technicians to respond to a failure
    • Preventative maintenance: maintenance can be scheduled based on monitored usage, reducing overall failure rate and downtime
    • Predictive maintenance: predicting errors that are likely to occur. This is substantially more effective than preventative maintenance because it also considers any anomalous behaviour of devices. Manufacturers who deliver effective predictive maintenance have typically invested in new capabilities such as big data analytics and machine learning.
  3. Intelligence: Not only is data analysed to provide business insights and predictions, devices are actively monitored for security purposes (for example detecting attempts to implant malware), for certain issues they may be self-healing as well as automatically interacting with the rest of the print and broader IT ecosystem.
  4. Innovation: Beyond a hardware sale, associated value-added digital services may be sold multiple times, representing new revenue streams and competitive advantage. This may be selling new document workflow services, providing value-added embedded apps, remote security monitoring and remediation services. In addition, sensor data is a rich information source that can be used to track product usage, understand user behavior, segment populations for targeted marketing and personalise customer interactions.
  5. New ecosystems: This enables the print infrastructure to be connected to other IT equipment within a building, but also to other systems across an organisation. The data gathered by a service provider makes it possible to remotely assess the condition of every piece of connected technology from anywhere. Furthermore, data from multiple customers can be aggregated anonymously so customers can benefit from each other’s experience in some circumstances, for example shared threat intelligence.MFP data could also potentially connect to smart building management platforms.For instance, the Connected Building Platform by Bosch Software Innovations provides an overview of energy consumption and energy savings for each piece of equipment, each floor, and the entire building and visualisation of presence data on the use of rooms; also as heat maps for optimizing building efficiency.

Today, most MPS providers are at stage 1, 2 or 3 of an IoT maturity model. Proactive service is provided, and some leading MPS providers use predictive analytics as the foundation for their strategic business reviews.

In order to differentiate their offerings, MPS providers must exploit the IoT analytics opportunity. This demands new expertise and competencies in business intelligence which should be built through a big-data talent acquisition strategy, driven either organically or through new collaborative partnerships.

Those that are able to drive innovation in their services by exploiting the wealth of data generated by smart MFPs will ultimately enjoy a clear competitive advantage.


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