Value-led engagements in practice: Case Study 1

Using predictive maintenance IoT solutions to reduce downtime, improve the customer experience & create new revenue streams

What was the problem?

New advances in technology are causing the shipping industry to change at an alarming rate, lowering the barrier for entry for new entrants and rapidly making the shipping industry much more heavily saturated with competitors.

This business in the shipping industry was experiencing lengthy periods of downtime for their product offering as they were unable to diagnose issues quickly or accurately. Issues took a minimum of 2.5 hours to diagnose and up to weeks to resolve due to repeated specialised nature of engineer site visits required to assess the problem and length ad-hoc back-and-forth communication between the on-site engineers and diagnostic teams, meaning that their customers were left without service for way too long.

The leadership team knew that they desperately needed to develop a new predictive maintenance capability for their product that would allow them to monitor their solutions more efficiently to provide the necessary level of service required to remain competitive.

A predictive maintenance solution was identified as the best course of action as it would allow the company to “predict” ahead of time when the solution might fail. Additionally, by implementing the foundational data platform required to support the development of the predictive capability the business was able to move forward with their goal of offering an as-a-service offering for their customers, lowering the barrier to entry around large capital expenditures to attract smaller and niche customers.

What happened throughout the consulting process?

Initial data collection:

The consulting engagement followed a classic value-led approach and began by initiating a set of data collection exercises, developing an understanding of the stakeholder landscape, and hosting 1-2-1 in-depth user interviews with key stakeholders to dig deep into specific problem areas.

Design-led thinking workshops:

A series of design-led thinking workshops were conducted to help the client understand the exact needs of the end-user before designing a use case for the solution that would specifically meet their requirements. This allowed for the development of an in-depth understanding of the client organisation but was also particularly useful for fostering trust and deep stakeholder buy-in towards the new solution throughout the organisation. This was particularly important due to a strong legacy mindset of the client team.

Business case development:

An in-depth financial business case was also developed to support the predictive maintenance solution, to make sure this would be a worthwhile investment for the business. This allowed the client to see how much they could save operationally and how much new revenue they could potentially generate by developing this solution.

MVP development into long-term delivery:

The identified use case was delivered initially through an MVP pilot project that allowed for the successful demonstration of the solution into production, whilst the previous activities laid the foundation for the development of an incremental solutions roadmap to be delivered over time.

What was the outcome?

  • Reduction in issue resolution time from 2.5 hours to 0.5 hours.

  • Business case identified initial cost optimisation and revenue generation opportunities of over $7million.

  • Employees that were originally very sceptical were fully bought into the new solution and future technology transformation projects.

  • Identified as-a-service model that would enable the organisation to reach new customers and diversify revenue streams.

Charlotte Fuller is an award-winning digital transformation consultant. She helps her clients get to the heart of what their business needs, so they can create competitive, digital strategies that enable growth. Subscribe to her newsletter and never miss an update.

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