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November 13, 2019 New Financing Trend Increases Equipment Sales

OEMs leverage pay-per-use trends from the sharing economy to offer usage-based equipment financing in an effort to increase machine sales.

November 13, 2019

Original equipment manufacturers are taking the first steps to sell more equipment and combat market loss by offering usage-based financing to equipment buyers. The industry owes the birth of such a financing framework to the sharing economy, as its service-inspired business model challenges the future of OEM equipment sales.

Unlike traditional financing methods, usage-based financing, also known as pay-per-use financing, is similar to a conventional lease agreement, but instead of paying a fixed amount every month, repayment is calculated based on the equipment’s usage rate.

So instead of equipment buyers paying high upfront investments to acquire new machinery, buyers undergo a per-unit financing agreement that leverages smart contract automation and IoT technology to generate periodic, utilization-inspired invoices.

The win-win situation allows OEMs to receive the full purchase amount immediately without their books being affected, while their customers enjoy flexible payment options.

The Sharing Economy Inspires New Financing Methods for OEMs

An increasing number of industries are exposed to the sharing economy mega trend, where users prefer renting their products over purchasing them. The best example being the e-scooter mania where users pay per ride as opposed to owning scooters out-right.

From micro-mobility startups to macro-automotive behemoths, leading automotive manufacturers like Daimler Mobility and Hyundai now offer similar pay-per-use schemes where installments are based on actual kilometers covered, instead of traditional, fixed lease payments. These sales models accompany new flexible financing methods that permit the purchase of new equipment.

A wise move from the trucking business considering heavy-duty truck orders have reached their lowest level in nine years, with factory output expected to decline 22% by 2020.

While the heavy-duty truck industry shows early signs of pay-per-use adoption, more industries may be at risk of traditional sale structures failing to meet the evolving demands of modern customers. By offering service-inspired financing models, OEMs hope to achieve two primary goals:

  1. Lower purchasing barriers for existing and new customer segments to increase sales and prevent market share loss.
  2. Leverage machine usage data generated by service models to create smarter business intelligence.

Usage-Based Financing Removes Customer Buying Hurdles

Early adopting OEMs have begun pushing this flexible payment model because it helps their customers acquire new equipment with more convenience. Currently, buyers have trouble spreading the hefty upfront costs associated with a traditional purchase to coincide with money coming into the business.

Furthermore, manufacturers encounter negative cash flow, depreciation, and balance sheet effects, for example, when compromising scalability for burning a substantial amount of money during initial purchasing and ramp-up phases.

Usage-based financing’s potential lies in providing a layer of payment variability not yet achieved by any other service offering. These usage-based models help overcome purchasing hurdles that machine buyers encounter with its flexible and scalable design since installments are pegged to equipment utilization.

Machine users who do not have the required upfront capital that traditional financing calls for can leverage pay-per-use financing and enjoy flexible payment options, all the while maximizing their business’s performance.

Buyers who externally finance machinery with traditional methods are required to pay back the same amortization rate, regardless of their machine’s utilization. With usage-based financing, on the other hand, whether a manufacturer produces more or less for a given month, it’s debt payments are pegged to its production output. Thus the user can focus more on maximizing its production operations and stress less over meeting high production quotas.

Early adopting OEMs who leverage new fintech solutions to offer a more personalized and customer-centric sales strategy can achieve greater competitiveness, further market penetration, and overall growth.

Usage-based financing produces invaluable business intelligence

The industrial internet of things prompts new ways to collect, analyze, and share such data with third parties to add tremendous benefits to how each party conducts future operations. The unique data generated from pay-per-use financing models are invaluable to the future success of OEMs and equipment users alike.

When properly analyzed, OEMs can develop more in-depth insights into what causes machine downtimes and uptimes, leverage predictive applications to better prepare for maintenance cycles, and introduce new products with disruptive go-to-market strategies. Similarly, manufacturers can leverage usage-insights to increase productivity, ensure high availability, and monitor maintenance cycles, to name a few.

The future of equipment sales lies in the hands of personalized financing

The usage-based business model has massive potential to innovate industries outside of heavy-duty trucks, such as industrial manufacturing. Other OEMs may encounter similar buying hurdles and will need to find new methods to meet their customer’s expectations. New demands inspire disruptive activities that have the potential to shape the future of industry 4.0, as we know it today.

About the Author
Paul Bruckberger is CEO and co-founder of linx4, an Industrial IoT Fintech company that specializes in delivering data-driven pay-per-use business models for corporate clients. linx4’s data management solution allows third parties to share end-to-end encrypted equipment usage data to enable more intelligent products and services. Paul holds a master’s degree in entrepreneurship and executive management and started his career at Red Bull, where he was responsible for sales and partnership.

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