This article originally appeared in the January/February, 2018 issue of PARCEL


    The proliferation of ride-sharing platforms and on-demand delivery services poses a serious question to the parcel delivery industry: Can a similar crowdsourcing model be harnessed for final-mile distribution? We believe so. Based on the success of Amazon Flex and our own experience, it’s clear that when leveraged effectively, crowdsourcing can yield major operational benefits, particularly in small parcel delivery.

    Let’s dive deeper into the applicability of crowdsourcing up to the final mile of delivery, taking a look at the common misconceptions around the economics of the model, the key benefits of crowdsourcing, and how technology can solve the two largest implementation challenges — trust and performance level. Finally, we would argue that crowdsourcing should not be the sole domain of disruptive technology companies like Uber and Amazon. With the right mindset and investments in technology, carriers too can harness the gig-economy to better capitalize on the growing demand for drivers in the final mile.

    Tapping the Crowd

    When discussing final-mile crowdsourcing, we refer to a distribution model in which dispatchers

    outsource delivery routes to a large network of qualified drivers in the form of an open call, often through a technology platform. In other words, rather than solely relying on permanent employees or contractors to perform delivery tasks, dispatchers can expand their reach by tapping a crowd of available drivers for single-day tasks. The key to this model is that delivery tasks must be simplified and standardized such that even non-professional drivers can successfully complete them with their own vehicles without much trouble.

    While crowdsourcing is often associated with on-demand or point-to-point deliveries, the model can also be applied to scheduled, high-volume distribution. One company that has already harnessed this model successfully (and continues to expand it) is Amazon. Drivers who enroll and pass background screening on the Amazon Flex platform are assigned delivery routes of up to 60 parcels, which they complete using only their private vehicle and the Flex mobile app.

    Launched in 2015, Flex already has over 100,000 crowdsourced drivers, delivering millions of parcels daily in over 50 US cities (and, more recently, in seven new UK markets). If Amazon can harness the gig-economy to high volume distribution, why wouldn’t other carriers be able to do the same?

    What Makes Crowdsourcing Attractive?

    The Common Misconceptions

    There are two common misconceptions around the attractiveness of final-mile crowdsourcing.

    The first misconception is that crowdsourced drivers are generally more cost-attractive than professional independent contractors. According to this argument, since crowdsourcing effectively increases the supply of available drivers, most drivers settle for a lower pay to remain competitive in the marketplace. In reality, however, this is not always the case.

    In most US markets, crowdsourced drivers such as those driving with Uber, Lyft, or even Flex typically earn $16-$22 per hour. During hours of peak demand, at night or on weekends, ride-sharing drivers can expect to earn north of $30 per hour. Evidently, these rates are not necessarily lower than those of independent contractors who currently drive with most regional carriers or local courier companies. Moreover, due to the temporary nature of the crowdsourced employment (most crowdsourced drivers only drive in their free time or between jobs), crowdsourcing platforms often find themselves spending significant capital on acquisition of new drivers to combat the high driver churn. The benefit of the model therefore lies elsewhere.

    A second common misconception is that crowdsourcing is disruptive to traditional delivery businesses because it enables shippers to ‘skip the middleman,’ that is, bypass the operator and instead work directly with the driver. This, too, is an inaccurate statement; in principle, just like traditional delivery models, crowdsourcing platforms need operators to coordinate between customers, drivers, and consignees, and solve real-time problems. Crowdsourcing is not inherently ‘leaner’ than traditional delivery models.

    The truth is, that most cost advantages associated with crowdsourcing have little to do with the model itself, and much more to do with the superior technology that crowdsourcing platforms use. Uber and Amazon are able to skip the middleman because they automate large parts of their operations and rely on smart algorithms, instead of relying only on flesh-and-blood decision makers.

    The Benefits Lie in the Flexibility

    Contrary to common beliefs, the most significant benefit of final mile crowdsourcing lies in the incredibly flexible nature of this model; crowdsourcing platforms can ramp and up and down their capacity at a short notice, and more easily match supply of drivers with the fluctuating demand for deliveries.

    Amazon, for example, can instantly scale its final-mile fleet by posting more routes to its Flex app or by temporarily increasing the proposed pay to drivers (a concept it has borrowed from Uber’s surge pricing). Companies who leverage crowdsourcing therefore have a ‘winning card:’ they can quickly scale capacity and capitalize on business opportunities in times of high demand, without incurring the high costs and headache of hiring for temporary work. This is especially true during the holiday season, when demand for drivers tends to climb rapidly.

    A second advantage relates to the labor misclassification risk – which has become increasingly concerning for carriers who use professional (permanent) independent contractors. Compared with an individual whose daily work is to deliver parcels for the same company along the same route, crowdsourced drivers are “truly independent;” they are free to work with multiple platforms simultaneously and have greater control over their schedule. Therefore, compared with the traditional model, crowdsourcing may present reduced exposure to labor misclassification risks (although note that this question is far from being decided by the courts).

    Note that the benefits of crowdsourcing do not lead to the conclusion that companies should completely replace their existing fleets with crowdsourced drivers. After all, the cost of maintaining a large crowdsourced fleet can be cumbersome, and experienced delivery drivers are still valuable. Rather, delivery companies should use crowdsourcing as an effective and flexible means to complement their existing fleets and quickly ramp up when more capacity is needed, or to make deliveries for what we call the “micro-mile:” taking deliveries from a forward delivery consolidation point such as a neighborhood convenience or grocery store to the consignee – be it a home or a business.

    Overcoming Implementation Challenges

    Admittedly, the implementation of crowdsourcing in the final mile is not a straightforward one, although it is certainly feasible. It requires us to address two main challenges.

    Trust and Reliability

    Almost all delivery companies today rely on drivers with whom they have a continuous employer-employee or customer-contractor relationship. It is common to assume that such drivers are less likely than a single-task crowdsourced driver to steal, be late for work, or drop out without notice. Therefore, the first challenge for the implementation of crowdsourcing is to achieve satisfactory levels of trust and reliability.

    Companies like Uber, Lyft, and Amazon solve these issues by performing continuous background checks prior to and throughout the driver’s work. They leverage GPS tracking, robust chain-of-custody procedures, and real-time ratings and reviews that they collect from consignees, and they provide their drivers with strong incentives to refrain from any misconduct. These procedures can result in an even higher level of safety and reliability than those of traditional delivery businesses. Moreover, most consignees in the US are already familiar with the sharing economy concept and are seldom concerned about a non-uniformed driver showing up at their door with a package.

    Similarly, last minute drop-out can be largely prevented with proper incentives and timely check-in requirements. For example, Amazon requires its Flex drivers to check in on the app some 45 minutes prior to their scheduled route. When repeatedly failing to check in on time, drivers lose access to the platform. This way, Amazon has been able to increase its reliance on Flex drivers even during holidays or unwelcoming weather, when drivers are otherwise more likely to drop out.

    Performance Level

    The second challenge concerns the performance and efficiency level expected from a delivery driver. Professional drivers traditionally have had an advantage over crowdsourced drivers because they often repeat the same route and thus gain critical know-how: They learn how to avoid common GPS inaccuracies, where to park the vehicle, how to get into certain buildings, or how to prioritize commercial deliveries. This allows them to save valuable time en route – which ultimately also benefits their delivery company and the shipper. Most drivers need a few weeks to reach this level of proficiency.

    Critical to the success of crowdsourcing is therefore the ability to simplify and standardize these delivery tasks such that any crowdsourced driver could perform them almost just as well as a professional driver. Here, too, technology is the solution.

    Time for Technology Upgrades

    If crowdsourced drivers were given a paper manifest and expected to figure out the route on their own, crowdsourcing would never take off. One of the most important factors contributing to the success Amazon Flex is that it provides drivers with the most advanced technology to complete their routes while eliminating any opportunity for error. We believe that carriers can have the same capabilities.

    Dynamic routing, geofencing, online route book to correct any GPS errors, a photo database of all drop-off locations, and clear capture of any specialized services – such as cash-on-delivery (COD) or signature required – should all be part of a smart mobile app that provides drivers with easy step-by-step instructions. Live tracking, chat tools, and an instant settlement system can help operators gain control over any crowdsourced operation while removing unnecessary friction. The good news is that these technologies already exist in the market – and can be adapted for any kind of operation regardless of crowdsourcing. It is only a question of whether one is willing to make the investment, and there has never been a better time to make it.

    Conclusion

    Despite the proliferation of crowdsourcing platforms, traditional delivery companies are still best positioned to win in tomorrow’s final-mile space. Long accumulated operational expertise and on-ground volume consolidation give these companies a baseline cost advantage over disruptive “asset light” entrants. Adding crowdsourcing provides traditional carriers an opportunity to further leverage these capabilities, but it requires a change in mindset and a proper investment in technology. Those who will take advantage of this opportunity and put crowdsourcing to use will be best prepared to profitably capitalize on the massive growth that is projected in the final-mile space.

    Rick Jones is the CEO of Van Pool Transportation. Formerly, he served as the CEO of Lone Star Overnight, a regional carrier headquartered in Texas. He has over 30 years of experience managing large scale delivery operations.

    Itamar Zur is the founder and CEO of Veho Technologies, a technology and crowdsourcing platform for final-mile delivery. Veho is winner of the 2017 Harvard Business School New Venture Competition.

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