{"id":26921,"date":"2017-11-15T23:00:37","date_gmt":"2017-11-16T04:00:37","guid":{"rendered":"https:\/\/digital.hbs.edu\/platform-rctom\/submission\/convoy-poised-to-win-the-startup-trucking-race\/"},"modified":"2017-11-15T23:36:25","modified_gmt":"2017-11-16T04:36:25","slug":"convoy-poised-to-win-the-startup-trucking-race","status":"publish","type":"hck-submission","link":"https:\/\/d3.harvard.edu\/platform-rctom\/submission\/convoy-poised-to-win-the-startup-trucking-race\/","title":{"rendered":"Convoy Poised to Win the Startup Trucking Race"},"content":{"rendered":"

Fragmented Market. Fragmented Data.<\/strong><\/p>\n

Convoy\u2019s truck sharing model will spur innovation from new entrants, but ensuing carrier fragmentation and adoption of Internet of things technology will require Convoy to help shippers produce actionable analytics.<\/p>\n

Control Towers<\/em>\u00a0<\/strong><\/p>\n

Shippers increasingly setup complex \u201ccontrol towers\u201d that analyze supply chain data from a multitude of sources to forecast supply and demand, diagnose failures and improve product design.[i]<\/a> Documenting, ingesting and identifying causal relationships across data from many sources is no simple task. For example, driver performance metrics, such as jobs per day or idle time, could reflect driver competence, tendencies of a dispatcher, site specific limitations (e.g. steep hills), product characteristics (e.g. hazardous materials) or numerous unknown factors.[ii]<\/a> Such complexities limit a control tower\u2019s ability to derive actionable insights from supply chain data.<\/p>\n

Internet of Things <\/em><\/p>\n

The rise of Internet of things technology usage among carriers increases the breadth and depth of available data. This presents exciting opportunities such as the ability to monitor travel circumstances (e.g. temperature or exposure to light).[iii]<\/a> However, each additional variable increases complexity and therefore cost of analysis.<\/p>\n

Sharing Economy<\/em><\/p>\n

Convoy\u2019s sharing model lowers carrier asset costs, inducing new entrants[iv]<\/a> that may possess differentiated IoT technologies. This may significantly increase the composition of available carrier data, as sharing is expected to comprise 15% of the trucking market by 2025.[v]<\/a> However, Convoy will need to deliver fragmented data from a multitude of carriers to shippers in a format that control towers can use. To achieve this, Convoy may need to tightly integrate with complex customer systems.[vi]<\/a><\/p>\n

 <\/p>\n

Convoy\u2019s Response<\/strong><\/p>\n

Convoy is turning this challenge into an opportunity by forming long term shipper partnerships and advocating for blockchain adoption across the industry.<\/p>\n

Long term partnerships<\/em><\/p>\n

Convoy formed a long-term partnership with Anheuser\u00ad-Busch centered around sharing real-time shipment data.[vii]<\/a> Working directly with this large shipper\u2019s control tower will increase Convoy\u2019s competency in delivering actionable data that aligns with the shipper\u2019s overall strategy. For example, Anheuser-Busch has already revealed that it aspires to set facility specific targets and increase trust with drivers via efficiency and transparency.[viii]<\/a> As the sharing economy continues to fragment carriers and IoT technologies become pervasive, Convoy will be uniquely poised to align new data sources with supplier systems and goals.<\/p>\n

Blockchain<\/em><\/p>\n

As a charter member of the Blockchain in Trucking Alliance (BiTA),[ix]<\/a> Convoy is priming the industry to adopt technology that can standardize transmission of data in a fragmented marketplace. Blockchain protocol eliminates the need for custom software integrations with each shipper and carrier. Rather each activity performed by any participant in the supply chain is recorded sequentially on a decentralized and distributed ledger.[x]<\/a> Furthermore, blockchain creates possibilities for smart contracts that leverage IoT data to automatically charge or pay carriers for bad transit conditions or delivery,[xi]<\/a> thereby reducing disputes.[xii]<\/a> By removing the need to integrate with many systems and embracing smart contracts, Convoy will enable shipper control towers to act upon fragmented IoT data sets.<\/p>\n

\u00a0<\/em><\/p>\n

Recommended Actions<\/strong><\/p>\n

Stay disciplined<\/em>\u00a0<\/em><\/p>\n

Long term partnerships with large shippers are likely to require significant customization. Wherever possible, Convoy should identify trends in feature requests and prioritize engineering resources around product improvements that can benefit its entire ecosystem over customizations that may only benefit a single customer. Doing so will help Convoy standardize the manner in which it collects and transmits fragmented IoT data to the benefit of all customers.<\/p>\n

Build IoT community<\/em><\/p>\n

Convoy should lead the transition to IoT technology within its carrier network by forming an IoT community. In a leadership role, Convoy can promote technologies that align with shipper priorities and integrate well with the sharing platform. Ingredients of successful community may include a digital forum for carriers, shippers and IoT vendors to share experiences, as well as a knowledge base of best practices. The literature suggests that a sense of community among carriers likely already exists as a result of the sharing platform itself.[xiii]<\/a><\/p>\n

Target clusters<\/em>\u00a0<\/em><\/p>\n

Increasing Convoy\u2019s presence within logistics clusters, or nodes where many carriers and other logistics service providers congregate, may catalyze the growth of Convoy\u2019s IoT community. Furthermore, it is likely to increase uniformity of IoT technologies adopted (and therefore data collected) within its network, as actors in clusters have been known to share information and collaborate.[xiv]<\/a><\/p>\n

Potential areas for further research include: 1) a deeper look into Aheuser-Busch\u2019s control tower and logistics operation, 2) limitations of blockchain and barriers to supply chain adoption, 3) insight into Convoy\u2019s product roadmap, 4) playbook for building digital communities, and 5) patterns of technology sharing within logistics clusters.<\/p>\n

(782 words)<\/p>\n

 <\/p>\n

[i]<\/a> Blanchard, Dave. 2014. “Supply Chain & Logistics: Digital Technologies Realign the Traditional Supply Chain.” Industry Week<\/em><\/p>\n

[ii]<\/a> Islam, Samsul, and Tava Olsen. 2014. “Truck-Sharing Challenges for Hinterland Trucking Companies.” Business Process Management Journal<\/em> 20 (2): 290-334.<\/p>\n

[iii]<\/a> Shanley, Agnes. 2017. “Real-Time Logistics.” Biopharm International<\/em> 30 (9): 47-48.<\/p>\n

[iv]<\/a> Deloitte. 2016. “The rise of the sharing economy. Impact on transportation space.” 1-12.<\/p>\n

[v]<\/a> World Economic Forum. 2016. “White Paper Digital Transformation of Industries: In collaboration with Accenture. Logistics Industry.” 1-31.<\/p>\n

[vi]<\/a> Ocicka, Barbara, and Graz\u0307yna Wieteska. 2017. “Sharing Economy in Logistics and Supply Chain Management.” Scientific Journal of Logistics<\/em> 13 (2): 183-193.<\/p>\n

[vii]<\/a> Konrad, Alex. 2017. “Convoy Scores A Win In The Trucking Startup Race With Anheuser-Busch Alliance.” Forbes.<\/em> October 17. https:\/\/www.forbes.com\/sites\/alexkonrad\/2017\/10\/17\/convoy-allies-with-anheuser-busch\/#7524de0d2502.<\/p>\n

[viii]<\/a> Cassidy, William. 2017. “Even largest shippers struggle with real\u00adtime visibility.” JOC.com.<\/em> November 6. https:\/\/www.joc.com\/technology\/even-largest-shippers-struggle-real-time-visibility_20171106.html.<\/p>\n

[ix]<\/a> Blockchain in Trucking Alliance. 2017. Members.<\/em> https:\/\/bita.studio\/members.<\/p>\n

[x]<\/a> Haughwout, Jim. 2017. “Blockchain: A Single, Immutable, Serialized Source of Truth.” Material Handling & Logistics.<\/em><\/p>\n

[xi]<\/a> Shanley, Agnes. 2017. “Real-Time Logistics.” Biopharm International<\/em> 30 (9): 47-48.<\/p>\n

[xii]<\/a> Kilcarr, Sean. 2017. “Blockchain Viewed as a Protective Measure for Trucking.” Fleet Owner.<\/em><\/p>\n

[xiii]<\/a> Mo\u0308hlmann, Mareike. 2015. “Collaborative consumption : determinants of satisfaction and the likelihood of using a sharing economy option again.” Journal of Consumer Behaviour<\/em> (14): 193-207.<\/p>\n

[xiv]<\/a> Rivera, Liliana, David Gligor, and Yossi Sheffl. 2016. “The Benefits of Logistic Clustering.” International Journal of Physical Distribution & Logistics Management<\/em> 46 (3): 242-268.<\/p>\n","protected":false},"excerpt":{"rendered":"

Convoy, the digital trucking service that matches shipments with carriers, can win the startup trucking race. 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