The logistics industry is experiencing a huge transformation with innovations that go from crowd-shipping to drones. The “uberfication” of logistics is now a trend hence more capital is invested in these new models relying on independent courier networks. However, there are still unsolved issues in the supply chain and in the case of emerging cities, lack of urban planning, infrastructure and technology.
Some companies are focusing their work on optimizing transportation — there are many startups centered in express deliveries using scooters and bikes. Nevertheless, in urban freight, most time and costs are spent on finding an unloading area and dealing with streets without names, not on driving — particularly in Latin America, where there is considerably time-consuming costly operations from the picking to the dropping step.
We’ve targeted inefficient processes affecting the whole logistics chain in businesses that go from retailers (brick-and-mortar), banks, telcos to supermarkets. Besides all the painful last mile delivery operations we encountered, there are still unserved needs involving stock replenish — even to “duty free” shops inside airports. Next, we´ll present some of those problems, but ultimately how we’ve solved them.
The following is a list of issues found:
- +1 hours waiting time to load in warehouses;
- Finding unnamed roads;
- Lack of coordination with recipients causing delays and customer service hell;
- Scarcity of parking, city logistics infrastructure and unloading zones;
Warehouses meet crowd-delivery
Crowdshipping might seem the panacea of city logistics, though executing a seamless operation with outdated warehouse systems (extreme as having no internet in their facilities) can become a hassle. If the correct tools are not used properly, companies could spend too much time labeling, sorting and routing shipments — plus the time loading large-sized products (appliances). Some companies can take up to 2 hours to authorize drivers to start their route — not a business for UBER-like systems where couriers will wait a maximum of 5 minutes at any given stop before marking it as undeliverable.
One key solution for a better picking process is to migrate from manual whiteboard routes scheduling — a common practice of warehouse and fleet managers — to an optimized route planning and consolidation software based in the geo-spatial data obtained from shipping addresses. Based on our experience you can reduce up to 2 hours by planning routes ahead or applying dynamic routing technology, while orders arrive within a specific time window. Interesting features provided in our software will match large-sized packages with available fleet capacity — an issue you will commonly find at office and home supply stores.
Consolidation and route creation is a game changer for crowd-shipping where trucks, vans and medium-sized vehicles play an important role to dispatch hundreds of packages per driver during the day. As a result, compensation per courier is higher thus prolonged crowd engagement and lifetime value.
Sadly, this solution is not easy to implement without solving the right data gathering problem we´ll talk about next.
Successful deliveries to streets with no names
Once in transit, drivers commonly need to use address references and GPS apps to effectively arrive to the customer’s doorbell, leaving us the task of providing the right geolocated information to the courier — here relies the most critical obstacle in Latin America, where even Google Maps has trouble finding unnamed streets.
While operating the logistics of small e-commerces and large enterprises, we found that the majority of them have a big trouble collecting the right shipping information from their customers — they rarely obtain it effectively and what they get is hard to convert into geospatial gold. Main sources of shipping information are: sales phone calls, in-store sales and online forms — typos and orthographic errors happen either when asking clients verbally or when filling online forms before purchasing. Such things as zip codes rarely work in emerging markets and geocoding a text full of ambiguous information won’t become a proper geolocation.
To solve this data problem that affects the scalable functioning of a crowd-shipping model, we rely in software that cleans, classifies and curates it; but most importantly in a community actively fixing all data collected on the field.
Turning dark data into useful information
Reaching the customer through an SMS text message or email (that includes a digital link to track their delivery) to invite him/her to follow the shipping process is essential to receive their feedback in advance. Customers are able to fix address issues and suggest local references to help couriers before they depart.
Customers want to pay for speed, but also for accuracy and planning ahead, reading their minds and anticipating with solutions. To create a new standard, we implemented engaging strategies (gamification) to harness the knowledge of the recipient, inviting him/her to participate and collaborate for a better shipping experience — in consequence, completing the missed data of the offline world.
On time vs right time
Real-time tracking is the standard but we wanted to go beyond that simple website that exchanges live information, adding end-user participation to fix the unstructured and wrong shipping information and creating a new solution that takes advantage of courier-customer (peer to peer) collaborative communication. These new chat tools make sense when we see that rich messaging is now Amazon’s default customer service option on mobile and that conversational commerce with chatbots is a trend.
Even though there are proven solutions that we commonly apply to avoid unsuccessful deliveries and unwanted returns (like parcel shops, lockers and neighborhood crowdsourced storages), these are not suitable for special operations requiring recipients to be at the destination for document signatures, photo proofs, and paperwork exchange with drivers.
In order to build a customer centric logistics solution we’ve got to create tools that can scale and enable collaboration among all members of the process. Instant communication with customers allows drivers to perform better in their deliveries — at the same time, enabling customers to ask questions, as well as give specific instructions — avoiding miscoordination and helping the system understand real-time data and common behaviors when two people agree to meet and fulfill a mutual interest.
Some of the results we’ve gathered, after a year of distributing this technology over thousands of retailers and e-tailers are:
- Decrease in operation costs and time-consuming tasks like dealing with customers’ phone calls asking where the delivery is and when will it arrive.
- Enhanced customer service in a more meaningful and personal way.
- Reduction of delivery time in a 20% after drivers get to collaborate and agree in time-space with recipients.
- 60% of risks reduction on failed delivery attempts.
Unloading zones provided by the crowd
Emerging cities have an additional component which impacts the scalability and proper execution of crowdshipping initiatives such as the limited provision of delivery bays and parking areas that increase the shipping cost.
Lack of information and accessibility to off-street parking zones, led us to the necessity of implementing a crowdsourced solution that involved not only our community of couriers but also parking owners — making it possible to map residential parking spots and commercial-dedicated parking with availability during off-peak hours. A merge of technological solutions and community management is imperative to harness “the wisdom of the crowd” — plus motivating that crowd to share knowledge besides their unutilized assets — making a democratized and smart model possible.
There’s plenty of undiscovered data independent drivers are able to collect on the field when delivering a parcel in a favela in Rio de Janeiro, a complex commercial area in Mexico City or a ghost town in Ecuador. Researchers assure that data gathering relies on resource-intensive field observations — a reason why our proposal is based on the information provided by mere participants of daily commerce activities (Shipper, courier, receiver) — thus becoming the keystone to build a urban logistics atlas.
Crowd-sourced solutions like WAZE, built on top of communities, marked the beginning of many others. However, as we state before, transit is not the only issue that affects on-time shipping. Building tools to get the right data from a strong community is the first step towards a big data and machine learning application.
In upcoming articles we will share further developments on how we are harnessing our community — showing present challenges of building a strong courier network, willing to collaborate with compromised discipline to use our technology. Finally, we will be able to analyze strategies executed to keep the right compensation scheme — widely different from Uber-like models as time goes by.
About Shippify :
Shippify is a technology company that uses sophisticated software tools on top of crowdsourced methodologies to connect vehicle owners with companies that need them to transport goods. Shippify currently operates in the main cities of Latin America, focusing its solutions in emerging markets, where the principle objective is to create an on-demand and cost-effective last-mile logistics answer that optimizes the supply chain.