Insights from Frank Clary, VP for Sustainability at Agility

In only a few months, the COVID-19 virus has been responsible for tens of thousands of deaths, with cases in 180 countries. The global pandemic has overwhelmed health systems in highly-developed markets, including Italy and Spain. Informed by the devastating impact of the COVID-19 pandemic on more developed countries with strong health systems, the humanitarian community is coming to terms with what could happen in vulnerable countries in Africa, Asia, and Latin America, already challenged with weaker institutions and networks.

Cascading, systemic risk in vulnerable countries

The combined weakness of core systems – health, telecom, education, food, transport, and others – means vulnerable countries face what are called cascading risks. Upon actualization of one risk, in this case, a health system overwhelmed by a global pandemic, more systemic risks are actualized, leading to the combined collapse of core systems, and potentially complete societal collapse.

In a country with many poor and vulnerable citizens, governments have limited levers that they can pull to help prevent or slow community spread. Many people live day-to-day and risk loss of livelihood if they self-isolate. Many live in precarious, crowded situations where self-isolation is not possible. It will not be possible to control community spread of the virus in communities where individuals must work every day to survive.

A shortage of personal protection equipment (PPE), already an issue in many countries in Europe and North America, precipitously increases the infection rate of first responders. Once infected, first responders cannot conduct tests, contact tracing, or treat patients. With first responders incapacitated, the public health system is considerably weakened, which could increase infection rates and contribute to significant death toll.

Humanitarian supply chains  

In a humanitarian emergency, logistics is critically important for saving lives, and typically accounts for 75-80 percent of total spend. This crisis will be no different. The logistics challenge is particularly acute due to the global nature of this crisis, now that more than 50 countries currently restrict the export of medical supplies, including India, where a large proportion of the Active Pharmaceutical Ingredients (APIs) used in medicines originate.

Agility is working together with other logistics companies that make up part of the Logistics Emergency Team which supports the Logistics Cluster, led by the United Nations World Food Programme. The companies are creating a dynamic database of information that will be essential to ensure that the 40+ essential items on the WHO’s COVID-19 Disease Commodity Package get to vulnerable countries. The exercise includes data collection and analysis of 4 key factors critical for fast humanitarian response.

• Geographies of risk: which populations are most at risk of systemic failures?
• Export restrictions for countries that are producing essential items
• Import restrictions in vulnerable countries that apply to these essential items
• Capacity constraints for air, ocean and road freight from production countries to vulnerable countries

The sooner test kits, PPE and other essential goods can get to people who need them, the more likely these countries can manage the crisis before it gets out of hand. Agility is also donating warehouse space for storage of humanitarian supplies in Ghana, Malaysia and Dubai.

At the same time, Agility is leveraging its global network, and particularly relationships with suppliers and local governments in emerging markets to get up-to-date information on how the situation is changing. Agility’s COVID-19 Global Shipping Updates are maintained by a network of logistics service providers all over the world, offering information in real time from their countries, as the situation evolves.

A Call to Action: we all can help vulnerable countries respond to COVID-19

For this global crisis, what you do to build resilience in your community, your company, or your supply chain affects the quantity and availability of life-saving products for vulnerable countries. We must keep life-saving cargo moving. 

For logistics companies: share information that we can share with humanitarian organizations, particularly in terms of fast-changing export and import restrictions and available capacity

For shippers: collaborate closely with your freight forwarders, carriers, and others – especially for pharmaceutical industry. Sky-high air freight rates and capacity shortages are prompting players to go it alone, just when we need to work together to bring costs down and free up capacity. Collaboration between stakeholders can improve asset utilization, which could help bring costs down and overcome capacity constraints on some critical trade lanes.

For governments: governments need to ensure that exports of humanitarian supplies to vulnerable countries continue, especially to countries unable to limit community spread and to locations where cascading system breakdowns could lead to heavy loss of life and societal collapse. Catastrophe in vulnerable countries will prolong the global crisis for everyone. Particularly for those countries that are ramping up production of PPE and life-saving equipment, it is important to work with humanitarian organizations to consider how to ensure that humanitarian cargo is able to flow freely to vulnerable populations.

For individuals: self-isolate, and reserve PPE and medicines for first-responders who really need them to do things such as contact tracing, testing and treating patients. The faster communities recover, the more expertise, PPE and other life-saving commodities will be available in the global supply chain to reach more vulnerable populations.

The global trade system has a responsibility now to keep cargo moving in order to protect vulnerable populations. #keepcargomoving

Making every mile count

Revolutionizing logistics with digital freight matching

What if you could streamline your business, bolster productivity and slash your environmental impact?

Digital technologies are gaining traction in supply-chain logistics, unleashing a wave of efficiencies and unlocking multiple side benefits. In addition to boosting revenue and slashing operational costs, innovations like digital freight matching are reducing emissions, bolstering productivity and creating a more sustainable industry.

Using transport management software to match a vehicle’s capacity to nearby waiting shipments offers great potential, since lorries and trucks keep the global economy moving. In the US alone, they handle more than 70% of all freight tonnage.

Here are some of the key benefits offered by digital freight matching, which uses online and mobile technology to connect shippers who have cargo to drivers and trucking companies looking for loads:

1. Fewer empty trucks

Empty miles cost money. About 20% of the distance driven by US truckers is non-revenue generating, according to a report by the American Transportation Research Institute. Many industry experts say the actual number could be even higher.

By marrying the cargo to the truck as accurately as possible, applications that offer digital freight matching help eliminate these empty miles, boosting profitability while also lowering emissions and reducing the carbon footprint of the supply chain.

2. Better use of space

In the same way that they help to eradicate empty miles, digital freight tools can also make sure cargo space is being used in the most efficient way. Even experienced shippers can struggle to get the most out of the space on offer in each container and get the best return on investment.

Digital freight matching algorithms quickly calculate the optimal way for loads to be carried, helping drivers ensure they have cargo to carry in both directions before they set off – and all but eliminating the wasteful empty “back-haul.”

One company operating in Saudi Arabia offers a template of how this can work. There, 40% of trucks complete the return leg of their journey completely empty, costing the economy around $5 billion every year, according to the digital platform Homoola, which has financial backing from Agility.

“Knowing how big the inefficiencies were in the traditional way of doing things, we could see the enormous potential of a digital solution that made load-carrying more efficient,” Homoola’s co-founder Ziyad Alhomaid says.

3. Less time waiting

Using the technology in this way also cuts out the time drivers spend sitting idle while waiting for cargo. Connected systems facilitate planning that reduces loading, unloading and clearance logjams at ports and warehouses. In addition to a cost benefit, there’s a huge environmental upside, since an idling engine can produce up to twice as many exhaust emissions as an engine in motion. That releases a range of air pollutants including carbon monoxide, nitrogen dioxide, and other particulate matter.

4. More efficient fleets

Using digital freight matching technology allows firms to accurately estimate the numbers of vehicles and drivers required, not only for a given shipment, but also over a longer period. This enables them to right-size their fleets and driver pools, potentially saving significant amounts of money.

5. Less traffic on the roads

Cutting out unnecessary journeys reduces congestion and emissions. Any technology that helps reduce the number of heavy goods vehicles will have an instant environmental impact. In the UK alone, they are estimated to account for around 17% of greenhouse gas emissions from road transport and more than 20% of road transport nitrogen oxide emissions, while making up just 5% of all vehicle miles.

6. Paperless deliveries

Documentation associated with shipping often mounts up. Digital freight matching apps allow this to migrate to the cloud, saving time, money and energy, instantly cutting waste.

“Shipments often come with a lot of paper,” says Homoola’s Alhomaid. “We’re reducing this on the carrier side, as well as for shippers, and working towards a paper-free solution. It saves time, money, energy – and the environment.”

7. More transparent pricing

Technology can also aid price negotiations, letting both sides see a range of different prices, in real time, at the click of a button. Faster, more liquid transactions conducted via an app can be beneficial to both sides.

In 2016, US businesses spent more than $1 billion on logistics, much of which was procured in long-term contracts of more than six months, according to a report by the consultancy firm A. T. Kearney. Signing lengthy commitments is a financial risk for both the shipper and the carrier, whereas a more dynamic market – created by digital freight matching – helps to mitigate these risks because both parties have a better handle on fuel prices, surcharges, tolls, taxes, tariffs, driver’s rates and other costs that they will incur.

Such tools also improve transparency, visibility and comparability of pricing structures, and can be updated in real-time.

8. Stronger safety standards

In the same way that it bolsters pricing transparency, digital freight matching also gives better visibility to the documentation that’s involved in the industry and can help make the safety aspect less opaque. Driver certifications and safety records can be made easily accessible and readable on mobile devices. In time, distributive ledgers could also create instantly shareable records.

At any given time, for example, a shipper can see a truck’s location, have transparency over the associated costs, and gain insights into important points like on-time delivery. Certificates and records are accessible to all who need them, whenever they’re needed.

For Homoola co-founder Asim Alrajhi, this safety aspect goes together with enhancing quality control.

“It’s a fragmented market,” he says. “Things are done on the phone rather than digitally, and often there’s no quality assurance.” While digitalization is still at an early stage, the market in trucking is set to balloon to around $80 billion by 2025, up from around $11 billion currently, according to estimates from market research firm Frost & Sullivan, which also predicts digital freight brokerage will make up the lion’s share of that.

Once such technologies are adopted, they will improve predictability, speed, transparency and sustainability. This will ultimately result in the seamless delivery of any item, anytime, anywhere at a lower economic and environmental cost.

Originally published at the WEF Agenda blog on January 17th, 2019
This article is part of the World Economic Forum Annual Meeting

• Small businesses have global potential thanks to e-commerce.
• SMEs active on the internet export more than traditional businesses.
• Heightened economic activity can especially benefit women.

Globalization got a bad rap in part because, by sweeping aside barriers to the movement of capital, labour and goods, it was perceived to have favoured large corporate interests over all others.

With the unfolding e-commerce revolution, however, a fairer and more inclusive balance is reshaping the global business environment to provide more room and opportunity for small businesses, especially those headed by women.

E-commerce: small business accelerator

Today, small businesses – even one-person “social sellers” – can run as global entities thanks to the growing availability of inexpensive digital tools that allow them to source, ship, deliver, pay, collect and virtualize other key aspects of their operations. The fast-developing e-commerce ecosystem, which includes marketplaces, payment gateways and online logistics, is helping to reduce barriers to trade across borders.

Export participation rates for traditional small businesses (those that typically do not sell online) range between 2-28% in most countries. In contrast, 97% of internet-enabled small businesses export, according to the World Trade Organization.

Why is this a big deal? Because firms participating in global value chains see the strongest gains in productivity, income and quality of employment. A report by the World Bank points out that in developing countries like Ethiopia, firms that are part of global value chains are twice as productive as other firms. And in a broad number of emerging markets, companies that take part in global trade are also more likely to employ more women than others with more traditional, male-dominated business models. Female participation in the labour market, in turn, correlates strongly to societal gains in health, education and overall prosperity.

Put simply, e-commerce is creating economic employment opportunities for new sets of players. Amazon claims that the 1 million small businesses selling on its platform have created 900,000 jobs in the process. Alibaba’s Taobao, one of the largest e-commerce platforms in China, has 3,200 “Taobao villages” in rural areas where a significant percentage of the village is engaged in e-commerce transactions. No wonder then, that some non-governmental organizations and think tanks are touting e-commerce as a model for developing rural Africa.

E-commerce: gender accelerator

When it comes to the gender effect of e-commerce, the research is still emerging and much of the data is localized, but early signs are promising.

The International Trade Centre (ITC) has found that despite having less access to technology, women use digital platforms to their advantage. The head of the ITC says four out of five small businesses engaged in cross-border e-commerce are women-owned, while just one in five firms engaged in offline trade is headed by women.

Meanwhile, there is more and more evidence to show how e-commerce and digital technology are bringing women to the fore of global trade:

• A McKinsey study on Indonesia’s e-commerce sector found that women involved in online commerce generate more revenue than that contributed by those in traditional commerce.
• Taobao says 50% of its online shops were started by women, whereas only 3.7% of businesses across 67 other industries in China are headed by females, according to the South China Morning Post.
• The World Economic Forum says one in three Middle East start-ups is female-founded. And Cairo-based ExpandCart, one of the region’s most successful e-commerce enablement platforms, says that one-third of small businesses on its platform are owned by women.

Cross-border e-commerce is the fastest-growing segment of international trade, so all of this should come as welcome news for globalization’s critics and fans alike. More importantly, it can help change the two-decade narrative about opportunity, inclusion, fairness and balance in the global economy.

Technology and e-commerce are finally democratizing access to the benefits of global trade, helping globalization live up to its original promise of shared prosperity and growth.

Originally published at the WEF Agenda blog on January 17th, 2019
This article is part of the World Economic Forum Annual Meeting

• Sustainable trade will require the participation of emerging economies.
• Finding the right balance between sustainability and economics is crucial.
• The technology exists; the real barrier is changing existing mindsets.
• Eliminating avoidable emissions is a good starting point.

Getting to zero emissions in logistics is a daunting prospect. Developing zero-emissions fuels and vessels is a critical pathway forward, but this approach has its limitations. In a cost-driven industry, a high-cost, high-risk focus on zero-emissions technology may position many players in emerging markets as part of the dirty past – not the clean future. We need a pragmatic approach that balances high-tech practices with practical ones that offer a role for everyone. We can reduce avoidable emissions through more efficient supply chains, but we need to shift mindsets. That’s where we should take immediate steps while continuing the longer journey.

Without the willing participation of emerging market players, a sustainable future for global trade is at risk.

Trade is growing most and fastest in emerging markets, with the growth of import volumes into Asia’s emerging markets as an example. In 2018, developing economies accounted for 64% of seaborne trade. Engaging this majority of actors is essential for the success of the zero-emissions project.

At the same time, we need to balance the environmental with the social and economic aspects of sustainability. If we require investment in new vessels and bunkering infrastructure to participate in global value chains, some actors will simply not comply, and will be left out – and if a port or a country is left out, so are its small and medium-sized firms (SMEs). For SMEs in these markets, accessing global value chains is critical to achieving stable growth and creating jobs. Keep in mind that SMEs contribute over 50% to GDP and account for two-thirds of formal employment in many countries.

Even in mature markets, the largest industry players can’t agree on who should cover the cost of transitioning to a zero-emissions logistics industry.

Logistics is a highly cost-sensitive industry. Just consider that second-generation biofuels are commercially viable, but not available, because no one is yet willing to consistently pay higher costs to ship goods. When given a chance, only a handful of shippers choose the environment over cost. The industry consensus is that a global fuel levy will be necessary to incorporate the social cost of carbon into fuel costs – but action on this has stalled, because oil companies don’t think it’s fair that they shoulder most of the cost burden, even if that cost is ultimately passed on.

Will emerging markets be able to afford the transition to cleaner fuels?

Transitioning to new fuels will be expensive in the short term. Recent research by the Global Maritime Agency – due to be published in late January – estimates that out of up to $1.9 trillion in investments needed to fully decarbonize maritime shipping by 2050, only 13% is for ships. The remaining 87% would be for land-based infrastructure and production facilities for alternative fuels. The International Renewable Energy Agency says “any shift toward a cleaner sector will require important changes to port terminal infrastructure and operational equipment [see chart below], as well as daily operational practices”.

Consider coastal African countries, or Viet Nam, where newly-discovered offshore oil resources have the potential to drive considerable growth. How should these countries consider these potential assets in a zero-emissions future? Should they not plan to benefit from their natural resources? Should they, instead, invest in port infrastructure for zero-emissions fuels that they will likely need to import? Is that fair?

The industry should mobilize around practical, system-level approaches to address avoidable emissions across supply chains.

No matter what the fuels of the future will be, it will be useful to reduce the total amount of fuel needed to power global trade. More fuel-efficient transport modes, supply-chain optimization and operational efficiency should be prioritized for their emissions-reducing potential. These solutions are not, and cannot be mode-specific, but must address global logistics as a system.

To address avoidable emissions, data-informed optimization across modes and supply chains deserves more industry attention.

Avoidable emissions are embedded into inefficiencies at every step along the supply chain. It’s tough to measure their contribution to overall transport emissions, but the share could be substantial. Consider that in many markets, sometimes more than 40% of trucks on the road at any given time are moving empty, and a much greater percentage are underutilized.

Beyond individual shippers or supply chains, optimization across the logistics system makes better use of transport assets across a country’s distribution network, or back and forth along a trade lane. On a global scale, the containerization of US agricultural exports addressed the asymmetry of cargo flows between the US and China. Digital freight booking platforms, like Cargo X in Brazil, can drastically improve asset utilization, reducing trips, kilometres, costs and emissions. In the US, when Ocean Spray and Tropicana, two fruit juice competitors, collaborated to enable sharing of empty refrigerated rail boxcars, both parties reduced transport costs, and Ocean Spray’s emissions were reduced by one-third.

The barrier isn’t tech. It’s mindset. How do we shift it?

Logistics is full of myriad actors with high levels of interdependence and competing interests, and this drives down costs. Fierce competition leads to such low prices in road freight that often it is cheaper to send a dedicated truck less than half full than it is to use a small freight carrier. From this baseline, how can industry players work together – in ways that preserve competition – for incremental environmental gains?

First, emissions should be a measured key performance indicator against which supply chain performance is evaluated. For example, some shippers have instituted an internal carbon price. Other sustainability performance rankings can help, both internally and for third-party service providers, but we must be careful to avoid the proliferation of varying questionnaires, and include incentives to improve environmental performance. Immediate exclusion of carriers that can’t meet high environmental standards won’t shift behaviour, and may bankrupt smaller players.

Second, we need to amplify the message about the business case. Logistics services providers can use their visibility across supply chains to identify collaboration opportunities and estimate cost and emissions savings, so shippers can visualize lost value. We all must be retrained and our data systems redesigned to actively look for these opportunities. When collaboration is successful, we need to transparently communicate these stories to clarify what’s possible and set higher environmental aspirations.

Reducing avoidable emissions alone won’t get us to zero. But this approach is open to everyone everywhere, starting now, and it can save fossil fuels in the present, and open the door to zero-carbon fuels in the future.

How to integrate new technology into your supply chain

Let’s assume you’re sold on the promise of the digital supply chain. A brave new world awaits if you commit to best use of rapid technological advances. The big question now is how to integrate these innovations into your business.

In our Guide to a Digital Supply Chain, we outlined why an agile approach, based on scalable pilot programs, is essential to evaluating new technologies in a way that is fast, efficient and cost-effective. Here, we will show what that looks like in practice.

Choose your evangelists

Choosing your team is just as important as deciding which technologies to test. The right people will have a mix of the technical knowhow needed to exploit the technology, a broad understanding of how the business operates, and the emotional intelligence to collaborate and communicate effectively with stakeholders.

This is a rare combination – people who possess those traits are to be treasured. More likely, you will create a small team whose members collectively bring these traits. Ideally, this team will represent a cross-section of your business, so that each member approaches the pilot with a different set of questions and priorities.

The job of this team is to evangelize change, so you need personalities excited by change, rather than team members who see change as a threat. If a pilot shows promise, you need people who can spread it wider, scale it up, and convince reluctant colleagues of its benefits.

You will want a mix of subject matter experts, operational personnel and systems integration specialists. Ask yourself what contributions and expertise you will need not just to run a pilot but also to evaluate its success, and then select accordingly. Consider also whether your choices will be able to cope with a fast pace of work in addition to their normal day jobs, and whether they have the interpersonal skills to work well with partners.

Small is beautiful

There are many reasons to keep initial pilots small – starting with the cost. Very few companies can afford unlimited R&D spend, and large-scale trials are expensive. The point of an agile, empirical approach is to try many things to see which work best, so a series of smaller, cheaper tests will tell you a lot more than a complex and expensive pilot.

Small pilots are also easier to integrate into the normal running of your operations, by limiting disruption, and the number of people involved. Change is hard for most people, so the fewer who need to have their daily routines changed for an experiment, the less resistance the pilot team will encounter.

Small pilots can also adapt quickly to different variables. For example, it might become clear very early that the particular IoT device you are testing to track consignments isn’t accepted on your preferred air cargo partner. A small pilot involving one customer’s deliveries could experiment both with changing IoT devices and with trying a different airline with limited ramifications.

Learning by failing

Most successful pilots can start small, then scale up. But you will also learn from the pilots that fail.

Embracing failure may not come naturally, but it is essential. The simple fact is that many, and perhaps most, of the pilots that you launch will run into serious obstacles. The teams will need to decide whether to persevere with the current solution, try again with a new approach, or move on to the next project. Remember the wisdom from the old ballad “The Gambler” by Kenny Rogers: “You got to know when to hold ‘em, know when to fold ‘em, know when to walk away, know when to run.”

Honest appraisals of why a pilot didn’t work will reveal a great deal about both the technology and the way your own organization is operating. All the knowledge gained should be shared and factored into the design of future pilots, in a constant iteration. Work out in advance how to capture what has been learned. A comprehensive debriefing process is essential.

Failure isn’t final. In any debrief, you should ask yourself whether an unsuccessful pilot is worth trying again and, if so, when – for example, when the technology reaches a certain price point or when a supplier’s or customer’s technical sophistication reaches a certain level.

Picking your partners

In the supply chain, no improvement can be made entirely in isolation. How your suppliers and customers adapt to the changes you make, and vice versa, will determine the success of the chain as a whole.

In Agility’s experience, collaborating on pilots is a win-win. But your partners need to share common goals and agree the following questions: What problem are we trying to solve? How much do we want to invest in finding a solution? Are we prepared to walk away without recrimination if the pilot is not a success? How far are we willing to share what we have learned with the other parties?

If the answers to those questions don’t match, then this might not be the right pilot.

It is also important to run pilots with different types of partners – something that worked well with a local family business might not scale up when applied to a large corporation. Agility collaborates with the full range: from an IoT cold storage pilot with a small firm specializing in one particular cargo in one market, to trials of blockchain with IBM and Maersk.

Don’t rest on your laurels

An experiment doesn’t end when a pilot shows promise. In fact, that is when the hard work begins – working out how to scale the pilot up and what other aspects of your business it can be applied to.

Constant experimentation can be draining, so communication is vital to bringing your workforce with you on your transformation. Strong leaders need to articulate why innovation is necessary, explain the journey, and inspire people to believe that the gain is worth the pain. But they also need to listen to concerns such as increased workload or a fear that their jobs may disappear as a result of the new technology. Anticipate these concerns and have a plan – the hardest part of getting new technology to work is people.

What success looks like

To judge success or failure, you need clear KPIs agreed in advance. A pilot may work in an operational sense, but will you actually extract value from the technology? What are the implications in terms of costs, revenue, customer satisfaction, staffing levels etc? Defining these parameters in advance will stop people getting carried away by a shiny new toy that may not be as cost-effective as it appears.

At Agility, we are constantly running pilots. We evaluate not only the four core technologies that we believe are at the heart of the digital supply chain – blockchain, Internet of Things, Robotic Process Automation, and Data Science [link to each article] – but a watchlist of 16 technologies, ranging from machine learning and the Cloud to 3D printing, virtual reality, autonomous vehicles and drones.

The template for every pilot is the same:

• First define what success will look like, by identifying the key business outcomes we are looking for
• Analyze exactly what we did, and what we found, at each stage of the pilot
• Decide on the next steps, who will be responsible for carrying them out, and the timeframe
• Identify the risks encountered on the way, and what can be done to mitigate them

Using this scientific approach, you can find the technologies that will give you the competitive edge to thrive as the digital supply chain becomes a reality.

Data science can predict the future

The car you drive is the product of one of the most complex logistical endeavours ever attempted. Tens of thousands of components and raw materials criss-cross the world to get to the right place at the right time for each vehicle to roll off the production line.

Holding spare stock costs money, so manufacturers prefer to rely on steady supplies of parts that are delivered exactly when they are needed. But the “just-in-time” model that underpins the automobile industry is vulnerable. Unexpected delays can have far-reaching and costly knock-on effects all the way along the supply chain.

The old saying that “for the want of a nail, a kingdom was lost” resonates in an industry where the want of a container of ball bearings can do serious damage to an automaker’s bottom line. But what if the company shipping that container knew that the usually reliable route would take too long this time, and automatically switched it to a quicker alternative?

Any tool that can predict when and where delays might happen, and work out ways to avoid them, will be extremely valuable. People cannot take into account every single one of the extraordinary number of variables affecting a sophisticated supply chain. Data science can.

What is data science?

Data science involves analyzing information from the past and present, and using it to predict the future. And it isn’t new. Individuals and companies have long used ledgers, spreadsheets and computers to identify trends and spot potential problems and opportunities.

But the digital revolution is allowing data science to grow beyond anything seen before. Technologies such as the Internet of Things (IoT) are providing unprecedented quantities of data and track goods in real time as they move along the supply chain. Blockchain allows companies to trust that the data they are using (for example that a product has left a warehouse) is genuine and secure. Robotic Process Automation, or RPA, is eliminating errors from the data, guaranteeing its accuracy.

The result is data that gives a very detailed picture of the world. Using machine learning, computers can sift the information, looking for patterns. When a pattern is repeated often enough, it can be used as a guide to what is likely to happen in the future.

Why does it matter for supply chain?

Uncertainty is damaging to every part of a supply chain. But for shipping companies themselves it can be fatal. Competitive pricing depends on correct estimates of the costs incurred. If you estimate too high, you risk being outbid. If you estimate too low, you will lose money on the delivery.

Reputation is extremely important to shipping companies. Customers rely on the promises we make in order to run their businesses. If those promises are broken, the crucial bond of trust is weakened. As supply chains become ever more sophisticated, data science will be essential for accurate pricing and ensuring that the promises made will be kept.

Although cost and speed are the decisive factors in many deliveries, other considerations are becoming more important too. Political and economic volatility make the security of a supply chain ever more important. An increased awareness of the environmental cost of transporting goods means that emissions and carbon footprint are becoming key factors in deciding routes.

Data science allows shipping companies to account for new pieces of information, such as a change in a security situation or new environmental regulation, much more quickly. The same reaction speed also means new markets and routes can be evaluated sooner.

Opportunities…

Knowing what the optimal route will be is one thing. Acting on that information is another. This is where artificial intelligence (AI) can play a role.

AI is the use of computers to react to data in the same way a human would. If a warehouse manager knows that a spilled load has caused a logjam at the site entrance, he might want to alert incoming trucks to postpone their collection, and warn the next link in the chain to expect a delay. But will he have the time to call each driver while he’s sorting out the spill?

AI systems can be programmed to immediately alert all the relevant links in the chain. A truck that was due to collect from the warehouse can be diverted to another delivery until the site has been cleared. The aircraft that would be waiting for its consignment can be loaded with an alternative cargo.

AI could also work out a new route for the delayed consignment that falls within tailored parameters. When does the delivery actually need to be at its final destination? Is it a perishable good that means speed is paramount? Or is a low carbon cost the most important factor?

The efficiency dividend of this kind of AI could be enormous. Avoiding bottlenecks in real time will ultimately drive down the cost, improve the speed, and mitigate the environmental implications of the entire logistics and supply industry.

…and challenges

To make the kind of AI described above possible demands a high level of integration and interoperability. Data from multiple sources needs to be stored in a way that is accessible to all the relevant parties. This requires common standards and procedures so that different systems can effectively talk to each other.

The question of data ownership is controversial, and has not yet been resolved. Who, if anyone, can own the data? Who decides who can use it, and how? For example, take the case of tracking a shirt with an embedded IoT device from factory to retailer. Is the tracking data owned by the owner of the shirt? When does ownership of the shirt switch? Or does the data belong to the shipping company that is actually doing the tracking? Can the shipper use it to create proprietary business models? What happens to the data if the factory switches shipping companies? And whose rules apply in trade routes that span multiple countries?

These questions can only be answered as part of a broader global discussion. In the meantime, companies should ensure that they are compliant with data regulations that apply to any country jurisdiction they do business with. The EU’s GDPR laws are increasingly being seen as a gold standard that other countries will follow.

The final challenge is how to ensure AI responds in the right way. It is possible for computers to find patterns in data that are circumstantial, and have no predictive value at all. That means AI systems need to be monitored and evaluated.

Where now?

Data science is already playing a leading role in designing, managing and monitoring supply chains for bigger companies. Cloud computing is quickly making the technology cheaper and accessible to all. Shipping companies like Agility are already integrating advanced machine learning and AI into end-to-end services that are affordable for any customer, for example with our Shipa brand.

The data science revolution isn’t coming – it’s here already, and everyone can take part.

What we are learning

The greatest impact we’re seeing so far is in risk management. Until now, shippers have been using data to manage their “exceptions” – those instances when something in the supply chain goes wrong.

The next frontier is predictive analytics that allows shippers to address problems before they occur. That includes demand forecasting based on social media trends, consumption figures and other data to remove spikes and troughs in the supply chain and eliminate inventory bottlenecks.

Reaping the rewards of Robotic Process Automation

Two ships carrying identical cargoes have just docked at a busy port.

One shipment experiences the usual delays and frustrations. A customs declaration for one container mistakenly refers to 1000 units rather than 100. One item of cargo has the wrong safety certificate. Some of the delivery addresses are incorrect, leading to confusion with the truck dispatchers. One consignment has the wrong parts because somebody misread a decimal place.

The mistakes are eventually sorted out, but it takes time and money.

The second shipment clears the port with no errors. All the information is 100% accurate. Why? The supply chain has been managed with robotic process automation.

What is robotic process automation?

Robotic process automation, or RPA, does not involve robots as they exist in the popular imagination.

RPA is the use of software to carry out repetitive tasks that we do on computers. Increasingly, it is having a dramatic effect on costs, productivity, and accuracy.

The supply chain involves a vast amount of paperwork and manually entered data  – emails and digital forms. Purchase orders, invoices, cargo manifests, customs declarations, delivery dockets, warehouse inventories – all necessary documents to ensure that the right package gets to the right place at the right time, in line with all relevant regulations.

Inputting data and generating the right documents is time-consuming, monotonous work. When people do the same task again and again, they inevitably make mistakes – because they are tired, bored, overworked, or unmotivated.

But machines don’t make those mistakes. Rules-based, repetitive work is ideal for a computer. It can carry out the same task 24 hours a day, doing exactly what it has been programmed to do without errors.

Why does it matter?

Businesses are under constant pressure to reduce overhead. Hiring people and training them on complex IT systems is expensive. When the work those people are doing is largely drudgery, it doesn’t just lead to errors: It is a waste of a valuable resource – the skills, talent and experience of that worker.

RPA can free employees to do more of the things that humans excel at and computers don’t: problem solving, reacting to unexpected events, creative thinking, and dealing with other people. Individual employees are not only more productive, but they experience greater job satisfaction, and are less likely to leave for other jobs.

Studies have shown that robotic process automation can make back-office operations up to ten times faster, and cut average costs by 37%.  

Opportunities…

Many back-office jobs have been outsourced to external providers in an effort to minimize costs. But the efficiency savings of this trend are tailing off, partly as a result of growing wages in many of the countries where jobs have been transferred. Outsourcing the work also involves reputational risk: mistakes and poor-quality service by external providers and third-party contractors can have a damaging effect on a company’s brand.

RPA gives companies the opportunity to bring much of this work back in house. Improved customer service can pay huge dividends in supply chains where trust is a significant factor in deciding who to work with.

As the accuracy of data improves, more can be done with it. Combining RPA with data provided by technologies such as the Internet of Things (IoT) will allow companies to build highly accurate models of supply chains. Gaps in the market, and potential problems, can be identified, Companies which make the right use of this data will have significant competitive advantages.

…and challenges

Designing an automated process for a particular task using a particular interface is relatively simple. But when different IT systems and interfaces are used, making sure that one program can understand the data provided by another is more complicated.

Even within individual companies, IT systems can vary widely. The warehouse may be run on an entirely different operating system from the accounts department. In a complex supply chain with multiple stakeholders, this problem is amplified dramatically.

For RPA to achieve its full potential, systems need to be integrated enough to allow data to be transferred seamlessly from one end of the chain to another. This means companies must consider what systems their partners use. Compatibility will be a key factor in any decisions about upgrading systems to avoid expensive mistakes.

Robotic processes will do exactly what they are told to do with the data they are given. Although more sophisticated systems can spot anomalous information, there will always be a need for people to monitor and improve processes to ensure the desired outcome.

Where now?

RPA is already being used across the industry. But in many organizations, it  is deployed in silos. Many companies have already automated their invoicing, and also their delivery operations. But most have done so separately – the two systems don’t work with each other.

Agility is looking to integrate these processes all the way along the supply chain. End-to-end services like our Shipa brand are designed to make logistics easier and cheaper. This kind of business is ideal for RPA – ensuring the right goods get to the right place with the minimum of fuss.

What we are learning

At multiple points in the supply chain, the movement of freight is still reliant on manual data entry. But even limited deployment of RPA is exposing how those points so often become points of failure.

The most rapid adoption of RPA to date involves forwarders and carriers using it to automate event tracking and to bridge gaps between systems that require data transfer. Watch for faster, broader take up as the heavy cost of continued reliance on manual entry becomes clearer.  

Warehousing is in the midst of a tech-driven revolution as companies race to identify and adopt emerging technologies that cut costs, optimize operations and improve overall supply chain efficiency. In some of the largest economies and companies, warehouse drones and robots already have been employed.

It’s not just logistics giants who are adopting innovative tech-based solutions. With the cost of automation falling, increasing numbers of SMEs and startups are investing in these efficient technologies. The top nine technologies shaking up the traditional warehousing scene:

1. Drones

Small maneuverable drones are appearing in warehouses as companies around the world seek to automate inventory and asset management. With stock stored up to ceilings as high as 12 meters in many warehouses, hard-to-reach barcodes have traditionally meant hours of labor using equipment such as forklifts and ladders. Scanner-carrying drones increase speed and accuracy by navigating warehouse shelves and taking automatic registry of stock. RFID tags can be read and located through cameras from a distance of 10m. Still needed are advancements that allow numerous drones to navigate tight spaces without colliding.

2. Robots

Robots are a game changer. They are programmed to guide themselves and to pick and pack orders into waiting carts or trucks. Some warehouses have already made the shift to full automation through use of robots. The distribution warehouse at online British supermarket Ocado uses thousands of robots to pack groceries into individual boxes. The robots run on complex algorithms that teach them where to pick up inventory and guide them to the exact grocery bag to drop it into, all while making sure that they don’t collide as they roam around filling orders.

3. Better Batteries

Batteries might not seem directly linked to warehousing, but they can power the machines that facilitate warehouse operations. So how can the latest innovations in battery technology advance warehousing?

Advancements in lithium-ion power cells have created impressive battery lives that can last up to ten years before needing to be replaced. Tesla’s latest batteries focus on alternative and affordable energy sources, drawing on solar power and energy from nearby power grids. Just think how powerful, efficient and cost effective robots, electric forklifts and other warehouse machines could be if they utilized these battery technologies. Heating and cooling warehouse space can consume large amounts of energy, so using improved batteries to power these systems could also mean significant savings on this front.

4. 3D Printing

3D printing could shake-up the entire global supply chain by bringing manufacturing closer to consumers and other end users. Take the example of auto parts now made in Asia for vehicles assembled in Mexico and sold in the United States. Production of some parts is likely to move closer to the market to cut down on shipment times and costs. 3D printing could reduce costs associated with complex trade and customs red tape for vast amounts of goods, because they could just be printed on demand near their final destination.

5. Automated Guided Vehicles

Automated Guided Vehicles (AGVs) differ to robots because instead of operating more autonomously they follow guided routes around warehouses. A huge advantage of AGVs is that they replace forklift trucks, so it’s not necessary to change the basic configuration of a warehouse. AGVs are also designed to come to a safe stop if they run into anything. This increases efficiency as AGVs can run continuously without breaks. AGVs are expected to become practical in even the smallest distribution centers, such as those of SMEs, as their cost continues to decrease.

6. Cloud Technologies

As with other industries, cloud storage is revolutionizing the productivity of warehousing as the instantaneous and self-updating systems cut down maintenance, infrastructure and the labor costs associated with the upkeep of management systems. Cloud technologies are also user-friendly and can be used by all employees, leaving companies less vulnerable if highly-skilled tech workers move on.

7. On-demand Warehousing

The “uberization” of warehousing – on-demand warehousing – is an emerging way of buying warehousing services and space on a pay-per-use basis. This method of warehousing gives customers more choice and flexibility over location, cost and supplier, either as a complete substitute to owning warehouses, or as partial replacements when new warehousing locations become necessary. The biggest disadvantage logistics companies face when adopting on-demand warehousing is that they’re exposed to fluctuating market rates for space, which is often overpriced in locations near ports, airports, rail spurs, major roads and urban centers.

8. Internet of Things

Internet of Things (IoT) technologies are not new on the logistics scene, and devices such as wearables, sensors and radio-frequency identification tags (RFID) are already used in many warehouses. By communicating relevant information to other IoT devices, the technologies reduce human error and the need for manual labor. Warehouse managers also get real-time visibility of order fulfillment, allowing them to process goods more efficiently.

Security concerns have blocked some of these advancements from reaching their potential, but a number of emerging technologies are being developed to enhance the safety of applying IoT sensor technology to large logistics operations. Microchips that allow more efficient encryption are one of the innovations that will ease security concerns about adopting the IoT in warehousing, and drastically increase efficiency in the future.

9. Composite Panel Technology

Clever developments in the construction and maintenance of warehouses are set to optimize insulation, air-tightness and durability through the use of new materials in composite panels. The latest panel technology can improve warehouse energy efficiency by around 20%. The cost and emission savings will be especially important in cold-storage facilities such as chilled and frozen food warehouses, where maintaining the correct temperature requires significant resource.

Composite panel technology is set to have global impact on the logistics supply chain: not only does it increase sustainability, it can also decrease warehouse build time and costs by one fifth.