Automated Spot Bidding: Maximizing Revenue for Freight Brokers

The logistic industry underwent many ups and downs, battered by pandemic-induced delays, lockdowns, and resource shortages. As a result, there were several shifts in business-as-usual to get stocks out as soon as possible and adjust to the new normal. Spot bidding, for instance, gained traction as many shippers tried to catch up with the lost time immediately after stringent lockdown rules were relaxed for a bit. As per reports, spot-market load postings have been up 176 percent.

What was supposed to be a unique opportunity for freight brokers to increase revenue with spot bidding became a major roadblock for many. Hence, shippers and freight brokers increasingly turned to Automated Spot Bidding to save their day.

What is Spot Bidding, and Why Automated Spot Bidding is Required?

A spot bid sale immediately follows items or goods offered for sale. Buyers bid on the offered items examined, rejected, or accepted on the spot to close the deal.

For freight brokers, nearly 80-90% of demand is generated through traditional EDI channels or direct customer calls. The freight business runs on a good relationship between freighters and customers. Hence, the bulk orders coming from these fragmented channels consume most of the sales teams’ bandwidth in fulfilling these orders. On the other hand, leads posted directly on consumer portals have a minimal conversion rate; yet 100% of them are spot loads garnering higher revenue and profit potential.

Sadly, these orders get neglected most of the time.

Automated Spot Bidding has the potential to scan millions of loads shared on customer portals, place competitive bids and increase revenues on untapped spot market loads without human intervention.

Challenges in Spot Bidding

From a freight broker standpoint, spot bidding is complex and time-intensive, involving too many human touchpoints. Hence, the entire process is rift with errors, compounding into thousands of other errors.

A few challenges and issues with legacy spot bidding are elaborated below:

Labour and time-intensive: The legacy spot bidding is manual, with spot bids on portals needing constant human monitoring and placing of orders manually. Freight brokers have to continuously monitor multiple shipper websites, figure out the characteristics of a load when it is posted, determine if they want to bid on it, create a competitive quote, and then bid on the shipper’s portal.

The process is rife with human errors: Handling bulk orders in a short window of time leave room for errors. In addition, due to heavy bandwidth, most granular nuances remain unresolved, thereby reflecting poorly on profit-loss statements.

Little scope for conversion tracking: In the absence of data, tracking the loads across portals and checking for conversions is challenging.

Increase operational costs: Too much dependency on humans add to operational costs for freight brokers and shippers. Moreover, ramping up the process with an additional workforce translate into more cost and higher subscription charges on multiple logins.

Volatile and dynamic market: With daily fluctuations in the demand-supply chain, businesses struggle to adjust to the changes intelligently.

Direct client conversations: Since most of the business is run on a word-of-mouth relationship basis, many freight brokers prefer direct client conversations over spot bidding. But unfortunately, this prevents them from getting the right price. Hence, revenue loss is a constant reality the freighters and shippers have to deal with.

Maximize the Potential of Automated Spot Bidding

The freight brokers, shippers, and bidders thus require an automated bidding solution as a new activated revenue generation engine. Simple Robotic Process Automation can efficiently address all the above challenges by keeping humans out of the loop. This approach will increase overall revenue, bid won rates, and gross margins.

An automated spot bidding system uses bots to scan millions of loads across customer portals, qualify them based on custom rules and goals, query the pricing engine or tariff to generate a good quote, and place competitive bids without human intervention.

Further, with a conversion rate of less than 10%, the bots can easily garner hundreds of millions of dollars without increasing overheads.

What is Automated Spot Bidding, and How does it Work?

Automated Spot Bidding takes the heavy lifting and guesswork from the human workforce. It sets bids automatically based on historical data to meet your performance goals and increase the likelihood of getting conversions.

In an automated spot bidding process, a bot will:

Gearing up for the Future with Automation

The global pandemic was eye-opening for businesses, especially freight brokers and shippers. Finding more use cases for automation has become imperative, as most competitors today are moving to digital freight brokerage solutions. The future of logistics can be streamlined, hyper-efficient, and connected by leveraging the power of automation. Automated spot bidding is probably the first step in that direction.

Giving Logistics Businesses the Boost of RPA

In a report about the impact of COVID-19 on logistics, the International Finance Corporation finds that, “the cost of logistics as a percentage of GDP can be up to 25 percent in some developing economies…Better efficiency in the sector can, therefore, boost competitiveness and stimulate economic growth in emerging markets.”1

This search for ‘better efficiency’ has been a hard one. It is here that logistics players are seeing immense value in Robotic Process Automation (RPA).

What is RPA?

RPA is the deployment and management of software robots to do repetitive tasks by mimicking human actions. For instance, a logistics company processes thousands of orders each day. This involves multiple steps such as order bidding, segregating orders, verifying details, scheduling, confirmation, etc. These can be a series of repetitive and rule-based tasks ripe for RPA.

In the logistics industry, especially, this can improve efficiencies significantly. Here’s how.

RPA in logistics: Areas of business impact

Process transformation

Do you need to send reminders? Update new information on multiple platforms? Check if compliances are up to date? Autofill forms? Collect and process documents? A good RPA tool can automate all these processes and more.

In fact, due to the COVID-19 pandemic, one of our clients faced difficulty in invoice processing and collections. Their process was that the client’s customers post invoices on internal/third-party vendor portals. To check the status of each invoice, the client’s staff had to visit each website/portal manually. This was time-consuming and led to a large amount of Daily Sales Outstanding (DSO), impacting the client’s cash flow. You can read more about how RPA helped the client in this case study.

Business continuity

An important part of running any enterprise is ensuring they have the resources for business continuity. This means knowing ahead of time when the stock is running out and performing necessary tasks to prevent it from happening.

RPA can take care of this autonomously. Since companies have a uniform process to initiate purchase orders, this part of the business is perfect for automation. An RPA tool can monitor the stock situation, raise alerts when it falls below pre-determined levels, automatically raise purchase orders and email them to the corresponding vendor.

Reporting and analytics

Every enterprise uses a wide range of tools and software for their everyday activity, such as ERP, CRM, stock management, fleet management, finance, accounting, invoice processing, vendor management, etc. Each of these tools holds specific information about the task they are performing. This causes two distinct problems:

A good RPA tool can solve both these problems. It can regularly evaluate if all the systems have the same updated information. It can either raise alerts to invite vendors/staff to update information. Or automatically update information across all platforms based on the single source of truth.

In addition, RPA can be a fantastic tool to consolidate information from across sources to enable analytics and dashboards. In the process, RPA can also be used to clean data.

Compliance management

Logistics companies are often liable for both internal and external compliances. Depending on the kind of products they transport, the number of compliances for each truckload can run into hundreds. This includes internal quality checks, local/national/international regulations, customs, health and safety measures, and so on. Today, most enterprises manage this compliance manually, taking up significant time, causing delays and inefficiencies.

A good RPA tool can take care of filling forms, collecting documents, filing proofs, identifying errors, and sending reminders for signatures without any manual intervention at all. This not only eliminates the bottleneck of the number of orders a company can manage in a day, it also dramatically reduces the loss of revenue due to errors or incomplete compliance filings.

Give your business the boost of RPA

As the logistics industry is reinventing itself for the post-pandemic world, digital transformation is growing to be extremely important. For the logistics industry, RPA has the potential to supercharge digital initiatives, accelerating outcomes and eliminating inefficiencies instantly.

Learn how AssistEdge can help transform processes across the logistics value chain.


Addressing Complexities in a Disrupted Consumer Goods Industry with Procurement Intelligence

Unexpected disruptive forces can dramatically alter the existing market status quo. The consumer goods industry is one such example that is on a constant roller coaster ride of disruption for multiple reasons, especially when it comes to the procurement and demand value chain.

Hence, more stress is given to timely identification of such disruptive forces before they occur by deriving procurement intelligence using the right set of tools and technology.

Why Procurement Intelligence is Important

As mentioned earlier, Consumer Goods companies mostly need a 360-degree overview of the procurement channel using the right technology set. The reason being, this particular sector is highly susceptible to changes. The chief procurement officers of CG companies have changed their perspective when hiring a new set of suppliers and sourcing vendors. Nearly 91% of CPOs agree that procurement must be more agile to respond quickly to market changes, wherein 65% of them expect more visibility in the supply chain that should extend beyond the Tier 1 suppliers.

However, cost savings remain a top priority with at least 78% of procurement leaders.

Even though automated procurement systems can very well address most of the needs and expectations of CGs, the smooth transition of the traditional approaches to implementing changes is ridden with many errors.

And the sole responsibility lies in poor data capture and other issues.

Challenges and Roadblocks in the source-to-pay (S2P) landscape

The entire landscape is rife with many roadblocks, a few of which are mentioned below:

Unstructured Data

Siloed data captured in different formats and inconsistent data mapping often fail to obtain actionable insights when needed on time.

Poor Visibility

Missing connections between internal and external insights make identifying and executing opportunities cumbersome. This restricts data visibility.

Execution Delays

Traditional procurement systems fail to offer the necessary intelligence and insights, especially procurement transactions. On top of that, execution silos, delays in information flow, and the lack of a feedback loop make execution unachievable.

Stakeholder-Specific Objectives

Varying stakeholders within the procurement and supply chain network have different and varied role-specific objectives, thus complicating matters further.

Move beyond legacy systems – The Next-Way Forward to Procurement Intelligence

End-to-end visibility into the supply chain and procurement cycle has become the need of the hour. The stakeholders and CPOs have realized that the next way forward is to leverage advanced analytics solution that delivers procurement intelligence.

This new technology doesn’t replace the legacy system; instead, it complements existing tools and technology already in place.

An effective spend visibility and analytics solution functions as a complement to CGs’ existing technology component with:


Procurement intelligence can help transform your business. Hence, a platform like TradeEdge can award the CG companies a 360-degree view of the entire demand-supply chain and take necessary measures based on procurement intelligence. This simple and user-friendly interface actionizes and amplifies procurement outcomes and yields great business results, from 5% additional savings, 50% enhanced visibility from curated insights, 25% higher productivity, and 20% leakage avoidance through periodic monitoring of internal and external risks.

As mentioned earlier, procurement intelligence is needed to predict timely anomalies such as changes in demand, procurement, supply chains, and so on before they become a major hindrance. However, the traditional approaches to capturing such data provided minimal actionable insights, resulting in significant disruptions.

Understanding the Power of Connected Automation

The sudden disruption in the traditional approach to business during the COVID pandemic was a glaring signal that the pandemic recovery would be digital. Soon after, business leaders were hit by the inefficient, traditional enterprise models. Companies are now looking at a more Connected Automation strategy. They need to implement autonomous operations with Intelligent Automation to keep up with the increasing digital competition.

Despite the conjoined efforts put by many to complete the transition, enterprises adopting Intelligent Automation struggled to scale and realize value from their automation investments.

How can enterprises scale their automation journey? What is Connected Automation, and how can it help?

Overview of the Current State of Automation Programs

Intelligence process automation (IPA) investments have accelerated within two years, with a projected $10.9 Bn spent in 2021 alone. Yet many failed to realize the full potential of this investment or earn a substantial ROI.

The inability to adopt Intelligent Automation strategically can be seen as one of the many reasons for such failures. Only 10-12% of enterprises have achieved a semblance of scale in their automation adoption initiatives. Selecting the wrong processes for automation is another reason attributed to enterprises’ inability to accrue the benefits of Intelligent Automation. Most commit to the error of focusing on ‘quick-wins’; instead, the best approach should be converting labor, time, and cost-intensive tasks first.

The Barriers to Scale Intelligent Automation

There will be various roadblocks and multiple challenges as enterprises move along the automation maturity curve. Such barriers can vary from the narrow mindset of people to their technology immaturity. A few such hindrances are mentioned below:

Implementing Automation in Silos: Large enterprises work through several overlapping but disconnected solutions that perform a single task but not necessarily together. They don’t work together, share information or serve any unified purpose. Hence, implementing Intelligent Automation in silos can be a significant hindrance to scaling its success across the length and breadth of the company.

Cost-focused Automation Approach: When automation is tactical or cost-focused, transforming the full potential of Intelligent Automation becomes difficult and fails to cater to larger digital transformation goals.

Knowledge and Skills Gap: Talent and skill unavailability or lack of idea readiness can pose a significant roadblock in full-scale Intelligent Automation implementation.

Lack of Contextual Intelligence :
Data silos or fragmented data scattered across unstructured documents or formats hinder the smooth transition of existing processes to automation.

Fragmented or Broken Processes: When business processes are broken or fragmented, automation implementation can fail to deliver expected outcomes. Also, implementing automation in silos deter proper sharing of information, which often results in wrong process automation adoption.

Automation Disconnected from Human Capital: In the absence of a human-centric holistic approach to Intelligent Automation, only a tiny percentage of employees can fully leverage the benefits of Intelligent Automation. Simply deploying automation to substitute machines for human workers reduces cost but does not translate into value.

What is Connected Automation?

According to experts, Connected Automation is the final state of Intelligent Automation, bringing people, processes, and data together. These are the core aspects of any operation.

Strengthening the Process Connect with Automation

Business processes are central to any transformation. But, process fragmentation poses a major barrier to delivering Intelligent Automation at scale. This happens when a unified workflow is absent in critical processes. Connecting processes can bring end-to-end processes into a
unified workflow and accelerate automation.

Deepening Data Connect with Automation

Data is another fuel for transformation. Unfortunately, poor quality or unavailability of contextually relevant data can be a challenge in scaling Intelligent Automation. Connecting data enables decision-making by unearthing relevant data for enterprises and unlocking insights captured in unstructured documents.

Widening People Connect with Automation

People are the heart and soul of transformation. Connecting people is all about democratizing Intelligent Automation for innovation and embedding it in the organization’s culture. When you increase the number of people involved in transformation, you expect higher speed, scale, and impact at a strategic level.


Sudden disruptions, unpredictable changes, and other challenges are becoming common in the business landscape. No one is immune to such changes. Nevertheless, such disruptions are carriers of immense opportunity, just as we had seen after the COVID pandemic hit the world.

However, leveraging Automation in isolated pockets will continue to inhibit its full potential. Hence, platforms like AssistEdge 19.0 can be the real game-changer for businesses trying to ride the change successfully.

How Automation and AI are Salvaging the Global Supply Chain and Making it More Resilient

If we consider all the significant innovations in human history, we might be able to see that quite a few are connected with global crises. For example, the world was introduced to penicillin, jet engines, and radar technology during World War 2. Likewise, the global supply chain network realized the importance of automation and new-age technologies like artificial intelligence and machine learning in the face of extreme disruptions following the pandemic.

How the Pandemic Impacted the Global Supply Chain?

It is expected that the world will be a lot different from what it used to be before the COVID pandemic engulfed all the nations.

Even while the COVID crisis was at its peak in 2020, the global supply chain found itself at historic levels of disruption. With factories pulling down their shutters, freight costs mounting, and loss of jobs, the challenges compounded for consumer goods companies and others worldwide.

For retailers, the issues were slightly different. The year-long lockdown created mayhem of bulk buying among residents. Hence, nearly 72% of retailers experienced too many out-of-stocks for fast-moving products as a top inventory challenge.

Unfortunately for businesses with global footprints, the compounding challenges in the supply chain network became unmanageable due to the lack of supply chain visibility and technological immaturity of local vendors and suppliers.

What is Supply Chain Visibility, and Why is it Important?

The concept of digitally optimizing the supply chain network was always there. However, the global pandemic became the key driver, pushing the final pieces of the puzzle into place. Business leaders had the foresightedness to presume such a change is inevitable. However, the time of the change was not determined until the global crisis.

Now, when new-age technologies are the only answer to the impending crisis, the visibility of end-to-end supply networks gained the spotlight. Here’s why:

Visibility in supply chain and logistics refers to easy tracking of how every component works in the network to complete the product’s journey from supplier to the manufacturer and finally to the end-user. And this visibility is no longer restricted to tier 1 and tier 2 suppliers. Rather, it is about gaining upstream and downstream visibility into supply chain activities.

Also, companies relying on antiquated visibility and traditional tracking methods using spreadsheets or disconnected software systems faced difficulties keeping up with remote workforce management, a massive rise in e-commerce orders, varying demands of new customers, and supply chain disruptions during the crisis.

Further, they realized that visibility is crucial to building resilient supply chain networks that can override the challenges of any disruption, including global crises like the pandemic. However, without data, supply chain resilience is far-fetched.

Hence, the focus shifted to the digital supply chain. As a result, many companies stepped up their investment to offset the pandemic’s negative impact on businesses.

How Modern Technology became the Ultimate Salvation for Supply Chain

Data is the foundation for supply chain resilience, as mentioned by Arnold Kogan, Managing Director and Partner of Boston Consulting Group. Data is needed to forecast the future and make informed decisions aptly. Unfortunately, the traditional data mining from spreadsheets is time, labor, and cost-intensive.

Digitally addressing the shortcomings of data extraction using Automation and Artificial Intelligence is the best bet for companies. Automation can easily fuel efficiency and enhance the visibility of the global supply chain network. More and more companies are investing in automation because they do not have the luxury of waiting for the next 3-5 years.

Here’s a brief overview of how automation helps maximize supply chain visibility and foster resiliency of the global network:

Responsive Supply Chain: Automated solutions increase supply chain visibility, equipping suppliers with real-time data about what’s happening and where, when, and why. Such data allows concerned parties in the network to act immediately when disruptions start appearing. Hence, increased transparency results in increased responsiveness of the supply chain.

For example, 33% of CGs cited improved responsiveness to changes in supply as one of the top benefits of new technology like AI and ML.

Employee Engagement: With automation, employees feel more in control when handling customer inquiries or improving customer satisfaction with on-time product delivery.

Dealer Experience: AI in the supply chain provides visibility into the market consumption of original equipment, the equipment’s health, and parts in high demand.

For example, 52% of CGs state that new technology like AI and ML improves responsiveness to changes in demand.

Customer Satisfaction: When all parties are connected directly or indirectly to the supply chain, we can expect better customer service, focusing solely on upscaling their satisfaction.

So, can AI Salvage Supply Chain from Disruption?

The answer is – a definite Yes!

New-age technology like automation, AI, and ML have proved to be more than efficient in streamlining various complexities existing within business networks. Hence, applying the new technologies combined with data helps optimize and create a resilient supply chain that can survive any disruption.

Disrupting the Commercial Insurance Landscape with AI

We had come a long way when a pound of flesh was demanded against delayed loan repayments. Nevertheless, mentions of the importance of insurance as a guarantee against money loaned were already there in the ancient texts. Commercial Insurance stemmed from the need to protect commerce, business, and trade.

With the advent of new technologies, financial lenders are opting for Automation and Artificial Intelligence in Insurance to stay competitive.

Here, we will explore everything we need to know about AI Insurance.

Understanding the Potential of AI in Insurance

As per experts, Artificial Intelligence has the potential to drive up to a whopping $1.1 trillion in annual value for the entire insurance industry. Like human intelligence, AI is evolving continuously, and it won’t be long before we see a change in dominance of its use cases from ‘detect and repair’ to ‘predict and prevent.’

Presently, most Artificial Intelligence Insurance use cases are centered around automating back-end administrative tasks. But, if we take an eagle-eye view of the future of insurance, especially commercial insurance, there is an entire area of unexplored opportunities. Since this sector lags in AI adoption, as compared to others, AI plays and will play a dominant role in the quest for complete digital transformation.

Here is the list of commercial insurance areas where Artificial Intelligence and Automation can bring a competitive difference:

Below are a few benefits of AI in Commercial Insurance:

According to experts, insurers have no alternative if they wish to remain competitive and transparent. Unfortunately, the sector is slow in adopting the technological shift. In order to realize the full potential of digitization and Automation, there are roadblocks to overcome, such as navigating complex legacy system landscapes with unlinked datasets in sales, managing insurance applications and claims processes, and addressing anti-selection risks from overly generalized automated solutions and severe regulatory obstacles.

5 AI Insurance Use Cases

AI insurance is not a relatively new concept. A handful of early adopters have applied this AI in the following use cases and are currently reaping the benefits of processes transformation.

Streamlining Claims Processing: Largely paper-based claims management processes eat up 80% of premium revenues and are most prone to human errors. Such inefficiencies and delays only add to the insurer’s operating costs. Artificial Intelligence in Insurance, coupled with Deep and Machine Learning, RPA, and IoT, can address the time, cost, and labor-intensive tasks, making them more efficient, thereby reducing the operating costs for insurers.

Accelerated Claims Adjudication: Both insurance providers and customers expect fast insurance cycle time. AI Insurance can quickly speed up the entire process by taking up most labor-heavy and dangerous inspection tasks from human resources.

Rapid Document Digitization: Legacy insurers largely depended on paper-based, print documents. Manually re-typing information is cost, time, and labor-intensive. With Document AI, rendering every pixel accurately became easy, and translating them into digital inputs is a piece of cake. Experts suggest that Automation of documentation can drive up to 80% in cost savings for every process.

Faster Underwriting: The insurance sector has become more intricate; hence rule-based underwriting and risk engines no longer suffice accurate estimates. Technologies such as AI, Automation, and Computer Vision paired with IoT devices help insurers record the asset state of underwriting in real-time and make adjustments as and when needed.

Fraud Detection and Prevention: Big insurance companies lose billions of dollars annually to fraudsters. AI document processing provides valuable intel to analysts for addressing various shortcomings of earlier applications and detecting anomalies before they compound into significant losses.

The Future of Commercial Insurance

While commercial insurance may be more traditional, the winds of change are being felt even in this area of insurance. It is only about time before we see a full-scale digital transition in the said sector, all courtesy of Artificial Intelligence and Automation.

Unfortunately, AI Insurance is still at its nascent stage but not for too long!

The commercial insurance space presents ample scope for AI and other new-age technologies to foster profound change. From engaging a prospect and assessing risk factors during underwriting to settling claims and retaining customers, the sustainability of an insurance enterprise demands accuracy and efficiency across the value chain.