In-house vs. pre-built: The best emission solution for TMS

As global awareness around climate change intensifies, regulatory bodies worldwide ramp up requirements for carbon disclosure and emissions accountability. In sectors with high environmental impact, like transportation—which accounts for nearly 28% of greenhouse gas emissions in the U.S. alone—these demands are especially pressing.

So now, as a Transportation Management System (TMS) provider, you’re uniquely positioned to support this shift by offering solutions that not only streamline logistics but also provide crucial insights into emissions tracking.

One of the key requirements for this is adding emissions capabilities to your TMS, which opens doors to several advantages: clients can measure and report their environmental impact more accurately, make data-driven optimizations in route planning, and boost overall supply chain efficiency—all while contributing to global sustainability goals.

To align with the Net Zero Emissions by 2050 (NZE) Scenario, emissions must fall by 15% from 2022 to 2030, declining at roughly 2% annually. ^{[International Energy Agency Organization]}

Yet, choosing the right path to implement emissions capabilities isn’t straightforward. The question arises – Should you invest in developing an in-house emissions tracking system tailored to your platform or opt for a pre-built API that fast-tracks implementation? Each approach has its own set of challenges, from technical and resource constraints to data accuracy and regulatory demands.

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1. Why developing emission API is challenging
2. In-house development challenges of emission API
3. Issues faced due to unreliable emission data

Why developing emission API is challenging

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Creating a custom emissions tracking system isn’t as simple as adding a feature; it’s a complex, multifaceted project that takes time, expertise, and funding. To begin with, transport management system companies must acquire specialized knowledge to measure emissions accurately, often by hiring experts or training internal teams. This can be particularly challenging due to the ever-changing nature of emissions regulations, which demand that businesses stay continuously updated to remain compliant.

The transport sector is responsible for approximately one-quarter of greenhouse gas emissions. ^{[United Nations]}

Building a reliable emissions system requires expertise, extensive coding, rigorous testing, and complex integration processes. These stages alone can take months, often extending project timelines and causing unexpected setbacks. For businesses focused on meeting delivery schedules and managing logistics, this process can divert valuable attention and resources away from core operations.

Key bottlenecks in building emission capabilities for TMS

Two significant bottlenecks typically arise for TMS providers in the pursuit of emissions tracking: 

1. Challenges with in-house development
2. Issues with unreliable emissions data

Building an emissions tracking system in-house might seem a good option to maintain control over data and processes. Still, significant challenges can impact a transportation management company’s core operations and efficiency. Below, we break down the main bottlenecks TMS providers face with in-house development, illustrated with real-world examples and outcomes.

As a TMS company, if you choose to build emissions capabilities with in-house developed emission API, here are the challenges you will likely face.

Part A: Challenges with in-house development

• Extended learning curve

Your development team begins the project eager to create a robust emissions API to build TMS emissions capabilities. However, they quickly discover the need for specialized expertise in climate data and emissions calculations. To address this gap, they hire a climate data specialist and invest time in training sessions for the existing team.

Outcome: This focus on building expertise extends the project timeline by three to six months. Meanwhile, competitors who opt for pre-built emissions APIs launch their solutions, leaving the company disadvantaged in the market due to delayed entry.

• High development costs

As your team delves deeper into the project, they face unplanned mounting development costs. Building a custom solution requires extensive resources for coding, testing, integration, and quality assurance. What is initially budgeted at $250,000 rapidly escalates due to unforeseen expenses, including necessary regulatory compliance adaptations and additional infrastructure requirements.

Outcome: The final project cost approaches an unwanted expense of $100,000, leading to an unrealized development cost increase to $350,000. This diverts funds from other essential initiatives, such as product updates and customer support enhancements. This financial strain hampers overall growth and limits investment in other critical areas.

• Complex compliance management

During the development phase, new emissions regulations introduce additional challenges. The in-house system requires frequent updates to align with the changing regulatory landscape. These ongoing adjustments demand significant attention, diverting resources away from developing core functionalities.

Outcome: The constant need for compliance updates stretches the team thin, making it difficult to focus on the project’s primary objectives. As the pressure to remain compliant intensifies, essential projects stall, increasing the risk of potential penalties for even minor non-compliance and leading to clients losing trust.

• Operational disruptions

With more resources allocated to the emissions API, core operations suffer. The support and development teams, which typically focus on enhancing system performance and customer support, become consumed by emissions API development. This shift leads to delays in addressing crucial emissions capabilities feature development.

Outcome: Customer satisfaction drops as response times increase for delivering emissions capabilities, leading to complaints about service quality. Frustration mounts among clients, prompting the team to question whether pursuing an in-house emissions API is the best strategy.

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• Long implementation time

Initially projected to take six months, the emissions tracking project extends to over 18 months due to various challenges, including compliance issues, cost overruns, and the steep learning curve. During this extended timeline, competitors successfully implement pre-built APIs, allowing them to offer emissions insights and attract eco-conscious clients.

Outcome: By the time the in-house system is ready for launch, numerous opportunities are missed. Clients seeking emissions-tracking solutions turn to competitors who provide reliable data without delay, highlighting the limitations of an in-house approach.

While this was just part A of the challenges that you would, as a TMS vendor, have to face, part B will be awaiting to steep down your emissions offerings further.

Part B: Issues with unreliable emissions data

As a TMS developer, you know that even a well-functioning emissions API faces significant challenges due to unreliable data. Let’s dive into some common bottlenecks you encounter, complete with scenarios and outcomes that highlight the impact of inaccurate emissions data on your TMS operations, product image, and positioning among target audiences.

• Inaccurate reporting

Assume your logistics client uses the emissions insights from your dashboard to create their sustainability reports and track their carbon emissions. They discover discrepancies in the figures that do not align with their operational metrics because the emissions API you rely on or develop internally has emissions data from multiple unreliable sources. As a result, their workflows become messy, leading to inaccurate reports that hurt their credibility and compliance efforts.

Outcome: This inaccurate reporting not only puts your client at risk of compliance violations but also damages their credibility with stakeholders. Their frustration leads to losing trust in your services, jeopardizing your relationship.

• Poor decision-making

Consider a shipping company that relies on the emissions capabilities provided by your TMS to optimize its route planning. They expect to make informed decisions that reduce fuel consumption and enhance efficiency. For example, they plan a longer route based on incorrect emissions insights that suggest it is more environmentally friendly, only to find out later that it results in higher fuel consumption and emits more emissions than they plan, leading them to surpass their emission targets.

Outcome: The shipping company faces significant financial strain, ultimately impacting its bottom line. Frustrated by these inefficiencies, they question your reliability as a TMS partner and start looking for alternatives to provide more accurate and dependable emissions information for route planning.

FYI, to avoid such poor planning, here is what the shipping industry has adopted –  Member States of the International Maritime Organization (IMO) adopted the 2023 Strategy on Reduction of GHG Emissions from Ships, setting enhanced targets to address harmful emissions.

Member States of the International Maritime Organization (IMO), meeting at the Marine Environment Protection Committee (MEPC 80), have adopted the 2023 IMO Strategy on Reduction of GHG Emissions from Ships, with enhanced targets to tackle harmful emissions.^{[International Maritime Org.]}

• Regulatory risks

Your client in the freight sector relies heavily on your emissions capabilities to ensure compliance with environmental regulations. They depend on accurate emissions data to prepare reports and demonstrate their commitment to sustainability. However, alarm bells ring if they find inconsistencies or inaccuracies in your data.

Outcome: This discrepancy leads to serious consequences, including potential regulatory penalties for inaccurate emissions reporting. As government authorities increase their scrutiny of compliance practices, your client faces audits and fines, putting their business at risk.

• Customer trust issues

A trucking company provides emissions reports to its retail clients to support their sustainability claims by relying on your TMS for visibility of emissions across the transportation supply chain. When these clients discover the emissions data is unreliable, it undermines their marketing efforts and credibility.

Outcome: These clients post negative reviews on platforms like Google and Trustpilot, which tarnishes your reputation in the market. This dissatisfaction often leads to negative word-of-mouth publicity, causing potential customers to reconsider their choices and eroding the built reputation and positioning of your TMS in the marketplace.

• Operational inefficiencies

Suppose a 3PL company integrates your emissions data into its logistics operations to enhance efficiency and meet customer sustainability goals. Unfortunately, when your emissions data proves unreliable, their optimization efforts crumble.

Outcome: They face operational inefficiencies, leading to increased costs, delayed deliveries, and inaccurate carbon footprint reporting. This disruption frustrates your client and prompts them to question the value of your TMS, as it hinders their supply chain efficiency.

Summing up

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With mandates for emissions monitoring becoming more commonplace, companies are exploring various solutions to integrate emissions data into their operations effectively.

While developing an in-house emissions API to build TMS emission capabilities may seem like a sound investment, this approach will often lead to lengthy timelines and unpredictable costs. Instead, leveraging a pre-built emissions API from a climate data company that relies on scientifically vetted workflows will allow TMS offerings to build efficient emission capabilities with a cost-effective solution that will enhance time-to-market, customer satisfaction, and revenue growth.

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