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On-Demand Masterclass: Trusting LCAs at Scale

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Top 10 Key Takeaways

Understanding the Importance of LCAs at Scale 

Scaling up Life Cycle Assessments (LCAs) involves expanding their scope while ensuring they remain reliable, transparent, and verifiable. This requires a disciplined approach to maintain the integrity of LCAs as they grow in complexity. Emphasizing the importance of scaling LCAs is essential for companies aiming to achieve meaningful sustainability outcomes and enhance stakeholder trust. 

Three Foundational Pillars for Successful LCA Scale-Up 

The three pillars essential for scaling LCAs are: 

  • Robust Data and Data Landscapes: Ensuring high-quality, comprehensive data is crucial for accurate assessments. 
  • Consistent Methodologies: Standardizing methodologies across assessments to maintain consistency and comparability. 
  • Comprehensive Documentation: Detailed documentation is necessary to provide transparency and facilitate verification processes. 

Challenges and Misconceptions 

There is a common misconception that LCAs at scale are of lower quality compared to traditional LCAs. It was clarified that while LCAs at scale may be perceived as less transparent, they can actually provide higher accuracy and representativeness. The key is to address documentation and transparency challenges effectively. 

Data Collection and Integration 

Traditional LCAs often involve manual data collection and adjustments, which can introduce errors and inconsistencies. LCAs at scale, however, use automated data collection directly from ERP and PLM systems, ensuring higher accuracy and reducing human error. This approach allows for more precise and reliable data integration. 

Modeling and Mapping 

In traditional LCAs, modeling and mapping are manual processes prone to errors and variability. LCAs at scale automate these processes, enhancing reproducibility and consistency. Automated modeling and mapping eliminate the variability and errors associated with manual data handling, leading to more accurate and reliable assessments. 

Documentation and Verification 

Documentation and verification are critical bottlenecks in scaling LCAs. Innovative approaches are needed to streamline these processes. This includes developing new standards and practices to ensure that LCAs at scale meet the required documentation and verification standards without excessive manual effort. 

Quality Assurance and Transparency 

Achieving high-quality results in LCAs at scale requires ensuring that the data and models are well-documented and transparent. This involves creating detailed quality assurance reports and maintaining consistent documentation practices. Transparency is key to building trust and credibility in the results. 

Leveraging Technology for Efficiency 

The use of technology, such as automated data integration and modeling, significantly reduces the time required for LCAs. This efficiency allows for more frequent updates and continuous improvement, which are essential for maintaining accurate and up-to-date assessments. Technology enables companies to scale their LCAs without compromising quality. 

Addressing Data Gaps 

Handling data gaps is a critical challenge in LCAs at scale. Strategies for filling these gaps include using standard components and merging data from different sources. Ensuring comprehensive and accurate assessments involves identifying and addressing data gaps effectively. 

Future Directions and Best Practices 

The future of LCAs at scale involves ongoing innovation and improvement to meet evolving sustainability goals. Emphasizing the need for best practices in documentation and verification, continuous collaboration with partners and stakeholders is essential for developing and refining these practices. 

On-Demand Masterclass: How to Evolve Beyond Spend-Based Scope 3 Reporting

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Sustainability reporting has moved from being a niche requirement to a central element of modern corporate strategy. For many organizations, the focus on Scope 3 emissions — which account for most of their product’s carbon footprint — presents an opportunity to lead in environmental responsibility and drive innovation. Yet, most companies still rely on spend-based methodologies that provide limited accuracy and fail to capture the full picture of their impact. As stakeholders demand greater transparency and regulators implement stricter compliance measures, businesses must evolve their approach to ensure they remain relevant and resilient in a competitive landscape.
 

In a recent Makersite Masterclass, our data experts Fabian Hassel, VP of Services and Pablo Downer Päster, Principal Sustainability Engineer, provide a roadmap for organizations looking to transition away from spend-based approaches.

The session emphasized the need for robust, data-driven strategies that go beyond surface-level reporting, providing organizations with the tools and strategies needed to begin the transition.

Below are 10 key takeaways you can use to optimize your sustainability practices. By implementing these strategies, businesses can not only meet compliance requirements but also unlock long-term value in their operations.
 

Top 10 Key Takeaways

Understand the Limitations of Spend-Based Reporting

Spend-based reporting has been a common practice due to its simplicity and scalability, but it is heavy with drawbacks that limit its effectiveness in meeting modern sustainability goals. We highlighted three major weaknesses of this approach:

  • Lack of Accuracy: Relying on industry averages often fails to capture the complexity and uniqueness of individual supply chains.
  • Overlooked Factors: Key variables, such as material choices, product design, supplier energy sources and production efficiencies, are ignored.
  • Regulatory Risks: Increasingly stringent regulations demand more product level granularity and transparency, making spend-based methodologies insufficient. 

To keep up with global standards, businesses must transition to data-driven methods that go beyond high-level estimates.

 

The Power of Granular Data in Scope 3 Reporting

Accurate, granular data is a necessity for sustainability reporting. Transitioning from general estimates to detailed, material-specific information allows businesses to make better decarbonization decisions and take targeted actions.

Granular data provides:

  • Material-Level Insights: A clear understanding of the impact of each material in the supply chain.
  • Product-Specific Assessments: Precise measurements of emissions tied to specific products.
  • Supplier Data Integration: A more accurate and strategic approach to managing supplier emissions.   

This actionable level of detail equips businesses to develop proactive sustainability strategies rather than merely meeting reporting requirements.


Digital Twins as a Game-Changer

Digital twins are virtual data models that replicate real-world products, processes, and supply chains. We emphasized their transformative potential for Scope 3 reporting.

Digital twins enable companies to: 

  • Simulate scenarios to evaluate sustainability interventions.  
  • Identify “hotspots” of emissions in supply chains to focus on reduction strategies.  
  • Foster greater collaboration among procurement, research, and engineering teams to align sustainability goals.  

For example, a manufacturer of complex systems like wind turbines could use digital twins to visualize emissions across thousands of components and adapt processes accordingly.


Navigate Transition Challenges 

Moving beyond spend-based reporting is rewarding, but it isn’t without challenges. As we identified the most common roadblocks and how to address them: 

  • Data Gaps: Ensuring suppliers provide accurate and comprehensive data.
  • Integration Barriers: Streamlining fragmented data systems into a unified platform.
  • Cost and Complexity: Investing in advanced tools and frameworks for long-term gains. 

Despite these obstacles, high-impact organizations have successfully overcome these barriers with meticulous planning and the right tools.


Industry-Specific Insights for Scope 3 Reporting

Different industries face unique challenges and opportunities in Scope 3 reporting.

Here are some examples discussed in the masterclass: 

  • Automotive: High supply chain complexity coupled with strict emissions regulations.
  • Electronics: Significant impacts from raw materials requiring circular practices.
  • Heavy Machinery: Long product life cycles and complex components necessitate precise data collection.  

Tailoring reporting strategies to industry-specific needs is essential for achieving both accuracy and actionable insights.

 

Preparing for a Shifting Regulatory Landscape

Regulations like the EU Corporate Sustainability Reporting Directive (CSRD) and SEC climate disclosure requirements demand unprecedented levels of transparency. We emphasize that companies need to: 

  • Build traceable and robust supply chain mechanisms.  
  • Adopt methodologies that exceed regulatory expectations to ensure long-term compliance and readiness for future standards. 

Organizations that begin adapting now will gain a head start over competitors once these regulations are fully enforced.

 

Advanced Master Material’s Approach to Scope 3 Reporting

To achieve your Scope 3 reporting goals, the importance of integrating an AI or tech tool to simplify and assist in the transition to more accurate Scope 3 reporting.

What you should look for in a tech tool to help you achieve your goals in Scope 3 Reporting:

  • Automated Data Integration: Seamless integration with ERP and PLM systems consolidates disparate data sources.  
  • Material and Supplier-Specific Modeling: Detailed emissions data to guide informed decision-making.
  • Collaboration Tools: Enables real-time engagement between cross-functional teams, such as procurement and sustainability managers.

By addressing key challenges of data granularity and system integration, you should look for a tool that supports businesses in meeting their sustainability goals effectively.

 

Turning Scope 3 Reporting into a Competitive Advantage

Far from being a regulatory burden, Scope 3 reporting can be a strategic opportunity.

We highlight its potential to drive business growth by: 

  • Market Differentiation: Establishing leadership as a sustainable brand.  
  • Data-Driven Innovation: Creating better products informed by actionable insights.
  • Supply Chain Resilience: Building transparency to adapt to disruptions and mitigate risks.  

Forward-thinking companies are leveraging Scope 3 as a catalyst for innovation and lasting competitive advantage.

 

Real-World Scenarios

We discussed  two different global manufacturing companies we worked with faced the common challenge of inconsistent and missing Scope 3 data, which led to inefficiencies in their product design and cost analysis.

The solution involved:

  • Enhanced Precision: Transitioned from generalized spend-based estimates to precise, material-level reporting, empowering data-driven decisions.
  • Cost Efficiency: Identified inefficiencies and optimized procurement strategies, driving measurable savings and sustainable growth.
  • Compliance Assurance: Secured full regulatory readiness, ensuring confidence and adherence to the highest industry standards.

For a deeper dive into our success stories click here.

 

Actionable Steps to Get Started   

If your organization is ready to evolve beyond spend-based Scope 3 reporting, here are four practical steps to take today:  

  • Assess Your Current Process: Identify gaps and areas for improvement in your current reporting practices.
  • Engage Stakeholders: Collaborate across departments—procurement, sustainability, engineering—to align goals and define data needs.  
  • Adopt Advanced Tools: Leverage advanced data management and integration tools, specifically, sustainability or environmental focused reporting platforms for accurate data integration and emissions modeling.
  • Pilot and Scale: Launch pilot projects to refine methodologies before scaling them across the organization.

Unlock the Full Potential of Scope 3 Reporting  

Accurate Scope 3 reporting is more than just a regulatory requirement—it’s a pathway to innovation, efficiency, and sustainable growth. Companies willing to embrace advanced methodologies and tools will not only meet compliance standards but also position themselves as leaders in a rapidly evolving market. 

By taking incremental steps, businesses can gradually transition to more advanced reporting practices without overwhelming existing systems. 

Curious to learn more about overcoming the Scope 3 Reporting challenges?

Click here to meet with a Makersite team member.

 

 

 

 

 

On-Demand Masterclass: Solving Sustainability Data Challenges

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In a rapidly evolving business landscape, managing sustainability data has become a critical challenge for industries worldwide. During our recent masterclass, Solving Sustainability Data Challenges, Makersite’s data experts Sophie Kieselbach and Niclas Rabel explored the hurdles organizations face in aligning their sustainability efforts with robust data practices.

From understanding different maturity levels across industries to tackling common data management obstacles, this session provided actionable insights to help businesses enhance their sustainability journeys. Below are 10 key takeaways from the masterclass that can guide companies in improving their sustainability data practices and integrating them into long-term strategies. 

10 Key Takeaways 

Sustainability Maturity Levels Across Industries 

By using data gathered through our Maturity Index submissions the data experts analysed and presented how various industries are at different stages in their sustainability journeys. They were categorized into three maturity levels:  

  • Novice (76.06%): This group comprised industries like automotive (19.72%) and consumer durable goods (23.94%) that are just beginning to integrate sustainability efforts. They are largely unaware of their entire value chain and tend to have limited visibility into sustainability data beyond Tier 1 suppliers.  
  • Intermediate (19.72%): These industries have started to address sustainability but are still in transition. Automotive and building materials make up a portion of this group, where data integration is underway, but decision-making is hindered by inconsistent and siloed data.  
  • Advanced (4.23%): These are the most mature companies in terms of sustainability data, often found in consumer packaged goods. They have harmonized data and an end-to-end view of their supply chain, allowing them to make informed decisions and leverage sustainability as a profit driver.  

These maturity levels indicate that most companies are still in the early phases, struggling with integrating sustainability into core business processes.

To find out where you sit on the maturity ladder and how you compare to companies similar to yours fill out our Maturity Index.

  

Data Challenges  

These are some of the most common challenges businesses face when managing sustainability data:  

  • Internal Awareness Gaps: Many companies are partially aware of their internal data but lack insight into the entire value chain. This creates blind spots beyond Tier 1 suppliers and disrupts accurate decision-making.  
  • Supply Chain Visibility: Limited data visibility can lead to delayed decisions, supply chain disruptions, and missed regulatory requirements.  
  • Data Silos: Inconsistent and siloed data across departments (product development, procurement, etc.) makes it harder to drive sustainability initiatives. The inability to share and integrate data from different sources prevents a holistic view of sustainability impacts.  

The goal here is to shift from fragmented, inconsistent data management to a fully integrated, transparent data landscape that supports sustainability efforts across the entire supply chain.  

   

Sourcing Challenges  

Sourcing data for sustainability presents several key issues:  

  • Data Accessibility: Difficulty in accessing data due to proprietary restrictions and varying data quality standards from suppliers.  
  • Missing Descriptions: Purchased parts often lack proper descriptions, leading to inefficiencies in understanding their sustainability impacts.  
  • Integration Complexity: The complexity of integrating internal databases with third-party providers and IoT devices can lead to fragmented data management systems.  
  • Inaccuracy and Inconsistency: Manual data entry errors, outdated information, and inconsistent data formats further exacerbate the problem. Companies often find that the same data point varies across different systems, making it difficult to trust the data.  

Addressing these sourcing challenges requires robust data integration tools and governance frameworks that standardize the collection and storage of data.  

   

Real-World Scenario

We discussed a real-world scenario where a company we worked with faced the common challenge of inconsistent and missing data, which led to inefficiencies in their product design and cost analysis. The solution involved:  

  • Data Governance Framework: Implementing a data governance framework to harmonize data from various ERP (Enterprise Resource Planning) and PLM (Product Lifecycle Management) systems.  
  • Enhanced Data Quality: Improving data quality through integration tools helped the company make better decisions, reduce costs, and design more sustainable products.  

The use case emphasizes the importance of unified data governance to overcome fragmented data systems, highlighting the role of tools like Makersite in ensuring smooth integration and accuracy of data. 

For a deeper dive into our success stories click here.

   

Data Management  

Systematic data management is a vital ingredient for a successful business, it includes organizing, storing, and maintaining data. Three core benefits are:  

  • Driving Business Decisions: High-quality data enables businesses to make informed and timely decisions, especially regarding sustainability.  
  • Enhancing Operational Efficiency: Proper data management reduces errors and inconsistencies, leading to streamlined operations.
  • Fostering Innovation: Accurate data supports research, product development, and innovation, particularly in creating sustainable products.  

There is often a high cost of poor data quality. For instance, Gartner estimated that poor data quality costs businesses $12.8 million annually, and 95% of organizations acknowledge its negative impact on business performance.  

 

Competitive Advantage  

Prioritizing data quality and management gives companies a competitive edge. We looked at how with accurate and comprehensive data, businesses can:  

  • Stay Ahead: Beat the competition by enabling better decision-making, efficient resource allocation, and long-term planning.  
  • Consolidate Data: Understanding their data landscape empowers businesses to consolidate information across departments, leading to more integrated and effective sustainability strategies.  
  • Enable Planning: Accurate data allows for stable long-term planning, which is crucial for efficient resource allocation and maintaining a competitive advantage.  

By focusing on data quality, companies not only comply with regulations but also turn sustainability into a key driver of profit and innovation.  

   

Best Practices for Data Management  

These are some of the best practices to ensure high-quality data governance:  

  • Clear Policies: Developing and enforcing data management policies to maintain data integrity across systems.  
  • Training and Awareness: Conducting training sessions and raising awareness about the importance of data governance within the organization. This helps foster a culture of responsibility for data quality.  
  • Continuous Improvement: Monitoring data maturity and striving for continuous improvement, such as through regular data audits, validation, and cleansing processes.  
  • Integration Tools: Using advanced data management and integration tools to standardize and simplify data handling.  

These practices ensure that businesses can maintain high-quality, accurate data, which is essential for driving sustainability efforts and making informed decisions.  

   

Before You Begin

It is necessary to initiate engagement with both internal experts and external stakeholders to address data challenges from the very beginning. Key actions would include:  

  • Data Workshops: Conducting workshops to align on data requirements, sources, and quality expectations early in the project lifecycle.  
  • Collaborative Approach: Ensuring close collaboration with stakeholders to resolve data issues promptly.  
  • Proactive Data Quality Maintenance: Identifying and addressing data quality issues before they escalate, and involving the right stakeholders, such as sustainability experts, from the start.  

Early engagement and alignment on data management practices ensure a smoother, more efficient sustainability data integration process.  

 

Preparation is Key

To prepare for successful sustainability data management you should first focus on:  

  • Data Discovery: Starting with a thorough review of the company’s existing data, its sources, and stakeholders involved.  
  • Pilot Projects: Running a pilot or Proof of Concept (POC) project to test the integration of the source data into the system, which helps prepare for a full rollout.  
  • Workshops and Feedback: Conducting detailed workshops with IT teams to identify all data points, receive feedback, and suggest improvements. Data enrichment processes ensure the data is ready for system integration.  
  • ETL Process: The Extract, Transform, Load (ETL) process connects raw data from various sources to the system. After user training and acceptance testing, the project can go live.  

By focusing on data quality and system readiness early on, companies can achieve smooth integration and reliable sustainability outcomes.  

   

Actions You Can Take Now

Throughout the Masterclass our data experts emphasized the need for a robust data strategy. These are some of the key action points to kick of a successful data strategy:  

  • Data Awareness: Understand the organization’s system landscape and ensure data completeness and accuracy.  
  • Leadership Involvement: Prioritize data governance and quality, with leadership setting the tone for an organization-wide focus on data integrity.  
  • Regular Audits: Perform regular data audits and implement validation processes to maintain data quality.  
  • Employee Education: Train employees on the importance of data quality and management, which is crucial for long-term success.  
  • Advanced Tools: Leverage advanced data management and integration tools to stay ahead of data governance challenges.

Sustainability data challenges can hinder a company’s ability to make informed decisions, drive innovation, and stay competitive. By addressing these challenges with structured data management strategies, clear governance frameworks, and continuous improvement efforts, businesses can unlock new opportunities.   

Prioritizing data quality not only supports sustainability goals but also positions companies for long-term success and profitability.

Want more information on how to overcome the sustainability data problem? Read our playbook on that and more now.

Solving the Scope 3 challenge

Makersite CEO Neil D’Souza recently sat down with The Scope 3 Podcast’s Tom Idle and Oliver Hurrey to discuss the key supply chain challenges facing organizations today – and how Makersite can help to solve them. You can listen to the full episode below or using the link here.

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Five key takeaways on product sustainability and scope 3

The real impact comes from products

It might sound simple, but when it comes to Scope 3 we need to take things back to the source. As Neil notes, “100 % of the impact that we see in the world today comes from the products we make and use. If you really think about it, whether you’re a service company and you’re flying around, well, it’s the plane that’s creating the impact, right? If you’re on your desk, then it’s the laptop and the electricity you use to run it.”

Just reporting isn’t enough. If you truly want to fix something and resolve the problem of the impact that’s being created, then you need to do your homework and properly understand the implications of designing a product in a certain way – from the raw materials you use to where you source them from to the end of life of that product.

Sustainability isn’t about ‘being green’

It’s all very well for a company to want to flex its green credentials. But if you want to properly affect the product you make, then you need to go deeper. “Out of 250 odd projects that I’ve worked on,” Neil says, “there is not a single project that was implemented just because it was green.”

So what is it about? Business is about making trade-offs. It’s about asking yourself the right questions. “What will I get if I were to reduce its impact by 30%? What will I get in terms of, ‘will I be able to sell more in more jurisdictions?’ Would it address a different market? What would be the cost implication of it? Would I still be able to sell it given compliance problems that I may have? Would it still be safe?”

The design must be separated from the implication or the understanding of the implication.

Facilitating the demand for better products

Now more than ever, manufacturers in a variety of markets are facing an increasing pressure to make better, more sustainable products. But not only is there a greater demand from consumers and stakeholders for this approach – there’s also a greater propensity to pay higher premiums for better design.

However, these markets (from building and construction to automotive to chemicals) generally have very complex supply chains and products, and traditional tools and traditional approaches can’t solve the hurdles they need to overcome in order to meet those demands.

Makersite powers the systems used by the people (from engineers to procurement) in organizations who can make the difference – the CAD tools, the PLM tools, the ERP tools, the procurement tools.

With that help, they can ensure that the product that is being designed follows the rules of the region in which they’re trying to sell it.

2030 is too soon

Many companies have positioned ambitious Scope 3 and Net Zero targets for 2030. But, says Neil, that’s not giving anyone enough time. “In reality, if you think of this from an engineering standpoint, an average technical product takes five to seven years to go to market. 2030 is six, seven years away. You’ll be able to make one product change. That’s about it. There’s not a lot you can do with one product iteration.”

For Makersite, it’s about the bigger picture. The longer term. And it’s about stopping the same mistakes being made over and over again: “What we want to do is every iteration from now until 2050, every iteration of every product that is new, that is innovative runs through Makersite. If we do that, then we’re not making the mistakes that we’ve continuously made over time.”

The tools we have now are smart – but not smart enough

In order to properly service the market and the demand from consumers, the tools we have now need to be refined. They are good, but they could be better.

Neil D’Souza: “The first is engineering tools. Engineering tools need to become smarter in order that we make the right decisions during design. The second is procurement tools. Procurement tools themselves also need to become smarter. We need to be able to not just quantify what are the impacts of the products that we’re buying, but identify where are the low carbon products that we can buy. And the connection of these two tools is important for that to happen.”

Ultimately, if organizations want to decarbonize, then they must provide their procurement teams with the flexibility to look at the market for low carbon solutions, as well as the level of information to not buy the wrong thing. This is a connection that can only happen when you connect product development tools with procurement tools.

With that, there will then be an understanding of the material constraints and the production constraints that you need to have to make that product successfully.

Overcoming the hurdles: Why people, processes and bad data are hindering sustainability

Sustainability is a buzzword. Sustainability is just about annual reports. Sustainability is a tool to appease investors. We could write a whole blog on the common objections – or dismissals – that are raised when it comes to implementing a more sustainable approach to product design and manufacturing.

There will always be critics. Doubters. People who see sustainability as an obstacle in the way of progress, rather than a catalyst for it. But the numbers don’t lie. Businesses who are embracing sustainability are on the front foot. Those who aren’t are in real danger of being left behind.

Running the numbers

A recent Bain & Company study found that while only 40% of businesses are on track to meet their sustainability goals, companies have an increasingly conscious and proactive base of consumers willing to pay 11% more for sustainable products and employees that will help.

IBM noted in a recent report that organizations that embed sustainability in their product design processes experience a 16% higher rate of revenue growth. They’re 52% more likely to outperform their peers on profitability. And they’re two times more likely to attribute great improvement in operating costs to sustainability efforts.

NYU Stern’s Center for Sustainable Business found in 2022 that the share of CPG products marketed as being sustainable grew twice as fast as conventional products, accounting for one-third of the total revenue growth in the industry. Customers paid 27% more for those products.

There is a need for a more sustainable approach – and there is a willing audience too. But in order to get there, there are still a few hurdles left to overcome.

Internal challenges

An organization with a fully functioning and proactive sustainability function is likely to reap many benefits. But getting that sustainability function set up in the first place is, for many, the more significant battle.

Our recent study with Forrester showed that 27% of respondents placed ‘create a dedicated sustainability function within the organization’ as their top initiative to prioritize over the next 12 months. The need is clear and well understood. However, 18% of respondents to the study saw breaking down data siloes to enable cross-functional collaboration as among their biggest headaches. Such data siloes are the hallmark of organizations not yet ‘mature’ enough to fully realize the benefits of embracing an approach with sustainability front and center.

It’s also clear that, at least in part, there is still some way to go before there is proper acceptance of the role sustainability has to play in a business, particularly when it comes to reporting.

In the study, 66% of respondents showcased an awareness and understanding of the potentially severe impact on product and operations that not toeing the regulatory line would bring about. Furthermore, a full 10% of respondents ranked ‘strengthening regulatory compliance’ as their greatest business priority during the next 12 months, while 35% in total ranked it as being within their top 3 priorities. Out of the 10 options given to those surveyed, ‘strengthening regulatory compliance’ came top of the list.

However, that relatively low number indicates there is some way to go before there is a full understanding of the importance of increasing regulatory sustainability reporting. With only 35% of organizations having the initiative to solve the challenge, the research suggests an element of indecision and uncertainty, exacerbated by competing priorities coming from different angles.

The struggle to gain momentum

Currently, in more ‘immature’ organizations at least, sustainability advocates are struggling to gain momentum at the top table. And it’s not just competing priorities that are causing the problem. Interconnected governance issues continue to dominate top PLM challenges, with maintaining data, securing executive buy in, and breaking siloes causing the biggest headaches.

53% of respondents to the Forrester study struggle with securing executive support for incorporating sustainability in product lifecycle management, while half find it hard to obtain budget to gather material, component, and supplier intelligence integral to optimizing their product’s quality, cost, and sustainability. Over half experience difficulties measuring and quantifying the environmental impact of their products which can be a factor for the lack of leadership alignment. These governance challenges are a manifestation of poor maintenance of availability, cost, sustainability, and performance data in manufacturer’s material and component libraries – an issue for 49% of decision-makers.

Lacking the necessary data means that sustainability advocates are unable to take the necessary measurements, ultimately meaning that the support and budget they need to continue their work is not forthcoming. It’s a cycle many are finding hard to break.

It’s also a problem not limited by borders. Across US and European markets, governance obstacles are widespread. European respondents in particular highlighted their struggles influencing a strategic shift to sustainability, commonly citing a lack of management commitment when it comes to driving substantial changes (46%) and difficulties developing a business strategy for sustainability (44%).

Data management challenges remain fundamental and acute. When asked which three challenges create the most profound impact, leaders hone in on their data shortfalls: one-in-five decision-makers rank maintaining libraries with up-to-date data rises as one of their biggest issues.

Data siloes hinder stakeholders across functions as they balance costs, risks, and sustainability criteria in product design and sourcing. An inability to embed multi-criteria data around sustainability and resilience in their generative design processes handicaps manufacturers with less mature PLM processes. Even more advanced manufacturers are challenged by the ongoing maintenance of aspects of their materials and components libraries.

Remedying the problem

Solving the problem again comes down to one key thing: data. A better and more reliable collation of availability, cost, sustainability and performance data eases the burden of obtaining budget in order to gather material, component and supplier intelligence. Similarly, better data libraries, ensuring up to date data and breaking down data siloes are all key when it comes to enabling cross-functional collaboration and ensuring that sustainability-focused voices are heard.

A business looking to succeed and grow should understand that building high-performance, cost-effective, sustainable products will create a competitive advantage. Sustainability, implemented correctly, can be a significant differentiator when positioning and marketing products.

Manufacturers must become quicker, smarter, and — given the urgency of sustainability — more environmentally conscious to thrive. They need to become more efficient and effective as they design and source products.

Data quality and accessibility form the foundation of efficient product design and sourcing, and both are significantly improved when adopting a product lifecycle intelligence solution. By modernizing product innovation processes and platforms, senior leaders at manufacturers will not only be able to satisfy regulatory mandates for product-level sustainability, but will also be able to empower designers with product lifecycle intelligence in order to modernize product innovation and achieve balanced product cost, performance, and sustainability goals.

Whether it’s people, processes, LCA software data or technology – or a combination of all four – that currently present the biggest obstacles to embedding sustainable practices in an organization, one thing is clear: those who are able to move those obstacles will thrive. Those who don’t – or won’t – will find themselves facing an uphill battle.