Category: Uncategorized

1. Thinking it’s just business travel

Rather than measuring what matters, we’re often measuring what’s easy to do. Since scope 1 and 2 data is easily accessible, these emission factors have come to be relatively well understood. For scope 3 emissions, however, companies often take only employee commuting, business travel and sometimes, logistics, into account. In reality scope 3 consists of 15 emission categories. For manufacturing companies, nearly all emissions come from the categories ‚purchased goods‘ or‚ use of sold products‘. But because for these categories it is hard to collect data and to find quick solutions, companies often skip some of their most important emission drivers.

2. Sacrificing depth for coverage

Some companies are going to great lengths to estimate all scope 3 categories, while the results are only of use in sustainability reports – not for any meaningful mitigation plan. If you don’t know the impact of raw material X from supplier Y, you won’t be able to benchmark and make changes. If you don’t quantify, in detail, the impact of product use, how do you plan to enable engineers to make trade-offs during design? Given limited time and capacity it is important to focus on what matters and what can be changed. This will help you free up resources to get beyond reporting and increase granularity, identify opportunities, exploit them, and measure progress.

3. Believing you’re set up for change

Quantifying scope 3 emissions is actually the easy bit. Many companies don’t realize that large parts of their organization need to work differently to make the necessary changes. In manufacturing companies, for example, the research and development and the procurement teams are at the heart of change. These teams decide the kind of products to make, materials and processes to use and where to buy. Providing them with the tools and data they need to make granular decisions at speed will determine if a company progresses towards its targets or not. Modern technologies are of aid when it comes to enabling them.

4. Thinking your teams want change

You might consider this mildly cynical, but most successful companies don’t want to change. Today buying green electricity and investing in carbon sequestration projects are the two main levers used to reduce a company’s impact. It enables companies to demonstrate reductions, without improving. Change is a threat to the status quo and therefore needs robust incentivization for it to happen. Internal carbon prices and targets are an effective way of repurposing current incentive models to drive decarbonization at all levels of the company.

5. Expecting suppliers to cooperate

The time and effort spent on collecting data about the emissions of suppliers are often underestimated. Carbon footprints are increasingly becoming a differentiating factor in procurement, which is good news. However, suppliers fear that transparency on carbon will inevitably expose intellectual property or disadvantage them against other suppliers. Many suppliers are therefore hesitant to be transparent and even those who want to cooperate are lacking expertise in generating this kind of data.

 

What is the cost of your BOM? It is a simple question, yet difficult to answer.
Calculating product costs is essential for financial guidance and strategic planning. Knowing that it can make all the difference when it comes to the profitability of your products, it is important to choose the right method to calculate product cost. Although companies used to rely on partner and supplier quotes, should-cost analysis is now more widely used by top organizations.

 

What is a should-cost analysis?

Product cost is a complex concept including a wide array of costs, from supplier and transportation margins to materials prices. Companies operating worldwide also have to deal with taxes, labor regulation, and heterogeneous standards. They can vary a lot depending on the season of the year or the country where your operations are based. However, these costs often have nothing to do with the core price of the product.

So to remove the parasitic parameters from the equation companies are now turning to should-cost analysis.

A should-cost analysis is a way to assess what a product should cost based on raw materials, manufacturing processes, and distribution costs. Unlike strategic sourcing, which relies on partner and supplier quotes, should-cost analysis can use reverse-engineering and calculations performed internally to predict the price of a product more accurately.

 

How accurate is should-costing?

It is important to understand that the goal of should-costing isn’t to give perfect estimations of product costs. It is a leverage tool to use for supplier negotiation. Suppliers might correct some aspects of the calculations, but that is where the negotiations come in. The basis for the discussions will be set by you, giving you the upper hand on the situation.

In the end, this will ensure that even if you don’t end up paying the prices you projected, you will still significantly drive the costs down and most likely put you ahead of your competition, whether you choose to then rethink your product margins or lower the selling price of your products.

How to perform a should-cost analysis

The first step in a should-cost analysis is to determine where the calculation comes in during the product design process. Depending on the stage, you will have to cope with non-optimal decisions: material choices, design options, and so on. The closest you are to the beginning of the product design process, the easier it will be to deal with these parameters.

The second step is to list all the materials and processes involved in your product composition. Some knowledge of product manufacturing is important here: the more you understand the whole value chain, the more your estimations will be close to reality. The should-cost analysis relies on a lot of assumptions, so results can only be as good as your hypotheses.

Finally, once the list is complete, cost management, engineering, and design teams need to gather data and perform calculations to estimate the product price.

Why choose should-cost analysis?

This method presents a lot of benefits to companies. Used correctly it is a growth driver as it is a useful tool for supplier negotiations: negotiations plus should costing is proven to be more efficient than negotiation alone, with potential savings going from 5% up to 20% according to product costs experts. When translated into profit gain,reducing product costs by just 5% can drive an 85% increase.

Yet should-cost analysis can typically take weeks to complete and quickly become obsolete if it is not supported by appropriate tools and data.

Fortunately, new technologies like data fusion and artificial intelligence emerged that can change the story. It is now possible to confront hundreds of data streams updated every day in seconds, transforming outdated analysis in dynamic reports.

The next generation of product costing

Makersite combines the best of modern technologies to help companies worldwide to improve their cost management processes. All you need to do is to import your Bill of Materials (BOM) and we do all the rest!
Our platform is intuitively designed to quickly evaluate product performance across several dimensions: cost, but also sustainability, environmental impact, and compliance.

We gather hundreds of product data sources, from raw material cost to manufacturing and distribution. With more than 20 product databases included, Makersite is constantly updated to reflect changes in costs, markets, competitors, science, regulations, and product evolutions.

So if you want to perform extensive and dynamic should-cost analysis, we would be happy to hear from you and set up a personalized demo!

The current situation has created a lot of disruptions in the global supply chain network. With a reduction of more than 30% of the global supply chain activity, chances are you will have to find alternatives for your products and integrate them quickly. That is why we put together this guide on how to successfully manage product change.

 

Find alternatives

It goes without saying: in order to find the best option for your product, you need to have candidates. If that step is arguably the hardest one, there is still a couple of options available to you.

The first one is to check with your current suppliers. They know your needs, so they often can help source alternatives that can be relevant for you. They also already went through your compliance checks, which helps limit compliance risks associated with the onboarding of new suppliers.

Another option is to look for alternatives online or in manufacturing catalogs, by comparing the different specifications with the engineering requirements to find alternative components which might be suitable for the application. However, this approach can be time-consuming and prone to error as each specification needs to be checked and compared individually. This may work for changing a single component in a small assembly but for a Bill of Materials with hundreds of changes, these manual checks can add up quickly.

Finally, you could use dedicated tools to help you like Octopart, Mouser or Makersite. With the advances of AI and Big Data, these tools can combine thousands of databases to automatically find relevant options for your product,  helping to save time and provide more accurate results. Alternatives are automatically suggested by comparing key performance requirements, cost and compliance considerations to find other components to meet your needs. Some systems even include supplier finder applications to locate alternative suppliers for key products, components or materials in your supply chain.

 

Check your options against your requirements

After gathering suitable alternatives, the next thing to figure out is whether or not the candidates match your requirements. From the design and engineering aspect to the compliance aspects, it is crucial to rely on a thorough due diligence process.

If most companies still rely on manual process to investigate their suppliers, they are time-consuming and often fail to go past Tier 2. In order to avoid unfortunate replacements, you can use tools to automatically check product and suppliers options against multiple criteria, including localization, cost, compliance, and sustainability.

Communicate the change across the organization

It can be hard to maintain effective communication throughout the value chain, especially during product changes. With cross-functional teams working on different products across different portfolios and increased remote working, it becomes even more challenging.

However, it is crucial to keep everyone updated to avoid issues across the supply chain such as missing drawings or outdated specifications which could lead to problems down the line in testing, production, or even with the end customer. Product Data Management tools are especially valuable here since they allow your teams to stay on the same page and collaborate more effectively. Downstream, supplier collaboration tools can help you accelerate due diligence processes and mitigate compliance risks beyond Tier 2.

 

Keep on improving

Even during this crisis, product changes can be the opportunity to improve your product. Whether you decide to go local for your supply chain, to switch to more sustainable processes or to pick a more efficient alternative for your packaging, there are plenty of ways you could change the way your products impact your business and the environment.

If you would like to go further, you can sign up for these simple tutorials that we hope could be helpful for anyone struggling to assess the impacts of COVID-19 on their supply chain. 

And, if you would like to know how Makersite can help you and your teams to find out how to successfully manage product changes, you can contact us here.

Product development is core to business success: we covered this relationship in our previous article on “Good design, good business?”. In the following article, we make the case for the “digital twins” – a novel approach to enabling better product development processes within manufacturing organizations.

Today, digital twins are an operational tool used to represent a product’s properties and status in a live setting. They provide companies with the ability to detect physical issues sooner, predict outcomes more accurately and potentially build better products. These digital footprints include massive, cumulative, real-time, real-world data measurements across an array of dimensions that are put together on modern, scalable technology.

What if we used the same principle with a focus on supporting designers and engineers so they can make more informed decisions about their products across aspects like regulatory environments their products will be sold in, alternative technologies that may give them a cost or environmental advantage, or market requirements that should drive design criteria?

In other words, what if we could use data to represent and model a product’s financial and non-financial performance, a digital twin, allowing teams to quantify and improve business outcomes together, in real-time, right from first designs?

 

Development strategies today

Modern products are increasingly complex, customer specific, competitive and technology advantages are becoming smaller. Companies are scrambling to keep up or get ahead. In this environment, the most significant drivers of product success[1] broadly rely on the quality of execution, the creation of sustainable product advantage and competent cross-functional teams. 

For most companies, these goals translate into a strategy around increasing development speed and product success rates, while reducing complexity and business risk from early on. Different companies approach these with different degrees of focus depending on how they are positioned, but they all invariably integrate core elements of each into their strategies.

For example, some companies focus more on standardization and modularization programs to simplify manufacturing and design with the aim of reducing lead times, and production costs while increasing quality and efficiency. Others focus on better ingredients/designs and sustainable supply chains & operations with the aim of differentiated product offerings and reducing operational risk.

A common theme to all strategies, however, is the pursuit of better communication about the product as early as in the design phase as possible, with the goal of reducing innovation cycles (and therefore time to market) and creating more successful product designs through cross-functional solutions to market requirements. This goes beyond messaging or project management tools and is typically brought about through attempts at centralizing design, manufacturing and market information across the organization.

 

So, what is the problem?

 

The balancing act slows things down

Modern product design and management are extremely tedious due to the difficulty to collect and connect heterogeneous product data like risks, impacts, and costs to designs. Any change to the design modifies the equilibrium of all other criteria. Teams constantly transfer data such as design (CAD, PLM), materials, environment & health (EHS), risk, compliance, sales (CRM), and procurement between systems and suppliers with the aim of finding decent compromises across the multitude of design criteria. That constant back and forth slows down new product development and therefore is very often skipped/short-circuited in many organizations.

 

Adaptability is not easy, nor cheap

What further complicates matters is that companies today are compelled to adapt to an ever-increasing breadth of market requirements (the “tightening noose”), many of which were not at the forefront just a decade ago. These considerations include things like stricter regulations, new science about health concerns of different materials etc.

All this is new and complicated for engineers. For example, circular economy considerations mean that the afterlife of products and their environmental impacts must be thought through from the design stage. This information is not just difficult to come by, but also difficult to understand for non-experts. The solution that most companies adopt is to add additional specialist resources at the end of the design chain that typically end up being not as integrated as they would need to be to derive significant value.

 

Current tools don’t really help

Some companies spend millions on customizing ERP and PLM systems to suit new requirements and supplement data gaps with expensive purchases, which for most organizations is not just too costly, but also with average implementation times of 2-4 years, is just not a here-and-now solution. Tools that exist today are single purpose/department, expert tools that are very often offline in nature – none of which support the need for collaborative yet secure interactions, and cross-functional solutions to modern day design challenges.

What results very often is stop-gap solutions to new challenges at best, and procrastination of addressing the challenges at worst. Both these approaches only delay the inevitability of losing the competitive advantage to younger and more agile companies as we have seen in almost every sector today.

 

The digital twin

It could be argued that the concept of the digital twin was born out of the need to bring together disparate information in real-time, to understand how different environmental and performance characteristics interact with each other. This simplified the task of predicting how products would behave under different conditions (CAD). Digital twins also filled the gap that sensor systems left – understanding how multiple factors interact with each other to affect performance. Having all that data centralized and time-synchronized removed the complexity of manually connecting the data together to find relationships and simply diverted cheaper and faster computational power to the problem. It also solved the issue of adding more data sources/considerations into the mix dynamically. Teams that employ digital twins, spend more time trading insights than data. 

Why not use the same approach for design criteria? That’s what we do at Makersite. We connect best-in-class data for costs, markets, risks, materials, regulations, environment, health, suppliers and more to create a “digital twin” of product design or formulation. Tools are built-in to create reports, apps, and maps to visualize clearly the data that matters.

That way dependencies between product ideas and their business performance become immediately transparent. Once the digital twin has been created, data flows continuously from several sources into a single system. That allows teams to collaborate on the same project and understand the impacts of design changes on parameters outside of their core expertise.

Combined with unique security features that enable data exchange with suppliers while protecting everyone’s IP, Makersite technology allows teams to analyze how products are made and how to improve performance across the full value chain and life-cycle. They can get immediate answers about the product, people, planet, and profit – and the connections between them.

For more information about how Makersite works and how it can help with product development, check out our solutions.

Contact us to get your BOM analyzed.

[1] ‘Product development in the automotive industry: crucial success drivers for technological innovations’, Int. J. Technology Marketing, Vol. 3, No. 3, pp.203–222

Extending Life Cycle Assessment (LCA) throughout your entire Supply Chain

Understanding the impact of your products goes beyond analyzing your sole business. With the rise of customer awareness, companies are held accountable for their impact on the world and being able to pinpoint a product footprint along its entire supply chain is now a crucial competitive argument. In order to provide this level of accountability for their products, companies need to perform more extensive Life Cycle Analysis (LCA), in a shorter amount of time.

But how to conduct in-depth LCA with the increasing complexity of supply chains?

What is LCA?

Life Cycle Analysis (LCA) is the globally acknowledged method used to evaluate the environmental impacts of economic activities. It serves as a valuable tool for businesses by providing insights for decision-making processes, aiding in the development of products, processes, or buildings, and contributing to educational endeavors. Additionally, LCA plays a crucial role in product labeling, supply chain management, waste management, and pollution studies. The practices of LCA are integrated into the ISO 14000 environmental management standards and align with frameworks like the Green House Gas (GHG) Protocol, ensuring comprehensive environmental assessment and management practices.

Why is LCA important?

LCA allows for a holistic approach to understanding the environmental impacts of a product or process throughout its entire life cycle. This includes all stages, from the extraction of raw materials, through production and distribution, to use and disposal. By analyzing each stage, LCA can identify potential areas for improvement in terms of resource usage, emissions, and waste generation. This information is valuable for businesses looking to reduce their environmental footprint and promote sustainability. LCA also allows for the comparison of different products or processes, providing a basis for informed decision-making. Additionally, with growing consumer awareness and demand for sustainable products, LCA software can serve as a tool for companies to differentiate themselves in the market.

Product Life Cycle and LCI

A product’s life begins with raw material extraction through materials processing. After manufacturing, and distribution, the product enters its use phase, during which it can be repaired and maintained. The end of life of the product is usually disposal or recycling.

The inputs from nature associated with all these stages include water, energy and raw materials. The outputs include releases of substances to air, land, and water. These inputs and outputs from and to nature are called “flows”. To develop an inventory of flows for the life cycle of a product, a model is constructed using data on inputs and outputs. This data is called the Life Cycle Inventory (LCI).

Inventory analysis is followed by impact assessments. This phase of LCA evaluates the significance of potential environmental impacts based on the LCI flow results. It consists of the selection of impact categories, their classification, and their impact measurement.
Due to globalization, the rapid pace of research and development of new materials and manufacturing methods are continually being introduced to the market. Many consumer goods for example, such as electronics, foods or apparel are redesigned frequently, creating a need for ongoing data collection. Similarly, the transformation of the energy mix toward renewable sources can fundamentally change the environmental impact of entire countries or sectors for the better.

Data quality is crucial

When comparing different products with one another, the analysis is only as valid as its data.

• Comparable, accurate and current data are crucial for analysis. They often aren’t.
• Traditional Life Cycle Assessment Data typically does not connect to other dimensions, such as costs, waste, impact location, water footprints, and others.
• LCA results are often only used by LCA experts, rather than the designers and engineers who conceive products.
• Complex products take a long time to compute to get results, sometimes days.

Extend LCA to your entire supply chain

Makersite augments LCA data with other impacts, keeps data current and networked and dramatically increases computing speed for impact analysis.

Once imported, Makersite automatically establishes connections between Unit Process data and other data, such as regulatory, chemical, material or cost information across supply networks. This allows product teams to augment their LCA data and seamlessly optimize product designs not only for the environment but also for other criteria.

Pulling connected modeling data into the design stage is paramount for product development teams. It reduces the total development cycle and extends the use of lifecycle data into other domains and across the supply chain.

Makersite provides a next-generation approach to life cycle assessment through open and connected data. This extends to integrations with other applications on the desktop as well as in the cloud.

Fast LCAs and powerful APIs

Makersite’s benefits are numerous:

• Greatly augment your LCA data: make it visual and instant.
• Makersite’s computing power renders LCA data in seconds.
• Connect to other tools, such as CAD, via Makersite’s powerful API and enable ECO-Design across your organization.
• For companies in time-pressured industries, moving from stage gate process to lean and concurrent design efforts helps shorten development timelines.

If you would like to see how our product sustainability tools could transform your business, don’t hesitate to reach out to us for a personalized demo.