PLM and the Cloud, by Siemens PLM Software
Written by Eduard Marfà (pictured) Director Teamcenter, EMEA Marketing, Siemens PLM Software
Product Lifecycle Management (PLM) and product design have been applications that have been slow to move to the Cloud, for a number of reasons. But as companies increasingly switch on to the flexibility, scalability and affordability that Cloud platforms offer, so adoption has increased.
Though many improvements have come to PLM software over the years, the overall framework hasn't changed much. Cloud-based PLM offers a significant change.
Furthermore, as designers have needed to share product data with stakeholders both inside and outside the organisation, so the need for PLM in the Cloud has grown. As such, this call has come from a range of stakeholders including engineering, operations, manufacturing, quality, procurement, regulatory and even marketing.
That said, there are still challenges that need to be addressed if this approach is to get buy-in from everyone.
Many companies recognise the benefits of cloud-based PLM solutions. However, the lack of confidence in existing approaches to privacy and data security remains one of the biggest obstacles to a faster market penetration of PLM Solutions on the Cloud. There are also lingering concerns around availability and predictability.
Fortunately, the general adoption of Cloud continues and security and authentication is a top priority for most Cloud providers. This can allay many of these fears, and modern encryption can ensure data is protected in transit. This is evidenced by the fact that even many government departments and defence forces have deployed some of their software systems on the Cloud.
In principle, PLM is just like any other application that has migrated to the Cloud. But because these design tools can require large files, complex 3D visualisations and high-speed responsiveness, there has been a lot of reluctance to move the applications and associated data to the Cloud. Here, the increasing ubiquity of high-speed connections and the proven responsiveness of big name Cloud providers has brought the technology up a level whereby users can get a similar experience using PLM on the Cloud than using it as a local application.
For some, there is also a fear that a Cloud approach will lead to vendor lock-in. But application freedom can be assured by implementing PLM in the Cloud through an Infrastructure-as-a-Service (IaaS) platform, rather than Software-as-a-Service (SaaS).
PLM Solutions on the Cloud need to be thought of as a utility. It needs to always be there, offering ready and secure access to data whenever it's needed. It also needs to offer predictable service levels with no ebbs and flows based on competing traffic or geographical location.
The benefits of Cloud in PLM
With these concerns addressed, there are a lot practical benefits that a cloud-based deployment approach brings to PLM.
As with all Cloud-based systems, this allows for fast deployment on a dynamically scalable infrastructure that can adapt to changing project needs.
It also enables IT departments to shift their focus to application management rather than infrastructure management, while built-in redundancy ensures business continuity. These two factors can deliver significant cost savings, as deploying systems on the Cloud avoids the need to purchase and maintain hardware assets, and dedicate facilities and personnel to support them.
The global geographic footprint of certified cloud providers enables greater application and service reach with lower latency. The ability to use virtualisation, and allocate and split resources easily makes it simple to rapidly deploy new environments for in-house testing, development and training, that be spun up and shut down as needed.
In essence, similar to on-premise PLM, PLM in the Cloud is a helpful tool for product data management because it allows manufacturers to consolidate information about product development, streamline change orders and requests and improve communication with suppliers.
But these technological benefits are only the top of the iceberg when it comes to the potential of PLM in the Cloud.
Cloud collaboration and innovation
When implemented correctly, a PLM system deployed on the Cloud can bring new levels of collaboration and innovation to an organisation.
To be at its most useful, up-to-date product data must be seamlessly accessible across business lines to both suppliers and customers—especially in high tech organisations that often outsource. Design and manufacturing requires the input of a number of different departments, who need to collaborate on changes and send manufacturing data at high-speed, which makes cloud-based applications ideal for data transference across geographically spread organisations.
Because the Cloud is location agnostic, a Cloud PLM system is accessible to anyone with an Internet connection. As such, it is an easier way to manage complex product data in fast-moving and geographically dispersed organisations, enabling a new level of 'concurrent engineering'.
Those firms that have embraced the Cloud for PLM are now rethinking their traditional approaches to innovation and are seeking more collaborative forms of product development.
Cloud-based PLM enables users across the organisation to easily derive knowledge from previous product development cycles, coordinate disparate design activities and analyse a wide range of metrics ranging from time-to-market to bill of materials.
Cloud and mobility
The final piece of the Cloud PLM puzzle comes in the form of mobility.
Cloud services PLM and design systems are notoriously resource hungry applications. Because a Cloud platform enables the 'heavy lifting' to be done on the back-end, it opens up a number of possibilities for accessing applications through mobile devices.
Engineers are never going to do complicated designs on a tablet or smartphone. But being able to perform simpler tasks like reviewing changes, communicating with other stakeholders or checking simulation results through a mobile device further enhances the levels of collaboration and productivity.
Combining these effects highlights how the Cloud has the potential to enable smarter decisions, which can help manufacturers produce better products, more efficiently and collaboratively.
Product innovation is the core of any enterprise, but manufacturers are facing more competition and faster development cycles than ever before. On the other hand, design and engineering teams are increasingly geographically spread, and the use of outsourcing is on the rise.
The end result is that collaboration is ever more important, but also more difficult. This is what makes a Cloud-based deployment approach to PLM so compelling. It enables anyone, anywhere to securely access the most up-to-date designs – creating smarter decisions – and to collaborate and innovate with colleagues across the business, as well as partners outside the organisation to make better products.
But in order to achieve this, the challenges and fears surrounding Cloud PLM have to be addressed. This is why Teamcenter solution from Siemens PLM Software is built on an open, future-proof architecture. Because it's based on an IaaS model, customers have the flexibility to use their preferred technology platform and provider, giving them peace-of-mind regarding security, accessibility and performance, while allowing them to use the tools they are already familiar with.
When everyone has access to the tools, data and resources they require, the can collaborate more closely. This makes it possible to gain unprecedented leverage on the product design process and deliver real innovation and differentiation.
NTT DATA Services, Remodelling Supply Chains for Resilience
Joey Dean, the man with the coolest name ever and Managing Director in the healthcare consulting practice for NTT DATA and is focused on delivering workplace transformation and enabling the future workforce for healthcare providers. Dean also leads client innovation programs to enhance service delivery and business outcomes for clients.
The pandemic has shifted priorities and created opportunities to do things differently, and companies are now looking to build more resilient supply chains, none needed more urgently than those within the healthcare system. Dean shares with us how he feels they can get there.
A Multi-Vendor Sourcing Approach
“Healthcare systems cannot afford delays in the supply chain when there are lives at stake. Healthcare procurement teams are looking at multi-vendor sourcing strategies, stockpiling more inventory, and ways to use data and AI to have a predictive view into the future and drive greater efficiency.
“The priority should be to shore up procurement channels and re-evaluate inventory management norms, i.e. stockpiling for assurance. Health systems should take the opportunity to renegotiate with their current vendors and broaden the supplier channel. Through those efforts, work with suppliers that have greater geographic diversity and transparency around manufacturing data, process, and continuity plans,” says Dean.
But here ensues the never-ending battle of domestic vs global supply chains. As I see it, domestic sourcing limits the high-risk exposure related to offshore sourcing— Canada’s issue with importing the vaccine is a good example of that. So, of course, I had to ask, for lifesaving products, is building domestic capabilities an option that is being considered?
“Domestic supply chains are sparse or have a high dependence on overseas centres for parts and raw materials. There are measures being discussed from a legislative perspective to drive more domestic sourcing, and there will need to be a concerted effort by Western countries through a mix of investments and financial incentives,” Dean explains.
Wielding Big Tech for Better Outcomes
So, that’s a long way off. In the meantime, leveraging technology is another way to mitigate the risks that lie within global supply chains while decreasing costs and improving quality. Dean expands on the potential of blockchain and AI in the industry.
“Blockchain is particularly interesting in creating more transparency and visibility across all supply chain activities. Organisations can create a decentralised record of all transactions to track assets from production to delivery or use by end-user. This increased supply chain transparency provides more visibility to both buyers and suppliers to resolve disputes and build more trusting relationships. Another benefit is that the validation of data is more efficient to prioritise time on the delivery of goods and services to reduce cost and improve quality.
“Artificial Intelligence and Machine Learning (AI/ML) is another area where there’s incredible value in processing massive amounts of data to aggregate and normalise the data to produce proactive recommendations on actions to improve the speed and cost-efficiency of the supply chain.”
Evolving Procurement Models
From asking more of suppliers to beefing up stocks, Dean believes procurement models should be remodelled to favour resilience, mitigate risk and ensure the needs of the customer are kept in view.
“The bottom line is that healthcare systems are expecting more from their suppliers. While transactional approaches focused solely on price and transactions have been the norm, collaborative relationships, where the buyer and supplier establish mutual objectives and outcomes, drives a trusting and transparent relationship. Healthcare systems are also looking to multi-vendor strategies to mitigate risk, so it is imperative for suppliers to stand out and embrace evolving procurement models.
“Healthcare systems are looking at partners that can establish domestic centres for supplies to mitigate the risks of having ‘all of their eggs’ in overseas locations. Suppliers should look to perform a strategic evaluation review that includes a distribution network analysis and distribution footprint review to understand cost, service, flexibility, and risks. Included in that strategy should be a “voice of the customer” assessment to understand current pain points and needs of customers.”
“Healthcare supply chain leaders are re-evaluating the Just In Time (JIT) model with supplies delivered on a regular basis. The approach does not require an investment in infrastructure but leaves organisations open to risk of disruption. Having domestic centres and warehousing from suppliers gives healthcare systems the ability to have inventory on hand without having to invest in their own infrastructure. Also, in the spirit of transparency, having predictive views into inventory levels can help enable better decision making from both sides.”
But, again, I had to ask, what about the risks and associated costs that come with higher inventory levels, such as expired product if there isn’t fast enough turnover, tying up cash flow, warehousing and inventory management costs?
“In the current supply chain environment, it is advisable for buyers to carry an in-house inventory on a just-in-time basis, while suppliers take a just-in-case approach, preserving capacity for surges, retaining safety stock, and building rapid replenishment channels for restock. But the risk of expired product is very real. This could be curbed with better data intelligence and improved technology that could forecast surges and predictively automate future supply needs. In this way, ordering would be more data-driven and rationalised to align with anticipated surges. Further adoption of data and intelligence and will be crucial for modernised buying in the new normal.
These are tough tasks, so I asked Dean to speak to some of the challenges. Luckily, he’s a patient guy with a lot to say.
On managing stakeholders and ensuring alignment on priorities and objectives, Dean says, “In order for managing stakeholders to stay aligned on priorities, they’ll need more transparency and collaborative win-win business relationships in which both healthcare systems and medical device manufacturers are equally committed to each other’s success. On the healthcare side, they need to understand where parts and products are manufactured to perform more predictive data and analytics for forecasting and planning efforts. And the manufacturers should offer more data transparency which will result in better planning and forecasting to navigate the ebbs and flows and enable better decision-making by healthcare systems.
Due to the sensitive nature of the information being requested, the effort to increase visibility is typically met with a lot of reluctance and push back. Dean essentially puts the onus back on suppliers to get with the times. “Traditionally, the relationships between buyers and suppliers are transactional, based only on the transaction between the two parties: what is the supplier providing, at what cost, and for what length of time. The relationship begins and ends there. The tide is shifting, and buyers expect more from their suppliers, especially given what the pandemic exposed around the fragility of the supply chain. The suppliers that get ahead of this will not only reap the benefits of improved relationships, but they will be able to take action on insights derived from greater visibility to manage risks more effectively.”
He offers a final tip. “A first step in enabling a supply chain data exchange is to make sure partners and buyers are aware of the conditions throughout the supply chain based on real-time data to enable predictive views into delays and disruptions. With well understand data sets, both parties can respond more effectively and work together when disruptions occur.”
As for where supply chain is heading, Dean says, “Moving forward, we’ll continue to see a shift toward Robotic Process Automation (RPA), Artificial Intelligence (AI), and advanced analytics to optimise the supply chain. The pandemic, as it has done in many other industries, will accelerate the move to digital, with the benefits of improving efficiency, visibility, and error rate. AI can consume enormous amounts of data to drive real-time pattern detection and mitigate risk from global disruptive events.”