It has been almost 5 years since Autodesk turned the switch “PLM cloud” on. Tech-clarity blog – Autodesk’s announced PLM solution 360 Nexus – so what? can take you back in the history.
Autodesk put a lot of emphasis behind the announcement, with CEO Carl Bass bringing up his famous anti-PLM rap where he said the only companies with a PLM problem were Dassault (Sytemes), PTC, and UGS (now Siemens PLM). His message now is that “we did not want to do PLM until we could do it right” and that the time has come.
Fast forward into 2017, all PLM vendors are offering some sort of the cloud PLM. Things are heating up in cloud PLM universe – the debates about true vs false cloud can be heard very often. You can check cloud PLM buyers’ guide 2015.
But probably the most important and interesting thing to learn about is cloud PLM adoption. PLM research and consulting outfit CIMdata decided to bring clarify and announced collaborative research program about cloud PLM. Here is an interesting passage:
The research program includes several elements, including an initial Webinar highlighting the key issues. The Webinar will also introduce a global survey to learn more about industrial organization cloud adoption processes and status. Interviews with thought leaders from Sponsors and their lead customers will be published on the CIMdata.com blog and actively promoted on social channels by all participants to encourage broader discussion on the topic and to promote survey participation. In addition to materials developed with the Sponsors, CIMdata will also publish the results more broadly for use by members of the PLM Economy.
According to Mr. Stan Przybylinski, CIMdata’s Vice President of Research, “Cloud-based solutions are a fact of life in many other enterprise software domains, but adoption in the PLM market has been spotty. Helping to better understand why is one of the main goals for this research. This will also be the first step in documenting how industrial companies are moving their core product and process development work to cloud-based solutions.”
According to TenLinks article, research program will be collaborative sponsored by 4 leading CAD and PLM vendors:
To kickoff this research program, CIMdata enlisted several leading PLM solution and service providers as founding sponsors: Autodesk, Dassault Systèmes, PTC, and Siemens PLM Software. The extended research program team will collaborate to help identify the crucial issues facing potential cloud adopters and lessons learned from companies that have made this change.
As it is hinted by CIMdata, cloud PLM business is not going through the roof and all PLM vendors are interested to learn what are inhibitors of cloud PLM adoption. While I look forward to learn more about CIMdata research, the announcement made me think about what makes cloud PLM to go slower than vendors want. In the past few years, I had many discussions with users about cloud software, cloud PLM and cloud adoption (disclaimer – I’m CEO and co-founder of openBoM developing cloud based BOM and Inventory management system). Based on my experience and business consulting service, I can bring a list of top 8 potential inhibitors of cloud PLM services (note – I ranked them in order of their influence).
1- Concerns about security, data privacy and data protection. Although security is usually scored as #1, I can say that companies are much less concerned about that compared to what I’ve heard 5-7 years ago. Most of companies are adopting variety of cloud services and learning how to deal with cloud and security.
2- Dependencies on legacy IT system. The longevity of PLM and related systems is amazing. And each (even SMB) manufacturing company has some system in place to manage product data and development processes. It is very hard to jump from existing system and established processes to something new. So, legacy system status quo is a significant inhibitor to move into fully blown cloud PLM strategy.
3- Interoperability and Integration difficulty. Directly connected to the previous topic. Integration of cloud system is not easy compared to existing desktop and client-server technologies. SQL hacking and Excel-ware cannot help and, as a result, companies are slowing down to adopt new cloud systems.
4- Control over data, users and applications. Control is easy when data is in SQL database in IT department or in Excel spreadsheet on the network drive. Cloud brings some uncertainty here. The questions about data availability and control are not uncommon.
5- Accessibility of services. What if service won’t be available tomorrow. On premise PLM can exist decades after vendors stopped developed them. It cannot be said about cloud services. This is a legit question and many companies are asking what will happen if company will shutdown cloud PLM tomorrow.
6- Internet connectivity. With all respect to internet providers, outage might happen and companies are asking how to access mission critical systems in that case.
7- Lock-in with a specific service provider. Companies believe that by controlling databases and IT servers, they can easy migrate from one provider to another. Although, it is not as simple as companies might think about, cloud-service brings an additional level of uncertainty.
8- Cloud management difficulty. There are so many old-school people in engineering IT. Many of them are not very much familiar with cloud tech and can be defensive about new cloud PLM services.
What is my conclusion? I look forward to CIMdata research. Cloud PLM made a huge jump for the last several years. Still, cloud PLM is not a mainstream PLM option these days. Most of PLM providers took an existing PLM paradigm, system and architecture and moved it to the cloud. While it is a big step by itself, it might be not enough to change a trajectory of PLM adoption. Just my thoughts…
Want to learn more about PLM? Check out my new PLM Book website.
Disclaimer: I’m co-founder and CEO of openBoM developing cloud based bill of materials and inventory management tool for manufacturing companies, hardware startups and supply chain. My opinion can be unintentionally biased.