Resource Library – Cloud vs On-Premise PLM: Side by Side Comparison Eguide2019-01-03T13:38:13-04:00

CLOUD VS ON-PREMISE PLM

Debunking myths & setting the record straight

Cloud products dominate the enterprise technology landscape. Increasingly, core business functions are powered by the cloud software, like CRM (Salesforce), ERP (SAP S/4HANA), and even CAD (Onshape).

But there is one holdout. Product lifecycle management (PLM).

According to CIMdata, only 10% of the PLM market was cloud-based in 2017 — far below any other business-critical software.

Cloud Adoption for Business Critical Software

Sources: 1 / 2 / 3 / 4

But we think cloud PLM isn’t just the future.
It’s here, and it’s here right now.

This guide will cover:

  • The difference between cloud and on-premise (on-prem) PLM solutions.

  • Why cloud is the most cost-effective approach to PLM.
  • How cloud PLM achieves enterprise security.
  • What we mean when we talk about scalability.
  • Why cloud PLM implements in weeks, not years.

Cloud / On-premise Differences

Technically, the difference between cloud and on-prem PLM solutions is simple.

Cloud PLM is when the solution is delivered over the internet, and the software and product data that it empowers are stored in the cloud (e.g. a datacenter somewhere operated by someone else, like Amazon or Microsoft).

On-premise PLM is when the PLM software and the product data it uses is stored in a local server, owned and managed by the company using the PLM product.

But that difference has a number of implications — most significantly, cost, security, scalability, and implementation processes.

Now that we’re all on the same page, let’s get to the good stuff.

Cost

Multi-tenant cloud PLM is far less expensive than it’s on-premise counterpart, opening up the world of PLM to smaller organizations.

Cloud PLM

Hosting cost is shared among all the clients on a server.

Hosting and server maintenance is completed by specialists, driving down costs with comparative advantage.

Implementation fees are included in the per-user licensing fee.

No upgrade/rev-up cost.

No capital outlay at the start of the project.

On-premise PLM

Cost of building, scaling, and servicing servers is borne solely by the company.

Servers are maintained by internal staff, increasing IT headcount and cost.

Significant implementation fees drive up activation costs.

Annual upgrades are the norm.

Significant capital outlay as the organization buys server hardware.

  • Hosting cost is shared among all the clients on a server.
  • Hosting and server maintenance is completed by specialists, driving down costs with comparative advantage.
  • Implementation fees are included in the per-user licensing fee.
  • No upgrade/rev-up cost.
  • No capital outlay at the start of the project.
  • Cost of building, scaling, and servicing servers is borne solely by the company.
  • Servers are maintained by internal staff, increasing IT headcount and cost.
  • Significant implementation fees drive up activation costs.
  • Annual upgrades are the norm.
  • Significant capital outlay as the organization buys server hardware.

28% of on-premise PLM revenue came from implementation services in 2017.

(CIMdata)

0%

Security

Security is a continuing challenge for PLM because end-users are reluctant to store product data, the “crown jewels” of manufacturing businesses, in the cloud. In reality though, cloud applications have proven themselves to be more secure than their on-premise counterparts again and again with reliance on automated systems over error-prone manual processes.

Cloud PLM

Highly secure physical environment with 24/7 security, biosecure doors, and tiered security passes.

Automatic daily backups.

Rapid response security teams on-call 24/7.

Power and utility redundancies with generators and direct grid access.

Fewer server interactions so fewer potential vulnerabilities.

Automatic scaling reduces the risk of DDoS.

On-premise PLM

Physical environment might just be a basement or behind a locked door.

Manually-managed backups that may happen daily… or not.

Managed in-house by the IT team, who don’t have the capacity to work around the clock.

No power or utility redundancies.

Manually created server interactions, increasing software complexity and risk.

DDoS attacks remain difficult to defend against.

  • Highly secure physical environment with 24/7 security, biosecure doors, and tiered security passes.
  • Automatic daily backups.
  • Rapid response security teams on-call 24/7.
  • Power and utility redundancies with generators and direct grid access.
  • Fewer server interactions so fewer potential vulnerabilities.
  • Automatic scaling reduces the risk of DDoS.
  • Physical environment might just be a basement or behind a locked door.
  • Manually-managed backups that may happen daily… or not.
  • Managed in-house by the IT team, who don’t have the capacity to work around the clock.
  • No power or utility redundancies.
  • Manually created server interactions, increasing software complexity and risk.
  • DDoS attacks remain difficult to defend against.

The 60% of enterprises that implement appropriate cloud visibility and control tools in 2018 will experience one-third fewer security failures.

(Gartner)

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Scalability

How do you know what your PLM needs will be before you deploy? You don’t. But with cloud PLM, you don’t have to because adding more resources happens literally at the click of a button.

Cloud PLM On-premise PLM
Adding new resources doesn’t require additional hardware purchases. IT teams have to buy and spin up new servers to increase capacity.
Elastic computing means that spikes in demand (e.g. lots of users on at the same time) can be handled without affecting user experience. Spikes in demand are impossible to handle if the spike exceeds available resources.
New users can be added by simply purchasing more licenses. Adding new users requires significant hardware resource investment.
Scaling down is simple — just buy fewer per user licenses. Once the hardware is purchased, there’s little to gain from running fewer licenses.
Scaling up is instantaneous. Scaling up consumes significant time and resources.
  • Adding new resources doesn’t require additional hardware purchases.
  • Elastic computing means that spikes in demand (e.g. lots of users on at the same time) can be handled without affecting user experience.
  • New users can be added by simply purchasing more licenses.
  • Scaling down is simple — just buy fewer per user licenses.
  • Scaling up is instantaneous.
  • IT teams have to buy and spin up new servers to increase capacity.
  • Spikes in demand are impossible to handle if the spike exceeds available resources.
  • Adding new users requires significant hardware resource investment.
  • Once the hardware is purchased, there’s little to gain from running fewer licenses.
  • Scaling up consumes significant time and resources.

Implementation

Big PLM companies and their consultants made around $4.1 billion from implementation fees alone in 2017. In contrast, cloud PLM historically offers implementation fees about a third of what on-prem ones are, and increasingly, no implementation fees at all.

Cloud PLM On-premise PLM
No custom coding to get cloud PLM up and running. Significant (and expensive) custom coding needed to “turn on” the PLM.
Built for integration using simple APIs. Integrations and connections sold separately (and can cost $10,000 each).
Configurable workflows adapt to the organization. Organizational change management (OCM) needed to re-engineer a business to suit the PLM. This regularly costs 30-40% of the total PLM budget.
Up and running in weeks. 13-30 months is the average implementation time.
Implementation is free. Implementation can cost several million dollars.
  • No custom coding to get cloud PLM up and running.
  • Built for integration using simple APIs.
  • Configurable workflows adapt to the organization.
  • Up and running in weeks.
  • Implementation is free.
  • Significant (and expensive) custom coding needed to “turn on” the PLM.
  • Integrations and connections sold separately (and can cost $10,000 each).
  • Organizational change management (OCM) needed to re-engineer a business to suit the PLM. This regularly costs 30-40% of the total PLM budget.
  • 13-30 months is the average implementation time.
  • Implementation can cost several million dollars.

On-prem implementations take 2 years on average, vs
21 days for cloud PLM.

(SpringerLink)

Closing Notes

Cloud technology is changing how we buy and use software. And PLM is no exception. Cloud PLM allows small and medium-sized businesses to access PLM for the first time, while enterprise organizations increasingly looking on enviously at the rapid implementation and low cost. And as adoption of other cloud enterprise accelerates, the writing’s on the wall — cloud enterprise technology is here to stay.

The only question is: are you going to be an Early Adopter, or a Laggard?

Is cloud PLM right for you?

Find out with our free PLM evaluation.

Get My Evaluation
Upchain

We’re Upchain. We work with manufacturers to make product innovation easy. Our goal is to take product data beyond engineering while letting people use the tools they already know and love. With Upchain cloud PLM, people can work the way they want with a software that just… works.