<strong>Data-Driven Business: A Playbook for PLM Vendors To Capitalize on Data: Part 2</strong>

Data-Driven Business: A Playbook for PLM Vendors To Capitalize on Data: Part 2

In my article today, I want to continue the discussion I started in Part 1 of my article about turning PLM into a data-driven business.

Enterprise software businesses have long been focused on delivering high-quality software solutions to their customers. Companies are run by processes. The control of company processes was a key element of how software vendors concurred businesses. As part of the control, vendors hold companies hostage, by keeping their data inside the systems and databases. This is how the first MRP and later ERP brands were built. Their business was surrounded by controlling company finance and organizing production and transactions needed to support them. Similar processes happened around sales and customers. This is how large CRM software suites were built controlling important activities related to company business. CAD and growing engineering software became the foundation of what we know today as PLM. In addition to that, it is important to mention the MES business, which focuses on the organization of shopfloor operations.

For a long time focus on process orchestration was the key element that provided a strong foundation for enterprise software. However, in today’s increasingly data-driven world, simply providing software is no longer enough. In order to truly succeed, enterprise software businesses must also be able to turn data into a business. By leveraging the vast amounts of data available to them, these businesses can gain a competitive edge and deliver even greater value to their customers.

In Part 1 of my series of 3 articles about how PLM vendors can capitalize on the data, I described why data is a fascinating opportunity for PLM businesses and how turning “Data” into a first-class citizen in PLM software can PLM vendors to realize the full potential of the capabilities of PLM platforms.

To make data a “first-class” citizen in the enterprise environment is a big deal. It will be the first step towards sustainable data management architectures and new PLM paradigm shifting. It is an opportunity for new and existing vendors to create a digitally connected enterprise. While digital transformation can potentially free data from legacy systems, it is important to approach this process carefully and ensure that data ownership, governance, and security are still properly addressed. Making data broadly available can support a new generation of PLM services.

Today, I want to explore what needs to be done in order for PLM data platforms will become a foundation of data drive enterprises. I will talk about why turning data into a business is key to success in the enterprise software business, and how businesses can leverage data to drive success.

From Data Standards to Standard APIs

For years, the problem of data was mostly focused on data formats and standards. Data was belonging to software and was stored in databases or files. To bring data in and out, required to agree on special formats and standards. This is a story of data interoperability and data integrations. Most software packages used proprietary protocols and APIs to access information. In the jungle of system integrations, accessing data via databases and SQL was one of the most popular ways, but was bringing a risk of data integrity, breaking vendor schemas, and additional complexity.

Things are changing now with modern standard REST APIs that simplify access to data and break data silos. This is a standard code that helps you to build connections and integrations easily. The APIs provide a universal translation that can be used in writing applications in multiple programming languages. It allows modern SaaS products to communicate fluently with any application. Modern REST APIs techniques also solve the problem of version compatibility when supported correctly by vendors. The standard-based code will remain the same after the upgrades. Once API is publicly available, vendors should not be changing these endpoints to SaaS services, which ensure the stability of integration protocols.

Online Data Services

Think about the transformation of product lifecycle management applications into SaaS products with standard REST API. This is where the digital thread begins. Product lifecycle management (PLM) SaaS software is transforming into online data services that is available to everyone to support direct data communication and provide access to information. Of course, everything is controlled by licenses and robust access rights.

One of the key advantages of these new Online Data Services is the ability to access data from anywhere, at any time. This makes it easy for businesses to collaborate and share information, regardless of physical location. Online data services also offer greater scalability, as businesses can quickly and easily expand their storage capacity as needed, without the need for additional physical infrastructure.

Another benefit of online data services is the improved security. Many online data services use advanced security measures to protect against data breaches and unauthorized access. This can provide peace of mind to businesses and individuals alike, as they know that their sensitive data is being protected. In addition, online data services often offer regular backups and data recovery options, which can help businesses recover from a disaster or data loss event. Overall, the benefits of online data services make them a valuable tool for businesses and individuals looking to leverage the power of data in their operations.

Data, Tenant Models, and Manufacturing Networks

Multi-tenant data models refer to a way of designing databases and software applications where a single instance of the software or database serves multiple customers or tenants. This approach allows different customers to use the same software or application while keeping their data logically separate from each other.

Multi-tenant data models play a critical role in facilitating instant data sharing and collaboration among multiple parties. By enabling different users to access the same software or application, while keeping their data isolated and secure, multi-tenant data models allow for seamless collaboration without compromising data security.

In the context of data sharing and collaboration, multi-tenant data models provide a number of benefits. For one, they enable real-time collaboration, allowing multiple users to work on the same data set simultaneously. This can greatly increase efficiency and reduce the time it takes to complete projects.

Multi-tenant data models also make it easy to share data with external parties. For example, a business may share data with its suppliers or partners, allowing them to access and analyze the data in real time. This can help to improve supply chain visibility and optimize business processes.

The multi-tenant model provides the next step in the PLM platform capability to organize communication between suppliers and contractors allowing everyone to get access without the need to export data to another format. It is a foundation for the future of manufacturing networks.

What is my conclusion?

Manufacturing companies can gain a lot from the switch to modern PLM software solutions that make data a first-class citizen. Switching from propriety databases to standard APIs, unlocking data to become available as product data services, and developing multi-tenant platforms that can allow companies to share data and communicate in real time will build a future foundation of data-driven business for manufacturing. Just my thoughts…

PS. In my last (Part 3) article about Data Driven Business for PLM vendors, I will talk about how data will become a source of additional revenue. Stay tuned.

Best, Oleg

Disclaimer: I’m co-founder and CEO of OpenBOM developing a digital cloud-native PDM & PLM platform that manages product data and connects manufacturers, construction companies, and their supply chain networksMy opinion can be unintentionally biased.


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