PLM Single Source of Truth Evolution and Data Management Solutions

Manufacturing companies are always looking for ways to improve their operations and increase efficiency. One way to do this is by implementing a PLM system. For many years, PLM systems very promoted and sold the idea and value of a “Single Source of Truth” (SSOT), which established a single place for the company to store product information, and its lifecycle. PLM helped you manage your data more effectively and ensure that everyone has access to the most up-to-date information. Fundamentally, a PLM system can help you make better decisions based on real-time data. How much of these PLM ideas are left on paper and in PowerPoint presentations will be the topic of a separate blog post. The idea of SSOT is a powerful one and until now it holds value and supports a business case for many enterprise software.

However, modern manufacturing reality and modern technologies are transforming the original idea of SSOT. In my article today. I’d like to speak about the evolution of a single source of truth, the values of modern SSOT for the product development process, and how PLM software vendors can solve modern data management challenges, analyze data, improve data governance and bring relevant data to multiple systems.

The idea of SSOT and Why It Is Hard To Achieve?

In a typical manufacturing company, the data lives in various silos across the enterprise. It is very hard for companies to make a decision without getting access to all relevant data and even more, to operate without access to the same information. The situation is typically called “siloed data”. To solve the problem and to establish reliable data sets that can be used by everyone, companies came up with the idea of a single source of truth (SSOT).

Fundamentally, the idea is bold, simple, and great. What can you say if someone suggests you organize the data management solutions in a way everyone will access the same data and solve all data management problems. However, here is a problem. While “silos of data” are usually presented as a bad thing, on the other side, the reason why silos exist are naturally coming from the way companies are operating and managing their business. Each department is using tools and these tools naturally create data and, later form what is called “a silo”.

These two dimensions create the biggest paradox in data management governance and data management. Killing silos is nearly impossible because it requires killing all departmental systems. At the same time, operating in silos makes the product development process and product lifecycle management very inefficient.

Over the course of time, companies were coming up with different strategies that swung from one side to another. Introducing one system to manage all data was one of them. Choosing the dominant system was hard and raised many debates (including political). Using a central data storage for all data (data warehousing and master data management) was another big step. Later companies tried and sometimes were very successful in establishing an “enterprise data bus” to flow data between systems and people.

Larger companies with more resources achieved better results in the establishment of a single repository for all data and centralized data management. In smaller companies, with fewer resources, the problems often were unsolved.

PLM and SSOT in product development and manufacturing 

Manufacturing organizations’ data management systems are typically aligned with fundamentals. of the product development process including design, engineering, production planning, manufacturing, sales, maintenance, and support. Things are naturally distributed among departments, however, such an organization’s data management is not simple. The main reason for that is that each department is connected with others by the process. The data lives in each department are connected and data management and handover between departments and processes are becoming a huge problem and root cause of many process inefficiencies.

Past SSOT technological realizations

For many years, companies were trying to come up with technological solutions to solve the problem of data silos, and the organizing of a single source of truth for data access. Here are some of the most popular solutions:

1. One system for All
2. Central database to collect all data from silos
3. Enterprise Bus and Workflow / Process Orchestration

For the last 2-3 decades PLM vendors and other technology providers made multiple implementations of SSOT solutions. One database was probably the most prominent solution and was provided in multiple variations from just a database (RDBMS) to hold information, enterprise software platforms (PLM, ERP, etc), and a variety of specialized databases – warehouse, product information management, etc.

One system for all was more a dream than a realistic realization. Although, some vendors even today strategically believe that they can build a platform capable to provide an all-inclusive solution for holistic data management to cover an entire product lifecycle from early ideation to maintenance, support, and recycling.

Enterprise Bus and several types of workflow (later business process management) solutions were born out of the idea that integration as a technology can be used to create an overall platform for enterprise companies. Most of these companies successfully trajectory into a future business enterprise software platform.

Modern Transformations and Distributed SSOT

The modern manufacturing environment brings new types of challenges to organizations of a single source of truth. Here are the most visible ones that redefined and expand the number of problems any SSOT and data management strategy must face.

1. Go beyond a single company
2. Data complexity
3. Demand for intelligence

The manufacturing world is changing. Here are the top 3 trends that I can see outside that can impact massively how future SSOT solutions can be built. One of the biggest changes is a switch from a single company view into multiple sources (companies or even bigger – network) environment. Companies are not working alone anymore and they work as a network of companies connected together.

The complexity and scale of data management are growing. It includes the complexity of products that need to be manufactured as well as logistical routes around them. Last, but really important is the huge demand for data, data intelligence, and everything else that is associated with the world of data.

In my next article, I will speak about possible technologies to solve these new challenges.

Conclusion 

The digital world is transforming the way we work, collect and use information. In the past we wanted to buy a physical vinyl or CD with music, later we did the same, but virtually, now we just want to get access to this in a reliable way.  In the old fashion driving process we wanted to remember the road or have a paper map helping us to drive. For the last 30 years, we transformed from the system that centralized everything in the car (map, PDF, GPS nav) to a system in which we can access the right information at the right time contextually. The system itself doesn’t hold all info, but collect it on demand in a smart way to make it available to you when you need it. Getting back to PLM and product development, while SSOT is a powerful paradigm, the way realization comes is changing. What was the attempt to have a SSOT as a file or as a database is shifting to formation of infrastructure and services helping to organize and get the information as you need it for all stakeholders in the product development process including customers. It is a big transformation and it includes technological adjustment, architecture shifts, changes in user experience, and business models. 

In an essence, this is what digital transformation is all about. Just my thoughts… 

Best, Oleg 

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