Industrial enterprises face a wide variety of data challenges. With digital transformation, companies increasingly rely on data to differentiate products and services. However, the data challenges of siloed enterprise software systems can stifle the benefits companies may hope to achieve in these endeavors.
“Siloed-ness” is a common characteristic of legacy software and even many modern software systems. Individual functions or departments within a company might initially deploy software to help with their specific needs. But, as organizations mature, especially in the case of digital transformation, there is a natural progression toward functions and departments needing to provide more support to the business around them. It can be incredibly difficult to collaborate in this way if the software tools aren’t designed to do so. The result? Information and value is left siloed within individual departments.
To realize the full value of their data, industrial companies today are searching for ways to address siloed systems and the three critical data challenges they create: Duplicated efforts, multiple sources of truth, and data inaccessibility.
Below we explore these complications in more detail, how they impact a company’s ability to create value from data, and lastly, how implementing a digital thread strategy can resolve all three data challenges at once.
When the software systems along a company’s value chain are siloed, moving information from one to next is a drag on productivity and a common way to introduce errors. Imagine the chaos that would arise if you had to manually update your calendar across each of your devices for every invite, reschedule, and cancelation you receive. This is what industrial companies contend with on a business scale.
If systems are siloed there will always be a significant amount of manual work to be done transferring information between departments, functions, and even companies. The notion of relaying data, manually, from one system to another is a non-value-added step but often done by people since it requires some flexibility to adapt the data from system A to B to C. In addition to being error prone and time-consuming for the user, this manual process also slows down all the core business processes that rely on the data being duplicated.
If data is being duplicated across two or more software systems, then there will be an inherent data challenge: multiple sources of truth. Given multiple disparate software systems, which are each individually responsible for housing the same data and for enabling different activities along the value chain, there is ample opportunity for misalignment of goals and activities across departments and organizations.
For example, if the bill of materials of a product exists in a manufacturing execution system (MES) and a product lifecycle management (PLM) system, who is responsible for ensuring the two agree? When there is disagreement, the costs can be tremendous depending on what activity in the product lifecycle is impacted, how long it takes to identify, and the steps needed to resolve the issue. These kinds of disagreements can affect any department that shares data manually but keep their own records. Simply put, multiple sources of truth are just multiple opportunities for mistakes.
With digital transformation initiatives enabling more reactive and insight driven changes to products and services, the frequency that these systems need to be updated can increase exponentially. Without a digital process ensuring consistency across systems, every activity that accesses one of many “sources of truth” risks working from out-of-date or entirely false information.
Last, but not least, siloed systems inhibit the ability for employees across an enterprise to access data that could improve the accuracy and speed of their decision making. There are two ways siloed systems can cause this data challenge.
Primarily, siloed systems result in information obscurity. It can be difficult enough for employees to access data that rests somewhere outside their department, but the very existence of pertinent data outside their typical purview could be a mystery. Especially now that companies are collecting more and more data along the product lifecycle – from design to manufacturing and service. There can be treasure troves of data in one department that go unutilized by the broader organization, simply because people don’t know it exists or where to find it.
Compounding the issue of data obscurity is the poor implementation of role-based access, which often restricts data access to the specific roles or functions who most closely rely on it. This approach can inadvertently turn any function within the product lifecycle into an information bottleneck if the data proves valuable across roles or departments. It also has the effect of making any person with access to pertinent data a rogue data governance officer, burdening them with the task of disseminating data without the oversight often needed to ensure such activities are appropriately executed and accurately recorded.
A digital thread “closes the loop” between the physical and digital activities of an enterprise and in doing so enables continuity of data across departments and collaboration across functions to improve the product, the physical processes, and empower the people who are involved at every step.
This approach eliminates the data challenges of siloed systems by facilitating an end to end flow of data between departments and functions. With the proper strategy and tools, industrial companies today are implementing digital threads that can seamlessly move data up and down the product lifecycle to enable functions anywhere within a company to make better, faster decisions.
A digital thread removes the need for duplicated efforts and instead promotes value-add collaboration across departments. Further, by tracing provenance of data as it moves through an enterprise, a digital thread can ensure the integrity of information being shared and acted upon to eliminate the risks of maintaining multiple sources of truth.
To learn more about creating a digital thread and how it can help your organization address its data challenges, click here.
Will Hastings is a research analyst manager on PTC’s Corporate Marketing team providing thought leadership on technologies, trends, markets, and other topics. Previously Will was a senior analyst for ARC Advisory Group, where he conducted PLM and additive manufacturing research. Prior to ARC Advisory Group, Will was a lead mechanical design engineer for product development programs at Sensata Technologies.