Manufacturing project costs are high, especially when it comes to producing new products and parts. When mistakes and delays happen, unforeseen costs add even more to the total expense. There are many factors that can impact the smooth completion of a project. But when it comes to delivering on time and in budget, there are two key issues that large manufacturing operations struggle with:
For large manufacturers orchestrating complex projects, teams need to be assembled based on specific expertise and skillsets. However, finding the right expertise can be incredibly difficult. Expertise is often hidden in documentation, buried in SharePoint, or a private conversation on Slack. Team leaders often resort to recruiting who they know, which can result in knowledge gaps and inefficiencies.
In addition to knowledge gaps, successful collaboration within project teams is difficult. Different teams get information and perform tasks using different systems. Systems that are disconnected from each other, and use varying terminology to refer to the same things, causing confusion. Add to that the variety of languages used by a team spread across the globe, and the task of knowledge and information sharing becomes incredibly disjointed.
The result of this complexity is that teams waste valuable time searching across PLM systems, CRMs, and collaboration tools to find the project guidance they need. In many cases, the search is so frustrating that teams forge ahead without critical data that could support project assumptions, or just start over from scratch. This results in even more duplication of content and an increased chance of errors and delays.
A typical manufacturing organization can employ 30,000 workers or more, run dozens of operations all over the world, and use hundreds of different applications. Tens of millions of documents are created in these massive organizations, that are stored across an untold number of systems, locations, and formats. Just managing product information alone requires a multitude of systems, including PLM, ERP, PPM, and GCH systems. In fact, it’s not uncommon for a single part to yield at least three million documents.
In addition, many manufacturers have decades of documentation. But over time, part numbers change, processes change, and issues are solved. This leads to multiple versions of the same document, which makes finding the authoritative source of truth a challenge.
Without an intelligent search solution in place, surfacing ALL of the relevant information from the universe of siloed data is virtually impossible. What happens instead, is that employees recreate documents and solve the same problems over and over again, either because they didn’t know something similar already existed, or because it was too hard to find.
The same part might be designed and built multiple times because it’s easier than trying to track it down. Sales proposals are repeatedly written from scratch because other usable versions are inaccessible. Teams waste hours solving a problem that had already been addressed in the past.
This behavior not only adds to the information overload but more concerning, it reduces productivity and causes delays that can lead to a lawsuit.
The central issue at hand here is how to harness the huge amount of data and information that lives within manufacturing organizations. If manufacturers can connect data silos and give employees a single point of access to find what they need, productivity will increase, and errors and costs will decrease.
Intelligent search is the solution. With intelligent search, manufacturers can unify digital repositories, business applications, and communication platforms to give development engineers a complete view of information to make the best decisions possible.
By connecting all relevant information sources and surfacing critical documentation, past issues, and available expertise, manufacturing organizations can reduce costly production errors and delays.
The beauty of a well-designed intelligent search solution is that engineers get a familiar and intuitive search experience. Instead of searching across multiple repositories, they can use one, central place to uncover insights, even within unstructured data sources. They can find the answers they need quickly, and also find experts and expertise within the organization, boosting efficiency and minimizing duplicate work.
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