One of the most common issues for businesses, particularly those working in large organizations, is locating and accessing their data. In 2022, a joint survey conducted by Sinequa and CMSWire found that a third of employees can’t find the information they’re looking for in their workspace, which includes heterogeneous file repositories, enterprise systems, etc.
With growing external pressures, such as decreasing time to market and threats of disruption to the global supply chain, leaders need their teams to be operating effectively. They can no longer afford to implement inefficient processes and technologies. This is where innovations in AI are taking center stage.
Setting the scene
Imagine you are part of a large manufacturing organization. It’s likely you’re juggling multiple product lifecycle management (PLM) systems, and these systems are your lifeline, organizing and categorizing your product engineering information.
But there’s a catch. The search function within these applications is somewhat limited. It’s primarily a full-text search with sparse use of ontologies and semantics. So, it’s not easy to stumble upon data that might be related to your query but isn’t explicitly searched for.
In addition to this, most of your product information doesn’t reside within PLM environments. It’s scattered across collaborative apps, shared file systems, other enterprise systems like CRM or ERP, and various repositories. Suddenly, finding relevant content feels like finding a needle in a haystack.
For users, this maze-like journey from one enterprise application is not just frustrating; it’s a roadblock to operational efficiency and time-to-market. In the manufacturing industry, this can create a domino effect, triggering longer product development cycles, quality issues, and increased resolution time. When these challenges pile up, they can reflect poorly on the final product and your company’s reputation, potentially affecting customer satisfaction.
For manufacturers, digital threads are invaluable solutions that enable the continuous flow of product information from design through manufacturing and support. This not only spans the entire product lifecycle within a company but can extend outward and include suppliers and customers. Over the last year, leaders have been seeking ways to revolutionize these systems, and AI-powered search has given them the capability to do just that.
At the start of 2023, ChatGPT became a household term, and it has had ramifications for businesses across sectors. However, within manufacturing, leaders have sought ways to use its capabilities without its associated problems, such as data confidentiality, hallucinations, and a lack of transparency regarding sources.
Combining these capabilities with search is just one-way leaders have looked to resolve these problems. Neural search models use natural language processing (NLP) to scan enterprise data and generate accurate results for questions. This can give users specific responses using their company data, reducing time to insight, and empowering all employees to accomplish their jobs efficiently.
When linked with generative AI, you can produce automated summaries of findings generated by accurate and traceable data. Furthermore, with retrieval augmented generation (RAG), organizations can harness the power of the large language models without ever risking the leakage of confidential information to external parties.
The benefits for engineering teams are remarkable:
- Instant and accurate answers to critical questions.
- Unprecedented insights driven by data on parts and products.
- Seamless access to data across all product lifecycle management (PLM) systems.
- A streamlined workflow that empowers your entire team.
Maintenance and support teams also can leverage this cutting-edge technology to find relevant answers within vast technical documents during testing procedures. Instead of painstakingly combing through endless pages and manually compiling reports, these powerful tools offer concise summaries based on accurate, traceable data specific to your enterprise. It’s the perfect solution for firms embracing Gen-AI while ensuring utmost accuracy and avoiding any pitfalls.
Making changes for innovation
By using the available technology in the right way, leaders can start their journey to enhanced innovation and productivity. The first step is to eradicate information silos and empower your team to make more informed decisions based on data you already have but is challenging to access.
In today’s interconnected world, the power of the digital thread cannot be overstated. By weaving together the strands of technology, leaders can unlock a treasure trove of benefits. It boosts productivity by providing secure, real-time access to vital data and logistics. Additionally, unlocking “lost” knowledge or undiscovered content allows you to capitalize on prior research, regardless of its source or format, while maintaining security protocols.
Ultimately, these strategies promote faster innovation, enhance collaboration between internal and external users, and encourage your business to stay competitive in a fast-paced industry.