3 Ways Manufacturers Can Leverage Insight Engines

This article was originally published on Manufacturing.net.

As distributed manufacturing gains adoption by some of the world’s largest companies, products are finding their way into the hands of customers faster than ever before. But in the process, companies are becoming increasingly disconnected and less efficient in new areas.  Unlike in traditional manufacturing, where materials are assembled in remote, centralized factories and shipped to customers, distributed manufacturing takes place at multiple, decentralized plants where products are assembled closer to the customer.

Global manufacturing

The process of leveraging a network of geographically dispersed manufacturing facilities connected over the Internet helps eliminate many of the inefficiencies of traditional manufacturing. However, distributed manufacturing creates new challenges in the form of separate entities, languages and processes.

Teams once gathered under a single roof are now spread across multiple sites, working on projects and programs unique to their local area. These distributed teams are inadvertently scattering knowledge and data across continents and systems, creating information silos that leave workers disconnected.

Content and data have been scattered across a myriad of applications and repositories without any means for end users to surface accurate information with any confidence. In some cases, access to critical institutional knowledge, insights and innovation is restricted to a small few. As a result, disparate teams are spending countless hours making and solving the same problem over and over again, lowering productivity and delaying projects.

A digital solutions manager at a global manufacturing firm once told me, “We had thousands and thousands and thousands of places where our documents were shared, managed by check-in, check-out. In fact, we once had thousands of applications with no search capabilities.”

But once information is accessible from a single place, there are no longer countless teams scavenging for data and insights. With insight engines, manufacturers are bringing the best people together for new projects. Critical parts are easier to locate instead of rebuilding or re-designing them. Even proposals and RFP responses are being developed faster with information found and shared from other RFPs.

These improvements are the result of insight engines that combine cognitive analytics, artificial intelligence and NLP (natural language processing) to helps computers understand, interpret and manipulate human languages, dialects and patterns.

This technology helps manufacturers quickly respond to changing conditions and identify products, parts and components across multiple data sources despite their distance from one another. Here are three ways manufacturers can leverage insight engines to rediscover their synergies and avoid mistakes.

Building Teams Through a Patchwork of Data

Many companies struggle to create the best teams for new projects because expertise is hidden in large organizations with multiple divisions and product groups. Sometimes this task is made more difficult by employees who fail to enter their background and experience in their HR profiles or update them with new skills or certifications.

AI-powered insight engines leverage NLP to surface information from large volumes of data stored in hundreds of millions of files, and thousands of repositories and databases to uncover work histories, experience on different projects, expertise, training and education in order to locate experts. Projects employees have worked on, languages they write in, and locations where they’ve traveled are all easily queried and analyzed to identify experts within the company.

Avoiding Duplication of New Parts

In a distributed environment, it’s difficult to find parts across systems and continents. Sometimes it’s easier to make new ones. That’s because parts are generally indexed by labels, which can be difficult to identify correctly. As a result, the exact same part is recreated, sometimes up to five times, each version with its own label.

This is a complete waste of time and money. And when a part is recreated, there’s a greater chance of a new flaw being introduced, which can be catastrophic in industries like transportation or medical devices.

With insight engines, parts data can be contextualized for engineers to identify duplicate parts and eliminate duplications. For any company with a broad base of engineers, the cost savings from this approach can be enormous.

Increasing the efficiency of proposal development

Companies with multiple departments and divisions often fail to share technical information for sales proposals and RFPs. Consequently, proposals for an opportunity in one part of the world with many of the same requirements as others in different markets or regions must be developed from scratch.

And, if questions arise during the proposal process, it is time-consuming and difficult to get answers from engineers. Acquiring new customers in a complex environment with a highly engineered, configurable project is time-consuming by its nature. The inaccessibility of data makes it worse.

Insight engines surface information in context across emails, databases, and records. With this information in hand, companies can respond faster to sales opportunities and present a common face for the company overall.

In all three of these scenarios, information and insights are securely surfaced from content and data in every application and every repository from every location across globally distributed companies, which enables teams to cultivate, improve quality and take advantage of new opportunities.

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Ferring Pharmaceuticals selects Sinequa and Atos to boost Global Cognitive Search Capabilities for R&D

ferring-logoAs a testament of Sinequa’s fast growing footprint among leading life sciences organizations, we are very excited to announce that Ferring Pharmaceuticals selected Sinequa and Atos to boost its global cognitive search capabilities. Sinequa’s Cognitive Search & Analytics solution was recently deployed at Ferring Pharmaceuticals with Atos as the consulting and integration partner to empower the organization’s Global Pharmaceutical R&D group to look deeply into vast scientific research data sets in order to generate new insights and accelerate innovation

Headquartered in Switzerland, Ferring Pharmaceuticals is a research-driven, specialty biopharmaceutical group active in global markets. A leader in reproductive and maternal health, Ferring has been developing treatments for mothers and babies for over 50 years. Today, over one third of the company’s research and development investment goes towards finding innovative treatments to help mothers and babies, from conception to birth. Ferring has its own operating subsidiaries in nearly 60 countries and markets its products in 110 countries.

In today’s world, especially in the life sciences industry, it is impossible for humans alone to search, process and analyze all the world’s available scientific and research data, Sinequa’s Cognitive Search & Analytics platform  makes this scientific knowledge accessible any time by any given researchers. As Sinequa continues to expand its footprint in this very competitive industry, we are very pleased to count Ferring Pharmaceuticals among our customers. Together with our partner Atos, we are committed to help Ferring improve insights and facilitate innovation.

- Stéphane Kirchacker, vice president Sales, EMEA at Sinequa

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Atos, Sinequa’s strategic global premium partner was selected to design, implement, support and operate the platform at Ferring Pharmaceuticals to deliver the highest possible relevancies on search for the R&D teams in different locations.

Sinequa’s solution is bringing the power of AI to Enterprise Search to provide Ferring a “future proof” solution that offers a whole range of opportunities for future innovations. The dilemma of pharmaceuticals is to find the needle in the haystack – scientists need to screen tens of millions of documents from internal and external sources, from structured and unstructured data for identifying relations between genes, drugs, Mechanism of Action (MoA) and finding the right skilled subject matter experts. Other departments like Regulatory & Compliance, Legal & IP, Marketing & Sales, Clinical Trials, HR and more can benefit from customized Search-based applications on the same platform – finding relevant information instantly for fact-based decisions – no waste of time anymore.

-Alex Halbeisen, Expert Sales Big Data & Analytics at Atos

 

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Streamline Global Manufacturing with the Information Driven Supply Chain

This article was originally published in Manufacturing Business Technology.

A new kind of manufacturing company is emerging that leverages big data and analytics for a unified view of the supply chain. This new approach provides supply chain insights that enable these organizations to respond quickly and decisively to changing conditions despite geographically dispersed suppliers and customers. And yet at the same time, they can also pursue long-term opportunities by identifying products, parts and components across all the data sources where supply and demand spans states, countries and continents.

No matter the supply chain model, customers expect quality service, on-time delivery and the right product every time, which can be challenging if an organization manages erratic supply and demand on a global basis.

For most organizations, products consist of numerous parts that move through the enterprise and its network of suppliers, creating a need for parts logistics. Every part number within the organization takes on a life of its own and every department must have access to all the information surrounding it.

As organizations build new products, and service existing ones, they need cohesive and comprehensive visibility for a unified view of the entire supply chain.  This approach helps organizations optimize their supply chain and increase responsiveness by focusing on achieving greater visibility into products and parts inventory. Organizations that focus on these objectives can tighten the gaps in their supply chain and enhance their overall operations.

Supply Chain Unification

A unified view of the supply chain connects the enterprise and suppliers seamlessly to various applications and databases—such as enterprise resource planning, a data warehouse and customer relationship management systems.

This connected environment helps organizations keep abreast of the manufacturing process and supply chain management, and share relevant information across design, engineering, procurement, quality control and more. From understanding customer needs to building requirements, product prototyping and selling products, everything is streamlined and simplified across disparate systems.

By adopting a unified view of the supply chain, organizations can see what parts are in stock, which suppliers they re-order from and if those suppliers have available inventory. This gives engineers visibility into the specifications of components, the mean times between failures
for components, discontinuation plans and recent negative reports. It also promotes accurate shipping expectations and on-time delivery, while connecting all departments and partners in the supply chain into one efficient manufacturing shop.

Finding the right part information when and where needed

An information-driven supply chain makes it easier for workers to search and locate specific parts for production. Workers can create alerts to be notified when relevant information surfaces. Empowered and informed workers can then concentrate on manufacturing products on schedule.

A unified view of the supply chain helps engineers know who has previously worked with each part and learn from their experiences. If a component is found faulty during production, engineers could spend days trying to find who completed the original design. A unified view of the supply chain helps pinpoint the most knowledgeable workers and provides immediate access to information about the component and its design specifications. By empowering engineers, organizations are better able to meet customer demands.

This approach also empowers sales with information about specific parts to understand when to sell a specific version, and to know who to talk to if they need more information. Customers then get a confident, knowledgeable sales associate to help them make the right decision.

Knowing how and where to get parts in a hurry

Organizations must be able to respond immediately to customers who need replacement parts and immediate service. If a part is not available, they must know expected shipment dates, transit times and who can supply it. This is increasingly challenging with globally distributed suppliers and a dispersed customer base.

A unified view of the supply chain can resolve this issue by giving customer service representatives visibility into all parts across the enterprise, regardless of location, repository or format in which the information is stored. It can also extend access to information from supplier sites and applications.

To assist customers with support requests, customer service representatives need to be aware of past problems and how to identify and resolve them. With a unified view of the supply chain, they immediately know the parts associated with a problem and how it can be fixed.

In the final analysis, managing the supply chain is about information access. Although many applications are necessary to manage information at different stages of the supply chain, a unified view provides cohesive visibility across all applications that manage information about products, suppliers and customers. It is a critical part of streamlining and optimizing the use of an organization’s supply chain.

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