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  • Greg Zajączkowski

Leveraging Infor Document Management as a Preparation for Tailor-Made AI Implementation

The Strategic Imperative of AI in Business

 

In an era marked by rapid technological advancements and a push towards digitalization, international manufacturing and trading companies are increasingly adopting innovative technologies to stay competitive. Artificial Intelligence (AI) stands out as one of the most transformative forces in this digital revolution, offering unprecedented opportunities to enhance operational efficiency, enrich customer experience, and redefine decision-making processes. At the heart of this transformation lies the integration of robust IT systems, with Infor Document Management (IDM) playing a pivotal role in preparing businesses for these AI-driven changes. This article delves deeper into the nuances of integrating IDM as a foundational step towards achieving a seamless and successful AI implementation, ensuring businesses are well-equipped for the digital challenges and opportunities ahead.

 




Set Clear Objectives First

 

Before diving into the complex world of AI and IDM, it's imperative for decision-makers to clearly articulate and set objectives for what they wish to achieve through this digital transformation. Establishing these objectives at the outset will guide the entire integration process, ensuring that every strategic decision and technological investment aligns with the broader business goals.

 

Understanding Business Needs and Goals

 

Begin by conducting a comprehensive analysis of current business processes to identify areas where AI can have the most significant impact. This might include targeting operational inefficiencies, enhancing customer service, or identifying new market opportunities. Furthermore, understanding how competitors and industry leaders are leveraging AI and document management systems will help in setting realistic and competitive objectives.

 

Defining Specific AI Objectives

 

Determine whether the objective is to streamline operations, reduce manual work, improve process speed, or use AI to create new products or services. For businesses focusing on customer satisfaction, objectives may include personalizing customer interactions or understanding customer needs better through sentiment analysis. Define how IDM will enhance document storage, retrieval, and security and how it will integrate with AI systems and other business applications.

 

Let’s imagine the following possible use cases of document or photo understanding:

1.      Shipment notification – warehouses can receive notification about upcoming deliveries from a variety of suppliers and forwarders. It’s common receive documents in PDF format from many smaller companies, and then retype them into ERP. Documents of different formats contain similar information, thus could be read and structured within ERP as a forecast of upcoming deliveries.

2.      Customer orders – your company in various locations receives orders by emails i.e. with PDF attachments. Certainly, biggest customers could an should be automated with strict EDI messages, but it will never be possible for all. AI can get rid of manual typing, experienced specialist can be relieved from mundane manual work, and can focus on analysis and planning.

3.      Quality photos of purchased raw materials or it’s palletization – documents doesn’t necessarily need to originate from outside of your company. If Your company happen to report photos of bad quality materials or packaging, features present on these photos such as dents, cracks, missing boxes, color defects can be automatically identified by AI models and if needed they can be summarized to quality controller for further review. Even more, based on identified problems Generative Language Model can quickly prepare short claim text as a proposal of claim email.

 

Technology exists for text, photo, audio AI processing exists for many years, it just needs to be tailored according to business needs. Examples above are just a tiny hint of possibilities,

 

Measuring Success

 

Establish clear metrics and Key Performance Indicators (KPIs) to measure the success of AI and IDM implementation. Consider factors such as time saved, error reduction, increased customer satisfaction scores, or return on investment. As both AI and business needs evolve, objectives should be revisited and adjusted accordingly, promoting ongoing learning and adaptation.

 

The journey towards AI integration is filled with strategic decisions and investments. It's essential for businesses to understand the vast landscape of AI and its wider implications. AI is not merely about technology; it's about fundamentally redefining business models, workflows, and decision-making processes. It promises to automate routine tasks, unlock new insights from data, anticipate market changes, and offer personalized customer experiences. However, realizing these benefits is complex, requiring a deep foundation of quality data, robust IT infrastructure, and a skilled workforce ready to leverage AI's potential. Imagine, if Your company will not engage with opportunities, but other companies on the same market will – how competitive position of Your company will look like?

 

Short introduction into Infor Document Management  (IDM)



Infor Document Management is a comprehensive solution tailored to streamline the way businesses manage, access, and secure their documents and digital content. It offers a centralized repository where documents of all types can be stored and organized, facilitating easy management and retrieval. This system supports both the scanning of physical documents and the importing of digital files from various sources, including direct imports from email attachments, enhancing the versatility and efficiency of document intake.

 

The platform boasts powerful metadata store as part of document, and search capabilities, allowing users to conduct full-text searches within documents, alongside advanced filtering options to pinpoint specific information quickly in relationship to i.e. ERP transaction or object. Version control is a key feature, maintaining records of document revisions and providing audit trails to track access and modifications, which is crucial for maintaining data integrity and compliance.

 

Workflow automation stands out as a significant function, enabling the creation of automated processes for document reviews, approvals, and updates. This is complemented by customizable notifications and alerts to keep relevant parties informed about important tasks or deadlines. Infor Document Management emphasizes security with role-based access control and advanced data protection measures, ensuring that sensitive information remains secure while complying with industry standards and regulations.

 

Integration with Infor's suite of products and third-party applications is seamless, offering users a unified experience that enhances productivity and supports business processes. The system is accessible via mobile, allowing for document management on-the-go, and includes tools for collaboration such as document sharing, commenting, and annotations, fostering teamwork and efficiency. Overall, Infor Document Management is designed to support digital transformation initiatives by improving information governance and streamlining document-related workflows.

 

The next part of article focuses on Infor Document Management, but it’s just an example of document management system, with metadata linked to i.e. ERP system. If your document archive with metadata is linked to i.e. ERP, that this article is insightful also for Your business.

 

Focused Deep Dive into Infor Document Management (IDM)

 

IDM emerges as a one of critical enablers in the journey towards AI readiness. Its capabilities in managing a variety of unstructured document formats and linking them to structured data in ERP databases make it a vital tool in the AI toolkit. Let’s explain this viewpoint.

 

Centralizing Unstructured Data

 

IDM has many features, however in this article we’ll focus on IDM as a document archive, its ability to store a wide array of unstructured document formats is crucial in today's varied business environment, where data comes in numerous shapes and sizes. By creating a centralized repository, IDM ensures that a comprehensive range of data is available for AI training and analytics, facilitating a more robust and informed learning process.

 

Linking Documents to Structured Data

 

One of IDM's standout features is its capacity to link unstructured documents to structured data within ERP systems. Every piece of unstructured data — whether it be invoices, contracts, photos, email or even audio recordings — can be associated with relevant data such as customer IDs, supplier details, order numbers, delivery dates, product names, quantities, and prices. This structured approach is critical for supervised machine learning (ML), where the AI learns to understand and process data based on known outcomes and relationships.

 

Facilitating Supervised Machine Learning

 

Combining diverse data storage and structured linking, IDM becomes an ideal facilitator for supervised ML. This form of AI learns from labeled training data, helping predict outcomes for unforeseen data. The pre-labeled and structured data in IDM reduces the time and complexity involved in training AI models, significantly enhancing the efficiency and accuracy of AI solutions. I.e. shipment notification containing item names and quantities might be more accurately recognized, if AI model can look at the history of how items on unstructured notification documents were linked to precise items from purchase orders.

 

To illustrate the practical application of Infor Document Management (IDM) in teaching AI models, consider the scenario of processing shipment notification documents. An AI model can be trained to recognize and process various supplier details, purchase order line details etc from transportation documents by utilizing IDM to manage and label these documents effectively. For instance, when a shipment notification is received in i.e. PDF format from a supplier, IDM can be used to extract automatically and  label PDF document with metadata such as the supplier name, shipment date, and list of items and quantity being notified. This labeling process involves marking specific information within the document, such as text denoting the supplier name or shipment ID, as relevant data points for the AI model. Through supervised learning, the AI model is then trained on a dataset of these labeled documents, learning to identify and extract the necessary information automatically for future documents, even if the format varies slightly from one supplier to another. This capability streamlines the process of integrating shipment information into the ERP system, reducing manual data entry and improving operational efficiency.

 

Expanding the AI Readiness with IDM

 

As businesses advance towards AI, IDM's role becomes increasingly significant. Its capabilities in enhancing data quality, automating processes, and providing advanced analytics and insights position it as an indispensable tool in the AI toolbox. By automating document-related processes and employing AI for advanced analytics, IDM helps businesses uncover insights that lead to better decisions and strategies.

 

Enhancing Data Quality with IDM

 

Quality data is the lifeblood of effective AI systems. Especially while taking into consideration the following aspect. Subject Matter Experts need to refresh knowledge i.e. on periodic trainings, similarly AI models need to be retrained to learn about new patterns in data. IDM helps maintain high-quality data through its governance and validation features. By ensuring that data is accurate, consistent, and reliable, IDM provides a solid foundation for AI systems to function effectively.

 

Conclusion

 

Successfully leveraging AI requires a series of strategic steps. This involves investing in necessary infrastructure, developing relevant skills within the workforce, and fostering a culture of continuous learning and adaptation. IDM may serves as a one of pillars in this journey, providing the data management capabilities essential for effective AI implementation.

 

Infor Document Management is more than just a tool for managing documents; it's a strategic asset that prepares international manufacturing and trading companies for an AI-driven future. By offering a robust platform for data management, IDM lays the groundwork for successful AI implementation around Infor ERP systems. As businesses navigate this digital transformation, IDM ensures not only efficient document management but also a seamless transition to an AI-driven business model. Despite the challenges, the right preparations and tools like IDM equip businesses for an exciting path towards innovation and growth.

 

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