Efficient Knowledge Management in Purchasing

Procurement expectations are rising. Complex markets, different locations, field operations, and increasing data sets pose new challenges for purchasers. Intelligently linking and evaluating data is one of today's business-critical success factors.

The existing knowledge of a purchasing department is enormously broad, from offers to orders to supplier lists to project-specific RFP documents or negotiation strategies. The numerous pieces of information from interaction with external partners and the various company departments are often not centrally retrievable. Welcome, Mindbreeze InSpire!

Many companies have different storage locations, such as network drives, document management systems for versioned storage of offers and contracts, archiving systems, bid portals, or other specialized applications. In addition, product life cycle management tools contain valuable information about the product life cycle of components used.

It is becoming increasingly difficult to obtain an overall view of the available information stored in many different data sources (structured and unstructured). To act quickly in complex situations, a comprehensive view must be available to derivate concrete measures.

More companies are increasingly turning to intelligent knowledge management solutions such as insight engines. Insight engines combine enterprise search with artificial intelligence (AI) functions and structure existing knowledge in the company from all connected data sources. Instead of a manual search in the individual applications, insight engines access the entire knowledge base with just one search query.

In addition, they extract the relevant results and provide them to the user in clear 360-degree views. These solutions supplement the hits with context-relevant additional information.

The insight engine always considers the respective context of the user (such as role, department, application, workflow information, etc.) and their authorizations. All access rights are stored directly with the data sources and checked with every search to note changes on short notice.

Time and Location-Independent Access to the Knowledge Base

With numerous connectors, the various corporate data sources are connected to the insight engine and merged into a highly efficient knowledge database (index + graph). The information base updates itself continuously, analyzes and interprets the results, and establishes correlations between the information.

The query preview function is particularly convenient; users can quickly browse and filter results in advance. When interacting with the search hit, the user automatically switches to the corresponding application. Thanks to the mobile search function, information can be retrieved via all mobile devices. It is also possible to call up data even if the associated applications are not installed, as the preview function enables access to the content.

Dynamic filters and facets can be used to further specify and structure the results. Intelligent solutions offer the option of saving required information across multiple searches or transmitting it collectively to colleagues – whether in the company, home office, or on the road.

Insight Engines Understand Data and Users

The way people search for information has changed significantly over the last few years. Instead of keywords, users formulate actual questions – similar to what they know from interacting with other people (dialog-based exchange of information). Insight engines use a variety of speech recognition and artificial intelligence methods to identify the different parts of a sentence (nouns, verbs, adjectives), their meaning, and their relationships and dependencies.

Using Natural Language Processing (NLP), they capture and process human speech. Individual words, as well as entire sentences and text contexts, are identified. As a sub-discipline of NLP, natural language understanding (NLU) ensures that the intention of the query is interpreted. In short, insight engines can understand, process, and adequately answer naturally formulated questions.

Insight engines adapt their performance to the individual needs of the user. They analyze user behavior, identify the user's needs, and adjust the relevance of information accordingly. For example, the system classifies frequently accessed or processed documents as more important. This results in a model that automatically prioritizes and proactively provides relevant information based on past search queries, interactions with hits, etc.

One Step Ahead

Insight engines have established themselves as a central element of knowledge management in companies. They create a powerful tool primarily concerned with data analysis, understanding, and appropriate preparation. A uniform and complete view of a supplier or products are crucial to continuously optimizing purchasing processes, margins, and quality for one's company and the ability to react quickly and flexibly to situations.