Efficient information management: A shortcut to effective information management for IT decision-makers based on our learnings from a wide range of customer projects.
The digital transformation has revolutionised information management in companies. IT decision-makers face the challenge of providing an effective IT infrastructure to facilitate information management. In this blog post, we share our insights from various information management projects to help IT departments make faster progress.
Phase 1: The digital transformation of information management
In the early days of enterprise IT solutions, basic tools such as drives and Outlook servers were often used. Over the years, this has evolved greatly, from Microsoft 365 to intranet solutions and project management tools. But despite these advances, the complexity of information management has steadily increased.
Statistics show that employees now use an average of 5 to 6 different data sources to get the information they need. This does not even take into account the numerous add-ons and little helpers that are integrated everywhere. A realisation that is becoming more and more apparent: Not all users use every application to the same extent, and not all systems are used in the same way by all employees.
Power users, who use tools intensively, and occasional users, who rarely access them, emerge. The variety of applications configured differently in different departments leads to further complications. Some employees are already completely attuned to digitalisation, while others still work mainly in old data silos.
Especially for occasional users, orientation in this complex environment is difficult. Due to limited resources, not all users can be trained in all applications in detail. Surprisingly, increasing digitalisation does not necessarily lead to increased efficiency, but rather to increased complexity when it comes to finding the right information.
Phase 2: Frustration spreads
Initial assumptions that digitisation would make information management easier are overtaken by reality. While the realisation that there will not be THE one solution may not be surprising, the difficulty staff face in coping with the growing number of systems is often underestimated. Additional steps, such as internal surveys, are taken to capture the reasons for dissatisfaction. This reveals that staff complain that access to internal information and responsibilities for different areas of the systems are unclear.
One problem is emerging: the information is available in the systems, but finding it is difficult. The search is often a by-product and designed differently in each application, which leads to frustration on the part of the users. Hours are spent searching in the various data silos, asking colleagues or re-generating knowledge that has already been compiled.
The question of how to better structure the data in the systems is raised. In elaborate workshops, approaches are worked out on how files can be better labelled and organised. Training materials are produced to familiarise staff with the new structures.
Phase 3: Growing frustration about information management
Frustration about information management is growing. Staff point out the challenges they face. However, IT departments have difficulty in properly assessing the extent of the problem. This is partly due to the silent majority, but also because not all employees are aware of the technical possibilities.
Finally, the need for solutions is increasing, especially due to the trend towards artificial intelligence (AI). Use cases need to be defined that enable quick access to information in the dynamic business world. Employees in support and call centres need quick access to customer data, marketing departments need up-to-date studies for campaigns and product information, and in general, employees need to be able to familiarise themselves quickly with new topics.
Phase 4: Artificial intelligence revolutionises information management
The search for solutions leads to various approaches to master the challenges described. This is where enterprise search and generative AI come into play.
Enterprise Search enables access to decentralised systems from a central point. Access rights are taken into account. An example of this is “amberSearch“. The challenge of poor findability of information is solved by combining enterprise search and generative AI, in this case “amberAI“. This enables documents to be found independently of the search functions of the various systems. The previously laboriously maintained tags are no longer necessary.
Phase 5: The solution in information management is amberSearch
A combination of enterprise search and generative AI, as with “amberSearch”, can overcome many of the challenges described. Decentralised systems are made accessible, and the discoverability of information is drastically improved. The system enables one-click integration per system and a user-friendly interface similar to Google.
If IT managers had had access to such solutions earlier, they could make their information management much more efficient and avoid costly mistakes.
In today’s dynamic business world, efficient information management is crucial. The combination of enterprise search and AI-powered search can help IT managers control information chaos and provide employees with fast access to relevant data.