All relevant data on the table at last

by Dr. Helmut Abels and Andreas Bruns

Modern information technologies make even unstructured information quickly and efficiently accessible. This avoids errors due to information that is not accessible or not available at the right time. Even scheduling can benefit from this, as the following example shows. It essentially benefits from highly up-to-date information from sales and from the entire supply chain.

It is not an isolated case that an MRP controller optimizes the delivery readiness of a certain part by means of inventory build-up or framework agreements, while an important customer is looking for a better solution. The topic was discussed at the sales meeting. An alternative is already available. Conclusion: No hot spot in terms of acquisition. However, there is one problem. The current delivery readiness is criticized. And the key account manager passes this on to the dispatcher. The latter can only increase the supplier’s readiness to deliver via a framework agreement if he does not want to stockpile even more capital. With constant demand, this is not a problem. In this specific case, however, it is foreseeable that sooner or later unusable parts will accumulate in the warehouse, which will later have to be scrapped. Scenarios like this can be avoided if the information that comes into a company is made available to everyone involved in the company.

If the planner had been aware of the impending changeover, he would have increased the stock in the short term, obtained volume discounts that would have largely covered the debt service and not tied himself to a long-term framework agreement. Now you can distribute all minutes from all meetings to all employees. The result would be a flood of paper that nobody would be able to cope with. Also, not all information is important and relevant for everyone and at all times. The MRP controller needs the data when he replenishes the item. Not sooner, but not later either.

A wide variety of disposition methods often alleviate the information deficit, but the above-mentioned case cannot be ironed out with mathematical methods. This applies in particular to AY, BX and BY articles, as they do not benefit from the same management attention as AX articles, but can still generally account for more than 50 percent of sales. This means that additional methods need to be used to enable precise scheduling, as no one can have more than 100 items and the associated customer and supplier relationships in their head. Knowledge management systems make this possible efficiently for the first time by providing information largely automatically. They are based on groupware or web-based document management systems, for example. Both system approaches offer the possibility of storing all information centrally and thus making it potentially accessible to all employees. Information documents that are not available in electronic form can now be easily captured using powerful scanners and stored in plain text. From there, the information is made available to interested (and authorized) persons for inclusion in their planning processes and for further use.

Working with knowledge management systems

Knowledge management using a document management or groupware system looks like this: All relevant documents are read in centrally and decentrally using simple standard functionalities of a document management system, indexed and stored in full-text searchable documents. In this specific case, this leads to automatic indexing of the sales log by customer and product name, so that the dispatcher can also access such unstructured data when planning scheduling. However, a search query does not have to be limited to internal information; it can and should also be used to search for external information on the Internet. These search queries can include, for example, alternative supplier price lists, competitor information and current publications of the most important customers and their competitors. The dispatcher receives search results structured according to content. This is not structured according to “internal” or “external”, as this would inevitably lead to overloading effects for the user when processing information.

With a one-time query, the user can read the results in the form of a results list (similar to an Internet search engine). This completes the one-off search process. If a search is to be repeated periodically, for example every week over a certain period of time, the system automatically restarts the search at the relevant time and determines which deviations from the previous search result have occurred. These changes are then sent to the user by e-mail. This means that the user never receives the same information objects twice. By determining the frequency of terms in the search results, in both cases (one-off or periodic search) the search results are searched for new search terms based on the original search using full text analysis. If a new term appears frequently enough in the original search results, the user is asked via e-mail whether this term is relevant as a new search term for the user and whether a new advanced search should be started. If the answer is “No”, this term is forgotten by the system, and if the answer is “Yes”, a new search is carried out as usual and the previous information network is automatically expanded. We can therefore speak of a push and pull concept. The system provides new information if it is wanted, but it can also be asked for specifically. Accordingly, the search spectrum would be expanded and in this way a kind of growing term or node network would be created. For subsequent search queries for a term that is related to another, an automatic query is conceivable, which then also searches with linked search terms. As a result, information retrieval is optimized on a user-specific basis with increasing use of such systems. Another function is that the resulting term network can be displayed to the user. This allows them to refine their search directly if they find terms that might better match their query. To prevent the keyword hierarchy from growing endlessly, the user is given the option of rating incoming information objects according to content. The aim of the evaluation is that search keywords that lead to information that is classified as bad or worthless are removed from the hierarchy or can only be searched for in combination with other keywords. Once the system has settled, the really relevant information is extracted from a large number of data sources without neglecting newly emerging content. By reducing the time spent searching for relevant information, more qualified decisions can be made more quickly, giving the company in question a competitive advantage.

Knowledge management in order processing

We understand knowledge management as an approach that makes it possible to collect weakly structured, poorly quantifiable logistics and market-relevant information and make it available to interested / authorized company divisions or persons for further use in decision-making and planning processes. The result is essentially to transform personal knowledge into organizational knowledge for the company. For this purpose, a knowledge base or data pool must be established on the basis of known information technologies, in which weakly structured information can be suitably recorded.

Two properties are very important here:

  1. The information should be loaded “automatically” so that no additional input is necessary,
  2. Furthermore, access to external data must be possible, as this significantly expands the usable information base

Clarify technical requirements

When introducing a knowledge management system, the initial situation of the respective company must first be taken into account. From a technological point of view, it is particularly important whether the IT system requirements are in place or not. A homogeneous technical infrastructure is a basic prerequisite for the introduction of a cross-company knowledge management system. If a groupware system or a web-based document management system is to be introduced, investments in server capacities, bandwidths, databases etc. must also be budgeted in line with requirements.

Knowledge creation process

It is often the case that potentially available information is not used to create knowledge. Individual pieces of information only become knowledge and therefore relevant to decision-making when they are incorporated into an information processing procedure with other information and represent company know-how, so to speak, through analysis, consideration and/or the creative design of alternative courses of action. Organizational structures may therefore need to be optimized. The aim here is to create an organizational framework that enables knowledge to emerge from information. In addition to the electronic use and dissemination of knowledge, personal contact for the transfer of knowledge must continue to play a decisive role. In addition to sharing information, there should also be the opportunity to understand the perspectives and points of view of other employees. Only if the new information potential is discussed and evaluated between employees can information ultimately lead to added value for the company.

Definition of information logistics

It is also essential to analyze and evaluate the operational information and communication channels in order to determine the logistics process-oriented structures that the daily information objects should have. These structures must then be entered into the standard document management system so that every user receives their information in the way that the optimized information logistics envisage. As a rule, such information logistics are developed by experienced consultants in close cooperation with the management level and all employees involved.

An additional and independent structure is required for the additional modules for searching for weakly structured information, which are based on the standard solution. Systematic structuring is difficult here, as knowledge is subject to frequent change. However, it is possible to structure the information, e.g. by categorizing it or introducing key terms. The question here is what the relevant areas of knowledge are, which domains you want to develop and which skills should be expanded. For logistics, this could be terms such as “planning methods”, “rough planning”, “market observation” and similar.

Involve employees right from the start

If you are planning to introduce such a system, it is important that all employees involved are informed about the project at an early stage, as the willingness of employees to generate and use knowledge cannot be taken for granted. However, if, for example, the sales employee does not enter the above-mentioned pending customer decision into the document management system, i.e. does not make it public within the company, the knowledge management system is of no use. Therefore, all employees must be motivated not to store all non-personal information locally. The biggest obstacle is that employees fear that sharing knowledge will jeopardize their job. The active and joint development of a company-specific knowledge management system increases the acceptance of such a solution. As in other projects, management support therefore plays an important role. It involves not only communicating the importance of the project and providing the necessary financial and time resources, but also creating the conditions for open vertical and horizontal communication that eliminates departmental thinking and focuses on the common goal. It is often advantageous to involve a neutral third party as an intermediary between the parties involved.

Conclusion

It is important to ensure that operational knowledge management projects are always understood as a combination of technological, organizational and personnel measures. Linking these three aspects into a knowledge generation process is what makes it possible to increase the quality of the company in the long term. If one of the three aspects is neglected, knowledge management projects are doomed to failure.

Dr. Bernd Reineke

Dr. Bernd Reineke

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