Knowledge Management – If Employees Knew What Their Company Knew

What challenges do companies face in knowledge management today?

Probably the biggest challenge facing companies today is providing information and stopping the loss of know-how. How can companies make the right information available to the right people at the right time?

The retention periods of employees in companies are getting shorter and shorter while the experienced generation of baby boomers is slowly retiring and with it their knowledge. This comes along with risks such as the loss of know-how and experience, but also opportunities such as accelerated digitisation through a younger team that is more open to new tools. It is clear that this certainly does not apply to every representative of the respective generation, but certain attitudes of one generation are more universal than others. The baby boomer generation has built up a lot of knowledge over the years and contributes significantly with their experience to companies being able to successfully fulfil projects and customer wishes. However, this knowledge will not be available forever due to the generational change. Instead, the knowledge must be digitalised and made accessible to other employees through knowledge management.

It is up to each company to make the knowledge from the company’s history available to freelancers or younger employees quickly and efficiently so that they can handle projects just as successfully, even if they are not yet as experienced.

Where is the knowledge of the companies located?

In the past, before digitalisation, there were basically two data silos:

  1. The knowledge in the heads of long-serving employees.
  2. In paper files, which are a hodgepodge of all the printed documents on projects.

Nowadays, the world has become much more complex. Knowledge today is stored in almost innumerable data silos:

  1. Some of it is in the heads of employees
  2. files, although these are increasingly being digitised
  3. E-Mail inboxes
  4. Network drives
  5. Shared drives
  6. CRM systems
  7. ERP systems
  8. Document Management Systems

This list could go on and on. On average, companies use around 130 different tools, which often store different data.

The task of most office workers is no longer to carry out the actual processes, but to start them and feed them with the right information. The classic office worker has therefore become much more of a knowledge worker in recent years, whose main task is to know where which information is stored and how to use it as efficiently as possible.

In many companies, many tools for specific pain points have been introduced in recent years. As a consequence, data is stored decentrally, mostly in these tools. This has created the problem that employees no longer find information either in a file folder or by asking a colleague a question, but have a steadily increasing number of data silos in which information is stored.

One consequence of the diverse data silos is that information often cannot be assigned to just one tool, but to several. First of all, it must be clear where the information has to be stored. As an example, we will take the protocol of a meeting for the construction of an office building:

  • Does the protocol belong to a specific trade?
  • Does the protocol belong to a specific construction phase?
  • Is there a meeting folder in which all protocols are stored?
  • Is the protocol stored in a CRM or project management tool?
  • Where are the protocols stored if decisions on different trades and service phases are logged?

It becomes clear that it is by no means trivial how information is stored. It also depends on the respective employee:

  • Does an employee store the information in the right place?
  • Does a staff member store the information under the right name?
  • Will he save the document/information at all or simply leave it as an attachment in his email inbox if the protocol was sent by an external party?

This example shows how many correct decisions have to be made so that a single piece of information can be found again quickly by other employees. Especially for new employees, storing information is even more of a challenge.

Status quo in information retrieval

Employees have the option of clicking at length through the intranet, folder structures or other data silos. Alternatively, colleagues can be asked for help (and keep them from working). If this is also unsuccessful, employees start creating and saving documents again. There are now extensive studies that quantify the problem of finding. A McKinsey study shows that knowledge workers spend up to 1.8 hours a day searching.

At least many companies recognise this problem and are trying out new methods to cope with the exponentially growing amounts of data.

Solutions for knowledge management

Companies are therefore beginning to rely on “one-stop” solutions, as they hope to be able to handle the information better. This may help at first glance, but at second glance, mature solutions that perfectly cover a specific use case are exchanged for a standardised and much less mature solution. In the short term, this helps to make the information of certain steps more accessible to employees, but in the long term, the perfect business processes are mapped suboptimally. Moreover, at the end of the day, different data silos (e.g. email applications, divison-specific applications like HR or PR applications, etc…) always remain and, although they partially reduce the number of data silos, they do not solve the problem of data silos in the long term. In addition, companies make themselves completely dependent on the respective provider and have to go along with potential price increases.

What could be a better alternative?

If you think of each tool as an individual database, some tools store data in a structured way, but most tools store data in an unstructured way.

Since the development of databases, search and information retrieval has been a topic that developers have been dealing with. Over the years, they have developed good solutions for structured data. The problem, however, is that most data in companies is unstructured and the most valuable information is contained in, for example, project completion reports.

Since data is growing exponentially, there are providers who offer so-called enterprise search engines. The focus of an enterprise search engine is to make information from different data silos accessible to the user, taking into account access rights. Established providers often offer a somewhat better keyword search, which is sufficient for small amounts of data. However, as soon as the data volumes become larger, it is no longer sufficient to search only for keywords, but it is important to properly understand the content of an information and to use a scalable solution.

For various reasons, enterprise search engines have not been able to bring the so-called “Google Search Experience” into the enterprise. However, the desire to bring the Google Search Experience into the enterprise is getting louder and louder. Recently, start-ups have been working on using the latest developments in Natural Language Processing, a form of artificial intelligence, to bring the “Google Search Experience” into companies and make unstructured data findable. Where it was previously not possible to semantically understand information from texts in a similar way to Google, Natural Language Processing makes this possible. In the context of companies, Natural Language Processing is thus becoming one of the most promising technologies of the future.

If we return from this excursion to the problem, namely finding the company’s internal data, then a modern enterprise search engine with access to the various data silos can solve precisely the problem of finding the right information. If you combine an intelligent enterprise search engine with the applications that are specifically tailored to the use case, then I not only optimise the workflows in themselves, but I also give my employees comprehensive access to the company’s knowledge.

Enterprise search engines against know-how loss?

Digitised documents contain much more information than one would initially expect. Many employees find knowledge and information on topics that they did not even know your company had already compiled. An enterprise search engine is able to filter the right information from all data. So if employees can or have to stop asking more experienced staff for the right information and instead ask intelligent search systems, not only is independent working encouraged, but employees become more efficient by wasting less time (finding instead of searching, no asking colleagues, no re-creating information). In addition, knowledge is found that employees often did not know their company knew about.

A good enterprise search engine can thus help to address one of the biggest problems of our time, namely the loss of know-how and information.

Bastian Maiworm ist der Gründer des Enterprise-Search-Tech-Startups ambeRoad. Als Jungunternehmer spricht er über die neuesten Entwicklungen im Bereich Startup und Enterprise Search. Bei ambeRoad war er maßgeblich an der Entwicklung der Vertriebsstrategie beteiligt und kennt aufgrund seiner Erfahrung die Probleme, die sich bei Kooperationen zwischen Konzernen und Startups ergeben, sehr genau. Dies nutzt er, um die Digitalisierung und Zusammenarbeit zwischen Startups und Konzernen weiter voranzutreiben und zu optimieren.

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