The importance for an organization to retain and maintain business knowledge is well known. As such, there are many knowledge management (KM) resources available including educational materials and tools for general business practices such as enterprise computer and cloud applications. Despite all the available resources, there remain challenges within KM organization strategies and adoption practices that need attention. For instance, author Jay Liebowitz warns in his book, Knowledge Retention: Strategies and Solutions, that organizations are experiencing knowledge bleed as baby boomers retire and younger workers take over the work. The focus of this paper is twofold, (a) evaluate Liebowitz’s warning within the practice of engineering, and (b) assess the challenge of retaining and maintaining engineering expertise for the long term. The authors, each with over forty years of engineering experience, have observed that engineering departments are aware of the benefit of capturing current and legacy knowledge but often fail to do so. Instead, the habitual practice of business as usual remains the default. For instance, the capture of enterprise engineering methodology is attempted only when experienced and seasoned expert engineers are very close to retiring when it is generally too late to be effective, that is if any exit strategy exists at all. In addition, the maintenance of crucial engineering tools, especially those developed in house, relies on very few product line expert engineers with no one to assume the highly technical role upon attrition. A possible consequence of this habitual practice is to frustrate younger workers who are asked to assume an expert’s role too soon and unprepared. This frustration frequently leads young talents in search of competing firms that do a better job with their engineering KM. Instead of ineffective practices, the authors explore strategies for engineering knowledge retention and for putting good practice into place. Additionally, potential benefits to the company are discussed with regards to efficient knowledge capture and the grooming and retention of future expert engineers.

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