- Painting on the walls of the Tomb of Rekhmire showing the dough preparation step in a recipe to bake tiger nut honey cakes (Image source: Public Domain).
The need to manage knowledge has doubtlessly been around as long as knowledge itself. As far back as 1500 BC, ancient Egyptians were painting instructions showing how to prepare tiger nut honey cakes on tomb walls. Considering their task was to get that knowledge to the Field of Reeds, the Egyptian afterlife, the challenge of transferring knowledge between the living seems a lot more achievable…
Nevertheless, as the complexity and scale of manufacturing operations has progressively increased, business leaders have been compelled to treat the knowledge underlying their businesses as intellectual assets and work to understand how that knowledge is used.
Facing continuous pressure to both reduce the cost of maintenance and increase the reliability of equipment, asset maintenance managers have sought to extend the reach of internal expert knowledge. To do this they’ve looked to digitization and to one-to-many expert networks where experts are assigned to assist multiple generalist technicians with specialist activities. However, labor trends such as the great crew change and, most recently, the great resignation, have thrown a wrench in these approaches to knowledge management, exposing businesses to even greater risk of crucial knowledge following employees out the door.
To understand the knowledge management approaches available to industrial and manufacturing companies today, this post reviews the theories behind knowledge management strategies, discusses the emergence of digitization and expert networks in maintenance management, and maps out how the implementation of strategies has evolved and the opportunities that lie ahead.
The Theory: Two Knowledge Management Strategies – Personalization and Codification
In 1999, the Harvard Business Review published an article identifying two major knowledge management strategies employed by companies across various industries: personalization and codification.
Personalization strategy: Here knowledge is closely tied to an expert and is transferred directly, person-to-person. This transfer of knowledge is typically facilitated by the creation of expert networks.
Codification strategy: Here the aim is to codify and store knowledge where it can be easily accessed and used by anyone who needs it. This is sometimes referred to as a person-to-documents strategy.
Personalization and codification are still seen as the two main strategies available to companies in the area of knowledge management today. There is no set answer for which strategy is best: Companies could emphasize different strategies depending on how they serve their customers, the economics of their business and the people they hire.
For example, consulting companies whose economics are based on the high-margin fees they can charge for small, specialized teams of industry-leading experts may benefit from the efficiency of person-to-person knowledge sharing in small groups. On the other hand, a manufacturing company looking to scale their equipment servicing business may benefit more from the reusability and lower communication costs that a codification strategy would provide.
The emergence of newer technologies also has an impact on which strategy to emphasize. For example, technology that reduces the cost of person-to-person communication provides an opportunity to emphasize a personalization strategy. Technology that reduces the time required to codify knowledge provides an opportunity to emphasize a codification strategy. Conceptualizing how emerging technology can be used to support knowledge management is therefore crucial to identify whether a previously unworkable strategy could become viable.
Trends In Practice: Digitization And Expert Networks
Back when manufacturing processes were more rudimentary, manufacturing technicians could reasonably have been expected to know how to resolve just about any issue halting production. As manufacturing processes have become more complex and equipment has become more software-driven, specialist expert knowledge has become more frequently required to resolve maintenance issues — or even conduct routine maintenance procedures.
Many companies have sought to counter reliance on limited pools of experts by following a codification strategy. Approaches have often included combining extensive technician training with digitization (through CMMS systems that can help organize maintenance procedures and work order history) and with guides and manuals technicians can consult to resolve issues themselves.
But challenges remain. Most importantly, codification efforts are limited by the heavy burden of creating and updating knowledge databases and by the fact that many technicians cannot easily access digital systems during their shifts. Even in this era of technological progress, many technicians still pick up a 3-ring binder to find critical maintenance information.
In response, companies have moved to personalization techniques such as setting up expert networks: networks where experts are available to assist multiple technicians with specific maintenance tasks. The one-to-many relationship of experts to technicians has allowed companies to reduce costs by not requiring every technician to be trained to solve every issue. However, maintenance operations have had to adapt to the limited availability of experts necessitated by this one-to-many model. High travel costs (both monetary and time-wise) have further challenged the sustainability of this approach.
Trends In Practice: COVID Accelerates The Remote Expert Model
Regulations implemented by governments to curb the spread of COVID-19 restricted the movement of individuals the world over. While many regulations exempted expert technicians as “essential workers”, most were unable to travel to maintenance jobs as before. This resulted in an immediate need to facilitate remote communication between on-site technicians and remote experts that could share crucial knowledge.
This need coincided with the maturation of wearable technology – including head-mounted devices that could provide hands-free, see-what-I-see functionality – and many companies jumped to implement these assisted reality devices as a top priority. This also led to existing video calling software, such as MS Teams, building in support for these wearable devices.
Once this remote way of working was established, the benefits of the remote expert model became clear:
- Drastically reduced costs because travel expenses such as flights, hotel stays and meals are eliminated.
- Reduced time spent traveling resulting in experts being able to support more technicians.
- Reduced labor costs as activities such as site orientation and physical safety briefings are rendered unnecessary.
Many companies experiencing these benefits moved quickly to set the remote expert model as their “normal” way of doing things. Not only has this allowed companies with existing expert networks to operate more efficiently, it opened a new avenue for companies who could not previously implement expert networks to consider doing so. As such, the use of wearables such as the RealWear head-mounted-tablet (HMT) represents a great example of how emerging technology can make a previously unworkable knowledge management strategy viable.
- A RealWear HMT device being used with see-what-I-see remote expert functionality (Image source: RealWear).
However, there’s never too much time to rest on one’s laurels, and emerging labor market developments, such as the great resignation, have refocused the risk of over-reliance on personalization strategies in a high-attrition environment: 4 million Americans quit their jobs in July 2021 alone, with mid-career employees having the greatest increase in resignation rates: an average increase of more than 20% between 2020 and 2021. It’s clear that adapting knowledge management strategies remains as important as ever.
Mapping Implementation Of Knowledge Management Strategies In Industrial Companies
Looking at the trends discussed above, it’s clear that the way in which knowledge management strategies are implemented at industrial companies has evolved. Companies have moved on from the rudimentary initial implementation approaches such as stationing experts at every site (for personalization) or creating physical 3-ring binder knowledge bases (for codification). The personalization strategy is now more commonly implemented through the one-to-many expert network model. The codification strategy is commonly implemented through using digital, often cloud-based, knowledge bases including CMMS systems.
The impact of COVID-19 restrictions accelerated the adoption of wearable technology. The proliferation of wearables has revealed a new approach for implementing personalization strategies: creating remote expert networks. This overcame key challenges that had existed within expert networks up until that point: high travel costs and limited expert availability.
Given this impact on personalization strategies, what new avenues will wearable technology open for implementing codification strategies?
Implementation of Knowledge Management Strategies
To answer that question we’ve considered some key capabilities of voice-driven wearable technologies when combined with JourneyApps:
- The ability to use head-mounted wearable devices in a “hands-free, head up” way.
- The ability to use apps on wearable devices even when they are disconnected from the internet.
- The ability to search for information through natural language processing similar to Siri or Alexa.
- The ability for apps to intelligently gain situational context through barcode scanning, computer vision, or knowledge mapping.
These new capabilities converge with an objective we regularly encounter: reducing the need for expert technicians while maintaining high levels of effectiveness for maintenance teams. Examples of specific wearable projects our customers are pursuing include:
- Guided maintenance execution apps
- Step-by-step diagnostic procedure apps
- Procedure training apps
- Work order guidance and execution apps
- Apps that allow knowledge database and CMMS searching through wearable devices
These projects represent a move towards making knowledge accessible throughout a technician’s shift on a device that simply connects to their hard hat: Technicians can now take the complete trove of organizational knowledge with them wherever they go. This new category of self-assist apps carries important benefits over the codification approaches currently used, including:
- Knowledge can be accessed from industrial environments (even without internet connectivity).
- Context awareness reduces time to locate necessary information (e.g. procedure steps, maintenance history).
- The need for expert assistance is reduced with generalist technicians able to conduct more maintenance processes themselves.
Knowledge management remains a crucial function for industrial and manufacturing companies. Over time, the approaches to implement either of the two knowledge management strategies – personalization and codification – have evolved.
The advent of wearable head-mounted tablets presents a new opportunity to further develop knowledge management approaches. For the personalization strategy, we’ve already seen how wearables have brought about a shift to a remote expert model. However, emergent labor trends such as the great resignation makes companies with an over-reliance on personalization strategies vulnerable to knowledge loss. This brings codification back into focus as a sensible knowledge management strategy. Self-assist apps running on wearable devices represent the next opportunity for successfully implementing a codification strategy.
JourneyApps provides a rapid way to build custom apps for RealWear® HMT, mobile and desktop. Voice commands are simple to set up and manage, we provide offline support out of the box, and deploying apps happens with a single click. Comes with prebuilt ERP integrations. If you are interested, please contact us to schedule a demo. You can also visit our RealWear page to learn more and subscribe for notifications about new blog posts.