The retention of experienced employees’ knowledge is critical in today’s fast-moving technical and businesses environment. Companies struggling to attract and retain talent cannot ignore the hard-won skills of key employees. Retaining the knowledge –the core “knowhow” of key workers – before they retire, or following an acquisition, will support the future management and the competitive advantage of businesses. Also, many young employees move on frequently, taking with them crucial process knowledge.
By introducing programmes in mentoring and structured retirement action planning, companies can provide staff, who are planning to retire soon, with the tools and techniques they need to ensure they are effectively able to transfer their critical process knowledge to their successors. This data must be stored carefully in readiness.
Process control systems can assist in the retention of these critical skills with the incorporation into networks of the Industrial Internet of Things (IIoT) and Artificial Intelligence (AI). Process control and management systems automate manufacturing workflow. Such workflow software can capture the knowledge of individuals and the data using Internet-linked IIoT systems and from AI systems utilising machine-learning, sharing it and retaining this knowledge for future generations to build upon. Customer Relationship Management (CRM) and accounting systems will retain commercial knowledge but the complexities of process management – how best to make a particular product in high volume – can be retained in process automation systems incorporating AI.
As McKinsey and Company explain in an article about McKinsey Analytics in March 2019, “For decades, companies have been “digitizing” their plants with distributed and supervisory control systems and, in some cases, advanced process controls. While this has greatly improved visualisations for operators, most companies with heavy assets have not kept up with the latest advances in analytics and in decision-support solutions that apply AI.
Operators still rely on their experience, intuition, and judgment. This heavy reliance on experience makes it difficult to replace a highly skilled operator at retirement. However, AI’s ability to preserve, improve, and standardise knowledge is all the more important.”
This situation will prove to be a game -changer in retaining the critical “knowhow” of key employees about to retire, young key employees moving on or retaining core process information following an acquisition. The Harvard Business Review explains in “Why Companies That Wait to Adopt AI May Never Catch Up”, by Vikram Mahidhar and Thomas H. Davenport in December 2018, that it “may take a long time to develop and fully implement AI systems” There are no shortcuts to the necessary steps but then scaling up can be very rapid. Once late adopters are ready to go, the early adopters will have already won the greatest market share and be enjoying lower costs and improved performance. Process and business knowledge can be imagined in types or groups of knowledge: in Structured Knowledge, Unstructured, and in Nuanced Knowledge. Structured Knowledge holds critical system information, for example, about the location of perhaps hidden equipment and their maintenance programmes. Unstructured Knowledge is acquired from various sources and assists new recruits to become competent in new roles. However, the biggest challenge is in the acquisition of “Nuanced Knowledge” – the sort of knowledge in which the answer to a question about it gets the response “that’s about as long as a piece of string!” However, AI now offers support as ageing employees holding vital knowledge approach retirement. That knowledge need not now walk out of the door with them.
New AI systems being developed now will allow business users to capture and retain business process knowledge with little to no expertise in complex IT systems. Businesses may now structure and retain their own critical knowledge through automated business processes by a drag and drop, easy-to-use interface to capture the vital intelligence before it leaves their organisations.