Since the beginning of modern times, industry has been challenged with applying expertise consistently throughout the organization. Demographic trends and new technological advances promise to challenge the way industry approaches business. To stay competitive, industrial organizations will need to embrace new applications like cognitive computing, or simulating human thought processes in a computerized model.
Consistent Application of Expertise
Through the ages, men and women have sought methods to improve their situation based on what they learned. Ideally, the lessons learned today are rolled into the decisions of tomorrow. Parents teach children their experiences and conclusions with the expectation that the children will utilize and build upon that knowledge. When contemplating new challenges, the wise ask others what they have learned, so this knowledge can be applied to ensure future success.
Previously, in the corporate world, this approach to knowledge transfer became more institutionalized. Mentoring became a formalized and encouraged practice. This progressed into the adoption of standard operating practices which attempt to encourage the consistent application of expertise across an organization.
Expertise Spread too Thinly
Technology continues to increase in capability and flexibility, and companies continue to merge and grow. Companies move into new markets and must adapt to global pressures and cultures. The ratio of experienced to inexperienced personnel in industrial plants is changing. The procedures and standards prevent adoption of transformative technology and techniques and may not apply in all circumstances. Corporations are losing the expertise that can explain why the procedures were written the way they were and that can adapt them to different situations.
Retiring experts are also leaving holes in the organizations and the remaining experts are spread more thinly across the globe. As a result, collaboration and consensus are more difficult to achieve. Knowledge availability becomes limited to documentation, which may be difficult to find or difficult to understand without context.
In some industries, the projects are becoming more complex, presenting greater risk and bringing organizations into uncharted territory in which the intuition derived from years of experience would be crucial to success, but increasingly, is in short supply. New and innovative technologies promise to change the way industry does business, challenging the standards and procedures in place.
In this time of increasing technological change, declining heritage, and data overload, organizations must address the questions: “How do we effectively train and inform our new talent?” and “How can we access and apply knowledge faster and consistently?”
The Trend will Continue
In recent discussions with a major oil company, ARC Advisory Group learned that it expects to experience a 20 percent shortage in engineering staff over the next five years. This means, if the industry continues to operate with the same model, that projects will be staffed with under-qualified personnel and overall project quality will suffer.
Upkeep of existing facilities can also suffer for similar reasons and staffing will also become more expensive. Prior to the drop in the price of oil, the cost of technical expertise in Calgary had increased nearly 50 percent over the past five years for this very reason. A shortage of qualified engineers and other technical personnel is also one of the reasons why the major LNG projects in Australia have been running behind schedule and over budget.
Because demand is far outpacing supply, ARC expects this trend to continue for the foreseeable future. Therefore, the costs for technical talent will increase affecting projects and maintenance.
Standards and procedures generally cannot foresee new technology innovations and are inflexible by design. As a result, these older ways of conducting business may not apply to or fail to utilize the promise that new technologies make available. Innovation slows, and the organization risks missing competitive opportunities afforded by the new technology.
Cognitive Computing Could Help
Cognitive computing is the simulation of human thought processes in a computerized model. It involves self-learning systems that use data mining, pattern recognition, and natural language processing to mimic the way the human brain works. The goal is to create automated IT systems that are capable of solving problems without requiring human assistance. Cognitive computing systems use machine learning algorithms and continually ac-quire knowledge from the data fed into them by mining data for information. The systems adapt the way they look for patterns and the way they process data so they become capable of anticipating new problems and modeling possible solutions.
While it’s not likely that the technology will ever fully replace human expertise, experience, knowledge, and intuition, ARC believes that cognitive computing is just one of several emerging technologies that will help fill the gap by enabling self-learning computers to replicate human thought processes.