Less time searching, more time working
How cognitive systems can transform knowledge management and employee productivity
Helping employees find the right information when they need it represents a major challenge for businesses. An information worker spends two hours a day just searching for information. Aside from the obvious potential frustration for the employee, there’s also real business value at stake here: a recent study finds that employees could be up to 30% more efficient if they were armed with the knowledge needed to get the job done.
Cognitive computing has the potential to make real impact here, say Carla O’Dell and Lauren Trees in an article in KM World:
“We are on the brink of a paradigm shift involving the fundamental human processes that guide information discovery, insight extraction, problem solving and decision-making.”
They point out that industries as diverse as healthcare, software, financial services and oil and gas exploration are already starting to see results from turning to cognitive technologies. Being able to process massive amounts of data, both structured and unstructured, to provide “personalized, intuitive responses” offers significant promise for the field of knowledge management.
Cognitive systems open up the potential to answer the kind of questions that previously would have required human intervention:
“Traditionally, computers have excelled at queries with clearly defined right and wrong answers. Software has become much more sophisticated over the past two decades, and today’s cognitive systems and machine learning applications approach questions more dynamically. That allows them to tackle more complex problems, refine their responses based on influxes of new information and detect the best options among numerous viable possibilities. Those capabilities may eventually allow cognitive systems to respond to the type of multifaceted, context-driven inquiries typically reserved for human intelligence.”
So what are the drivers that will help create the next generation of cognitive knowledge management systems?
The first is the growing mass of data surrounding business processes, which continues to grow as more and more processes are digitized. “Cognitive systems are needed in order for organizations to get their arms around big data and detect patterns and insights among the chaos” state O’Dell and Trees. The second factor is the improvements that have occurred in computer technology, especially machine learning. Finally, the cost of knowledge work needs to be taken into account. This is a significant expense for many businesses so any improvements that can occur offer the potential for real business advantage.
The potential here are for systems that can take into account what an employee is working on and tailor recommendations which are personalized and relevant to the current context. The benefit?
“The hope is that employees will be able to spend less time searching for knowledge and more time learning from and using it.”
One example in the oil and gas exploration industry is Woodside Energy, Australia’s largest independent energy company. The company has employed IBM Watson to ingest millions of pages of engineering reports from previous drilling operations, and offers recommendations to engineers out on platforms using a conversational interface they can access on an iPad.
The organization is developing its own internal cognitive unit to continue to explore the potential for machine learning for the company’s operations.
Given the huge potential for cognitive systems to transform knowledge management, expect to see further investments and new developments in this space.
