Increasing the productivity of knowledge workers
Engineers and other knowledge workers have many software tools that help them become more productive and do better work, including various ways of mining, abstracting, and visualizing data. There are, however, many areas where the E&P industry could do much more to empower their knowledge workers and increase their productivity. An important example is the process of decision making.
Yes, we have made it easier for the engineer to arrive at good decisions through tools that provide improved situational understanding (“a better picture of the situation”), but there is often still a significant leap from having a good picture to making a good decision. In many situations, it may be very difficult to make a good decision even if you have a perfect picture of the situation. There are mathematical reasons for this that I shall not bore you with, but consider this: When playing chess you have a perfect picture, and it is still a very difficult game to play.
However, today we have seen a significant maturation of technologies with advanced problem solving capabilities that assist the user in doing their work and finding solutions to the problems they set out to solve. These technologies empower knowledge workers to do more and better work, they allow lesser skilled employees to approach the work quality of higher skilled colleagues, and they reduce risk and training time.
To give an example close to my heart, a client of ours was faced with a 400 percent increase in the size of its rig fleet, and the team managing the fleet could not cope with this. In complex operations, managing and scheduling rig fleets requires highly specialized skills. Recruiting and training was hardly an option; first because the skill set needed must be developed over years in the job, second because finding suitable candidates is hard, and third, the challenge of managing the fleet grows exponentially with the number of rigs (which often means that throwing more people at it will not solve the problem).
New technologies made it possible to deploy a system that was able to manage the large increase in the rig fleet while providing rig schedules that were optimized on several key performance goals. The new system assisted in the planning process (the long decision cycle, also called the “slow loop”), provided ways to run what-if scenarios, visualized the trade-offs between various choices and scenarios, and supported the tacit interaction between the various groups dependent on the schedule. It strongly simplified the decision process, empowered people’s expertise and enabled them to provide better solutions faster. It was also designed to operate as a decision support tool during operations (the so-called “fast loop”), providing optimized decision proposals and reworked schedules to handle changes and interruptions.
From the long list of benefits such a system provides, the one I would like to point out here is the extra mileage you get out of your knowledge workers when they have such tools. As an example, the regular rig fleet planning processes I mentioned went down from several weeks to five hours.
More reading
Roger Herman, Joyce Gioia, and Tom Olivo, “Impending Crisis: Too Many Jobs, Too Few People”, Oakhill Press, December 2002.
Peter Parry, Otto Waterlander and Varya Davidson, “Resourcing the challenges of maturity - an oil industry view”, Booze Allen Hamilton.
Juliane Kinast, Christian Reiermann and Michael Sauga, “Where Have the Skilled Workers Gone?”, Der Spiegel, June 22, 2007.
Edward E. Gordon, “The 2010 Meltdown: Solving the Impending Jobs Crisis”, Back Matter
David W. DeLong, “Lost Knowledge: Confronting the Threat of an Aging Workforce”, Back Matter
