1. “Soft System Analysis to Integrate Technology & Human in Controller Workstation,” Co-authored with Caroline Donohoe and Jonathan T. Lee, Presentation at 30th Digital Avionics Systems Conference and paper in Conference Proceedings, Seattle, WA, October 16-20, 2011.
Computer-based decision support tools (often known as cognitive computing) are finding increasingly use in the workplace. One example is use by air traffic controllers and pilots to plan aircraft trajectories. Successful adoption of cognitive computing concepts depends on both technology and humans performing as co-partners to obtain the intended benefits. This report discusses developing functional requirements for a controller workstation so that the controller can effectively and safely use cognitive computing technology to obtain efficiency and safety benefits. We call the approach in this work soft systems analysis. Steps include:
a. Define technology capabilities that will enable intended benefits.
b. Develop task descriptions for the roles of technology and humans.
c. Develop requirements for technology that enable the technology and human performance to function as an integrated set.
d. Develop benefit flow mechanisms and performance measures for integrated technology and human performance.
e. Identify feasibility issues of both technology and humans performing their tasks as intended.
2. Three Letters to the Editor of the Harvard Business Review commenting on following articles:
- “Six Ways Companies Mismanage Risk,” September 2009, p. 112 – Letter commented that companies mismanage risk not just because their risk assessment processes are inadequate as stated in the article but because they do not follow what their risk management analysis says because they do not want to give up potential profits and because everyone else is doing it.
- “How to Design Smart Business Experiments,” July/August 2009, p. 149 - Letter commented that while formal tests advocated in the article are indeed useful in cases where desired outcomes are defined and measurable and where many roughly equivalent settings can be observed, they are less helpful in softer situations, such as acquisitions and major changes in business models. Under those circumstances, simulation experiments are more useful.
- “Hardball: Five Killer Strategies for Trouncing the Competition,” July/August 2004, pp. 181-182 – Letter commented that while the article stated executives were spending too much effort with squishy things like organization culture, the article also gave an example of Southwest Airlines using soft, squishy organizational culture to fend off another airline moving into one of their major airport centers. Thus, the authors were putting too much emphasis on not paying attention to the soft and squishy aspects of successful management
- “Knowledge and Projects,” White Paper prepared for Working Knowledge Research Center, School of Executive Education, Babson College, October 2, 2006.
This paper was written at the request of Babson Executive Education program to cover how to provide needed knowledge to a project and how to convey the project’s resulting knowledge to the broader organization. Projects are increasingly becoming a way that organizations conduct their business. Most projects involve creating new knowledge in some form, such as solving a problem, increasing productivity, developing a new product, planning a new strategy, or designing and implementing a new process. To accomplish their work and benefit the organization, projects need to have appropriate knowledge to conduct their assignment and need to convey the resulting knowledge to the larger organization.
Specific techniques presented in the paper in include:
- Design projects as training grounds – Staffing a team with experienced staff with knowledge that can be conveyed to newer staff, and staff with newer staff to learn from the experienced staff. Learning from working on teams is effective since the learning occurs within the context of an actual problem or initiative.
- Show project staff new ways of working – Fresh perspectives on analysis and decision methods can be shared among team members.
- Transfer knowledge output to the broader organization means designing for future on-the-job learning – Design the project to leave a depository of knowledge or set up a means to spur learning, such as with a decision support system or query system.
4. “Toward a Robust Project Portfolio Management Process: Strengthening IT Project Portfolio Management by Adapting Principles from Economics, Psychology, Anthropology, and Other Disciplines,” Workshop co-presented with Sandy Lozito, NASA Ames Research Center, at IIR’s IT Project Portfolio Management Conference, San Francisco, California, April 3-5, 20, 2006.
Project Portfolio Management (PPM) is certainly concerned with aligning projects with the organization’s strategy. But success usually involves dealing with other factors that arise. Some examples are integrating the work of multiple business units and/or outside organizations working on projects; dealing with changes in goals, people, funding, and schedules; roles of software and humans in PPM; introducing project portfolio management into a skeptical business unit; and assuring that the portfolio continues to focus on bottom-line benefits as deadlines approach and funding is tight. There is much to learn about how to deal with this wide range of issues by drawing upon principles and techniques from other disciplines, such as economics, psychology, human factors, anthropology, marketing, and probability. This workshop covered these disciplines and described techniques that can be adapted from them to strengthen PPM.
The workshop covered:
- The types of issues with which Project Portfolio Management must deal beyond having projects that align with strategy to achieve a success portfolio.
- How to identify the issues that will affect the success of you company’s project portfolio.
- Adapting techniques from economics, psychology, human factors, anthropology, and other disciplines to address these issues and strengthen you project portfolio management.
5. "Increasing Knowledge Work Productivity: Integrating KM and Six-Sigma to Enhance Overall Results,” Workshop co-presented with Mary Ellen Miller, Raytheon, at Braintrust International 2005, The 7th Annual Knowledge Management World Summit, Institute for International Research, San Francisco, California, February 28-March 2, 2005.
Our workshop covered:
- How enhancing knowledge work processes differs from increasing the productivity of such traditional processes as manufacturing, logistics, and order processing.
- Focusing the enhancement of knowledge work processes on bottom-line benefits.
- Principles of KM for enhancing knowledge work processes.
- Principles of Six-Sigma for enhancing knowledge work processes.
- Putting it all together to increase the productivity of knowledge work.
- Implementing knowledge work enhancement in your organization.
- Examples from a variety of companies and organizations were presented throughout the workshop.
6. “Designing Performance Measures for Knowledge Organizations,” Ivey Business Journal, Richard Ivey School of Business, University of Western Ontario, March/April 2002, pp. 8-10.
Knowledge-based business processes are often not well defined, and it is not obvious what needs to be measured. This article discusses three factors that will help managers design useful measures for knowledge work organizations: (1) define what decisions are to be made and what information is desired from performance measures, (2) develop a narrative framework that clarifies how the processes work to create value and helps communicate what is being measured, and (3) develop qualitative and quantitative measures that fit with (1) and (2).
7. “Covering the Intangibles in a Knowledge Management Initiative,” IT Professional, Institute of Electrical and Electronics Engineers, Computer Society, November-December 2003, pp. 22-28.
Knowledge Management (KM) is about enhancing the use of knowledge in an organization to create a benefit. Knowledge Management (KM) is often defined as, “Getting the right information to the right person at the right time.” The danger in this definition is that it tends to emphasize the technology aspect of KM and can lead to ignoring the people side. It also tends to ignore considering how the knowledge will be used to create value.
This paper deals with the following intangibles of KM so that knowledge is not only shared but is also used:
- People roles and human interfaces: What will employees be expected to do with the knowledge provided by the KM initiative? What knowledge do employees need to do their work?
- Processes: Does the KM initiative fit with the current processes of the organization or will the processes need to be changed? Does the KM initiative add value to the work processes?.
- Organizational culture: Does the project’s way of dealing with knowledge fit the culture of the organization so that employees will find it valuable and will be encouraged to access, contribute, and use the knowledge?
- Technical: Will the technology work to gather, store, and provide knowledge when, where, and how needed? Will the technology fit the way work is performed?
- Implementation & Supportability: How difficult will it be to implement the initiative, including any change in processes that are needed?
- Strategic: Will the KM initiative be robust enough to serve the organization for a reasonable timeframe considering the future lines of business and future operations in which the organization is likely to engage?
8. “Identifying & Assessing Project Risk” at the IIR’s Project Portfolio Management: How to Select and Sustain an Optimal & Strategically Integrated Project Portfolio Conference, Wyndham Boston, November 17-19, 2003.
In conducting any project, there are risks of not meeting the planned schedule or costs, not achieving the intended results, or not have the product results accepted or utilized as planned. The occurrence of such adverse events make it difficult to obtain the intended benefits of the project or even cause the project to fail. Assessing project risks in advance can help decide what projects to pursue and to increase the likelihood of success for projects initiated by planning for the risks. This talk was provided tips on how to develop your own approach for project risk management to fit the needs of your organization.
The talk covered:
- Estimating the likelihood and severity of risks.
- Prioritizing risks and formulating mitigation actions.
- Using information on project risk to make project portfolio decisions.
- Assessing technical risks.
9. Measures Are Not a Cure All,” NYU Stern Business School, 4th Intangibles Conference on Advances in the Measurement of Intangible (Intellectual) Capital, May 17 & 18, 2001
These conferences were organized by Baruch Lev, Professor of Accounting and Finance at the NYU Business School, New York City, NY. The talk focused on measuring intangibles that support the success of a company’s internal processes and product/service development and delivery. Measures affect and are affected by behavior. Measures often assume processes work as intended and do not consider behavior. Employees may strive to do well on only what is measured with unintended results. Means to address these issues were covered:
(1) Identify what decisions and information are desired from the measures,
(2) Express measures in a narrative that shows the value creation mechanism, and
(3) Use mix of quantitative and qualitative measures since quantitative measures often miss important subjective elements of performance.
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