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Driving Strategies for Engaging End Users to Ensure Project Success William P Mahoney III

Driving Strategies for Engaging End Users to Ensure Project Success William P Mahoney III. Outline. What is NCAR? Why is this topic important? Defining a Decision Support System (DSS) Assessing the client’s culture Evolutionary software development process

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Driving Strategies for Engaging End Users to Ensure Project Success William P Mahoney III

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  1. Driving Strategies forEngaging End Usersto Ensure Project SuccessWilliam P Mahoney III

  2. Outline • What is NCAR? • Why is this topic important? • Defining a Decision Support System (DSS) • Assessing the client’s culture • Evolutionary software development process • Strategies for optimizing end-user buy-in • Case example – Road Weather?

  3. What is NCAR? Center Green Mesa Laboratory Mesa Laboratory Foothills Laboratory Boulder, Colorado USA

  4. What is NCAR? Programs in: - Climate - Air chemistry - Solar physics - Weather research - Supercomputing - Social Science - Research facilities - Applications and Technology Transfer

  5. Research Applications Laboratory • Size About 200 people, approximately half are atmospheric scientists, and half are engineers • Mission • Develop Solutions: Work closely with customers to develop applications designed to solve specific problems • Technology Transfer: Transfer knowledge and technology to US government agencies, the private sector, and foreign governments

  6. Why is this topic important? • The importance of connecting science & technology to society is increasing. • Many new technologies are not being implemented. • Developers have traditionally not been well connected to end users. • Learning how to engage end users is critical for advancing technology.

  7. What is being done? • American Meteorological Society has goal to reduce the gap between end users and the weather and climate enterprise. • More companies and research organizations are engaging end users directly. • Technology generators are starting to incorporate operations research concepts into their development cycle.

  8. AMS Commission Organization AMS Commission on the Weather and Climate Enterprise Commissioner: George Frederick Commission Steering Committee Commission Executive Committee Board on Enterprise Planning Chair: Terry Tarbell Board on Enterprise Communication Chair: Matt Parker Board on Enterprise Economic Development Chair: Bill Mahoney

  9. Commercial Weather Services User Community Government Weather Services Universities Weather and Climate Enterprise

  10. AMS Board on Enterprise Economic Development

  11. Decision Support Systems What is a decision support system? • An automated tool that makes decisions? • A semi-automated tool? • A handbook of recommended practices? • Local newspaper or news program? • Student assistant? Answer: All the above!

  12. Assessing the Culture Before one can consider developing or implementing a DSS, some important questions need to be asked to assess the client’s culture. End-user meeting

  13. Assessing the Culture First Question: 1) What problem(s) are you trying to solve? This must be asked several different ways before a potential solution may emerge.

  14. Assessing the Culture 2) What is the culture of the client’s organization? - Would a DSS be seen as threatening? - Does automation pose problems? - Are general support tools viewed positively? 3) What actual decisions could be supported? 4) What job categories would benefit most?

  15. Assessing the Culture TRS-80 Computer 5) What technical capabilities exist? - Is there an in-house framework to support the new technology? • Network system (external & internal) • Desktop computers for end-users • Remote field communications (PDAs) • Database of pertinent operations data

  16. Assessing the Culture 6) What are the potential benefits? - Safety - Property Protection - Productivity - Risk Reduction

  17. Assessing the Culture Management Staff 7) Who will champion the technology? - Management vs. staff - Technology push (by management) or pull (from staff)?

  18. Assessing the Culture 8) What are the users’ expectations? This is a big deal! It is critical that users expectations are at the appropriate level when new technologies are introduced. It is always better to error on the side of caution and let the users be creative on how they utilize new capabilities.

  19. Decision Support Systems • Application Categories: • Strategic Planning (condition prediction) • Tactical Planning (alert functions) • Operations Management (productivity) • Incident Management (notification function) • Risk Management • Evaluation of “What if?” scenarios • Training Tool (off-line assessments)

  20. Best Development Process

  21. Decision Support Systems • There are no off-the-shelf plug and play DSSs that can fully address the needs of all end-users. There are no “one-size-fits-all” solutions! • A “bottoms-up” rather than a “tops-down” approach should be used for DSS system development. • Stakeholders need to determine the level of sophistication that is required for their specific DSS application.

  22. Technical Risks & Challenges For Weather Related DSSs

  23. Weather Diagnoses & Forecasts Then Now • The weather information requirements of each user community are now highly specialized. • The weather research community has not traditionally been focused on the individual needs of specific user communities – change is occurring

  24. Weather Diagnoses & Forecasts • What is usually required? • - High resolution information • (misoscale = 40 m to 4 km) • - Rapid updates • (minutes to hours) • Both short term and long lead time (seasonal) forecasts • Diverse set of input data

  25. Weather Diagnoses & Forecasts Tmax Users are now seeking: - Probability metrics (or confidence) for key meteorological parameters Example: “What is the probability of the high temperature Reaching 95F between 4 and 6 pm tomorrow?” “What is the probability of 3 inches of rain falling into my reservoir?”

  26. Thank You WAS*Isers

  27. Winter Road Maintenance Case Example

  28. MDSS User Needs Acquisition • Surface Transportation Weather Decision Support System Requirements (STWDSR) • Identified large Stakeholder Group • Discussed overall goals and objectives with large stakeholder group • Created focus group from stakeholder group • Assessed current practice • Developed concept of operations • Developed prototype design • Developed prototype – first step that code was written! • Demonstrated prototype • Iterated • Kept stakeholders in the loop throughout process

  29. Current Capabilities The highway maintenance managers currently use newspapers, Weather Channel, USA Today, NWS, and private meteorologists to make decisions. Road weather information systems are not integrated with road management systems. The winter road maintenance decision process is generally reactive in nature.

  30. Expressed User Needs • On a plow route by plow route basis, users want: • Treatment Type (chemical, plow, sand, etc.) • Treatment Amount (lbs per lane mile, etc.) • Treatment Location (plow routes) • Treatment Timing (start/end)

  31. 2000-2007 State DOT Stakeholders 35 State Participants Includes the District of Columbia

  32. MDSS Products • Weather parameters • Air temperature • Relative humidity • Wind speed and direction • Precipitation type, rate, accumulation • Road Parameters • Road temperature • Bridge temperature • Bridge frost potential • Blowing snow potential • Road contamination & chemical concentration • Treatment Recommendations • Treatment Type • Treatment Location • Treatment Amount

  33. MDSS Display Application

  34. Field Demonstrations Iowa DOT Verify results and be honest with stakeholders Don’t come across as a typical salesperson!

  35. Research Needs • The meteorological community should develop a “Best Practices” guide for engaging end users. • Weather DSS Testbeds should be established in end-user operational environments to test advanced “products” (methods, techniques, etc.) and to learn how end-users utilize the new information. • Testbeds should be used to evaluate: • how to communicate uncertainty • new presentation options • how users interpret products • identify knowledge gaps in atmospheric science • societal aspects of new capabilities

  36. Research Needs • Weather DSS Testbeds for a variety of economic sectors could be established. Industry partners could help offset costs (in-kind contributions, hosting of technology, etc.) • Weather DSS Testbeds: Agriculture Aviation Surface Transportation Human Health Energy Construction Water Resources Emergency Management

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