Decision Support System Development: Engaging End Users Bill Mahoney National Center for Atmospheric Research Research Applications Laboratory (RAL)

Outline NCAR/RAL background Why is this topic important? Defining a Decision Support System (DSS) Assessing user needs Trends and opportunities DSS example – Road Weather

Research Applications Laboratory RAL 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

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!

Why is this topic important? The importance of connecting science to society has risen in the last decade. Most new research funding is targeted or directed to support a societal need. Researchers have traditionally not been well connected to end users making it difficult for society to take advantage of results. Learning how to engage end users is critical for advancing science and technology.

Decision Support Systems Before one can consider developing or implementing a DSS, some important questions need to be asked.

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

Decision Support Systems 2) What is the culture of your 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?

Decision Support Systems 5) What technical capabilities exist? - Is there an in-house framework for a DSS? > Network system (external & internal) > Desktop computers > Remote communications > Data base of pertinent data Remote Systems

Decision Support Systems 6) What are the potential benefits? - Safety - Productivity 7) Who will champion the technology? - Management vs. staff - Technology push or pull?

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)

DSS Development Issues There are no off-the-shelf plug and play weather and climate capabilities that can fully address the needs of all user communities. 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.

NCAR/RAL Development Process

Technical Risks & Challenges For Weather Related DSSs

Weather Diagnoses & Forecasts The weather information requirements of each user community are highly specialized. The weather research community has not traditionally been focused on the individual needs of specific user communities.

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

Weather Diagnoses & Forecasts 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?”

Winter Road Maintenance DSS

MDSS User Needs Acquisition Process Surface Transportation Weather Decision Support System Requirements (STWDSR) Identified Stakeholder Group Discussed overall goals and objectives with stakeholders 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

Current Capabilities and Practice 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.

Expressed Stakeholder 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)

2000-2005 State DOT MDSS Stakeholders 35 State Participants Includes the District of Columbia

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 amount Treatment location

MDSS Display Application State view for general awareness and weather & road alerts Route view for viewing specific routes covered by system Treatment selector for inputting selected treatments and doing “what ifs” Table view of weather and road condition prediction data Time series of weather and road condition predictions MDSS Display Application

Field Demonstrations 2003 - 2005 Iowa DOT Verify results and be honest with stakeholders Don’t come across as a typical salesperson!

Summary There are numerous challenges associated with the DSS development; however, scientific and engineering technologies are coming to fruition that, are likely to produce significant benefits new user communities. Engaging the end users early and often results in better products and user acceptance!