assessing service maturity through end user engagement and ... · assessing service maturity...

July 19, 2016

NOAA Satellite and Information Service | National Centers for Environmental Information

Deke Arndt & Mike Brewer

NOAA’s National Centers for Environmental Information Center for Weather and Climate

Assessing Service Maturity through End User Engagement and Climate Monitoring

2 NATIONAL CENTERS FOR ENVIRONMENTAL INFORMATION

Service Maturity, Customers, and Monitoring • What are service and engagement?

• How does the aspect of service apply to customer engagement for data provision and climate monitoring?

• Service Maturity?

NATIONAL CENTERS FOR ENVIRONMENTAL INFORMATION CENTER FOR WEATHER AND CLIMATE


Service Maturity, Customers, and Monitoring • Service: The supplying or supplier of utilities or commodities; the occupation of function of serving.

• Engagement: A degree of interaction with another party on a common interest or to move toward a common goal.

• People are the key component of both.



Customer Requirements & Use Cases

• Service involves not just knowing what customers need but what customers do

– Sacramento Municipal Utility District: Creates ‘rainy day fund’ to cost average utilities during extremes and limit rate increases.

– Blacksburg, VA Transit: correlating ridership with weather – Tulsa, OK Cancer Treatment Center: uses barometric data to calibrate some of their more delicate instruments

– Naval Weapons Station, Seal Beach, CA: Needed data to update their Integrated Natural Resources Management Plan.

– Major Global Chocolate Producer: climate data for cities around the world to target manufacturing and sales.

– Mozambique Travel: daily data for African cities supporting travel booking for 1,000+ hotels and remote lodges across the continent

– Brown University: correlating student absenteeism and rain/snow – Hot Air Balloon Competition Shreveport, LA: NEXRAD for low level wind climatology construction.

– Southern Illinois University: relating major league soccer performance to temperature.




– Colorado State University – SST for Baja California – turtle nesting population impact by El Nino

– Energy Information Agency – precipitation to look at state hydrological generation potential

– Medical Device Representative – snowfall summaries – provide 4x4 wheel chair if >20” per year of snow for 3 years

– FAA – SRRS data so they could examine weather prediction outside of Radar range

– Montreal – CCD and climate maps – company developed a snowman building tool and wanted info for sales studies

– National trucking firm – QCLCD hourly temps – fuel costs related to truck idling

– U.K – Storm Events DB hail – developed the Carportable and wanted hail information for insurance losses to help sell the product.




The use of a single NCEI product, GHCN-daily, combined with

supplemental information has been

shown to have a potential $4B impact on

the corn growing economy.


Climate Monitoring

•  … is a data service intended to equally serve members of larger communities (vs. “custom” reports for individual users)

–  puts latest data/information into a broader, and usually historical, context: a “play by play” of [some part of] the climate system

•  … typically distills information into pieces consumed across larger communities; often statistical in nature

• … occurs on regular intervals: daily, weekly, monthly, annually, etc.

–  Matches with typical timescales user for the user communities’ various analyses.


Climate Monitoring

• Levels of value added; more resources needed down the list:

–  [Aggregated] Observation –  Departure from a baseline –  Unusualness of obs or departure –  Trend associated with observation –  Impacts associated with observation


Climate Monitoring

• Like data services in general, it is important to know, understand and communicate with Climate Monitoring users

–  Private Sector: agriculture, energy, retail, logistics –  Public Sector: agriculture, energy, retail, logistics, economics, governance –  What are their needs for data latency? When in the month/season/year do they need

the information?

•  Similar (in many cases, identical) tools to track, identify, understand, and improve services for users.


Service Maturity

• Complement Stewardship MM with considerations of customers and use

• Evaluate (potential) utility of dataset to customers – Move outside of the machine-machine realm to real people – Is there service? – Can a customer’s question be answered? – Can a customer be directed to dataset? – Is dataset applicable and useful to a customer’s requirements?

• Apply using existing customer capabilities • Applicable to state of the art monitoring


Crosscutting Service Components

• Customer Service: The supplying or supplier of utilities or commodities; the occupation of function of serving.

– Level 1: No service and support available – Level 2: Point-Of-Contact information (phone number or/and e-mail address) online. Help

desk available but not trained. SME identified but not available. – Level 3: Custom service reps trained for this product. Detailed steps for obtaining customer

support & service online. SMEs identified and available. – Level 4: Level 3 + 24/7 support availability & on-demand; Customer service reps highly

trained. – Level 5: Level 4 + customized & on-site promptly if requested.

• Customer Engagement: A degree of interaction with another party to on a common interest or to move toward a common goal.

– Level 1: No engagement – Level 2: One-way communication (users -> customer service reps/SMEs). Passive. – Level 3: Level 2 + Two-way communication; Information-based. Customer-engagement

interaction is available but sporadic. – Level 4: Level 3 + Customer interaction is routine and collaborative. Tactical and problem

solving collaboration. – Level 5: Level 4 + customer is fully engaged & potentially involved in providing requirements

for new products or improvements to existing products or data. Strategic collaboration.


Crosscutting Service Components

• Impacts: Have a strong effect on someone or something. – Level 1 – No identified users or decision making based on the data or product – Level 2 – Identified users access and use data but no identified decision making processes. – Level 3 – Level 2 plus customer(s) use data/products in decision making without interaction

or understanding of limitations and applicable uses. – Level 4 – Level 3 plus Customers have an understanding of data/product appropriate uses

and limitations. – Level 5 – Level 4 plus data/product is the primary driver in customer decision making.


Data Monitoring Component

• Monitoring: Measurable practices applied to the dataset to display, check, assess, and report on the state of variable/event captured by the data for the specified time scales. The highest maturity in each level is given to the practices done for the most temporal and spatial scales of the dataset.

– Level 1 - None – Level 2 - Level 1 + Basic state relays (current value/spatial distribution if applicable,

averaged values/spatial distributions if applicable for selected prior time periods (domain/community-based) - last week, last month, last decade, last data collected such as cruise data)

– Level 3 - Level 2 + long-term (record length) average or normal & variation (temporal and spatial from selected/defined prior periods)

– Level 4 - Level 3 + putting variability into context using domain-based metrics, e.g., unusualness/ranking (reference to selected time periods - last year, last decade), extreme events/frequency, trends, … (variability can be diurnal, seasonal, annual, interannual, decadal, centurial, appropriate to the dataset)

– Level 5 - Level 4 + recurring basis with reports online or in the literature


Components for Future Consideration

• Data Discovery (assumes Accessibility) – Level 1: Information not published for public discovery or Internal or person-to-person

sharing only – Level 2: Minimal product information published for public users or Product findable on local

website – Level 3: Product described with standards-based metadata and published to discovery

catalogs or Metadata attributes included in HTML/other objects for indexing by web search engines

– Level 4: Web services supporting product are described with standards-based metadata and published to discovery catalogs or Product relationships described with standards-based metadata and published to discovery catalogs or Product granules described with standards-based metadata and published to discovery catalogs or Schema.org attributes included in HTML/other objects for indexing by web search engines

– Level 5: ?

• Discoverability is different from Discoverable. – Latter is a characteristic of dataset, the former is a capability applied or available to the

dataset (ex. UI) – Discoverability is different than accessibility and usability


NCEI Climate Facebook: http://www.facebook.com/NOAANCEIclimate NCEI Ocean & Geophysics Facebook: http://www.facebook.com/NOAANCEIoceangeo NCEI Climate Twitter (@NOAANCEIclimate): http://www.twitter.com/NOAANCEIclimate NCEI Ocean & Geophysics Twitter (@NOAANCEIocngeo): http://www.twitter.com/NOAANCEIocngeo

www.ncei.noaa.gov

NOAA’s National Centers for Environmental Information


assessing service maturity through end user engagement and ... · assessing service maturity...

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