SlideShare una empresa de Scribd logo
1 de 1
Descargar para leer sin conexión
Do your metrics hit the MARC?
Alan Fricker
Head of NHS Partnership & Liaison
Aiming for better metrics?
We want to have interesting and convincing discussions with our stakeholders.
A carefully created metric can be at the heart of these.
The Principles for Metrics report examines practice around metrics from a
wide range of settings including NHS and academic libraries. A Quality Metrics
Template accompanied the report to help with the creation, recording and
sharing of metrics.
Examining the four principles advanced by the report helps us understand the
how and why of metrics. Do your metrics hit the MARC?
References
Metrics Task and Finish Group (June 2016) Principles for Metrics. Available at: http://tinyurl.com/PrinciplesForMetrics
Metrics Task and Finish Group (June 2016) Quality Metrics Template. Available at: http://tinyurl.com/MetricsTemplate
Meaning – who cares?
The metric needs to be something people (not just you) care about.
Meaningful metrics often combine more than one facet – e.g. usage by a particular staff group
They should be aligned to organisational objectives and readily understood by stakeholders.
Framing metrics as a target should be approached with caution. Is your target meaningful?
Talk about how you are performing and then discuss whether this is more or less than is needed.
Metrics need regular reviews for changing priorities to ensure they remain meaningful.
Action – can you make a difference?
For a metric to be useful it needs to be in an area you can influence.
If you cannot improve it then you don’t want to be held accountable for it.
A good metric should drive changes to behaviour and service development.
The metric is only an indicator prompting research to understand what it might be telling you.
No numbers without stories
– no stories without numbers
Reproduce – can you measure it again?
A metric is a piece of research that should be repeatable.
This requires up front and ongoing transparency about methods.
You should see consistent results if you, or others, repeat research in a similar period.
Metric data collection needs to not be excessively burdensome. If it takes two solid months to
crunch the data then it probably is not reproducible.
You should use the best data available.
Compare – who with?
Metrics should allow you to see change over time.
Internal comparisons are most reliable as you can control more variables.
Be cautious and realistic if attempting to benchmark externally.
Even with reproducible metrics it is difficult to establish consistent data and avoid confounding.
For example – what is the impact of being in a Trust three times bigger? Or with three sites? Or
thirty? What kind of staffing model is in place? How is the service funded and delivered?

Más contenido relacionado

Más de Alan Fricker

Considering metrics for NHS Library Services
Considering metrics for NHS Library ServicesConsidering metrics for NHS Library Services
Considering metrics for NHS Library ServicesAlan Fricker
 
Extending ejournals to NHS partners (UKSG version)
Extending ejournals to NHS partners (UKSG version)Extending ejournals to NHS partners (UKSG version)
Extending ejournals to NHS partners (UKSG version)Alan Fricker
 
Quick introduction to critical appraisal of quantitative research
Quick introduction to critical appraisal of quantitative researchQuick introduction to critical appraisal of quantitative research
Quick introduction to critical appraisal of quantitative researchAlan Fricker
 
Point of Care tools - a four way look
Point of Care tools - a four way lookPoint of Care tools - a four way look
Point of Care tools - a four way lookAlan Fricker
 
How we redesigned a tired Library Space as a 24 hour knowledge hub
How we redesigned a tired Library Space as a 24 hour knowledge hubHow we redesigned a tired Library Space as a 24 hour knowledge hub
How we redesigned a tired Library Space as a 24 hour knowledge hubAlan Fricker
 
(The) health informaticist: collaborative blogging for health, fun and, erm, ...
(The) health informaticist: collaborative blogging for health, fun and, erm, ...(The) health informaticist: collaborative blogging for health, fun and, erm, ...
(The) health informaticist: collaborative blogging for health, fun and, erm, ...Alan Fricker
 

Más de Alan Fricker (6)

Considering metrics for NHS Library Services
Considering metrics for NHS Library ServicesConsidering metrics for NHS Library Services
Considering metrics for NHS Library Services
 
Extending ejournals to NHS partners (UKSG version)
Extending ejournals to NHS partners (UKSG version)Extending ejournals to NHS partners (UKSG version)
Extending ejournals to NHS partners (UKSG version)
 
Quick introduction to critical appraisal of quantitative research
Quick introduction to critical appraisal of quantitative researchQuick introduction to critical appraisal of quantitative research
Quick introduction to critical appraisal of quantitative research
 
Point of Care tools - a four way look
Point of Care tools - a four way lookPoint of Care tools - a four way look
Point of Care tools - a four way look
 
How we redesigned a tired Library Space as a 24 hour knowledge hub
How we redesigned a tired Library Space as a 24 hour knowledge hubHow we redesigned a tired Library Space as a 24 hour knowledge hub
How we redesigned a tired Library Space as a 24 hour knowledge hub
 
(The) health informaticist: collaborative blogging for health, fun and, erm, ...
(The) health informaticist: collaborative blogging for health, fun and, erm, ...(The) health informaticist: collaborative blogging for health, fun and, erm, ...
(The) health informaticist: collaborative blogging for health, fun and, erm, ...
 

Último

Cash Is Still King: ATM market research '2023
Cash Is Still King: ATM market research '2023Cash Is Still King: ATM market research '2023
Cash Is Still King: ATM market research '2023Vladislav Solodkiy
 
ChistaDATA Real-Time DATA Analytics Infrastructure
ChistaDATA Real-Time DATA Analytics InfrastructureChistaDATA Real-Time DATA Analytics Infrastructure
ChistaDATA Real-Time DATA Analytics Infrastructuresonikadigital1
 
YourView Panel Book.pptx YourView Panel Book.
YourView Panel Book.pptx YourView Panel Book.YourView Panel Book.pptx YourView Panel Book.
YourView Panel Book.pptx YourView Panel Book.JasonViviers2
 
Strategic CX: A Deep Dive into Voice of the Customer Insights for Clarity
Strategic CX: A Deep Dive into Voice of the Customer Insights for ClarityStrategic CX: A Deep Dive into Voice of the Customer Insights for Clarity
Strategic CX: A Deep Dive into Voice of the Customer Insights for ClarityAggregage
 
Elements of language learning - an analysis of how different elements of lang...
Elements of language learning - an analysis of how different elements of lang...Elements of language learning - an analysis of how different elements of lang...
Elements of language learning - an analysis of how different elements of lang...PrithaVashisht1
 
Virtuosoft SmartSync Product Introduction
Virtuosoft SmartSync Product IntroductionVirtuosoft SmartSync Product Introduction
Virtuosoft SmartSync Product Introductionsanjaymuralee1
 
SFBA Splunk Usergroup meeting March 13, 2024
SFBA Splunk Usergroup meeting March 13, 2024SFBA Splunk Usergroup meeting March 13, 2024
SFBA Splunk Usergroup meeting March 13, 2024Becky Burwell
 
5 Ds to Define Data Archiving Best Practices
5 Ds to Define Data Archiving Best Practices5 Ds to Define Data Archiving Best Practices
5 Ds to Define Data Archiving Best PracticesDataArchiva
 
TINJUAN PEMROSESAN TRANSAKSI DAN ERP.pptx
TINJUAN PEMROSESAN TRANSAKSI DAN ERP.pptxTINJUAN PEMROSESAN TRANSAKSI DAN ERP.pptx
TINJUAN PEMROSESAN TRANSAKSI DAN ERP.pptxDwiAyuSitiHartinah
 
CI, CD -Tools to integrate without manual intervention
CI, CD -Tools to integrate without manual interventionCI, CD -Tools to integrate without manual intervention
CI, CD -Tools to integrate without manual interventionajayrajaganeshkayala
 
How is Real-Time Analytics Different from Traditional OLAP?
How is Real-Time Analytics Different from Traditional OLAP?How is Real-Time Analytics Different from Traditional OLAP?
How is Real-Time Analytics Different from Traditional OLAP?sonikadigital1
 
Persuasive E-commerce, Our Biased Brain @ Bikkeldag 2024
Persuasive E-commerce, Our Biased Brain @ Bikkeldag 2024Persuasive E-commerce, Our Biased Brain @ Bikkeldag 2024
Persuasive E-commerce, Our Biased Brain @ Bikkeldag 2024Guido X Jansen
 
MEASURES OF DISPERSION I BSc Botany .ppt
MEASURES OF DISPERSION I BSc Botany .pptMEASURES OF DISPERSION I BSc Botany .ppt
MEASURES OF DISPERSION I BSc Botany .pptaigil2
 
Mapping the pubmed data under different suptopics using NLP.pptx
Mapping the pubmed data under different suptopics using NLP.pptxMapping the pubmed data under different suptopics using NLP.pptx
Mapping the pubmed data under different suptopics using NLP.pptxVenkatasubramani13
 
Master's Thesis - Data Science - Presentation
Master's Thesis - Data Science - PresentationMaster's Thesis - Data Science - Presentation
Master's Thesis - Data Science - PresentationGiorgio Carbone
 
The Universal GTM - how we design GTM and dataLayer
The Universal GTM - how we design GTM and dataLayerThe Universal GTM - how we design GTM and dataLayer
The Universal GTM - how we design GTM and dataLayerPavel Šabatka
 
AI for Sustainable Development Goals (SDGs)
AI for Sustainable Development Goals (SDGs)AI for Sustainable Development Goals (SDGs)
AI for Sustainable Development Goals (SDGs)Data & Analytics Magazin
 

Último (17)

Cash Is Still King: ATM market research '2023
Cash Is Still King: ATM market research '2023Cash Is Still King: ATM market research '2023
Cash Is Still King: ATM market research '2023
 
ChistaDATA Real-Time DATA Analytics Infrastructure
ChistaDATA Real-Time DATA Analytics InfrastructureChistaDATA Real-Time DATA Analytics Infrastructure
ChistaDATA Real-Time DATA Analytics Infrastructure
 
YourView Panel Book.pptx YourView Panel Book.
YourView Panel Book.pptx YourView Panel Book.YourView Panel Book.pptx YourView Panel Book.
YourView Panel Book.pptx YourView Panel Book.
 
Strategic CX: A Deep Dive into Voice of the Customer Insights for Clarity
Strategic CX: A Deep Dive into Voice of the Customer Insights for ClarityStrategic CX: A Deep Dive into Voice of the Customer Insights for Clarity
Strategic CX: A Deep Dive into Voice of the Customer Insights for Clarity
 
Elements of language learning - an analysis of how different elements of lang...
Elements of language learning - an analysis of how different elements of lang...Elements of language learning - an analysis of how different elements of lang...
Elements of language learning - an analysis of how different elements of lang...
 
Virtuosoft SmartSync Product Introduction
Virtuosoft SmartSync Product IntroductionVirtuosoft SmartSync Product Introduction
Virtuosoft SmartSync Product Introduction
 
SFBA Splunk Usergroup meeting March 13, 2024
SFBA Splunk Usergroup meeting March 13, 2024SFBA Splunk Usergroup meeting March 13, 2024
SFBA Splunk Usergroup meeting March 13, 2024
 
5 Ds to Define Data Archiving Best Practices
5 Ds to Define Data Archiving Best Practices5 Ds to Define Data Archiving Best Practices
5 Ds to Define Data Archiving Best Practices
 
TINJUAN PEMROSESAN TRANSAKSI DAN ERP.pptx
TINJUAN PEMROSESAN TRANSAKSI DAN ERP.pptxTINJUAN PEMROSESAN TRANSAKSI DAN ERP.pptx
TINJUAN PEMROSESAN TRANSAKSI DAN ERP.pptx
 
CI, CD -Tools to integrate without manual intervention
CI, CD -Tools to integrate without manual interventionCI, CD -Tools to integrate without manual intervention
CI, CD -Tools to integrate without manual intervention
 
How is Real-Time Analytics Different from Traditional OLAP?
How is Real-Time Analytics Different from Traditional OLAP?How is Real-Time Analytics Different from Traditional OLAP?
How is Real-Time Analytics Different from Traditional OLAP?
 
Persuasive E-commerce, Our Biased Brain @ Bikkeldag 2024
Persuasive E-commerce, Our Biased Brain @ Bikkeldag 2024Persuasive E-commerce, Our Biased Brain @ Bikkeldag 2024
Persuasive E-commerce, Our Biased Brain @ Bikkeldag 2024
 
MEASURES OF DISPERSION I BSc Botany .ppt
MEASURES OF DISPERSION I BSc Botany .pptMEASURES OF DISPERSION I BSc Botany .ppt
MEASURES OF DISPERSION I BSc Botany .ppt
 
Mapping the pubmed data under different suptopics using NLP.pptx
Mapping the pubmed data under different suptopics using NLP.pptxMapping the pubmed data under different suptopics using NLP.pptx
Mapping the pubmed data under different suptopics using NLP.pptx
 
Master's Thesis - Data Science - Presentation
Master's Thesis - Data Science - PresentationMaster's Thesis - Data Science - Presentation
Master's Thesis - Data Science - Presentation
 
The Universal GTM - how we design GTM and dataLayer
The Universal GTM - how we design GTM and dataLayerThe Universal GTM - how we design GTM and dataLayer
The Universal GTM - how we design GTM and dataLayer
 
AI for Sustainable Development Goals (SDGs)
AI for Sustainable Development Goals (SDGs)AI for Sustainable Development Goals (SDGs)
AI for Sustainable Development Goals (SDGs)
 

Do your metrics hit the MARC?

  • 1. Do your metrics hit the MARC? Alan Fricker Head of NHS Partnership & Liaison Aiming for better metrics? We want to have interesting and convincing discussions with our stakeholders. A carefully created metric can be at the heart of these. The Principles for Metrics report examines practice around metrics from a wide range of settings including NHS and academic libraries. A Quality Metrics Template accompanied the report to help with the creation, recording and sharing of metrics. Examining the four principles advanced by the report helps us understand the how and why of metrics. Do your metrics hit the MARC? References Metrics Task and Finish Group (June 2016) Principles for Metrics. Available at: http://tinyurl.com/PrinciplesForMetrics Metrics Task and Finish Group (June 2016) Quality Metrics Template. Available at: http://tinyurl.com/MetricsTemplate Meaning – who cares? The metric needs to be something people (not just you) care about. Meaningful metrics often combine more than one facet – e.g. usage by a particular staff group They should be aligned to organisational objectives and readily understood by stakeholders. Framing metrics as a target should be approached with caution. Is your target meaningful? Talk about how you are performing and then discuss whether this is more or less than is needed. Metrics need regular reviews for changing priorities to ensure they remain meaningful. Action – can you make a difference? For a metric to be useful it needs to be in an area you can influence. If you cannot improve it then you don’t want to be held accountable for it. A good metric should drive changes to behaviour and service development. The metric is only an indicator prompting research to understand what it might be telling you. No numbers without stories – no stories without numbers Reproduce – can you measure it again? A metric is a piece of research that should be repeatable. This requires up front and ongoing transparency about methods. You should see consistent results if you, or others, repeat research in a similar period. Metric data collection needs to not be excessively burdensome. If it takes two solid months to crunch the data then it probably is not reproducible. You should use the best data available. Compare – who with? Metrics should allow you to see change over time. Internal comparisons are most reliable as you can control more variables. Be cautious and realistic if attempting to benchmark externally. Even with reproducible metrics it is difficult to establish consistent data and avoid confounding. For example – what is the impact of being in a Trust three times bigger? Or with three sites? Or thirty? What kind of staffing model is in place? How is the service funded and delivered?