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explore close menu close search for: entire site art & design behaviour change business complexity design thinking education & learning ehealth emergence environment evaluation food systems health promotion innovation journalism knowledge translation marketing psychology public health research science & technology social innovation social media social systems strategic foresight systems science systems thinking uncategorized search for: search categories systems thinking complexity design thinking innovation social systems education & learning public health psychology behaviour change social media systems science evaluation research science & technology uncategorized health promotion emergence knowledge translation art & design ehealth tags complexity design innovation systems thinking design thinking evaluation psychology public health social media social innovation learning education knowledge translation developmental evaluation research mindfulness science health promotion health creativity archives september 2018 august 2018 may 2018 april 2018 october 2017 september 2017 censemaking contemplating complexity, designing innovation systems thinking complexity design thinking innovation social systems close back to top top evaluation meaning and metrics for innovation cameron d. norman on september 13, 2018 metrics are at the heart of evaluation of impact and value in products and services although they are rarely straightforward. what makes a good metric requires some thinking about what the meaning of a metric is, first. i recently read a story on what makes a good metric from chris moran, editor of strategic projects at the guardian . chris’s work is about building, engaging, and retaining audiences online so he spends a lot of time thinking about metrics and what they mean. chris – with support from many others — outlines the five characteristics of a good metric as being: relevant measurable actionable reliable readable (less likely to be misunderstood) (what i liked was that he also pointed to additional criteria that didn’t quite make the cut but, as he suggests, could). this list was developed in the context of communications initiatives, which is exactly the point we need to consider: context matters when it comes to metrics. context also is holistic, thus we need to consider these five (plus the others?) criteria as a whole if we’re to develop, deploy, and interpret data from these metrics. as john hagel puts it : we are moving from the industrial age where standardized metrics and scale dominated to the contextual age. sensemaking and metrics innovation is entirely context-dependent. a new iphone might not mean much to someone who has had one but could be transformative to someone who’s never had that computing power in their hand. home visits by a doctor or healer were once the only way people were treated for sickness (and is still the case in some parts of the world) and now home visits are novel and represent an innovation in many areas of western healthcare. demographic characteristics are one area where sensemaking is critical when it comes to metrics and measures. sensemaking is a process of literally making sense of something within a specific context. it’s used when there are no standard or obvious means to understand the meaning of something at the outset, rather meaning is made through investigation, reflection, and other data. it is a process that involves asking questions about value — and value is at the core of innovation. for example, identity questions on race, sexual orientation, gender, and place of origin all require intense sensemaking before, during, and after use. asking these questions gets us to consider: what value is it to know any of this? how is a metric useful without an understanding of the value in which it is meant to reflect? what we’ve seen from population research is that failure to ask these questions has left many at the margins without a voice — their experience isn’t captured in the data used to make policy decisions. we’ve seen the opposite when we do ask these questions — unwisely — such as strange claims made on associations, over-generalizations, and stereotypes formed from data that somehow ‘links’ certain characteristics to behaviours without critical thought: we create policies that exclude because we have data. the lesson we learn from behavioural science is that, if you have enough data, you can pretty much connect anything to anything. therefore, we need to be very careful about what we collect data on and what metrics we use. the role of theory of change and theory of stage one reason for these strange associations (or absence) is the lack of a theory of change to explain why any of these variables ought to play a role in explaining what happens. a good, proper theory of change provides a rationale for why something should lead to something else and what might come from it all. it is anchored in data, evidence, theory, and design (which ties it together). metrics are the means by which we can assess the fit of a theory of change. what often gets missed is that fit is also context-based by time. some metrics have a better fit at different times during an innovation’s development. for example, a particular metric might be more useful in later-stage research where there is an established base of knowledge (e.g., when an innovation is mature) versus when we are looking at the early formation of an idea. the proof-of-concept stage (i.e., ‘can this idea work?’) is very different than if something is in the ‘can this scale’? stage. to that end, metrics need to be fit with something akin to a theory of stage . this would help explain how an innovation might develop at the early stage versus later ones. metrics are useful. blindly using metrics — or using the wrong ones — can be harmful in ways that might be unmeasurable without the proper thinking about what they do, what they represent, and which ones to use. choose wisely. photo by miguel a. amutio on unsplash share this: twitter facebook linkedin google email pinterest pocket more tumblr print reddit like this: like loading... evaluation innovation understanding value in evaluation & innovation cameron d. norman on september 10, 2018 value is literally at the root of the word evaluation yet is scarcely mentioned in the conversation about innovation and evaluation. it’s time to consider what value really means for innovation and how evaluation provides answers. design can be thought of as the discipline — the theory, science, and practice — of innovation . thus, understanding the value of design is partly about the understanding of valuation of innovation . at the root of evaluation is the concept of value. one of the most widely used definitions of evaluation (pdf) is that it is about merit, worth, and significance — with worth being a stand-in for value . the connection between worth and value in design was discussed in a recent article by jon kolko from modernist studio. he starts from the premise that many designers conceive of value as the price people will pay for something and points to the dominant orthodoxy in saas applications “where customers can choose between a good, better, and best pricing model. the archetypical columns with checkboxes shows that as you increase spending, you “get more stuff.”” kolko goes on to take a systems perspective of the issue, noting that much value that is created through design is not piecemeal, but aggregated into the experience of whole products and services and not easily divisible into component parts. value as a factor of cost or price breaks down when we apply a lens to our communities, customers, and clients as mere commodities that can be bought and sold. kolko ends his article with this comment on design value: design value is a new idea, and we’re still learning what it means. it’s all of these things described here: it’s cost, features, functions, problem solvi

URL analysis for censemaking.com

https://censemaking.com/tag/cense-research-design/
https://censemaking.com/tag/teaching/
https://censemaking.com/category/social-systems/
https://censemaking.com/category/ehealth/
https://censemaking.com/2018/09/10/understanding-value-in-evaluation-innovation/?share=tumblr
https://censemaking.com/tag/organizational-change/
https://censemaking.com/page/57/
https://censemaking.com/2018/09/
https://censemaking.com/2018/05/16/how-do-we-sit-with-time/?share=facebook
https://censemaking.com/tag/research/
https://censemaking.com/tag/seth-godin/
https://censemaking.com/tag/arts/
https://censemaking.com/tag/innovation/
https://censemaking.com/tag/mental-health/
https://censemaking.com/2018/09/10/understanding-value-in-evaluation-innovation/

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Domain Name: CENSEMAKING.COM
Registry Domain ID: 1681857919_DOMAIN_COM-VRSN
Registrar WHOIS Server: whois.wildwestdomains.com
Registrar URL: http://www.wildwestdomains.com
Updated Date: 2018-06-12T08:04:26Z
Creation Date: 2011-10-13T00:38:29Z
Registry Expiry Date: 2019-10-13T00:38:29Z
Registrar: Wild West Domains, LLC
Registrar IANA ID: 440
Registrar Abuse Contact Email: [email protected]
Registrar Abuse Contact Phone: 480-624-2505
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Domain Status: clientRenewProhibited https://icann.org/epp#clientRenewProhibited
Domain Status: clientTransferProhibited https://icann.org/epp#clientTransferProhibited
Domain Status: clientUpdateProhibited https://icann.org/epp#clientUpdateProhibited
Name Server: NS1.WORDPRESS.COM
Name Server: NS2.WORDPRESS.COM
DNSSEC: unsigned
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  REGISTRAR Wild West Domains, LLC

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DOMAIN

  NAME censemaking.com

  CHANGED 2018-06-12

  CREATED 2011-10-13

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