Response to Ofgem’s open letter on vulnerability strategy

By Nicky Hodges

25 January 2019

CSE's Nicky Hodges responds to Ofgem’s 13 December open letter on vulnerability strategy ... 

In response to your open letter, I argue in this piece that the strategy would benefit from a more sophisticated visual model of the interacting multi-level factors that influence risks of vulnerability. This is both to help actors better discern what risk factors they need to attend to reduce vulnerability in specific areas of market activity and, in turn, to help the regulator and energy businesses identify appropriate levers for change, including making better use of available legislation. In other sectors, such models aid identification of factors at different tiers and encourage thinking about how policy and market interventions and other factors interact to influence outcomes (eg health outcomes or behavioural outcomes). The piece briefly picks up on the Equality Act as it applies to suppliers of goods and services as one underused lever for urging progress towards a more inclusive energy market.

Develop a more sophisticated model of vulnerability risk factors to support action

Ofgem’s working definition of vulnerability is concise [note 1] and, within the strategy, is backed by more detailed exploration of the risks factors involved. The vulnerability strategy rightly identifies that vulnerability is to do with risk factors, mentions interaction between different risk factors and recognises temporality as a dimension of vulnerability: a person can move in or out of vulnerability. 

The strategy also contains a simple visual representation of how risk factors interact to influence a consumer’s vulnerability:

Figure 1: Ofgem’s model to show factors that influence vulnerability.

The strategy references a variety of evidence of how specific individual characteristics, circumstances and situations are associated with or possibly are a cause of vulnerability. Since the strategy has been written, undoubtedly more recent evidence has been produced regarding how particularly individual or ‘circumstantial’ factors interact with particular forms of energy market activity (such as the smart meter rollout) such that some consumers experience greater than average barriers to engagement or experience unequal opportunities or poor outcomes. Hopefully also there is now emerging evidence of what interventions have enabled consumers experiencing disadvantage or detriment to engage equally in the energy market and to receive services in a way that helps them attain benefits and avoid detriment.

However, the short definition of vulnerability, out of the context of the strategy and simple model is extremely open-ended and provides minimal, if any direction on what is an appropriate scope and approach to mitigate harm for consumers associated with vulnerability. The model doesn’t name the various different risk factors or which sets of factors make vulnerability worse or more complex. It gives no sense of which individual vulnerability risk factors are easier or harder to identify, more or less intractable, or which, by being addressed, will achieve broadly shared benefits or address particularly acute cases of vulnerability.

Reported evidence of how a factor is associated with worse risk of harm is hidden in the text of the strategy – or in referenced documents. Without continued reference back to the full strategy (or hopefully, their own data and intelligence), people with strategic direction or day to day responsibilities for delivering a service to potentially vulnerable consumers may variously:

  • Feel overwhelmed by a long list of possible vulnerability characteristics and circumstances, with little sense of how these interact, compound, change over time, and the effect for risk likelihood or severity.
  • Resort to a convenient list of stereotypes and/or easy access ‘vulnerability’ identifiers: ‘older than x’, ‘uses electricity-dependent medical equipment’, ‘live in rural location’, ‘on means-tested benefits’, ‘on our PSR’, ‘gets Warm Home Discount’.  
  • Pick and choosing ‘easy wins’ and ignore more costly or harder to address vulnerability situations
  • Have limited sense of scale, scope, progress, remaining gaps, changes over time or how to prioritise ‘most acute vulnerability’, ‘most persistent vulnerability’, ‘most severe detriment’, ‘most widespread detriment’ or of the value for money of actions taken.
  • Have limited sense of where a more inclusive approach to service delivery is most appropriate or where it is currently necessary to provide the service in a different way for certain groups to achieve the same outcome. 
  • Overlook or be unaware of the specific needs and barriers experienced by consumers who do not ‘self-identify’ as vulnerable or who do not ‘show up’ via available indicators or mapping or other identification strategies, leaving them at risk of harm.

It is understandable that Ofgem does not want to prescribe a master list of ‘vulnerable’ groups of people. But that is what some operators have compiled for themselves in their efforts to work out who they need to support and how to go about this.

A more sophisticated visual model or a series of infographics centred around service areas or area of transformation could enable a sharpened focus on how switching services, smart metering support, billing, debt support,  could be reshaped to be inclusive by design, rather than Ofgem needing to design a  ‘safety net’ for people who don’t fit a ‘typical consumer’ model.

Particularly as the energy sector changes, there is opportunity for Ofgem to play a more active role as regulator in encouraging the development of innovative services that are inclusive by design and in a way that enables fair outcomes for different consumers, with flexibility to the different and changing needs and circumstances of consumers. A consumer-centred model that makes visible the different known or potential risk factors for vulnerability may help Ofgem achieve this.

Use of models and illustrations in other policy areas

The interaction between people’s own personal characteristics, their social, economic and cultural circumstances, events over their lifecourse and the particular way in which energy as a service is ‘delivered’ is complex and changes over time. This makes it hard to pin down who is ‘vulnerable’ and relative levels of risk of exposure to harm. 

In other policy areas, the recognition of interacting factors has led to the development of models which help with thinking through the issues and identifying possible ways to reduce risks of vulnerability and harm.

Social determinants of health models (eg Dahlgren & Whitehead 1991) show a rainbow type visual model of the personal characteristics at the core of the model to illustrate how social and environmental factors, people’s living and working conditions, and individual lifestyle factors can interact to determine people's risk of getting ill, their ability to prevent sickness, or their access to effective treatments:

Figure 2: Dahlgren & Whitehead rainbow - the social determinants of health [note 2].
The model has been influential in shaping research and its application of what influences health outcomes.

Behavioural change models similarly explore how different interventions interact with individual’s capabilities, opportunities and motivations to shape behaviour change. The COM-B model highlights how different policy categories can influence behaviour and how different intervention functions can influence behaviour, interacting with the capabilities, opportunities and motivations of the individual.

Figure 3: COM-B behavioural change model [note 3].

Illustrations of the social definition of disability draw attention to how factors in the built and economic environment, social attitudes and organisational rules create disability, as illustrated in the infographic below [note 4].

This philosophy underpins inclusive design or universal design approaches within the built design sector, encouraging identification of barriers to accessibility and usability for different groups of people in society and then towards design which enhances the overall usability for everybody.

Helping to identify new levers for action

Use of models that encourage a more holistic recognition of the factors that influence vulnerability and how wider factors interact with individual characteristics could help in identification of other levers for change. As an example, there is arguably potential for the vulnerability strategy to draw more on the Equality Act 2010 as a powerful lever for action, in terms of setting expectations for what energy companies must do as a provider of goods and services to avoid direct or indirect discrimination and to proactively identify and make reasonable adjustments to make their service accessible for disabled people. Such attention is likely to bring benefits for consumers more generally.


Ofgem needs to build on the 2013 strategy’s work to tease out the factors which interact to give rise to vulnerability in the energy market. The concise definition is good but leaves too much to interpretation. Ofgem needs to encourage the further building and application of evidence about vulnerability risk factors. A visual model or set of infographics that highlight which risk factors associated with different energy service areas – switching, debt management, billing, uptake of new technologies – could support industry-wide action. This is likely to interact positively with better data sharing and analysis. CSE are keen to help develop a model or set of illustrations and to engage with others in building the evidence of risk factors for vulnerability and changes that make for a more inclusive and fairer energy market, in the context of transition to smarter and more flexible low carbon energy system. 


Note 1 | Our definition of vulnerability is when a consumer’s personal circumstances and characteristics combine with aspects of the market to create situations where he or she is: Significantly less able than a typical consumer to protect or represent his or her interests in the energy market; or Significantly more likely than a typical consumer to suffer detriment, or that detriment is likely to be more substantial.

Note 2 | Image from

Note 3 | Michie, Susan & van Stralen, Maartje & West, Robert. (2011). The Behaviour Change Wheel: a new method for characterising and designing behaviour change interventions. Implementation science : IS. 6. 42. 10.1186/1748-5908-6-42.

Note 4 |

Nicky Hodges is a Senior Researcher at CSE with over 20 years experience in devising and undertaking qualitative and mixed method research.

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