Systems Practitioner 6: Stakeholders’ Mental Models

Mapping the system starts through exchanging the perceptions of a problem and exploring questions such as:

  • What exactly is the problem we face?
  • How did the problematic situation originate?
  • What might be its underlying causes?
  • How can the problem potentially be addressed?
  • What barriers exist to deal with the problem?
  • What or who are potential drivers in the system?

WORKSHOP TO GATHER THE MENTAL MODELS OF ALL STAKEHOLDERS

Running a workshop to elicit the mental models requires a good facilitator and some key ground rules such as:

  • All knowledge, opinions, information are regarded as valuable.
  • Allow for discussion in order for stakeholders to understand each other’s mental models.
  • Avoid conflict by respecting each other’s knowledge and recording all opinions.

It is important to remember that in order to communicate with another person, one does not need to think (construe) in the same way, but be able to construe how the other person is construing.

This means that while divergent views occur, the appreciation of one another’s views gained through ‘mapping the system’ helps stakeholders to converge on a common understanding of the management system.

Effective communication can also help to change perceptions and expectations to make them realistic and achievable.

Workshop settings with all stakeholders involved could often lead to a group of people that, say, work for the same organisation, but have different levels of seniority.

We have conducted many of these workshops, for example in sustainable tourism in Cambodia, where the stakeholders included the full range from top government officials, such as the Minister of Tourism and Director General, to officials responsible for implementing policies, young officials still in the lower ranks of government, hotel owners, and taxi drivers.

In this situation it was not possible to obtain honest and in-depth insights into the mental models of all the participants.

Changing the nature of the workshop to a ‘silent’ sharing of people’s perceptions and ideas solved the problem of domination by senior officials, while juniors and people with no power remained totally quiet.

All participants put their mental models (responses on the above questions) on notes that were then anonymously put into big containers. This process revealed a very rich picture of the tourism sector through full participation by all stakeholders.

The downside was that very little discussion took place that could improve the understanding of each other’s mental models.

However, once the mental models were obtained and integrated into a systems structure, much discussion and co-learning eventually did happen.

HOW TO PUT THE MENTAL MODELS INTO KEY THEMES

In the following example women small-scale farmers and relevant stakeholders (in a Gates Foundation’s project) identified the issues they see as the key to their problems, potential solutions, barriers and drivers.

Participants in the workshop were encouraged to share their mental models of how they viewed the circumstances under which they live and farm and to think about potential solutions towards achieving their main goal, namely to improve the quality of their lives.

The various ideas were written down on sticky notes and then pasted on a white board. Many of the notes were the same, in which case the participants put the notes on top of each other.

The participants were then asked to discuss the different variables and to identify the main themes that emerged. The notes were rearranged around these main themes to produce a visual map of the mental models that evolved.

This step provides an opportunity for the stakeholders to discuss their mental models with each other and develop an understanding of how different stakeholders construe. Even if people do not agree with each other, all the ideas are left on the board.

This is the first step towards co-learning and developing an understanding of what the system under consideration looks like.

It creates a basis for reaching consensus on the main goal, and initiates the process of thinking how the different variables relate to each other.

The grouping into main themes significantly helps to integrate the mental models into a systems structure/model.

How Blockchain Will Impact Marketing and Advertising in 2019 & Beyond?

Blockchain can make advertising more transparent. It can reduce ad fraud, which is a larger problem than many are aware.

Blockchain can help maintain better management of display advertising. Blockchain allows privatizing our own data and has the potential to allow individuals to control how their data is used in regards to ad engagement

Some of these startups are Blockstack, Brave and BAT that aim to decentralize and improve ad delivery, privacy and data exchange.

Artificial Intelligence and The 4P’s of Marketing

Tom Edwards, Ad Age Marketing Technology Trailblazer and Chief Digital Officer, Agency and Epsilon discusses how the 4 P’s of marketing; Product, Price, Place & Promotion will need to evolve as intelligent systems redefine how we advertise and connect with consumers.

Understanding Psychographics, Predictive APIs, working through Proxy’s and Pervasive intelligent environments represent a new framework for marketing in the near future.

Artificial Intelligence in Marketing

Use AI to help make decisions.

Audience targeting and automatic content creation are just a few of the many ways AI can be used to help grow your user base and increase sales.

This video presents how some startups are applying AI to the marketing space and then programmatically walk through some AI techniques like matrix factorization, SVD, and LSTM neural networks that help a marketer outperform the competition and get the optimal results for their business.

Some existing services to use:

Appier.com – Aims to provide artificial intelligence (AI) platforms to help enterprises solve their most challenging business problems, including audience prediction.

Drawbridge.com – Connects, unifies, and supercharges customer data to create a complete view of the people you do business with, including predicting times types of users will be on a specific platform.

InsideSales.com – Delivers an AI-powered SaaS platform to guide sales teams to build better pipeline and close more of the right deals, including helping to find 20% of customer base that will convert

Persado.com – Persado applies mathematical certainty to words to help create phrases and words for content that drives action.

Systems Practitioner 5: Involving Stakeholders

THE IMPORTANCE OF INVOLVING ALL RELEVANT STAKEHOLDERS

Identifying, mapping and prioritising a project’s stakeholder community are the most important first steps in managing complexity.

Projects and other initiatives can only be considered successful when their key stakeholders acknowledge that they are a success. This requires the effective engagement of at least the key stakeholders to understand and manage their expectations and then deliver the outcome to meet or exceed these ‘managed expectations’.

Unravelling complexity requires information, knowledge, data, opinions and ideas. The stakeholders form the richest source of knowledge, because they are intrinsically involved in finding solutions to a complex issue since they have a ‘stake’ in the outcomes of any decision making and taking action.

Researchers in the field of systems thinking and modelling have acknowledged the importance of involving stakeholders.

Allowing for different perspectives and divergent views is not only important to enrich the knowledge source for finding solutions for the root causes of any problem, but also helps to ensure continued involvement of the stakeholders in the further processes of solving the issues (‘I add value; my knowledge is respected’).

‘Buy-in’ is essential for success in stakeholder engagement. Every party must have a stake in the process and have participating members who have decision-making power. Every party must be committed to the process by ensuring any action they take is based on the decisions made through the engagement.

Involving stakeholders to participate in solving their management problems instead of bringing in outside experts to solve these problems can be described as a ‘participatory’ or ‘bottom-up’ approach.

In participatory systems analysis, the involvement of stakeholders allows the multitude of factors that may influence outcomes or objectives to be identified, whilst systems thinking provides a mechanism through which these stakeholders can interact and discuss their understanding of the management system and the dependent relationships between these factors.

DIFFERENT MENTAL MODES

Each of us has a different set of visions, aspirations and views (mental models) of how to deal with the world around us. Our mental models contain information accumulated through our lived experiences. They determine our perception of new information and help us create new knowledge.

All people relate to the world by forming hypotheses about it, ‘testing’ these hypotheses through their everyday behaviour, observing the feedback from these interactions with environments or other people, and revising their hypotheses if necessary to fit the situation.

The ‘hypotheses’ or patterns of thinking are known as ‘constructs’, because they deal with how people ‘construe’ situations; that is how they develop mental models.

Mental models are ‘…deeply ingrained assumptions, generalizations, or even pictures or images that influence how we understand the world and how we take action…’.

Mental models reflect the beliefs, values and assumptions that we personally hold, and they underlie our reasons for doing things the way we do. They are so powerful in affecting what we do because they affect what we see and they shape our perceptions.

Mental models are the filters through which we interpret our experiences, evaluate plans, and choose among possible courses of action. The great systems of philosophy, politics, and literature are, in a sense, mental models.

Unfortunately, we cannot simply look at other people and discern their mental models, any collaboration and consensus of people is a matter of shared experience, coincidence, or the result of honest discussion and understanding.

When people grew up and lived in largely isolated communities, individual mental models among members of the community tended to coincide.

In the 21st century, isolation is rare and diversity, complexity and ambiguity are the norm.

We have all become interconnected in a vast physical and digital web.

Potentially contentious issues, such as healthcare, environmental protection, gender relationships, poverty, mental health, economic development, migration, land use or water allocation (just to name a few), are now tangled and magnified in a global system of ecological, economic, social, cultural and political processes, ideas and dynamic interactions.

In any government, organisation, business or community system there are many individuals with an interest in such systems (stakeholders) and each will have a mental model of the system and its purpose depending on their individual understanding, experience, education and values.

This means that among stakeholders there can be a multitude of views and different implicit and explicit understandings of how the processes of the system they are involved in work and the factors that would affect the purposes of the system.

In managing purposeful systems, it is important to accommodate the different world views of the stakeholders involved so that any proposed management interventions are informed by a breadth of available experience, and are acceptable to those who will need to implement changes or live with the consequences of their implementation.

Token Economies at Home

Building blocks and blockchain: preparing kids for the technology of tomorrow —  How one tech-savvy parent brought the lessons of a token economy home Entrepreneur, Professor at Singularity University.

This talk was given at a TEDx event using the TED conference format but independently organized by a local community.

Systems Practitioner 4: ELLab Framework

THE SYSTEMS-BASED EVOLUTIONARY LEARNING LABORATORY FRAMEWORK

This section describes a comprehensive systems thinking approach, embedded in a cyclic Evolutionary Learning Laboratory (ELLab) framework that is designed to deal effectively with complex issues in a variety of contexts.

The ELLab is an innovative systems-based framework – one that differs from other systems frameworks and approaches.

Innovation is embedded throughout the concept, design and application of the ELLab framework. Research and documentation of systems thinking abound in the literature and research journals.

However, its practical implementation and tracking of discernible impact is at best unclear, disjointed and highly variable.

The ELLab recognises these deficiencies in the practical application of systems thinking and provides a framework and implementation pathway to bridge the gap between science, research and the need to make a difference in the varied economic and socio-political environments in which decision makers, managers and the broader community grapple with the complexities of the real world.

The ELLab recognises the multi-dimensional nature of the broad environmental parameters and creates a practical approach to the engagement with stakeholders, identification of issues and the analysis and synthesis of the issues. Above all, the ELLab recognises that the impact of research is of little significance if the science is right but the application, analysis and route of impact are poorly executed.

In the ELLab, which is both virtual (a way of thinking; a concept) and real (individuals coming together to work for consensus), all stakeholders involved develop a deep understanding of the system, a shared vision and skills for systemic continuous adaption, innovation and improvement.

The ELLab consists of a unique seven step iterative process of thinking and acting in which the participants engage in well-defined activities, creating a systemic framework and environment where policy makers, managers, local facilitators, members of the community and researchers collaborate and learn together in an ‘experimental laboratory’ – to understand and address complex multidimensional and multi-stakeholder problems of common interest in a systemic way.

The ultimate goal is to achieve coherent actions directed towards sustainable outcomes.

The process of establishing an ELLab is a unique ‘methodology’ to collaboratively integrate and use existing and future knowledge to help manage complex issues. It starts at the ‘Fourth level of thinking’ with an issues workshop (step 1) and a series of forums with specialist groups to gather the mental models of all stakeholders involved in the issue under consideration, their perceptions of how the system works, what they regard as barriers to success and drivers of the system and possible strategies (solutions) to overcome these problems.

This is followed by implementing the ‘Third level of thinking’ through follow-up capacity building (step 2) sessions during which the participants (all stakeholders) learn how to integrate the various mental models into a systems structure (step 3).

The Vensim software program is a valuable tool for the development of a systems model (Causal Loop Diagram) of the issue under consideration. This learning step is of particular importance in order for all involved to take ‘ownership’ of the systems model.

Once completed, the participants move to the ‘Second level of thinking’ by interpreting and exploring the model for patterns, how different components of the model are interconnected and what feedback loops, reinforcing loops and balancing loops exist. This step aims to assist relevant stakeholders to develop an understanding of their interdependencies and the role and responsibility of each stakeholder group in the entire system.

The main barriers and drivers of the system are discussed in more detail, which provides the stakeholders with an opportunity to develop a deeper understanding of the implications of coordinated actions, strategies and policies.

Overall, this process provides all stakeholders with a better understanding of each other’s mental models and the development of a shared understanding of the issue(s) under consideration.

The interpretation leads to the identification of leverage points for systemic intervention (step 4).

Leverage points are places within a complex system (e.g. an economy, a living body, a city, an ecosystem) ‘where a small shift in one thing can produce big changes in everything.’

Senge also refers to leverage points as the ‘right places in a system where small, well-focused actions can sometimes produce significant, enduring improvements’.

Identification of leverage points greatly assists the devising of systemic interventions (finding systems based solutions) that will contribute to the achievement of goals or solving problems in the system under consideration.

The outcomes are used to develop a refined systems model, which at the same time forms an Integrated Systemic Master Plan (step 5), with systemically defined goals and strategies (systemic interventions).

In order to operationalise the master plan, Bayesian Belief Network (BBN) modelling is used to determine the requirements for implementation of the management strategies; the factors that could affect the expected outcomes; and the order in which activities should be carried out to ensure cost-effectiveness and to maximize impact.

The process of developing good policies and investment decisions is based on the best knowledge (scientific data and information, experiential knowledge, expert opinions) that is available at any point in time.

The systems model can be used to test the possible outcomes of different systemic interventions by observing what will happen to the system as a whole when a particular strategy or combination of strategies is implemented. That is before any time or money is invested in the actual implementation thereof.

Once the systemic interventions have been identified and an operational plan has been developed, the next step for the people responsible for the different areas of management is to implement the strategies and/or policies (step 6) that will create the biggest impact. Targets are determined and monitoring programs are implemented to measure and/or observe the outcomes of the strategies and policies.

In many cases it only requires an adjustment of existing monitoring programs to comply with the targets set within the ELLab process (e.g. to include factors to be measured that were used in the construction of the Bayesian Management Model).

Because no systems model can ever be completely ‘correct’ in a complex and uncertain world and unintended consequences always occur, the only way to
manage complexity is by reflecting (step 7) at regular intervals on the outcomes of the actions and decisions that have been taken to determine how successful or unsuccessful the interventions are and to identify unintended consequences and new barriers that were previously unforeseen.

In summary, the ELLab framework is generic and is designed to deal with any complex issue, regardless of its context (e.g. from large organizations and natural or social systems, to a dysfunctional family or a small business that is not profitable) or discipline area (e.g. business, health, engineering, education, marketing, development, environmental management and so on). The following sections provide further elaboration on and demonstration of various successful applications of the ELLab framework in solving complex problems in a variety of contexts