Translating insights from a causal loop diagram into a game
C.E. van Daalen, P.W.G. Bots, M.J.A. Hendriks, J.H. Slinger
Faculty of Technology, Policy and Management, Delft University of Technology,
P.O. Box 5015, 2600 GA Delft, The Netherlands
Phone: +31 15 2781143
Email : elsd@tbm.tudelft.nl
This paper concerns a project of limited scope to study why innovations in health care often
fail to be adopted and how this may be improved. The project consisted of two workshops
with participants from different areas of health care. The objective was to identify factors
influencing adoption of innovations, relating the factors to each other, and looking for
measures to stimulate the adoption of innovations. During the first workshop, possible effects
of innovations and prerequisites for adopting innovations were identified and prioritised. This
resulted in draft causal loop diagrams. During the second workshop, refined diagrams were
used to identify measures for stimulating the adoption of innovations. In addition, a game
incorporating the results of the workshops was developed. The main causal mechanisms were
translated into the game which can be played by people who work in health care to improve
their understanding of some of the dynamics involved.
Key words: causal loop diagram, health care, innovations, game, group model building
Background
Concemed by a lack of adoption of innovations in health care, the Ministry of Health,
Welfare and Sport in The Netherlands requested advice from the Dutch Council of Public
Health and Health Care on measures to stimulate the adoption of innovations. Delft
University of Technology was asked to contribute to this project. Two workshops were held
with professionals and managers from different areas of health care. The workshops were
aimed at determining factors influencing the adoption of innovations, relating the factors to
each other, and identifying measures the Ministry can take to stimulate the adoption of
innovations. In this sense, the workshops were an addition to the extensive scientific
investigation of factors that can hinder or facilitate innovations in health care organisations by
Fleuren et al. (2002). The findings from the workshops were reported to the Council of Public
Health and Health Care, and were also translated into a board game that can be played by
people who were not involved in the workshops, but who would like to learn more about the
results.
In the next section, the set-up of the workshops will be explained. Following this, the results
of the workshops will be discussed. The final section concerns the design of the game and
some preliminary results of playing the game prototype.
Workshop design
The first workshop was a one day workshop aimed at identifying factors and relating these
factors to each other. The second workshop was a half day workshop which was geared
towards identifying measures that can stimulate the adoption of innovations. A variety of
methods were used to achieve these results. These methods will be explained below. Nineteen
participants attended the workshops. The workshop participants were from diverse
organisations in health care, such as patient organisations, hospital management, home care
organisations, ICT suppliers, insurance companies, and health care professionals.
The first workshop consisted of three general parts: (1) identifying the effects of, and
conditions for, the adoption of innovations, (2) brainstorming and prioritising the effects and
conditions, and (3) mapping the relations between the factors in causal diagrams.
The identification of factors was carried out in a novel way using a role playing method,
which we termed a ‘gamelet’ (Bots and van Daalen, 2005). Eliciting variables is often done
using a brainstorming technique. However, because the identification activity had to be
conducted at the beginning of the workshop and people did not know each other very well, a
role playing method, which allowed participants to speak out freely as they took on their role,
was developed. In addition, brainstorming does not include argumentation of the factors,
whereas in the role playing exercise people had to put forward their arguments. In the
gamelet, the participants were presented with a case description of an innovation that is still in
a research or test phase, but may become a real possibility in the (near) future. These
innovations were: operation robot, life shirt, online doctor, and hospital at home. The
innovations ranged from more technically oriented innovations with organisational
components to a purely organisational innovation. Each gamelet involved nine participants, so
the group was split up into two smaller groups. A brief case description of one of the cases
was handed out to the participants of a gamelet. The assignment was to play a meeting in
which three of the participants were in favour of the innovation and three other participants
had to be convinced of its merits. There were also three observers who wrote down all the
factors and arguments mentioned at the meeting table. The observers were also asked to note
any factors they thought of, but that were not mentioned. The meeting about one innovation
lasted for 15 minutes. Afterwards there was a facilitator-led discussion about the possible
effects of the innovation and conditions for adoption. A second case was then handed out to
the participants and another gamelet was carried out. Following the meetings and discussions
of all the cases, the effects derived from all the different cases were combined into one list,
and the conditions pertaining to the different cases were also combined into one list. This way
of identifying factors of importance to the issue proved very appealing to the participants. The
ten participants who responded to a questionnaire on the workshops gave an average of score
4.3 (scale 1 = bad to 5 = excellent) to the gamelets, with everyone giving a score of either a 4
orao.
The lists of effects and conditions were then entered into the computer and presented to the
participants in a Group Decision Room (Nunamaker et al., 1997). This is a meeting room
fitted with computers and specialised software allowing participants to, amongst other things,
generate and prioritise ideas. Both lists were presented to the participants. Participants were
asked to add factors to the lists that they thought were missing, e.g. possibly due to the
specifics of the cases used in the gamelets. These completed lists were then presented on the
screen and the participants were asked to electronically prioritise the lists in order to find the
most important effects and conditions. The appreciation of this method by the participants
showed substantial spread with participants either scoring this method very high or very low
(mostly 2 or 5).
After identifying the most important factors to be included, first version causal diagrams of
parts of the system were drawn. The first diagram showed the possible effects of adoption of
innovations. This was drawn in conjunction with the group in a plenary session to illustrate
the method. The other diagrams were drawn in three smaller groups. These diagrams
consisted of influences on client commitment towards adoption, on commitment of
professionals towards adoption and on management commitment. These four parts were
chosen because a preliminary analysis showed that there would be too many factors to fit into
one diagram and these seemed to form reasonable submodels that would be approximately
similar in size. The diagrams that were drawn up during the workshop were refined by the
researchers between the first and the second workshop and were used as a starting point for
the second workshop. The activity of drawing up the causal diagrams came much less natural
to the participants than the first two activities. It was difficult for the participants to see what
the contribution of this analysis would be. The method scored an average of 3.4 in the
evaluation of the workshop. This time, there was no sharp division in opinions, but a range of
scores.
During the second workshop, the way in which the causal diagrams had been refined was first
explained to the participants. The participants then split up into two groups. Each group sat
around a very large print out of one of the four refined causal diagrams. Using Nominal
Group Technique (VanGundy, 1988), they were asked to identify measures that could
influence the factors in the causal diagrams in a way that this would lead to an increased
adoption of an innovation. The measures were written on post-it notes and stuck onto the
causal diagrams next to the factors that they could influence. Each group discussed two out of
the four diagrams. Then the groups switched places and the facilitator explained the measures
that were identified by the other group for the other two diagrams. When all possible
measures had been clarified, the participants were given small coloured stickers to stick onto
the measures they thought were most important. This resulted in a prioritised list of measures,
including the factors that were considered to be influenced by the measures. The participants
gave an average of 4.1 as a score for the identification of measures using the causal diagrams
(ranging from 3 to 5).
Workshop results
The first workshop resulted in a list of the most important effects of an innovation and a list of
the most important conditions for an innovation to be adopted. The most important possible
effects (positive or negative) of innovations which were identified were:
effectiveness for client
efficient care
transparency
client satisfaction
costs
client empowerment
possibility for performance measurement
changing role of medical personnel
co-operation within organisation
systematic collection of patient (experience) data
The most important conditions for an innovation to be adopted were:
(scientific) justification of innovation, proven results
presence of believer or promoter of innovation
commitment of management / whole organisation
presence of a culture of quality
presence of implementation techniques
presence of ways of measuring added benefits
quality of leadership
¢ benefit to user
* organised client (patient) associations
« willingness to be held accountable / to be transparent
The initial causal diagrams from the first workshop were refined using the approximately 60
variables contained in the final prioritised lists. Although not all of these variables may have
been equally relevant to the issue at hand, they were all used in order to make the diagrams
recognisable for the participants. There are four different diagrams (factors influencing client
commitment to the innovation, factors influencing the professional’s commitment to the
innovation, factors influencing management commitment to the innovation, effects of the
innovation) which were drawn up separately. The interactions between the different parts are
assumed to be as shown in Figure 1. The connections between the different parts do not
originate directly from the workshops, but were inspired by Repenning (2002).
Figure 1. Schematic overview of main factors.
During the second workshop, measures that may stimulate the adoption of innovations were
identified. This was done using the detailed causal diagrams drawn up after the first
workshop. The most important categories of measures that were identified are related to
increasing the visibility of proven results, financial measures, and accountability
requirements. The measures which received the highest ranking in these categories are the
following:
Visibility
¢ independent institute (research, communication, network)
* awareness programme (in organisation)
e broad think tanks; innovation platform for health care
¢ multidisciplinary innovation brigades (visiting organisations)
Financial measures
¢ output financing
« feeding back profits to sector (e.g. profits due to shorter patient recovery times)
¢ structural financing directly related to innovation
Accountability
¢ benchmark for culture of leaning
¢ (require) external accountability
A schematic diagram of the influence of the measures at a very general level is shown in
Figure 2.
Figure 2. Overview of types of measures.
For the adoption and continued application of an innovation it is necessary that the
reinforcement loop that has been described by Repenning (2002) comes into play and works
in a positive way rather than in a negative way. Reinforcement loops for all the stakeholders
can be seen in Figure 2 above. For each of the stakeholders (management, professionals,
clients) the structure of the loop is the same and is shown schematically in Figure 3. Although
the structure of the loop is the same, the effects of an innovation will be valued in a different
way by each of the stakeholders. Their satisfaction with the same innovation can, and
probably will, be different.
commitment of stakeholder
Long =O M
satisfaction of stakeholder innovation adoption
effects’
Figure 3. Schematic representation of feedback from effects to adoption.
If adoption of the innovation leads to positive effects with which a stakeholder is satisfied,
this will lead to a higher commitment and continued application of the innovation. When the
net effect of adoption of the innovation is negative for a certain stakeholder, this will lead to
dissatisfaction and the innovation will no longer be supported. It is possible that negative
effects of an innovation only become clear in the long term, after which non-adoption or
rejection may occur (this effect is also mentioned by Homer, 1987). Another possibility is that
it takes longer than expected before the positive effects of an innovation become visible and
satisfaction and commitment will decrease (this effect is also mentioned by Repenning, 2002).
Repenning also indicates that people initially are often sceptical about an innovation and it is
necessary to take additional measures for the commitment to be directed in a positive way.
Translating the workshop results into a game
The game is aimed at people who were not involved in the workshops, but wish to leam more
about the results. The game gives the players the experience of being involved in decisions on
innovations with the objective of contributing to deeper learning than would occur by merely
reading the workshop report. Figure 4 (Sterman, 1994) shows that feedback from the real
world can cause changes in mental models. Sterman also indicates that for learning to occur,
each link in these feedback loops must work effectively (double loop learning). Since it is
difficult for people to obtain full information about the real process of adoption of innovations
in health care, and it is not feasible to experiment in the actual situation, a virtual world (a
game in this case) can contribute to the learning process (Sterman, 1994).
Teal world
lr wa
decisions information feedback
a a
strategy, structure, mental models
decision rules of real world
We
Figure 4. Introducing a virtual world (bold arrows) into the learning loop (adapted slightly
from Sterman, 1994).
The general point of departure for the health care innovation game has been to develop a
game which has correspondence with the diagram shown in Figure 2. The game is a role-
playing board game. There are three main stakeholders in the game (clients, professionals and
management). The stakeholders are roles that are played by the players. A board contains
positions for the three different players and the description of a specific innovation project can
be placed on the board. The game is played by each of the players going through rounds of
the commitment-adoption-commitment loop (Figure 3). This will result in a certain pattern of
adoption of an innovation project over time. Afterwards, the players can see how well the
innovations did over time, and discuss why these patterns are present. Reflection is necessary
for the game to be effective in stimulating the learning process (Sterman, 1994).
Translating the main loop into the game dynamics
When translating a system dynamics model or causal loop diagrams into a game, links
pertaining to decisions can be removed from the model, and these links can be replaced by
human decisions that are to be made by the players. In this way, the players add the
information feedbacks to the game. The main loop in this case was discussed above and is
shown in Figure 3. This loop is similar for all three roles. In the game, the automatic
connection between “satisfaction” and “commitment” is removed for each role. The players
will receive information about the payoff of a certain innovation (i.e. satisfaction) and decide
on their amount of support (commitment) for a certain project themselves. This support will
then automatically determine the level of adoption of the innovation. The effects will be
calculated and the satisfaction can then be calculated again. This allows players to choose
their next amount of support based on their satisfaction. A number of rounds (i.e. iterations of
the loop) are played in order to see the pattern of behaviour over time. The total amount of
support a player can give in each round is limited. This reflects the limited innovation
capacity of the stakeholder (how much change they can bring about).
Link between innovation and its effects
As can be seen in Figure 3, there is still a question mark between the adoption of the
innovation and the effects. The game includes different projects. Each of these projects
contains a description of the specific project and its specific outcomes. The outcomes are
values of the most important effects that were identified during the first workshop:
effectiveness, costs for client, costs for organisation, and work pressure/changing role. In
order for the game to remain comprehensible, only these four effects have been included.
Link between effects and satisfaction
At the beginning of the game, each player chooses a utility function. They can say in which
way they, of course from the perspective of their own role, value effects of an innovation. For
example, client satisfaction may only be based on effectiveness and costs to the client. This
would mean that for the client, the satisfaction related to an innovation would be calculated
purely on the basis of outcomes on these two effects, whereas management would probably
value all effects, but with differences in the weighing factors.
Link between satisfaction and commitment
As was stated above, the link between satisfaction and commitment is not one that can be
calculated in the game. Players choose their own level of commitment towards an innovation.
In addition to choosing how to represent the main causal mechanisms, various other choices
have to be made when designing a game (van Daalen et al., 2004). The general choices that
were made for the innovation game are summarised in Table 1.
Table 1. General design choices for the health care innovation game.
function learning about adoption of innovations in health care
plot stakeholders in an organisation have to take decisions about
supporting (or not supporting) different innovation projects
goal of game/incentive player’s goal is to achieve the highest satisfaction score (most
positive net effects)
roles client, professional and management - three stakeholders together
represent one project organisation
people playing real stakeholders, but not necessarily playing their own role
tules e rules for action: players have a limited amount of resources to
support innovation projects and at the beginning of each round
they place their support on one or more innovation project
descriptions; based on the support the players have entered,
there are calculation rules to calculate the implementation
level and effects of an innovation
e rules for interaction: players can freely negotiate about their
preferences and try to convince the other players to support
their preferred innovation project
physical system representation | e an organisation is represented as a table; the table has three set
places for the three players
e innovation project boards are placed on the table (in the
organisation); these project boards can show the support for
and progress of an innovation project
e aspecific innovation project is represented as a card with a
description and indication of its effects; an innovation project
can be placed in the middle of an innovation project board
« support fora certain project is represented by tokens; the
tokens can be placed on the project boards by the players
interaction environment « — no specific interaction environment within organisation, table
representation at which players sit is also negotiation table
¢ _ organisation has to provide a yearly progress report
Increasing the complexity
The basic workings of the game are discussed above. The game has been extended to make it
more realistic, to incorporate the possibility of implementing measures and to include a
diffusion loop (Repenning, 2002) whereby others observe the results of the innovation which
can also increase commitment.
There is always more than one innovation project on the table. Players have limited
resources to support innovation projects. This means they will have to choose between
different projects.
More than one game is played in parallel. Each game represents one organisation. By
playing various games in parallel, different organisations can be played. Each table plays
innovation rounds at their own pace. So one organisation can innovate faster than others.
There are three roles that don’t have a place at a specific table, but are overarching for all
games. These are: government, research institutes and health insurance companies. These
players have measures available to influence the adoption of innovations. The measures
are based on the measures that resulted from the second workshop. Research institutes can
influence the visibility of innovations. When the research institutes see that a project is
doing well in one organisation they can stimulate other organisations to initiate the
project. Government can provide subsidies or set legislation. When costs of health care
rise or fall, the health insurance player can increase or decrease client costs across all
tables. These three general players make decisions only at set times during the game, after
the organisations have delivered their yearly progress reports.
As in the beer game (Sterman, 1992), players calculate their own results. For each of the links
in the major loop, there is a calculation rule that the players use. Players keep track of their
satisfaction (i.e. pay off) on each project and the group (representing one organisation) keeps
track of the level of adoption of the different innovation projects. After the game, players can
see which projects did well and which projects did not do well and analyse the reasons for
this.
Results of working with the prototype
At present, the game is still in the prototype phase. The practical implementation of the game,
including (calculation) rules, is shown in Appendix A. The aim is to use the game as part of
the dissemination activities related to the release of the advisory report that the Council of
Public Health and Health Care will present to the Minister of Health, Welfare and Sport. This
report is due to for presentation prior to the summer of 2005.
The prototype game has been played a number of times with colleagues. In playing the
prototype game, some properties of the system which were described above (relating to the
behaviour of the loop) did indeed come to the fore.
« Players always start with the ‘easy wins’. These are the small projects with only benefits.
However, in the long run these advantages will be smaller than those of some of the larger
projects with more complicated benefits and costs. This means that it is difficult to start
projects that don’t have only positive effects or need a lot of support to start with.
« When they have been playing the game for some time, the players suddenly realise that
investing in projects that may not have only positive short term effects but that do have
large benefits on the long run, would have given them much better results. Once they
realise that it would have been better to start earlier with these types of projects, they are
more prone to investing in these types of projects that follow.
¢ It was also found that players usually start with a large innovation project portfolio and
then come to the conclusion that it would be better to concentrate on running a smaller
number of projects at the same time, and to try to get those projects to maturity first,
before starting new projects.
- A fourth finding was that after some time players see that they can make ‘package deals’
with other players in order to increase their own success.
Conclusions
This project incorporated a number of new ideas: the use of gamelets and translation of
workshop results into a game. Gamelets were used for generating variables and elucidating
arguments relating to these variables. The gamelets worked very well in identifying relevant
variables. The elicitation of variables is often done shortly after the beginning of a workshop
(see e.g. time-schedules for a typical one-day workshop by Andersen and Richardson, 1997)
and people may not know each other very well. A gamelet allows participants to speak out
more freely because they take on a role. It also makes participants look at the problem
situation from different angles because they have to take on different roles, and includes
argumentation of the factors. Participants were very positive about this way of identifying
variables. The gamelet concept can be used as a way of structuring this task instead of using
the Nominal Group Technique, for instance, or in addition to the Nominal Group Technique.
The second idea was that of translating the results of a group model building session into a
game. The starting point of the game is the reinforcing loop from commitment to adoption
and back to commitment. The general rule in designing the game was to replace a link
representing a decision (a link which closes an information feedback loop) by a human
decision (e.g. deciding how much support to give to a project in this game, or deciding on the
orders in the beer game) and have the players of the game make the decision. The game is
then played by going through the loop in rounds. Because this is a board game which does not
involve any automatic computations, rules for what happens at each step (in the loop) and
how the participants move from one step to the other (e.g. by calculating intermediate results)
had to be derived. Although the game is still at a prototype phase, tests with the prototype
indicate that the game can help participants in thinking about the consequences of supporting
or not supporting innovations. The game also shows that players start with the easy wins, and
hesitate to invest in projects that pay off only in the long run. Although the game was made
for application to innovations in health care, it can be translated to other fields of application.
References
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TNO-rapport PG/PVZ 2002.203.
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Sterman, J.D. (1992). Teaching takes off: flight simulators for management education. OR/MS
Today (October), pp. 40-44.
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10, Nos. 2-3, pp. 291-330.
VanGundy, A.B. (1988). Techniques of Structured Problem Solving. New Y ork, Van
Nostrand Rheinhold.
10
Appendix A.
management
Practical implementation of the game
Figure Al shows the configu-
vation of one table, which
represents a project organisation.
Each stakeholder has a colour
(clients: yellow, management:
ogo
blue, professionals: red) and a
set place at the table according to
the project boards (see Figure
A2). At start of the game, all
players receive ten support
tokens of their own colour. They
client
fit td i!
iil
also receive a sheet on which
they write down their utility
function and scores for each
|| professional innovation round (as will be
explained below). New projects
can be started by placing them
on an empty project board.
Figure Al. One project organisation per table.
‘Current supp
Implementation
End of project: after 2 rounds above pay-off treshold
no 900000000
#0 0 6 0 0 0000 0
390 00 600000 0
38.0 0 0.0.0.0 .0_0_0__O Pmt
7-0-0" -"G-- O-- OO OG ~ Oeeshat
692 920606000000
=50 00600000000
=40 00060600000 0
239 2000000 0 0
=20 000000000
=10 00 6000 00 0
Figure A2. Project board.
The project board (Figure A2) has an area fora
project card (see also Figure A3), space for
each player to lay their support tokens, and an
empty graph to enter the implementation level
of the project in each project round. In this
way, the support each stakeholder gives at a
certain moment is visualised by the tokens, and
the current and past states of the project are
shown at the bottom of the board. In fact, the
implementation level can be seen as a time
graph (see two examples below).
290000 0 © © © © © Oo
9 92 29290 9 902020090 9
Qo 9 2 2 9 9 oo 0 0 0 0
8.10000. O18, 9.9 9 0 9 oO
oO OG -O--O oO O° OOO
o oo @ 90 9 o 09 0900 0
20000 90 © 0 0 0 0 Oo
o 0 @ 60 0 O 0 0 @ @ 0 6
o 90 0 6 9 9 oo 0 0 @ 0
9 @ 0 090 90 0 @ 0 0 00
@ 0 0 000 @o00 80
The project board consists of an A-4 size paper
copy (in colour). The circles are filled up
(using pen) as the game progresses.
11
A project card
z-W (example in Figure A 3)
Tachnclogicaldeipeusiaiondlinnavailan shows a description of
' decrease workload ‘Technological-organisational innovation a project on one side.
content the project ‘2 decrease workload! The other side shows
worlod wl detcase In dan he weabent effets ay the values of the four
Bearman ere. sonnets Oy ee effects of the specific
etecs of the project 3 Se — ess — «| project represented by
ayaa tec || | Certain | numbers of
me, there wil bea retum onthe investment. The
acl alan rasa ig’ he toni ob
Project 3 fects). These effects
change once the pay-
Back Front off threshold has been
reached. Project cards
Figure A3. A sample project card. are reusable and are
covered in plastic.
Calculation rules
Project implementation
Project implementation is calculated in each project round:
* Current support = support / support minimally needed (only whole numbers, rounded
downwards)
* Implementation = previous implementation - 1 leak + current support
The implementation values are drawn in by colouring the circles on the project board, to
provide the graph over time.
A project ends after two rounds of support above pay-off threshold. The support tokens for
this project then fall free to be used for new projects, while the pay-off of the completed
project becomes permanent.
Client, management and professional
At the start, each stakeholder defines his or her own utility function (i.e. priorities) for the
four effects (Figure A4, top right hand comer). This means that they have to indicate the
relative importance for each of the four effects (e.g. how important do they consider
effectiveness in relation to decreasing workload, from the point of view of the role they are
playing).
Each project round, players calculate the scores for their personal score sheet (Figure A4)
where ‘smileys’ from the project card (Figure A3) count as +1 and ‘frownies’ as -1.
* Project Effect = (utility 1 x effectiveness count) + (utility 2 x cost for organisation count)
+ (utility 3 x workload count) + (utility 4 x cost for client count)
* Project Total = Project effect x implementation (note: project total indicates player
satisfaction)
The players write down their own personal scores on their score sheet. The player with the
highest score at the end of the game wins within the organisation and the organisation with
the highest total score wins the game.
12
Priorities (ota 7, max. 2x0)
Management fOr ann | vir enectuecenmene:
Name: * cost savings organisation:
Table number: + decreased worki
«cost savings client:
PROJET [innovation round
title yyy as 7 a 8 ay ay aa] 19] 1a] 18] a6] a7) 48] 49) 20
FT etfact
FT tar
P2 effect
Feta
PS effect
PS totar
Figure A4. Form for each player to write down utility and scores.
Yearly reports
At set times, each organisation delivers a yearly report with scores for each project.
* Organisation project score = implementation x ‘smiley count’ per effect (not taking into
account the utilities)
The players (or the facilitator, in case of few participants) with the role of government, the
role of knowledge institute, and the role of insurance company receive these sheets.
Government
Government looks at how well organisations score on innovations and can take measures to
stimulate certain innovations or organisations, e.g. to publish the scores of the different
organisations for all the players at all tables to see (representing a benchmark).
« Organisation project score per organisation and © Organisation project score per project
Knowledge institute
The knowledge institute can distribute additional support tokens to organisations to provide
additional stimulation. The number of additional tokens is calculated on the basis of how well
innovations are doing across all the organisations:
¢ Number of additional support tokens = © implementation of all projects in the game / 8
Insurance company
The insurance company calculates the total benefits (effectiveness, cost savings for
organisation, and cost savings for clients; not the decreased work load) over the past year and
redistributes this by way of points to the clients at all the tables. In this way, savings made by
certain organisations will find their way back to all the clients of the insurance company and
not just within the organisation.
¢ Insurance points for a project = > all effect ‘smileys’ except work load (because unlike
costs for organisation, work load decrease does not reduce the overall health costs)
¢ Project total = Insurance points x implementation of project
« Decrease of insurance burden for client = ¥ all project totals in the game / number of
project organisations (= #tables)
13
