Creating Effective Management Simulations: Rapidly, Responsibly, Relevantly

Abstract

This chapter presents a critical discussion of the current state of management simulations and considers this specific genre of software against the backdrop of wholesale gamification of activities within organizations and the widespread popularity of games that are available for a variety of computing devices. These two contemporary phenomena are presented as a tension to current management simulations that require synthesis. The chapter then progresses to an exploration of the possibility of a systematic approach to consistently define management simulations that encourage academic involvement through the authorship of games as well as building an aspiration to make simulations more “game-like” in their interface. The purpose of this approach is multiple. It provides a consistent framework that helps to democratize the creation of simulations, provides an input language around which developers can then develop multifunctional simulation platforms and engines, and, more speculatively, provides a solid platform on to which additional layers of visual “game” play can be developed. Being able to package the essence of a simulation into a distributable file that can be used interchangeably at other institutions also encourages wider use of simulations as the key kinesthetic form of learning within management education.

1. Introduction

The many opportunities for incorporating gamification within everyday life and the advantages that it brings are an important rationale for the increasing digitalization and digital transformation in all aspects of work and play. Gamification encourages purposeful engagement with a product or service for longer periods of time than might otherwise happen. Through apps such as Strava, our personal leisure time has been gamified, and Microsoft Viva tries to create the same emotional and even competitive responses with our work Outlook calendar.

Gamification is possible as part of everyday activities because of two closely interrelated phenomena. The first phenomenon is the widespread process that has driven the digitalization of “serious” products and services, enabling a systematic unpicking of processes, the sequences of actions and activities that can be isolated and manipulated. By viewing work and play as a sequence of smaller and more granular activities, it is possible to then attach numeric values and weightings to each undertaking and completing each activity in ways that create scores. Individual scores and relative rankings can then be shared through social media. A score or ranking is a more self-contained unit of comparison than the explanation required for all the actions that brought you to that outcome. Searching for “Strava rankings” through Google will even directly embed the top three cyclists in “Distance Leadership” on its results page. Achievements of this type can also become badges to permanently share through social media. Within the world of work and through the Open Badges system, LinkedIn enables professional success to be displayed in this way too.

An exemplar of the process of digitalization and the opportunities that this process brings is found in the move away from using physical media in the distribution of films and music. Shifting music consumption patterns onto a streaming service enables new music to be recommended based on listening preferences and enables everyone to have their own entirely personalized radio station. A user experience that effectively describes the product that is Spotify. Popular music is one example of gamification that existed prior to widespread digitalization. Because sales, downloads, or listens can be measured so readily that the use of the weekly music charts has existed for over 70 years. And Spotify has a range of charts to introduce a form of light competition across multiple dimensions of artists and songs that now includes a “daily viral song” chart. As such an integral aspect of popular music, it is sometimes difficult to recognize the long-term presence of gamification. But music industry also introduces an important lesson about the benefits of gamification. Gamification can reflect back positively on the core business by driving new sales and introducing greater awareness of new artists. Gamification does not necessarily work well if it is “tacked on” without thought and cannot clearly offer additional value for the end user.

The digitalization of core products and services benefits from being supplemented with additional digital assets, including badges, scores, and unlockable extras. But, briefly, moving away from consumer gamification there are similar benefits for the application of gamification within the internal operations of an organization. As consumer technology shows, turning an activity into a score enables comparison and inevitably, competition. Introducing a scoring mechanism can be a way to motivate people to retry actions to improve which can, in turn, improve overall efficiency and productivity. This is particularly useful in situations where repetition is necessary to bring mastery. It should be stressed that solely repetitive roles are those most likely to be automated. However, mastery within a role that includes variability and change is building the capacity to deal with the one-in-a-hundred, one-in-a-thousand, and one-in-a-million situations when they arise and being able to recognize these situations in the future. Within a work environment introducing a form of scored competition can encourage teams to compete in ways that improve overall performance and encourages knowledge sharing between team members to improve personally and collectively. The Leagues.ai system does exactly this. By providing a mechanism for competition at granular levels of the organization, it is possible to reward strong individual performance on a weekly basis. Over longer periods of time the Leagues.ai system can provide a rank order of success that imitates the team ranking table in a football or a cricket league.

Working alongside the new opportunities offered by the digitalization of “serious” goods is the second phenomenon that makes gamification possible; a proliferation and wide-ranging continuum of games. There is a vast array of “idle games” or “clicker games” that are downloadable from the various platform app stores for playing on mobile devices or directly accessible for play through a browser window. This specific genre of the game relies on the primary mechanic of clicking on items to use them in some way. Clicking generates an in-game income that can be increased by spending some of this income on upgrades. This is why the games are sometimes described as “incremental games”. This category of games employs three significant mechanics that are also highly relevant for gamification within other domains. In these games, there is a reward for returning, there is a push to leave (in order to return), and the dynamics of the game will shift as a player improves their experience and knowledge of the game [1]. These three elements can also be found in the application gamification tactics either singly or in combination across many examples. The creator of one of the best-known incremental game, AdVenture Capitalist, has documented the maths behind these games. In describing the variants around the exponential growth found in the games there are also indications of how the three key mechanics of clickers are embedded within this code [2]. In order to keep players coming back despite the relatively simple mechanics. These are games that have had the principles of gamification reflected onto themselves. Clicker games can also make good business. The Idle Heroes game was reported to have achieved US$70 m in net revenue in its first two years of availability [3].

However, these numbers pale in comparison to the “serious” games that require the advanced computing power of a dedicated games console or PC. The headline numbers show the scale of these activities with a global industry worth US$300 billion and 2.9 billion active users [4]. A more startling finding is that gamers, on average, spend 16 hours a week playing games and another 8 hours watching gaming streams [4]. The speculation from the industry is that these numbers will also continue to grow. With a third of the global population engaged in gaming and with an inevitable distortion in favor of the 70% of the world population living within developed economies, games are everywhere. All these figures indicate that games are a key aspect of popular culture and everyday life.

While the prevalence of gaming is impressive there are also strong indications that engagement with games is clustered more heavily among younger people. The uptake of a relatively simple word game, such as Wordle, offers a somewhat surprising indication of this bias and challenges the assumption that this simple word puzzle game might be more popular with older people. With 300,000 daily players in the US, the generational differences are noticeable. “In total, 26% of respondents in the [millennial] generation said they play “Wordle,” compared to 18% of Gen Zers and 9% of Gen Xers. Just 5% of baby boomers are playing the game.” [5]. Perhaps indicating different preferences for consuming and accessing games, the private British Broadcaster ITV reintroduce its gameshow “Lingo” in 2021 based on the success of Wordle and a full 33 years after the original 10-episode run, which was a licensed format taken from the US television. With a free-to-air broadcast time in the UK of 3 pm, the show is presented for primarily an older audience or those with home caring responsibilities.

The value of gamification rests on these twin pillars that see the digitalization of “everything” and the dominant role of games in popular culture. The benefits of successful gamification are significant as any product or service will benefit from increased engagement and long-term connections with its target audience.

2. The challenge creating by management simulations

A key area of activity where there is a continuous need to create effective and meaningful engagement is higher education. Within higher education, the various disciplines have developed a heritage of ensuring engagement with students that works at an immediate level, when the student enters education and still has relevance within their future careers. The pedagogic engagement is aligned with professional outcomes [6] and tends to sit within kinesthetic modes of learning rather than the more commonly used straight reading/writing or auditory modes. Put more simply, it is the Bunsen burner effect enjoyed by chemistry. A student walking into a chemistry lab on their first day is excited by a subject that lets them burn things. While the Bunsen burner may not figure a part of every lesson, it is symbolic of the discipline and may continue to be used by a graduate if they continue to work in chemistry. Similar examples can be found in other areas of higher education. At one point, there was a tradition in some universities offering aeronautical engineering courses that graduating students would build a wind tunnel as almost a form of a rite of passage. New students benefitted, as they had wind tunnels to place their new models into. It may be apocryphal, but there are claims that this graduating practice fell out of favor because the cumulative result was too many wind tunnels in the department.

The Bunsen burner effect can also be seen beyond the sciences. Theater and drama students have studios and theaters to practice and perform. In some universities, because these facilities were developed as part of recent new builds, the quality and capability of the spaces exceed in quality anything else available in the local area. In the area of health education, the use of patient simulators has extended beyond CPR dummies and covers areas including midwifery and the correct placement of monitoring devices. The concept of clinical simulation is an important tenet of nursing education where the reduction of risk and the avoidance of errors in real situations is essential. One curious indication of how embedded the use of patient simulators has become is the thriving second-hand market on sites, such as eBay, for antique and unusual examples.

Creating the Bunsen burner effect for business education brings several challenges. Although sometimes presented as a single discipline there are multiple bodies of knowledge to understand. To matters worse, these bodies of knowledge also span from the most qualitative to the most quantitative. While economics is regarded as a major intellectual contributor to the wider realm of business there is no one aspect of the body of knowledge that necessarily dominates. The learner is often guided to choose their —own specific priorities and preferences all without a Bunsen burner effect in sight. The UK makes use of subject benchmark statements, in an effort to create light touch uniformity across all degree awarding institutions. For business and management, the 2019 statement summarizes a three-point purpose for degrees in this area, as given below:

• Increasing understanding of organizations, their management, the economy, and business environment.

• Preparation for and developing a career in business and management.

• Enhancement of a wide range of skills and attributes, which equip graduates to become effective global citizens [7]

While there is a constant revision to the statements it is unlikely newer versions will shift noticeably from this intentionally vague, career-orientated but nonetheless worthwhile statement of purpose.

Further into the statement, however, the topics of knowledge and understanding that a business and management graduate should be able to exhibit are made more explicit. These is an extensive list: markets, marketing and sales, customers, finance, people, organizational behavior, operations, information systems and business intelligence, communications, digital business, business policy and strategy, business innovation and enterprise development, and social responsibility [7]. There is no expectation that graduates have equal knowledge of these thirteen or seventeen categories as many are interrelated. But despite this interlinkage, the list also emphasizes the breadth of knowledge expected of a graduate in this field. The list of expert skills that are expected to manifest within a business graduate is also impressive. The list covers seven or ten quite divergent capabilities: people management, problem-solving and critical analysis, research, commercial acumen, innovation, creativity and enterprise, numeracy, and networking. Graduating with the knowledge and skills expected by the benchmark statement does help to explain why business degrees are sometimes regarded as being general-purpose or even generic degrees but perhaps they are better seen as multipurpose.

The challenge that comes with such a broad range of topics and skills is that few Bunsen burner effects emerge with topics that can largely be taught in a traditional or online classroom. Students new to business studies can also bring many misconceptions to this classroom, driven by their own consumption of mainstream media representations. The HBO series Succession or the Netflix series Ozark may shape their understanding of how business works, it may even have been viewed by the prospective student as a type of documentary. A distorted and exaggerated representation of businesses permeates media consumption from an early age, for example, with the Krusty Krab, through to media requiring viewer discretion, such as Los Pollos Hermanos. There are most certainly lessons to be learned in all these examples that align neatly with the subject benchmark statement, but no business degree exclusively uses the deconstruction of popular media representations of business to deliver their intended learning outcomes. Teachers and academics will tend to focus on issues, examples, and concerns that are currently pivotal or were perhaps contemporary during the period of their own studentship. If the academic has actively engaged in research of the topic, they will tend to use this material in the classroom too. In 2018, the UK communications regulator Ofcom conducted research to identify news consumption patterns. Of the 12–15 age group, 40% indicated little or no interest in the news, but 53% said it was “important to know what is going on.” However, the most interesting news topics for this age group were sports (19%) and music (18%). Although this age group cited Facebook (34%) and YouTube (27%) as popular new sources only 34% thought that social media sources reported content truthfully [8]. This milieu of perspectives can create a frustrating session for an academic trying to bring some contemporary issues into a first-year business studies classroom.

These gaps in perspective need to be bridged to deliver effective teaching that will translate into contemporary learning. But a classroom environment does not reflect any graduate’s day-to-day reality. At this point business educators often turn to management simulations for a solution but the prevalence of games in everyday life and the potential misnomer of “business games” then opens up a chasm. Students are offered what appears to be a Bunsen burner moment with the tantalizing use of “games” only to be disappointed by—depending on the simulation being used—a clunky, nonintuitive interface that they must first be trained to use before they even begin playing a “game.”

Business simulations have a long history of merging the need for understanding key concepts within the framework of current and future issues. Although it may seem outdated now, MIT’s Beer Game from 1960 sets the tone for most subsequent simulations being used today. This heritage brings challenges. Reflecting this sixty-year heritage most business simulations present a user interface that will invariably feel dated to an audience who are daily immersed in the rendered game worlds, slick apps, streaming videos, and dynamic content. Almost all existing simulations are designed with pre-set values and built for a single disciplinary standpoint among the 13 or 17 options found in the subject benchmark statement. These simulations generally used fixed calculations and present a pre-configured scenario with set decision points. More recently introduced products have brought greater ability to “tweak” some values but generally only modestly in order to not overly disrupt the core scenario. Most management simulations can be characterized as standalone opaque-box software with variable capabilities to integrate with institutional Learning Management Systems (LMS).

Although somewhat of a tangent to the main thrust of discussion, the relatively slow evolution of management simulations in contrast to the development of entertainment game genres, does also reflect the absence of critical software studies within academic discourse. Examination of software as an artifact of the organization and the cultural conditions that built it is a fruitful but under-recognized line of inquiry. The tendency is to examine individual pieces of software as separate phenomena characterized by the descriptions of sales volumes or active monthly users. Reporting of this type reflects the assumed neutrality of software that pervades mainstream thinking. However, the software does shape opinions and perspectives. This can be evidenced by a variety of examples from social media where the anonymity of the 4chan system enabled the origins of the QAnon conspiracy theory [9], the use of the 3½” floppy icon to indicate the save function on even the most recent user interfaces despite not being in common use for 20 years [10] and then consider how during the COVID-19 pandemic people would always complain when asked to use a video-conferencing software that was the not first one they used [11]. The general basis of resistance was that it was not simple or intuitive enough in comparison to their favorite–first–video conferencing software they experienced. For the student of business taking a critical view of software is beneficial [11]. Many management simulations exist and these cover the full range of knowledge areas they must cover. As different products are offered by different companies there is no consistency of user experience between titles in this genre of software and there is often a need to “train” the learners on every new simulation they encounter.

The productization of management simulations means that few institutions now have the capacity or infrastructure to create their own simulations. Instead, they must identify the best possible fit from among available titles and either work with that existing configuration options or possibly pay additional fees to enjoy customizations that make the simulation closer fit the curriculum requirements. In a period when work to decolonize the curriculum [12] is receiving renewed and reinvigorated attention this lack of flexibility will eventually force more rapid evolution among simulation software vendors.

As it currently stands and much to the disappointment of many first-year learners, a business “game” is not what they expect.

3. The anatomy of a management simulation

Software tends to be judged by its user interface. This is an important part of all software and is why software engineers undertake user experience and user interface testing. But beneath the interface exists the code that manages the other aspects of all software. For management simulations, this code performs a relatively limited number of actions. The decisions being made in each turn are received from user input–usually a straightforward Web form-like interface—and formulaic calculations are applied. Some calculations will be informed by previous decisions made at earlier turns; some calculations will have random influences introduced to the calculation. These random influences can be as simple as a random number generator function between a specified range being applied in each turn. Some vendors also claim real-world influences can be incorporated into their simulation such as historical Nasdaq data.

At the core of a simulation are the calculations that it performs on the user’s decisions and subsequent input. The calculations are represented through a variety of algorithms that have been documented in a significant body of literature [13] that particularly covers supply, demand, marketing, and finance. However, the body of literature also reveals that for some calculations there is no definitive scholarly agreement about which algorithm correctly models the observed experience. Beyond this level of scholarly debate, experiments have been conducted with business students that purposefully inserted faulty algorithms into a simulation. The conclusion of this research was that players were unable to detect the error and the error’s presence had no impact on the quality of their economic performance [14]. In many ways, this conclusion confirms the opaque-box nature of simulations as students—or instructors—cannot see which algorithms are being utilized or when. It is a real consideration as to whether algorithmic validity is simply assumed when institutional purchasing decisions are being made, or whether algorithmic validity is only one aspect of the many considerations within the experience of the overall game world irrespective of the user interface [14]. Since the mid-2000s the number of academic papers discussing algorithms for management simulations have declined significantly. Two potential speculations regarding this decline are possible: the algorithms are now business sensitive to those companies productizing management simulations, and more generously, the algorithms that are being used are well-documented through conventional literature within the specific area of knowledge. This later speculation could be regarded as true for many common functions that are applied in everyday business, such as the power function and the price elasticity of demand. But as an opaque-box what specific algorithms are being used are obscured from the academic and their learners. The original Beer Game is perhaps a rare example of a largely transparent simulation, but this is partly a result of its longevity and relative simplicity. It is primarily based on the Bullwhip effect and the goal is to try and manage available resources on the wholesale side to minimize the amplifying effect of small changes applied on the retail side.

A common linkage between the Beer Game and many of the more recent developments is their connection to system dynamics thinking. That is a systems-based view of organizational activity that examines long-term change to recognize the functions of a system in order to abstract regular models of observed behavior. A system dynamics approach lends itself to algorithmic validity precisely because of this abstracted nature. While the algorithms will not model precise day-to-day behaviors, the tendency will be to provide an accurate outcome based on the received inputs. Many of the algorithms are relatively “simple”—with the benchmark for “simple” being the ability to recreate the algorithm as a formula within a single cell in Excel. But no commercial management simulation enables an individual installation to “tweak” existing underlying formulas or to completely replace the preferred option with an alternative perspective. The 30,000 papers regarding the bullwhip effect on Google Scholar offer the clear suggestion that there have been some refinements to the concept and its representation since the Beer Game was first introduced. Although some of these papers are also admittedly and effectively formal academic documentation of how to win the Beer Game. This specific body of work could be seen as a marker of how effective, debated, and engaged with that this particular simulation has been across its lifetime.

While software-based management simulation provides the kinesthetic learning and Bunsen burner effect for business students, there is one further example of a more practical experiment from the 1970s that goes beyond being the computer interface of a simulation to becoming the reality. It is notable that the project, directed by Stafford Beer and a cybernetician, came from a different intellectual tradition than that of system dynamics. This is a sufficiently different enough community of practice to have already seen Beer create an analog computer in the 1950s out of a pond with scientist, author, and artist, Gordon Pask [15]. Beer’s published work in cybernetic theory as well as related topics and practical work with United Steel, SIGMA, and the International Publishing Company all brought Beer to the attention of the new Allende government in Chile [15]. By 1971, Beer was in Chile working with the government building project Cybersyn to coordinate the many newly nationalized industries [16]. Project Cybersyn was closely modeled on Beer’s theorization of the viable system model, which present a specific model of how the parts of an organization relate to one another and to the external world. Beer applied these principles to create a centralized control room—echoing the title of his book that had first attracted the Allende’s government’s interest, “the Brain of the Firm.” [17] The control room received daily reports from individual industries, including farms and mines, that reported on outputs and other key metrics. Within the control room decisions were then made through a strategic lens considering the current prevailing international and domestic political and economic conditions. Most importantly individual production decisions were made with fuller knowledge of national conditions, including upcoming peaks in demands or changes to government policy. The resultant decisions were then conveyed back out to the different elements of the economy controlled by the government. In some cases, this may have been an instruction to reduce production or even to call for a temporary cessation of certain activities. Cybersyn used the latest technology of the period with custom-designed chairs for the control room—that oddly echoed those of the Star Trek television series a decade earlier—and Teletext machines to enable immediate nationwide communications [16]. In fact, Cybersyn was itself four sub-projects; Cybernet, the national network of telex machines, Cyberstride, the software system that created alerts when a variable fell outside an acceptable limit, CHECO, an attempt to model the entire Chilean economy, and the OpsRoom, the control room at the center of the system and based on the concept of the war-room with seven chairs facing each other representing separate elements of the economy that were being reported [18]. Ultimately, Cybersyn is an unfinished and unproven experiment as the Allende government was soon overthrown in a military coup, and Beer was forced to flee Chile.

The Cybersyn approach is instructive for a rethinking of management simulations in the way that it (necessarily) separates inputs, decisions, actions, and outcomes. The management simulation puts the student into the control room where they can see their decisions produce consequences in terms of resultant short-term and longer-term outcomes. The unfinished and inaccurate CHECO sub-project [18] also reinforces how difficult it can be to accurately define multiple models of different aspects of an economic situation that must also necessarily interact with each other. Sometimes, any decision is better than no decision, particularly in an environment that is permeated with incomplete data. The Cybersyn experience also raises a more mundane question for management simulations. This is a question of the default settings offered for each decision at each turn. Many simulations may force a student to make a decision each turn with a blank input box or a slider set to zero. Some simulations will use the student’s previous inputs as the default for their next turn—even if other circumstances have subsequently changed. Far fewer simulations will offer a “median” default option that would provide a “steady state” outcome for the turn being played. This approach would mean that the most neutral response would neither disadvantage nor advantage a student unexpectedly, something that is possible in the other scenarios for setting default values. This perverse situation can be occasionally spotted in practice too, when a simulation that uses the input of other students to calculate the current environmental situation accepts extreme inputs from disengaged students (such as “0”) and unwittingly rewards them as inaction was ultimately, and unexpectedly, the most suitable decision for that particular turn.

These examples all highlight different ways in which simple algorithmic validity is not the sole or even primary basis for a successful simulation. The way the game world is created and enables students to interact and compete with one another are equally crucial factors for a successful simulation. These are the gamification elements found inside a simulation. But even these considerations still ignore the way a simulation might actually be played as a game in the way that it might be popularly understood outside a university environment. The majority of simulations are text-based affairs with inputs based on variants of HTML based forms, for example, radio buttons, checkboxes, dropdown menus and free-text boxes. There is a general absence of a rendered, flowing or interactive game world.

These are the multiple areas in which all management simulations need to progress. But also important is the need to re-introduce the capability for academics to create simulations for their own specific needs rather than needing to resort to a productized and generalist simulation that best matches their requirements.

4. Rapid, responsive, relevant simulations

Confronted by the many challenges facing a business academic to bring a relevant simulation rapidly into the classroom, it is possible to see why some give up, some accept the nearest match to what they need, and some will accept whatever was offered on the syllabus last time around. It is by no means laziness on the part of the academic but a diminished capacity to deal with technologies that they are unfamiliar with, navigating internal approval systems to purchase something new, or having the time to understand the different forces being modeled in each new simulation. Change, in this respect at least, in terms of pedagogic practice is incredibly difficult. These are the many factors that are already at play before any consideration is given as to how new students may receive any form of changes being made to their learning experiences. While a new management simulation may bring quantifiable improvement on the previous syllabus there will still be a need to accommodate and adjust student expectations to decouple the association of simulation in management education from their perceptions of game-based simulators or games in general. The reality is that, in terms of the student experience, the clock can only be reset to zero with every new delivery not many have deep and sweeping change may be in contrast to the previous delivery.

The solution to the many issues raised by this current situation is not a simple, neat, or pretty one as it necessarily exposes the workings of a simulation beyond the attention of the developer alone. It could be argued to also be an idealistic one that expresses a preference for open access and open-source forms of working in preference to a closed proprietary system. The solution also requires more organizations to work together and interact then it is currently the case within the productised world of packaged software genre of management simulations. However, this level of transparency and collaboration is itself an appropriate way to transact contemporary business and focuses on the adage that you concentrate on what you do best. That is, academics are good at knowledge exchange and software developers develop systems that can enable this knowledge exchange. The solution is represented by four separate layers of activity and development. Each layer is independent of the other and can certainly function independently without knowledge of one another. Separating these four layers of activities enables existing organizations and individuals involved with management education to potentially contribute their own specialism without having to become specialists in any one of the other layers. Importantly, academics can (once again) become engaged with the creative process of building simulations by contributing their own existing knowledge without having to become technicians or developers. The additional benefits of this layered ecosystem are clear in contrast to the existing packaged software approach.

The four layers described in this proposed solution for a simulation ecosystem are the story layer, the simulation description layer, the decision-making layer, and the visualization layer. Each of these layers is presented as part of a dynamic simulation ecosystem.

4.1 The story layer

The story layer is the ideation layer of a simulation. It exists within completed research, case studies, and within the experiences of those creating the simulation. The story layer already exists through a range of resources, including the UK’s Case Center (thecasecentre.org), where thousands of different business case studies are curated and made available (for a fee) to students and academics. The value of cases as the core story for a new simulation is that they are relatively brief and, in the written form, they then follow a consistent structure. Importantly, business cases are not complete stories. “The case must quickly pull the reader in and force them to think about what they would do and why” [19] and “the most common mistake that new case writers make is that they think a case should be a story from the start to finish. In fact, it should be half a story. Students should be left asking, what am I going to do now.” [19] One of the reasons for the success of business cases in the classroom is the similar kinesthetic responses it provokes in students to that of a simulation—it asks them to do something rather than wait for the teacher’s next statement or observation.

The story layer sets out the environment, the constraints, and the general context in which the activities are occurring and then makes the student decide on the subsequent course of action. Most case studies ask for one set of decisions from students, possibly from a range of different variables. Working through a case study in a classroom equates to playing one turn of a simulation. The experience without the burden of software is a test of the story and its viability as a full-blown simulation. A simulation would continue the decision-making across multiple rounds and often pit the consequences of the students’ decisions against one another, presuming that they comprise the entire universe of external factors. In this way, running through a story is the starting point for constructing a game world reality rather than becoming enmeshed in a cycle of algorithm modeling and testing.

Stories can also be generated through other techniques too. In the classroom, a story can take shape through techniques, such as science fiction prototyping [20] or the Lego Serious Play methodology.

Simulations can find inspiration from within any story and become the narrative basis for the subsequent actions. Having a human frame of understanding and incorporating the flourishes of individuality helps to flesh out a game world and make it more real to those who will participate inside it. Being able to introduce local landmarks, local personalities, or names into the story can help to contextualize the learning and make the impact of their own decision-making within the game world seem more real and significant.

4.2 The simulation description layer

The description layer of existing simulations is locked away within proprietary software. This is the primary layer of existing simulations as it shaped the way that decisions made by students will be transformed through algorithmic manipulation based on a specific formula.

The proposed open-source description layer utilizes the advantages of creating an XML document that could be verified against a consistent XML Schema (XSD). The initial structure for an appropriate XSD has been shared on GitHub [21] by the author as a starting point for further development and discussion. The principle in play is one of simplicity, transparency, and a gradual handoff to the more technical elements of a more sophisticated management simulation engine. An XML document describing the simulation is a text-based document and can be edited by any text editor by multiple authors. The XML contain tags, similar to the way that HTML can be read by a browser to render web pages. In this case, the tags are specifically relevant to defining management simulations. A “storyteller” could easily recognize many of the elements of the XML document and assist to document their simulation in more structured way.

The core set of three tags <steps>, <variables>, and < formulas> are the key building blocks for the simulation. These tags contain further tags. Inside <steps> are <step> tags. Each <step> or turn of the game is defined in this way. Within each step, there is a < narrative> tag that explains the story so far and provides students with a contextualized understanding of what is happening within the game. Each <step> can contain multiple < decision /> tags. Each <decision/> is based on some student input, some static values stored by the simulation, some calculated outputs from previous decisions made by the student or other students, and/or some generated value that has been generated by the progress of the game including values taken from one of the simulation’s defined <influence /> variables. For the student, they would see the <narrative> tag’s contents at the start of their turn, and based on the decisions being made in the round the interface would also display the user inputs needed to get the expected student decisions for this turn. The inputs being asked from the student would relate to the variables that the game could not itself complete or calculate. The most likely reason would be the need for an input value required from the student based on the formula being used in each decision and what values were already available. Once the suitable inputs were received the simulation could progress to the next <step> depending on the conditions set by the <dimensions> tag and specifically whether this game was being run in “interactive” mode or not.

The <variables> and < formulas> tags are important to move some of the complexity away from the <step> tag itself. <formulas> contain many <formula> tags and < variables> contain many <variable> tags. Any <formula> will be composed of a combination of <variable>s being brought together to represent specific formulaic transitions that occur at <decision/> within each <step>. The XML Schema does not define where the values are stored or how they might be stored but the implication is that this would be done with some form of persistent storage such as an SQL database available locally or through a cloud-based service. This service would also maintain the logged-in state of the participants (against some form of institutional authentication) and their progress within the simulation itself.

The simulation description layer does exactly what it saysit describes the simulation completely in a single text document. For a simple simulation that runs for a small number of turns, this may be a relatively small document but the structure is flexible and a complex simulation running over many turns may require thousands of lines of description (and represent substantial academic output in its own right).

The description of the simulation sets out the individual steps of the simulation in a structured and consistent manner and in a format that remains largely readable by anyone involved in the design of the simulation. By separating out the <variable>s and < formula>s from each of the potentially many <step>s there is an opportunity to consistently reuse these components throughout the simulation without having to continuously redefine and repeat the same statements many times over.

4.3 The decision-making layer

In combination with variants of the description layer, this layer is found in all existing management simulations. The simulation takes in the decisions from participants through various types of form-like inputs, such as checkboxes and text boxes. The input is then applied to the internal algorithmic model and a response is prepared for displaying before the next round of decision-making. In effect, existing management simulations are this layer alone. In the proposed ecosystem, the decision-making layer does not change in purpose or in the way that it responds. The difference is found in the transparency between the <step>s of the description layer and the actions that are conducted at the decision-making layer. By using a consistent and structured description layer it becomes possible to create a decision-making simulation engine that can read in any similarly consistently formed XML document and then enable the simulation to be played through by an individual, a single group, or as part of global competition.

Decoupling the description of simulation from the engine that can deliver the interaction with a simulation enables a greater level of experimentation, customization, and the refinement of existing simulations (or formula) to reflect changing conditions or to update new academic knowledge in the area.

Using the description layer means that a small “tweak” can be tested in a simulation at steps nine and ten and then the <step>s can be returned to a simple repetition of the original definition used for the first eight <step>s. Defining simulations step by step also consciously encourages creativity by suggesting that influences change and shift over time and do not simply remain static for the convenience of a simulation developer.

Being able to separate the description of the simulation from the decision-making playing of the simulation also creates the prospect that more than one decision-making system might become available, and would be licensed by different institutions but that the descriptions of different simulations could freely be shared between academics and institutions to be used on their own institution’s decision-making systems in the same way that a JPEG can be shared fairly between different image “viewing” and “editing” software. This more open environment may also encourage some authors of papers and case studies to define a simulation based on the insight and learning expressed in their research to come out in a more practical and kinesthetic way. Taking this further it may even be possible for an organization to express their own operations in the same manner and encourage students to “play out” different scenarios to find the best possible solution. Students could even be rewarded to find the most effective solution to a particular challenge or blocker that the organization regularly encounters.

4.4 The visualization layer

Those with experience with existing management simulations may argue that the current crop of software also offers this final layer. However, the separation of the visualization layer is consciously done to reflect on the relatively poor gaming experience found within existing management simulations. It is a convenient that students are asked to fill in a form-like interface to record their decisions. This is a convenience that reflects the golden age of the “Beer Game” and the relative lack of progress in this aspect of management simulation development since then. While other forms of casual gaming have mastered the idea of the procedurally generated game world, this is an innovation yet to reach the world of simulations. The act of entering a two-digit number into a text box on a flat screen is one solution to data input. However, procedurally generated game worlds have also discovered many others. Within VR space dialing a floating knob to the correct position, drawing the number in the air with a finger, tapping an in-game device, or covering the chosen number with a suitable virtual object have all been explored in different environments.

Removing visualization from the decision layer also separated the more complex task of generating procedural worlds so that a student could provide input at the appropriate decision points through the keyboard but then move to a VR visualization of the same simulation and provide decisions through other forms of input. While this option appears challenging, projects that are entirely separate from the concerns of management simulations have been working to make this relatively straightforward. A ten-year-old project called CityGen3D developed a plugin for the Unity game creation engine that used 2D map data, such as OpenStreetMap to create 3D cityscapes [22]. The potential is that a simulation expressed through an XML description could be pulled through the decision-making layer and be represented within a local neighborhood render by extrapolation from OpenStreetMap. Given that the types of decisions that are required and the user inputs are already known through the definition layer, the challenge for the designer tasked with creating the visualization layer is to produce suitable input systems that can be triggered within the procedural game world. It could be that students have to go and record their decisions at any of the procedurally generated corner stores, or they have to locate a shared office space where they can record their decisions into the generated PC. Because ensuring the player’s ability to generate their input is the only requirement for the visualization layer, a designer can then focus on taking more cues from the feedback of the game’s progress to populate the virtual game world with elements that are representative. Perhaps, poor overall progress by all the teams would be reflected by streets more littered, creating higher chances of street violence (making it harder to go and make a decision) or a general decline in the urban environment. Similarly, teams enjoying generally good progress might see improvements in their local environment and even more convenient ways to make their next set of decisions.

As these scenarios indicate, better visualization may also provide players with clearer visual expressions of how good management decisions can have wider social value and benefits (and vice versa) in a way that current management simulations can often struggle to portray. This further expands the value of management simulations—as well as, for example, generally improving the awareness of sustainable development goals—beyond their current capacity.

5. Conclusions

Management simulation is an important aspect of the kinesthetic offering of business education. Management simulations, however, are not currently games in a way that new students would recognize and this mismatch between expectations and reality can be a difficult disappointment to reset once the realization has been made. However, this gap also represents an opportunity (and challenge) for management simulations to become more engaging and relevant for learners. By separating the storytelling, the description, the decision-making, and visualization of the management simulation, it is possible to chart a future for these games that encourages more engagement from faculty to design new opportunities, as well as for students to undertake a wider range of relevant and more contextualized simulations. The major challenge being described here is the urgent need to move management simulations onward from being an outdated genre of packaged software to a transparent and shared practical object of research that can have use impact and application long after the publication of the associated journal paper.