Chapter And Authors Information
This chapter describes the development of the use of visualisation techniques within management planning, reporting and decision-making processes towards the realisation of visual management. By drawing on exemplars and vignettes of visualisations that have been used in business and government as well as in academic literature the discussion charts the increasing capability found in all forms of visualisation techniques and technologies. This is a specific business maturity that enables visualisation to be used with value and purpose outside the largest of multination corporations. Exploring the trajectory of this development there is the implicit recognition that visualisations can now become the primary artefact for planning and decision-making rather than a secondary aesthetically pleasing representation of a concept or of some available evidence. This provocation – that the future is visual management – is carried throughout the chapter. Consideration is given to the extent to which all the necessary tools for the task have only coalesced – at best – in the past decade. The trajectory of this discussion then looks at the rise and advocacy for data-driven, data-informed and evidence-based management. The chapter concludes with a critical discussion on the relationship between strategic management practices and the visual artefacts used to guide them.
visualisation, management, decision-making, strategic thinking
Introducing Visual Managing
As the COVID-19 pandemic took hold in the UK in 2020, the Prime Minister began a series of daily national television briefings. An important prop in many of these presentations were a variety of graphs and charts used to represent the changing severity and response to the situation. The Prime Minister’s implication in many of the statements was that these charts and graphs represented the evidence upon which the UK government was basing its decisions and actions. The rhetorical question, in the context of this chapter, was whether the charts that the public were seeing represented only the tip of an iceberg of evidence that had fully been scrutinized and interpreted by the cabinet or whether the chart itself was the entire basis for the decisions that were being taken.
The popular reporting of the crisis lends substance to the suggestion that the visualisation that were being presented during these public briefings were also evidence for those making the decisions.
At the briefing, the UK government’s chief scientific adviser Sir Patrick Vallance presented a graph outlining a range of projections for the Covid death toll over the next month, including one from Public Health England and Cambridge University suggesting it could rise as high as 4,000 a day.
He also cited two other graphs illustrating “medium-term” projections from the government’s advisory committee SPI-M for hospitalisations and deaths up to 8 December (BBC 2020).
Former President Trump had an even more fraught relationship with visualisation as the tool for justifying planning and decision-making during his term of office. As with Johnson, the use of visualisation during the COVID-19 crisis particularly emphasized the double-edged sword between transparency and authority associated with presenting data through charts and the use of visualisations more generally. The popular responses to Trump’s charts also point to a public who understood that the visualisations were being used as the basis for top-level decision-making and the resulting actions. Charts such as a decision-tree outlining the planned national COVID-19 response (Figure 5.1) were mocked and became the basis for negative memes of the presidency (Sung, 2020). As the pandemic continued and Trump’s overall response as a leader was increasingly scrutinised, his persistent use of charts to justify his personal perspective also came to be more robustly critiqued (Diss, 2020).
Figure 5.1. COVID-19 planning visualization presented by former President Trump (Source: twitter.com/fransquishco/status/1238553012307550208)
As President, Trump effectively had limitless resources to access well designed and presented visualisations that could represent any situation. As a politician who was sensitive to receiving positive public opinion, Trump practically proved in his exchange with a critical Australian journalist that the presenter of any form of data needs to understand the insight that is being represented rather than attempting to bend a visualisation to suit their own current agenda (Diss, 2020). In one exchange, while the President was using a graph for political purpose, the reporter was able to read the graph accurately and cautioned the President that the basis for his claims (of a successful national COVID-19 response) was based on a variable that was not being used globally as an indicative measure. The point of contention was that Trump’s claim for a positive performance was based on “death as a proportion of cases” when the more widely used metric was “death as a proportion of population.” The President’s own underplaying of the severity of COVID-19 and its spread within the USA was itself contributing to an under-reporting of cases. Unfortunately, this is only the first case presented in this chapter of how claims based on a flawed visualisation can have potentially fatal consequences. Despite the specific outcomes in the USA’s response to COVID-19, the example of Trump and the use of graphs should not be read as a negative vignette but rather as the positive advantage of visual management. The fact that Trump’s interview statements could be challenged by a journalism is not a new phenomenon but the ability for this criticism to be based on an immediate response to newly presented data shows the increased transparency, openness and richness that visualisation can bring to key data in ways that invites meaningful discussion – and decisions.
These two high-profile examples of political decision-makers interacting with crucial public health data outlines the scene for understanding the role and value of visual management. The ability to synthesise and aggregate disparate sources of qualitative (Moretti 2007) and quantitative data (Russell-Jones, 1995) in graphical ways that enable rapid, transparent and appropriate planning and decision-making summarises the role of visual management. As the advocacy for data-driven or evidence-based management becomes increasingly prevalent within academic literature (Pfeffer & Sutton, 2006; Rosseau, 2006) the value of visualisation is its capacity to move strategic and visionary management statements into a clear and concise visual context rather than remaining tied to more traditional complex textual and numeric formats.
Visual management is a paradigm for strategic planning and decision-making (Figure 5.2). Planning incorporates the translation of models and concepts drawn from academic literature or experience and customised to reflect the needs of an organisation and its local environment. Decisions are informed by robust and meaningful graphical representations of the underlying data without the need to resort to formulaic or lengthy text-based reporting. Visual management crucially closes the loop by linking reporting and decision-making back to planning actions.
The successful application of visual management techniques is not confined to the last decade nor does the underlying data used in decision-making have to be solely quantitative. General Wade’s control of Jacobite sentiment in Scotland in the 18th Century relied heavily on the use of maps (Anderson, 2010). These maps initially laid out the intent and the focus of attention for military intervention into the Highlands as road-building activities that linked the key centres of army activity that also cut through physical areas of concentrated Jacobite dissent including the already notorious “Rob Roy Country” (Stevenson, 2004). As the intent became more tangible with a works programme throughout the 1700s the maps came to represent actual lines of control with secondary paths and settlement radiating out from these main roads. A side-effect of these actions was to bring about a significant increase in the accessibility of the Highlands exposing it to more casual investigation. Higher levels of mobility brought an increasing number of travellers from England and elsewhere. Boswell and Johnson’s 1773 visit to the Hebrides is only one celebrated example. These visitors brought about a re-invention of the Highlands and highlanders that during the Victorian period served to confirm the totality of Wade’s success. The remains of the roads as well as the maps themselves now remain as continuing historical reminders of English hegemony in Scotland (Anderson, 2010).
Figure 5.2. The relationship between planning and decision-making in visual management
Evidence for the more recent shifts towards visual management in perspective and practice can be identified with the popularity of tools such as Osterwalder and Pigneur’s Business Model Canvas (2013). This is a popular contemporary example of a tool that enables the qualitative mapping of business plans (Figure 5.3). The canvas has come to be used as a top-level visual representation of a business model that can be presented at high level meetings without any underlying documentation. The result is a dynamic representation that can be discussed, edited and agreed upon within the span of a single meeting. The transparency enabled by the Business Model Canvas is also a significant step forward in the development of a knowledge-based view of the organisation (Grant, 2002; Felin & Hesterly, 2007). Emphasising the strategic importance of visual thinking and decision-making within business references earlier work from critical studies such as McLuhan’s observation that the “medium is the message” (McLuhan & Fiore, 1967) and the data analysis perspective of Tufte that reaches its peak with his pointed critique of Powerpoint entitled The Cognitive Style of Powerpoint: Pitching Out Corrupts Within (2006). More recent works such as those of McCandless (2014) are also influential and instructive.
Figure 5.3. Osterwalder and Pigneur Business Model Canvas with additional notes (Source: alexandercowan.com/business-model-canvas-templates/)
With increasing reliance on the use of digital tools and the availability of rich data the use of visual management becomes closely linked with the concept of being an effective, digitally capable and strategic leader. As the vignette of Trump’s use of charts reconfirms, having strong visual data literacy is a significant key skill for a contemporary leader to inform and then justify their planning and decision-making activities. Data that is generated through the use of digital tools also emphasises that digital technologies should always be regarded as enablers. Being ‘digital’, in this sense, becomes a ‘verb’ synonymous with action rather than being used as ‘noun’ implying an endpoint outcome in its own right.
Contextualising Visual Management
The Long Evolution of Visual Management
The origins of visual management are arguably older than literacy and coincide with the beginnings of written numeracy. The proto-Sumerians used tally marks that were pressed onto the outside of sealed clay beads containing the corresponding number of tokens inside. This is a visualisation system from over six thousand years ago. The proto-Sumerians were effectively employing a technique for representing underlying numerical data in a way that could be consistently understood with shared meaning and recognition. As this system for agreed shared meaning expanded it became the basis for one of earliest forms of writing – the Sumerian cuneiform script. Taking the impact of this innovation to its most generous conclusions, it could be argued that the advent of written numeracy was the key technology that provided a form of competitive advantage that eventually coalesced as a result into the Sumerian civilisation. Considered in the context of visual management, the original dual purpose for the proto-Sumerian numeracy system was to document underlying physical data (the tokens embedded in the clay beads) as well as contributing to the planning and distribution of locally available resources (as each bead represented one sheep). This single example drawn from pre-literate ancient history is a telling indication that forms of visual management have been in some way an ever present but generally minor consideration throughout the period of written history.
The medieval development of European heraldry is a further example of early visual management. Distinctive coats of arms were developed to enable rapid identification of individuals on a battlefield reflecting an immediate combination of needs to simultaneously make resource allocation decisions while also reporting the current relative position of army units and leaders. More sophisticated and later use of heraldry came to visually represent the broad family alliances of individuals. This was particularly true of the marshalling – or the merging – of coats of arms together to show the combination of dynasties while cadency marks were used to indicate the sons and daughters of an arms holder. This can still be seen used on the coat of arms of the individual members of the British royal family with the use of a three or five pronged “label” usually indicating their personal distance in generations from the current monarch. The role of heraldry in English society evolved in the somewhat more peaceful times of the 16th and 17th Centuries as herald’s visitations. Heralds set out across the country under instructions from the monarch to record the use of coat of arms by titled and landed families (Ivall, 1988). Ostensibly undertaken to ensure the eligibility of those bearing arms and to avoid the duplication of designs these visitations represent the first (visual) prototypes for future national censuses.
More recent history and the precursors to contemporary visual management are evident in the use of shared visual languages. The work of Bliss (1978) on his proposed Semantography and Neurath’s earlier ISOTYPE (International system of typographic picture education) system (Neurath, 1937; Neurath & Kinross, 2009) offered frameworks for the creation of forms of universal visual languages. Although largely forgotten, Dreyfuss’s (1984) later work also attempted a synthesis of these works that articulated a sensitivity and awareness to the cultural differences in meaning that permeate all visual communication. The influence of these twentieth century authors can then be later identified in the work of Xerox’s Palo Alto Research Centre (PARC) which is credited with the development of the originally graphical user interface (GUI). The GUI now defines and determines nearly all forms of consumer interactions with computing. GUIs are a vital step towards the normalisation of a visual management perspective. The standardised visual language of icons and the various symbols used in all GUIs and associated with each individual window on a screen provides a common language for all users of the same operating system (which are now so tightly linked with GUIs as to be inseparable). Even between competing operating systems there is a visual commonality that connects images to specific actions and lets the “user” of one system have at least partial familiarity with the interface of another. Some of these consistent symbols are derived from the alphabet and conventional typographical symbols – particularly the use of ‘X’ to exit a window and the ellipsis to indicate more information or options. Other GUI symbols are pictographic in nature and at the same time embody tiny aspects drawn from the history of computing. The most evident of these is the persistent use of a 3½” floppy disk to indicate the save function (e.g. <) despite having fallen out of popular physical use by the early 2010s. The influence of Neurath’s earlier ISOTYPE system can also be clearly identified in popular symbol-based fonts such as Microsoft’s Wingdings and Webdings.
The value of a GUI as a prototype for a universal visual language is that any software built on top of this interface already contains familiar and intuitive elements for every new user. This ensures, at least in theory, that learning any new piece of software begins from the point-of-view of at least partial knowledge and familiarity. The pivotal tool for visual management among consumer software is Microsoft Excel. The history surrounding the development of this software (and of spreadsheets more generally) itself embodies a key thread in the recent story of visual management. Excel does not represent an endpoint in the potential and capabilities of visual management tools. However, it is currently a key enabler. The combining of spreadsheet functions with graphing tools is an important first synthesis of development as a “visual calculator”. The instantaneous updating of calculations across the entire spreadsheet when one input is altered is a much taken-for-granted but significant feature of any spreadsheet application. It is not a coincidence that an early competing product and inspiration for Excel was called VisiCalc. However, the third pillar of functionality, in what is described both apocryphally and humorously as “Microsoft’s best-selling database”, means that Excel’s capability to gather, store and interrogate data interactively makes it a suitable tool for strategic management and decision-making as well as for immediate calculation. The inclusion of this third layer functionality also echoes the name of an older competing product with the “3” in Lotus 1-2-3 representing a similar type of databasing capability.
The ubiquity of Excel in the organisational environment does not automatically translate into the ubiquitous presence of good visual management techniques. The current situation is that the consumer software tools that support good visual management can also be the tools for obscuring and misrepresenting underlying data either consciously or unwittingly (Tufte, 2006; Tufte, 2006a). The higher levels of organisational digital maturity required to make visual management effective is also an important factor in the evolution and realisation of effective visual management (Fenton et al, 2020). The implication is that competent visual management is also a “people thing” that is only possible in an organisational environment where there are consistently high levels of digital maturity, a cultural receptivity to innovation, high levels of performance where decision-making is evidence-based and a strategic mindset that can be found throughout and within its people. In more straightforward words, having the right combination of people for the job.
The Academic Input into Plannin
A key aspect in creating the people-focused organisational environment that enables successful visual management is having robust inputs for strategic planning. Increasing emphasis on the importance of generating impact out of academic research has evolved research “participants” into “stakeholders” and “beneficiaries”. Some national systems such as Australia’s Research Engagement and Impact Assessment and the UK’s Research Excellence Framework endeavour to quantify the social, policy and economic impact of research activities. Many, but certainly not all, research outputs whether actively or otherwise increase the reach of its impact by utilising visualisation of concepts, models and frameworks to exemplify and simplify the message of the text – the complex underlying evidential data. The value of models such as the Boston Consulting Group Matrix (effectively a 2×2 grid of two variables with each element of the grid representing the combination of high and low values) for breaking down a large problem into smaller, more solvable problems is found in its simplicity (Figure 5.4). Other applications with the same visual format can be recognised in the forms of the Ansoff matrix, SWOT analysis or the Johari window.
More sophisticated visual tools continue to emerge from the hybrid space of consultancies and “practademics”. The Business Model Canvas (Osterwalder & Pigneur 2013) is a more complex model that still achieves the goal of visualising a business “on a page” (Figure 5.3). The use and application of the Business Model Canvas sits at the strategic apex of organisational research, analysis and decision-making that enables the creation of a full business model but at the same time decisions made at the top level of the canvas can also be propagated downwards into the underlying organisational operations. Crucially by bringing together the details of an individual business into a consistent top-level format the Business Model Canvas of one business can then be compared with that of others in a meaningful way.
Figure 5.4. A prototype for breaking a problem into smaller components
A more persistent visualisation in the field of business planning is Porter’s Five Forces model (1979). It could be argued that the entire essence of the paper is conveyed in its one visual exhibit. More speculatively, the forty-year longevity of the paper in shaping strategic planning could also be attributed to this exhibit. A Google image search for “five forces” reveals that this single visualisation of the concept has been redrawn (and re-interpreted) many thousands of times. This is an additional indication beyond the metrics of citation count (which itself is approaching 7,000 including the one taken from this chapter) for the impact that Porter’s first Harvard Business Review paper continues to have in strategic planning. Porter’s model represents a visualisation of convergence or consolidation that can be recognised in other later models that focus on different aspects of business but with the purpose of bringing related concepts together into a specified whole (Figure 5.5).
Figure 5.5. A prototype for representing the combining of concepts or actions
More broadly in disciplines related to that of strategic management, other visual academic models such as Gibbs’ Reflective Cycle (Gibbs, 1988) represent a continuous cycle of activity without specific beginning or end (Figure 5.6). As with the Boston Consulting Group Matrix, the form of the visualisation has been adapted and applied to a variety of different organisational observations. The original publication that presented the Gibbs Reflective Cycle is now offered freely under a Creative Commons license which enables it to reach a wider audience. The template for Business Model Canvas is offered under the same form of license enabling free and much wider usage (with attribution) than academic models that are locked behind a paywall or embedded within expensive textbooks.
Figure 5.6. A prototype for representing a continuous cycle of action
The speculative hypothesis that can be drawn from what is admittedly a small sample of academic literature is that a concept has a greater chance of creating impact and achieving longevity if it is represented visually in the original paper. Although this hypothesis may be interpreted as a challenge to researchers who do not visually represent their concepts, the corollary to this initial hypothesis is that any academic concept can be represented visually. The academic challenge, then, is to capture the “right” representation for a concept in order for it to be used and to have impact. The purpose and value of critical academic enquiry remains constant but greater attention is needed in the review process to the value and veracity of visual models proposed by authors and the contribution that they make to the evolution and development of visual management techniques (Figure 5.2). Coupled with the need for the right people to develop a visual management perspective is a clear need for the right conceptual tools. A case in point is again Osterwalder and Pigneur’s (2013) Business Model Canvas (Figure 5.3). This specific representation is often regarded as the only version of the Business Model Canvas. However, this assumption is not borne out with the evidence of alternative (Maruya, 2012; Griffiths & Fletcher, 2020) and older versions (Stähler, 2001) placing different emphasis on various aspects of the business within the model itself. As a consequence, Osterwalder and Pigneur (2013) ignore, in their version of the business model canvas, the values and skills that are held by the people within the organisation and assume an already pre-defined organisational vision. The other forms of the Business Model Canvas, in contrast, ask for a clear articulation of these aspects of the organisation within the business model. There is not a single “right” visual representation for a business model – or any strategic concept. Longevity and popular usage will be the primary determinant for which of these versions will eventually have the most impact with the current indications pointing to the consciously more generic model of Osterwalder and Pigneur assuming this mantle in the context of the Business Model Canvas.
The Right Tools and People for the Right Job
As with other management techniques, visual management does not make specific prescriptions about how a business should be strategically or operationally managed. Instead, it collects together and labels the tools and mechanisms that offers a systematic technique for management. Poor management inevitably resolves to the capabilities and behaviours of people rather than being found within the tools that they have available to them. This recognition is regularly obscured in the digitally mature, or even just digitally enabled, organisation when data is pivotal to achieving organisational requirements and goals. As an enabling technology, digitally delivered tools, including the data they store, can create efficiencies and automate human action. However, all technology is itself a product of human action. In this way business technologies can be seen as a stored and deferred proxy for the original intent of people (the original stakeholders) and their underlying thinking that shaped its design. This artefact-based perspective on the digitally mature organisation presents an understanding that complements the knowledge-based view for creating strategic advantage (Grant, 2002; Felin & Hesterly, 2007).
The hand of the people behind the creation and use of technology further extends the argument for the need to undertake consciously critical reviews of the visual models offered by academics. Software – and all forms of technology – are never socially or economically neutral (Fletcher, 2020). The example of developers influencing the software that they create is an indicative example of this broader observation. Developers continuously make choices and decisions that shape the functionality as well as the “look and feel” of software. A common error made by developers concerns the assumptions made regarding the high levels of veracity of the data that will be brought into the software they are creating even when this data is highly subjective and based on human judegment – the results reconfirm the significance of the long-standing “garbage in, garbage out” (GIGO) adage. Increasingly complex software systems such as Enterprise Resource Planning (ERP) and Customer Relationship Management (CRM) are particularly sensitive to the GIGO effect as they rely heavily on input from external sources and systems in order to bring together data and create business intelligence that can then be (visually) reported out to managers and decision-makers. More recent criticism of the subjective influence and social bias in artificial intelligence (AI) models only further reconfirms the need for sensitivity regarding the veracity of data (Silberg and Manyika, 2019).
The decision-tree that came to shape any piece of software is ultimately unobtainable. Consider the complex and long history of Excel as an example of the futility in trying to specifically unpick the influences, biases and assumptions that are now integrally built into this software package. But critical awareness of the fact that these biases are ever present in the software and, in turn, trickle into the visual artefacts created by the software is a pivotal realisation for the digitally mature organisation. Tufte’s (2006) revelation of how poorly designed PowerPoint slides using its default formatting obscured and downplayed the safety risks associated with the Space Shuttle’s O-rings at low temperatures is indicative. His critical examination of the NASA slides with the scientist’s placement of the crucial statement in a third-tier bullet point reveals the sometimes-fatal apogee of deferred human action that is built into software.
What these observations emphasise is the need for simplicity – or more precisely to create organisational simplicity out of overwhelming environmental complexity as well as the associated qualities of volatility, ambiguity and uncertainty (Grabmeier, 2020). Visual academic models should clarify the situation by offering a systematised representation of reality or the actions needed to address that reality. These models should assist planning by enabling wider discussion within the organisation rather than being used as an instrument to stifle engagement (by presenting a pre-determined decision). Similarly, the reporting of organisational data should provide clarity for managers at all levels with the opportunity to interrogate more deeply but without necessarily having to do so. This is the basis for the criticism of many corporate dashboards developed without a critical viewpoint on their purpose or intended benefits. Dashboards primarily intended to produce slides for a corporate presentation preclude interactive and deeper (visual) interrogation of underlying data or re-presentation in a different form (which may improve understanding for different meeting participants and others in the organisation). The capacity for any visualisation tool to offer immediate recalculation and re-representation is an expectation that has already been set with the ubiquity of Excel – but can often be absent in other newer tools.
The current state of corporate dashboards emphasises the need to ensure that a link exists between the reporting back of data and the strategic planning process. In effect, the reporting of available data through a dashboard is only useful if it provides the insight that enables answers to the questions that have been raised through the planning processes. This is the feedback loop identified in the original model presented in this paper (Figure 5.2) and is one of the greatest challenges within any management technique. In the context of visual management, the challenge is made more complex in the attempt to reconcile this necessary linkage through visual artefacts. The visualisation of conceptual models found in academic work and elsewhere diverge significantly in style and form from the older and well-established representations of quantitative data. The baseline benchmarks for the reporting aspect of visual management are again set with Excel’s graphing tools. The breakthrough for visual management will occur when Excel (as well as other tools) enable a one-click creation of a planning visualisations that are informed with contextual, and potentially qualitative, data with the same ease that the reporting back of completed business actions can currently be done. The current availability of add-in tools such as Node-XL (smrfoundation.org/nodexl/) is an example of how Excel can handle more qualitative data. The more simplistic Business Model Canvas Excel template (demandmetric.com/content/business-model-canvas-template-excel) is an add-in with a more specific purpose. Both examples indicate how close the main technology of Excel is to closing the key linkage between reporting and planning (Figure 5.2). Excel will be at the very vanguard of visual management software when Microsoft links these existing capabilities with those of its often maligned Visio tool. The introduction of the technical capability in a software will not in itself bring about a revolutionary shift towards visual management. However, the presence of these type of tools within such a core business software will inevitably encourage people to learn these tools and to develop the skills needed to be able to engage with visual management.
Planning, Evidence and Decision-Making: the Critical Feedback Loop
Giving the rights tools to people as well as linking reporting with planning brings us back full circle to the purpose of visual management. If a management technique is to have value it must improve organisational decision-making processes. There are decision-making points occurring throughout the visual management model (Figure 5.2) echoing the representation of the continuous reflective cycle of Gibbs (Figure 5.6). If people are to have a long-term role in increasingly automated and digital organisation it is as strategic decision-makers. Physical automation, software based robotic process automation (RPA) and process mining ultimately place the majority of day-to-day operational decisions in the hands of algorithms trained on the systematic recording of actions repeated hundreds and thousands of times. These iterations represent an acceleration of the learning process that happens with an experienced (human) operations manager over many working years. The acquisition of experience is what gives the manager as well as the RPA the ability to respond appropriately when the “one in hundred”, “one in a thousand” or “one in a million” exceptional event occurs.
The challenge as the strategic manager is to act on the business intelligence returned by the day-to-day operation. But a key challenge to this perspective is the decision to be data-driven (Mandinach et al, 2006), data-informed (Wang, 2020) or evidence-based (Baba & Hakem-Zadeh, 2012). Visual management is capable of supporting any of these paradigms in the relationship of data to management decision-making. The data-driven approach implies an automated decision that is entirely shaped by the available evidence of the data. This is often the aspirational goal for many organisations in their own digital transformation project and in the approach to strategic management-decision making more generally. A fully articulated data-driven digital organisation could also imply an organisation without people – an ultimately challenging and potentially nonsensical concept.
Reconciling being data-driven with the necessary feedback loop linking the qualitative concepts of management planning and practice pushes towards a “softer” but more critical data-informed approach. Visual management provides a mechanism to translate plans into business logic and report back the results for subsequent decisions. By being visual the necessary decisions can be made collectively and rapidly with confidence that the visualisation is representative of the current situation. The more critical data-informed perspective more consciously recognises the bias of developers, system architecture and data gathering methods that impacts on the data in its transformation to becoming represented as insight.
The strategic (human) manager whose actions are measured in cycles of years have fewer opportunities than the operational level manager to learn the patterns delivered from multiple iterations of experience. Each cycle of activity has the potential to become a unique “one in a thousand” event – a realisation that prompts a severe challenge to applying RPA techniques for strategic management. A strategic data-informed approach benefits from a visual approach that encourages transparency in order to produce decisions that are based on, and utilise, the combined years of experience drawn from multiple people within organisation.
The Future is Visual Management
Despite the persistent of incomprehensible business intelligence graphics (Szafir, 2018) the value, benefit and opportunity to adopt visual management outweighs these rare disappointments. A ready reckoner for the changing mood can be interpreted from blogs that focus on business graphics. When examples of good visualisations predominate over the critiques of poor visualisations presented in these blogs a key shift in the maturing of visual management as a viable management technique will be marked.
The many multiple visualisations used by Trump and Johnson throughout the COVID-19 pandemic ranged from the overly simplistic to the exceedingly complex. The shifting decisions and policies of these two leaders and their governments were being immediately mirrored by the changing graphics. In contrast, the successful control of the pandemic in New Zealand was based on a consistent policy position from the beginning. Strict controls were implemented very early in the global spread of the virus in order to “flatten the curve” enabling New Zealand to completely eliminate the domestic presence of the virus. New Zealand’s Prime Minister Jacinda Ardern made use of a single graphic on the 14th March 2020 that was not produced by a government department (Keogh, 2020). Instead, Ardern opted to use a cartoon style image labelled “Flatten the Curve” that had been adapted from an earlier image created by an American health analyst Drew A. Harris (Figure 5.7). The image visually explained what was meant by the concept and the reasons why the action was required – to protect the health system by not overloading its capacity.
The disconnection of the New Zealand Prime Minister’s choice of image from official data representations arguably gave more power to her message. The message conveyed a sense unity coupled with the prevailing scientific opinion at the time. The message was also honest and ethical. It did not endeavour to overload a nervous public with details of the science or cast the Prime Minister as an ubermensch scientist. It was a suitable top-level representation of the actions required from the public that encapsulated the outcome of planning and decision-making rather than being embedded as part of the cycle (Figure 5.2). The image was a clear message that was easy to interpret. The political fine line between authority and transparency appeared more robust with a single graphic and a strict lockdown message. A further boost to the impact of New Zealand’s response was the government’s own continuous and transparent reporting of the situation (health.govt.nz/our-work/diseases-and-conditions/covid-19-novel-coronavirus/covid-19-data-and-statistics/covid-19-current-cases) that has been consistently detailed not as a result of morbid media obsession with a rising death toll but out of a positive community response to protecting the nation’s status as being (largely) free of the COVID-19 viru s.
Figure 5.7. Flatten the curve – describing the COVID-19 response
Visual management is a technique that business leaders, politicians and academics are still to fully learn, explore and understand. The purpose of any strategic management technique is to create an holistic perspective. For visual management the primary challenge is to reconcile the qualitative models of academics and practademics with the quantitative reporting drawn out of organisational data. In its initial iteration the loop back from the reported data into the academic models is a significant challenge. How can quantitative reporting data be seamlessly looped back into a qualitative planning model? The reality is that models do have opportunities to accept quantitative data. The Business Model Canvas (Figure 5.3) can accept values into the majority of its elements although in the first iteration most canvases contain more bullet point narratives. But the process of critically reconciling the two key aspects of the visual management model (Figure 5.2) is also the core of its power.
Figure 5.8. The Data, Information, Knowledge, Wisdom (DIKW) pyramid (Source: Zer-Aviv, 2014)
Understanding and recognising the strategic relationship between planning and reporting is to understand an organisation at all of its operational and strategic levels. With this detailed and integrated level of understanding the opportunity to also recognise the vision of an organisational becomes possible. Ultimately visual management represents the challenge of transforming the volumes of every present data through the creation of information and knowledge into the rarer commodity of wisdom (Figure 5.8) in a way that is continuous and can build productively on previous learning (Figure 5.6). While AI may currently promise some sort of facsimile of this process it remains a transition that is best undertaken by people.
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