Corporate leaders focus primarily on growing their businesses. They should also focus on mitigating potential setbacks (crises). Innovation (in its many forms) is a guided exploration of purposeful uncertainty. A company knows they want to grow but are generally unsure how. Customer-centric approaches such as participatory innovation are a recent focus for leaders looking to negotiate this tension. In contrast, crises are problems. They are part of an intricate system of related problems, and all crises are human-caused (Mitroff & Alpaslan, 2011). When leaders are unprepared, crises quickly spin out of control. This essay explores contextual factors and various perspectives related to the management of the tension between innovation and stability. It seeks to provide support for further doctoral research into the topic area.
We have a “violent Fondness for change,and greater Eagerness after Novelties”,
–Mandeville, 1732, p. 196
The idea of managing the interrelationship between flexibility and control in the workplace is not new. Virtually all organizations feel pressure to grow and yet the turnover of companies has gone from 1.5 percent a year in the 1930s and 40s to 4 percent in the 1970s. By 1998, the annual attrition rate had risen to 10 percent (Forster, 2010). The fast attrition rate (through acquisitions, mergers, or basic declines) during the past fifty years has attracted increasing attention in the media, popular press, and scholarly literature. One way companies attempt to manage their growth is through innovation. In May 2012, Leslie Kwoh wrote in The Journal: “A search of annual and quarterly reports filed with the Securities and Exchange Commission shows companies mentioned some form of the word ‘innovation’ 33,528 times last year, which was a 64% increase from five years before that. More than 250 books with “innovation” in the title have been published in the last three months, most of them dealing with business, according to a search of Amazon.com” (Kwoh, 2012). According to Google Book Search, use of the term “innovation” has increased 28% from 1993. The surge in interest in the topic has also been reflected on the internet, where a related search garners a plethora of websites, blogs, and journal articles.
Clearly, the issue of managing growth while protecting current assets is of growing, if not paramount, interest to leaders and employees alike. Virtually every business magazine (Inc, Entrepreneur, Forbes, Wired—to name a few) has its own top 10 or top 100 list of innovative companies. There are innovation summits and conferences. Companies are touting chief innovation officers, innovation teams, innovation strategies and even innovation days. Much is known with respect to how to make companies more innovative. Crisis does not receive the same level of expression in the media (such as top 10 lists or conferences), most likely because the topic is less popular to talk about or align a brand with. However, organizations starting to take notice of issues such as global warming, resource scarcity, and economic interdependency. Michael Klare (2012) discusses in The Race For What Is Left that in many cases, the commodities procured during this new round of extraction will represent the final supplies of their type; the race we are on today is the last of its kind that we are likely to undertake. Mentions of the word crisis in the Google Book Search decreased 3% from 1993 but is at an all-time high with an increase of 74% from 1950.
Despite all this interest, however, there is still much unknown about the difficulties of making the shifts in thinking and behavior that innovation requires. Most of the research to date has centered on technical solutions and organizational structure. This is understandable given the speed of change and pressure to grow, and the number of crises that organizations manage (Christensen, 2011; Mitroff & Silvers, 2010; Tushman, Smith, & Binns, 2011).Largely missing in the research, however, is an understanding of the impact of leadership bias and organizational anxiety. It is this dimension of the tension that leaders must manage.
The purpose of this essay is to explore the contextual factors and various perspectives related to the management of tension between innovation, stability, and crisis management in organizations to provide support for further doctoral research into the topic area. The structure of the essay is in three main parts:
An exploration of the antecedents of organizational culture: climate, culture, organizational lifecycle; ambidexterity
An exploration of leadership within the specific context of the management of organizational tension: understanding problems and errors; bias, anxiety, and ways of approaching problems.
Implications and future research directions. Based on the available literature, and the large unknowns about this subject, what are the future research opportunities for studying the role of management of tension in organizations?
Antecedents of Culture in Organizations
A number of studies have investigated the potential antecedents of organizational culture. Some have focused on the impact of the leaders, while others have examined the contextual factors that may contribute to organizational culture. The following segment this essay explores both the individual characteristics and organizational factors that contribute to how tension is managed.
Some researchers believe that the path to growth and the ability to ward off crisis effectively lies in technology solutions and organizational structure (Christensen, 1996). From other perspectives, however, leaders deal with significant challenges to managing welcome and unwelcome change: the pace of technological advances; stakeholder readiness to blame management for failures; leaders’ feeling that they must create growth at any cost; irrational goals for the company’s longevity; and, general fear and complacency (Sull, 2003; Ormerod, 2005; Tellis, 2006; Forster, 2010; Christensen, 2011).
Summarizing information from existing research studies imply that organizations are best positioned for success if they are: open to new information/experimentation; relatively flat; have good internal-external information flow; are aware of conflicts; have competences emphasizing ambidexterity; and, are customer-centric (Hauschildt, 1993; Tushman & O’Reilly, 2002; Leonard-Barton, D., 2007; Patniak, 2009).
Culture and Climate
Organizational culture and climate are concepts that focus on how organizational participants observe, experience, and make sense of their work environments (Schneider, Ehrhart, & Macy, 2011). They are fundamental building blocks for describing and analyzing organizational phenomena (Schein, 1984). Culture and climate have been approached from different scholarly traditions and have their roots in different disciplines. However, both are about understanding psychological phenomena in organizations. Both concepts rest upon the assumption of shared meanings—a shared understanding of some aspect of an organization.
Historically, the construct of climate preceded the construct of culture. The social context of the work environment, termed “atmosphere,” was discussed as early as 1910 (Scott, 1911). The term climate was formally introduced in the1960’s. It was primarily based on the theoretical concepts proposed by social scientist Kurt Lewin. As student of group dynamics, Lewin (1943) coined the term “force field”, which is analysis that provides a framework for looking at the factors (forces) that influence a situation—specifically, forces that are either driving movement toward a goal (helping forces) or blocking movement toward a goal (hindering forces). This was followed by empirical research (Lewin, Lippitt, & White, 1939) which included unconscious motivations in individual and group behavior (Scheidlinger, 1994). The important idea to understand is that climate is about experiential descriptions or perceptions of what happens. Culture helps define why these things happen (Schein, 1984; Schneider et al., 2011). However, not all of the literature makes a distinction between climate and culture and often refers to them synonymously. Additionally, culture is the most frequent term used in the business literature to describe both the what and why of organizational behavior. This essay adopts the same protocol.
Organizational culture is learned, passed on, and can be changed (Schein, 1984). It is more than a shared set of meanings. Schein (1984) defines culture as “the pattern of basic assumptions that a given group has invented, discovered, or developed in learning to cope with its problems of external adaptation and internal integration, and, therefore, to be taught to new members as the correct way to perceive, think, and feel in relation to those problems” (Schein, 1984, p. 3). Leonard-Barton (1998), who studied how managerial systems support and reinforce the growth of knowledge through carefully designed education initiatives and incentives, suggests that organizational values serve to screen and encourage or discourage the accumulation of different kinds of knowledge.
Thinking about the topic of culture has evolved from considering skills to be core if they differentiate a company and can be operationalized, to considering skills core if they can differentiate a company strategically (Leonard-Barton, 1998; 2007). When skills such as experimentation, the ability to work with autonomy, and integration of deep learning are not encouraged in an organization, the core strategic skill of asking the right questions also declines. Leadership is an important direct or indirect factor believed to influence organizational culture (Kozlowski & Doherty, 1989; Zohar & Tenne-Gazit, 2008) due to the fact that managers and leaders are largely responsible for communicating meaning (Schein, 1984). Even their personalities have been related to individual workers’ perceptions of justice in the culture (Mayer, Nishii, Schneider, & Goldstein, 2007).
An organization’s culture goes deeper than the words used in its mission statement. Hofstede (2001) would say organizational culture is a commonly held framework in the minds of its members. This framework screens, encourages, or discourages the accumulation of specific kinds of knowledge or behaviors (Leonard-Barton, 1998). Organizational culture is developed over time as people in the organization learn to deal successfully with problems of external adaptation and internal integration (Schein, 1999). It becomes the common language that employees speak and the common background they share among each other as they negotiate opportunities for and threats to the organization.
Though many try, leaders do not build products or declare a culture. Leaders build companies (systems) that build products. The most powerful thing a leader can do is change the system, not tinker with product features—that is where leaders can have the highest leverage. Culture is created through a leader’s behaviors which define what is permissible toward the implicit or explicit goals/values of the organization (such as profit, integrity with customers, or increased market share). Melvin Conway, a computer programmer introduced this idea in 1968. His formulation of it was dubbed Conway’s Law by participants at the 1968 National Symposium on Modular Programming. It states that organizations which design systems “… are constrained to produce designs which are copies of the communication structures of these organizations (Conway, 1968)”. For example, leaders cannot foster a culture of experimentation if they punish failure.
Cultures have many levels and facets. At the deepest levels are values that express enduring preferences. For example, customer-centered organizations are held together by a central value that every decision begins with the customer and with anticipated opportunities for advantage for the organization. A more accessible level of a culture is its norms, which are shared beliefs about appropriate or expected behavior. A common norm within customer-centered organizations is that employees are customer advocates. Another distinguishing norm shapes the individual employee’s willingness to share information with his or her counterparts: When this norm encourages sharing, the entire firm is in a better position to meet customer needs. Conversely, a destructive norm found in many firms is that sales ’owns the customer,’ which greatly impedes information sharing. Norms and values are a way to ensure alignment and consistency across the organization. Once established, they can contribute to a construct of the organization which can make the organization seek stability over evolution and become resistant to change (Leonard-Barton, 1998).
Cultural change follows from behavioral change. Although culture is generally the most significant impediment to change, there is no evidence that efforts directly aimed at changing a culture are likely to succeed. Cultural change is achieved by altering behavior patterns and helping employees understand how the new behaviors benefit them and improve performance. Senior management commitment, persistence, and intense communication eventually overcome inevitable resistance. The odds of success are much improved if there is a sense of urgency and a compelling strategic rationale (Sarros, Cooper, & Santora, 2008).
Strategies and Lifecycles
Organizations utilize three primary types of strategies in order to innovate or develop a lead in the market: as pioneers, imitators, or late entrants (Kalyanaram & Gurumurthy, 1998; Trott & Hartmann, 2009; Tybout & Calder, 2010). Pioneers specialize in performing the discovery research function that previously took place primarily within R&D functions of larger organizations. They innovate for the sake of innovation. Research suggests that the ability of a firm to commercialize disruptive technology ahead of competitors is a rare and valuable marketing capability and qualitatively different from those skills required for later entrants (Bowman & Gatigon, 1996; Kalyanaram, Robinson, & Urban, 1995). Interestingly, a number of explorers evolved as spinoffs of laboratories that used to be part of a larger organization (Chesbrough, 2003b). The breakup of the Bell System from AT&T Corporation provides a good example. AT&T needed to give up control of Bell Operating Companies, which provided local telephone service in the United States. This effectively took the monopoly that was the Bell System, and split it into entirely separate companies which would continue to provide telephone service.
As in nature, imitation is about scale and energy (cost) minimization. Also called “early or fast followers,” imitators base their strategy on being low-cost producers, and success is dependent on achieving economies of scale in manufacturing (Trott & Hartmann, 2009; Tybout & Calder, 2010). Such a company requires exceptional skills and capabilities in production and process engineering. This strategy is defensive. It involves following another company, except that the imitator’s technology base is not usually as well developed as the pioneer or the late entrant. Imitators often license technology from other companies. Early years of Microsoft illustrate this best, where in order to compete effectively in the productivity space, they acquired much of their technology (Word Perfect, Lotus, etc.) externally, later reverse engineering Microsoft Office to be an integrated suite of products, which took several years. Similarly, much of the technology that went into Windows 95 actually came directly from Xerox. From this position, it is then possible for imitators to incorporate design improvements to existing products (Hobday et al., 2004). Imitators require enough of a technology base to develop improved versions so that they may develop improved versions of the original product: improved, that is, in terms of lower cost, different design, additional features, etc. (Trott & Hartmann, 2009). An imitator needs to be agile in manufacturing, design and development, and marketing. Microsoft copied or acquired much of its initial technology offerings, perfecting the manufacturing path. This enabled it to respond quickly when a new pioneering company created a new market. Without much in-house R&D in the early days, the Microsoft’s response would have been much slower in getting Office or Windows to market, as this would have involved substantially more learning and understanding of the technology.
Late entrants come to the market once a product is established and the market is mature. Their costs for entry are typically the lowest as they enjoy the benefits of not needing to educate customers and have lower research costs. They can also learn quickly from a changing market since they lack the history of pioneering organizations. An example of this was Sony’s 1975 Betamax video standard, followed a year later by JVC’s VHS. The two standards battled for dominance, with VHS eventually emerging as the winner. One major reason cited was because the VHS recording length was 2 hours longer than Betamax. JVC not only listened to customers and responded to their frustration at Betamax’s inability to record movies, but they formed the right alliance with strategic partners, putting Sony at a disadvantage (Tan, 2008).
In order for leaders to gauge whether a problem is occurring at a normal time for their development stage, they must understand the corporate life cycle. Organizational life cycles are defined by the management of a particular kind of polarity: the interrelationship of flexibility and control (Adizes, 1988; Johnson, 1996). Much like human maturity, organizational life cycles are not defined by their chronological age, sales or assets, or number of employees. They are defined by the leader’s (and subsequently the organization’s) ability to distinguish between technical and adaptive challenges (Heifetz, 1994). Most of the challenges leaders face today are adaptive. These challenges require leaders to adapt their level or stage of mental complexity rather than simply apply technical solutions. The misapplication of technical solutions to adaptive problems (a type 3 error) is seen as a major source of dysfunction.
Chris Argyris (1999) has long proposed a model of leadership wherein the leader is implicitly being asked to have a self-transforming (or fifth order) mind. It is that mind that can understand the challenges at each stage of the development lifecycle, reduce the amount of death experienced, and attain the Prime (renewal) stage most frequently. Organizations age much as people do (Heifetz, 1994; Argyis, 1999; Keagan & Lahey, 2009), they manage tensions throughout each stage of development (Adizes, 1988; Johnson, 1996; Tushman, Smith, & Binns, 2011), and they scale like all other life forms (West, 2011). Corporate lifecycles have the following phases:
Courtship. Founders focus on ideas and future possibilities, plans are ambitious. Organization is small, power rests with founder, and the structure is simple. Information is simple to process. Courtship ends and infancy begins when the founders assume risk.
Infancy. Founders’ attention shifts from ideas and possibilities to results. Power is spread among investors and owners, specialization starts, information processing increases in complexity (Lester et al, 2003). The need to make sales drives this action-oriented, opportunity-driven stage. There is not much emphasis on efficiency, paperwork, controls, systems, procedures, delegation, or work-life balance.
Go-Go. The founders believe in their infallibility (Linnell, 2005), sales are the main goal and emphasis is on rapid growth. Due to arrogance and hubris problem identification can be challenging (Mitroff & Silvers, 2010). Founders see everything as an opportunity; their arrogance leaves their businesses vulnerable to obvious mistakes. They organize their companies around people rather than functions; capable employees can—and do—wear many hats, but the founders continue to make every decision—which increases cultural anxiety (Adizes, 1988).
Adolescence. Founders hire chief operating officers and organization starts to formalize but delegation is still an issue. An attitude of us (the old-timers) versus them (the COO and his or her supporters) hampers operations. There are so many internal conflicts, people have little time left to serve customers. Companies suffer a temporary loss of vision.
Prime. Leaders achieve balance between control and flexibility; tap into the right flow of internal-external and top-down flow of information (Adizes, 1988; He & Wong, 2004). Leaders are “managing the middle” of the polarity (Johnson, 1996). They are disciplined yet innovative, prepared yet not bureaucratic. Consistently meet their customers’ needs. New businesses sprout up within the organization, and they are decentralized to provide new life-cycle opportunities.
Stability. Companies are still strong, but without the eagerness of their earlier stages. They are larger than most of their competition, power is distributed among numerous stakeholders, structure is functioning and becoming more formal, and information processing is more sophisticated (Lester et al, 2003). Leaders welcome new ideas but with less excitement than they did during the growing stages. The financial people begin to impose controls for short-term results in ways that curtail long-term innovation. The emphasis on marketing and research and development declines
Aristocracy. Not making waves becomes a way of life. Outward signs of respectability–dress, office decor, and titles–take on enormous importance. Companies acquire businesses rather than incubate start-ups. These organizations are generally more widely dispersed, structure is divisional or matrixed, information processing is complex, and decisions emphasize the need for continued growth (Lester et al, 2003). The culture emphasizes how things are done over what’s being done and why people are doing it. Company leaders rely on the past to carry them into the future.
Blame. In this stage of decay, companies conduct witch-hunts to find out who did wrong rather than try to discover what went wrong and how to fix it. Cost reductions take precedence over efforts that could increase revenues. Backstabbing and corporate infighting rule. Executives fight to protect their turf, isolating themselves from their fellow executives. Petty jealousies reign supreme.
Bureaucracy. If companies do not die in the previous stage—maybe they are in a regulated environment where the critical factor for success is not how they satisfy customers but whether they are politically an asset or a liability—they become bureaucratic. Procedure manuals thicken, paper work abounds, and rules and policies choke innovation and creativity. Even customers—forsaken and forgotten—find they need to devise elaborate strategies to get anybody’s attention.
Death. This may come gradually or suddenly, with one massive blow. The organization has a centralized structure with few controls, information processing is not as sophisticated or current as it once was, decision making is centralized and generally top-down, and decisions are conservative (Lester et al, 2003). Organizations crumble when they cannot generate the cash they need; the outflow finally exhausts any inflow; customers and employees leave.
Effective responsiveness to internal or external disruption plays a key role in whether the organization can develop winning strategies for its survival. From this perspective, leaders (and employees) often tend to come up against, wrestle with, or try to harness invisible forces in the organization’s culture when attempting change. Innovation is viewed by most organizations as hard work. Why? When it fails to work, four primary challenges to innovation come up in the literature: 1) management is to blame (Agarwal & Echambadi, 2004; Leonard-Barton, 2007; Rosenbloom, 2000; Tripsas & Gavetti, 2000; Jassawalla & Sashittal, 2002; Prather & Turrell, 2002; Sanz-Valle, Jiménez-Jiménez, & Naranjo-Valencia, 2011); 2) all stakeholders have unreasonable expectations around growth (Allen and Zook, 2001; Foster and Kaplan, 2011; Collins, 2001; Olson, 2008); 3) there are irrational goals for the longevity of the company (Wiggins and Ruefli, 2002; 2005; Ormerod, 2005; Forster, 2010) and, 4) ineffective management leaders must contend with complacency and fear for themselves and the organization (Porter, 1998; Mitroff & Anagnos, 2001).
Organizational ambidexterity (or agility as it is referred to in organizations) is the ability to create processes for both small and large change simultaneously. Current studies on innovation management suggest that it is crucial to an organization’s survival. Successful firms are effective at using existing skills to create gradual improvements (exploitative innovations) while at the same time successfully exploring new skills and technologies to create breakthrough (explorative) innovations (Levanthal & March, 1993; Floyd & Lane, 2000; Volberda & Lewin, 2003; Gibson & Birkinshaw, 2004; He & Wong, 2004). To achieve this, an organization must reconcile internal tensions between the two innovation pathways as well as tensions caused by contradictory demands for fast growth placed on the organization by its external environment (Jansen et al., 2006). Openness to information and ideas reduces the need for formal controls and decreases the usefulness of bureaucracy. According to Burgelman (1991) and other researchers (Tushman & O’Reilly, 1996; Volberda, 1996; Eisenhardt & Martin, 2000; Benner & Tushman, 2003), an organization needs to learn how to achieve a balance between exploitative and explorative innovation activities if it is to achieve sustainably superior performance. An organization that fails to achieve this balance risks falling into a downward spiral of mediocrity (March, 1991).
Most companies are constrained by the pressures of the here and now and as a result have a short-term focus. They typically think quarter to quarter, driven by shareholders’ (and markets’) irrational and constant demands for growth. Some companies are highly reactive to this dynamic, while others take a more measured, proactive approach. To stay on top of ever changing demands, an increasing number of corporations are starting to engage with users in open-innovation (Burr & Matthews, 2008; Kruse, 2012; Wagner, 2013) as a strategy to manage internal / external information flow, bringing more of the outside-in.
Three studies illustrate good examples of the need for balance in order to innovate. Their suggestion is that leaders need to develop internally consistent structures and an internal operating culture that provides for excelling today while also planning for the future. While most Fortune 500 companies claim these dual processes today, very few have reset their markets with new truly new paradigms. These organizations manage inertia through iteration, and business continuity practices, resulting from the very capabilities that made them successful. Given the contrasting forces for change and stability, leaders need to create environments that celebrate efficiency as well as experimentation and discontinuous change simultaneously.
In the first study, O’Reilly III & Tushman (2002) use case study research to propose that in order to avoid long-term failure while focusing on short-term success leaders must manage an “ambidextrous organization (p. 15)” (as discussed above). The concept of ambidextrous organizations is not new (it was first suggested by R. B. Duncan in 1976), but O’Reilly III & Tushman add “innovation streams” to the discussion, which are the “patterns by which organizations develop new and better products and services (2002, p. 14)”. Success with innovation hinges on the understanding of the dynamics of technology cycles and management of these “streams” and being able to proactively shape these streams through irregular organizational change. Innovation streams and technology cycles require that managers periodically cannibalize what they are doing today in order to ensure leadership of other innovation streams in the future—to destroy their business while it is still working. The danger is that, out of fear of not making next quarter’s numbers, they regress back to the core capabilities that made them successful (O’Reilly III & Tushman, 2002; Leonard-Barton, 2007).
Tushman et al. (2011) did a later study researching 12 top management teams at major companies and suggest that firms thrive only when senior teams lead ambidextrously—when they foster a state of constant creative conflict between the old and the new. Tushman (2011) highlights three core tenants for success for CEOs: the development of a broad, forward-looking strategic aspiration that sets ambitious targets both for innovation and core business growth; the ability to hold the tension between innovation unit demands and core business demands at the very top of the organization; and, the ability to embrace inconsistency, allowing themselves the latitude to pursue multiple and often conflicting agendas. Chandrasekaran, Linderman, & Schroeder (2012) suggest that a competency in ambidexterity involves three capabilities at different organizational levels: decision risk (strategic level), structural differentiation (project level), and contextual alignment (meso level). They examined the relationship between qualifications and ambidexterity competency by collecting multi-level data from 34 high tech business units and 110 exploration and exploitation R&D projects. Their results indicate that decision risk and contextual alignment affect ambidexterity competency for high tech organizations. Structural differentiation does not affect ambidexterity competency but has mixed effects on R&D project performance.
In the third study, Sarros, Cooper, & Santora (2008) surveyed 1,158 managers and found evidence that transformational leadership is associated with organizational culture, primarily through the processes of articulating a vision, and to a lesser extent through the setting of high performance expectations and providing individual support to workers. Combined with the capacity to consider others’ feelings and recognize others’ personal needs, both indicators of providing individual support, leadership vision and setting high performance expectations are significant forces to be reckoned with (Sarros, Cooper, & Santora, 2008, p. 154).
Eight themes come to the forefront of the literature that characterize an innovative organization (Hauschildt, 1993; Tushman & O’Reilly, 2002; Leonard-Barton, D., 2007); they are: openness; flat organization; information management; awareness of conflicts; recruiting requirements; competences and responsibilities (in particular ambidexterity); and, customer-centricity. These characteristics are able to optimize organizational innovation processes leading to innovation success.
The openness of an organization is its ability to absorb information and effectively transform it into action. Innovative companies focus on relationships with opinion leaders. They are open to any kind of discussion. Employees at all levels are encouraged to be intellectually curious, willing and free to experiment and to explore knowledge creation (Davenport, Delong, & Beers, 1998).
A minimum level of organization is typical for innovative organizations. High-velocity, or high-uncertainty environments require simple routines, and a dependenceon people over process (Eisenhardt & Martin, 2000). To be creative, people need the freedom to manage their roles and responsibilities—a very high degree of autonomy. Only a limited number of rules define the joint working process. Work is not assigned to them: They create projects aligned to core business goals.
Openness and independence are also reflected in the information management of highly innovative organizations. Communication is organized by rules only to a small extent. People are not inhibited in sharing knowledge, and they do not fear that sharing knowledge will cost them their jobs. As a result, they are not alienated or resentful of the company.
Creative conflicts (experimentation) are the seeds for innovation. Innovative companies support cultures, where conflicts arise and are discussed. With conflicts the employees are trained how to handle new situations.
Innovative companies have accordingly adapted recruiting requirements. These organizations attract and hire people who reinforce the positive orientation towards creativity, innovation, autonomy, and adaptation. People need to have the ability to create conflicts and find ways how to solve them.
Competence and responsibility for innovation is shared within the entire workforce but is especially expected of the leadership team. Everybody within the organization is responsible to develop and push innovation. All employees have the one joint overall target (provided by leadership) to support the development of innovation as it aligns to customer needs.
The organization is not focused on selling products but rather on fulfilling customer needs (Levitt, 1960); the customer determines what a business is, what it produces, and whether it will prosper (Drucker, 1954).
A culture with a positive orientation to innovation is one that highly values learning on and off the job, and one in which experience, expertise and rapid innovation supersede hierarchy.
The following sections of this essay explore specific concepts relating to managing the polarity of flexibility and control. The axis of understanding is organizational anxiety. This exploration establishes the basis for dissertation research to contribute additional knowledge to this crucial and understudied aspect of transformational leadership, innovation, and crisis management.
How tension is managed (or not) included in this section all have applicability to help better conceptualize and understand the ways in which leaders operate in the organization. Successful management of this tension has unique characteristics, they can: effectively respond to internal or external disruption; correctly interpret complex, adaptive problems, and identify errors; and, they can manage a wide spectrum of change (from innovation to crisis), including the anxiety and uncertainty that comes with it.
Bias and Mental Models
There are two elements that leaders need awareness of in order to boost their odds of success: tackling cognitive biases and understanding their own impact on culture. Both of these factors contribute to the creation, nurturing, protection, and evolution of mental models. These elements also impact leaders’ ability to correctly identify opportunities they might be blind to and problems they might be misinterpreting.
Leaders of start-ups and long-time companies alike are mindful that factors such as timing, scale relative to the competition, and the ability to leverage complementary assets (Horn, Lovallo, & Viguerie, 2005, para. 1), geographic expansion, new products, and diversification efforts should prompt detailed analysis. However cognitive bias—that systematic error in the way we process information—can warp decision making (Mitroff & Silvers, 2010) of any kind—and rarely gets discussed. “The majority of bad decisions, errors, and mistakes that [leaders] make are … are the result of the highly standardized ways in which [leaders] are educated and of the enormous pressures placed on them to think and act decisively” (Mitroff & Silvers, 2010, p.xvi).
Leaders (and subsequently the organization) need to distinguish between technical and adaptive challenges. Ronald Heifetz’s Leadership Without Easy Answers (1994) defines technical leadership as doing what is required to address an issue or problem when there a known or knowable resolution. Adaptive leadership is when the solution was unknown and members of the organization need to be drawn together to discern a new direction.
When confronted with a difficult decision, most executives solve old and new problems with the assumptions, mindsets, and institutions of the past (Mitroff & Silvers, 2010). In essence, they are behaving like mere managers and technicians who, as part of the corporate machine, do already-known things right. Leaders need to pause and ask ‘what is the right thing to do?’ Solving the wrong problem perfectly prevents many leaders from developing an outside perspective and even from evaluating opportunities in the light of common predictors of success.
Biases enable hubris which can often lead executives to believe that a company’s skills are more relevant than they really are, that the potential market is bigger than it actually is, or that rivals won’t respond to the entry move. Heifetz warned that there were a number of perils involved in adaptive leadership, because such challenges require experimentation, the discovery of new knowledge, and various adjustments throughout the organization. Only by adjusting attitudes, values, and behaviors can the organization adapt to a new environment and sustain such change over time; this shift in values or perspective is the most difficult (Heifetz, 1994; Graves, et al, 2005, Keagan & Lahey, 2009; Argyris, 1999).
Bias impacts how leaders and organizations perceive, take in, and react to disruption—mental models provide a construct for bias to develop. Mental models and organizational capabilities rally in protection of current assets. A calcification of knowledge occurs and bureaucracy starts to set in. For change to occur, employees have to be disloyal to their past and some of the constructs and relationships that shaped it (Heifetz, 2007). For example, if an organization were to consider abandoning formal processes such as status reports, scorecards, and monthly review meetings, they would have to be disloyal to the processes utilized in previous generations of the organization which had achieved the successes they were benefitting from. Exploring new possibilities would mean considering the idea that current processes could be ineffective. One option might be to adopt a technical approach such as automating current processes may mask the more substantial change that could enhance the organization’s effectiveness. Or the organization might be considering radical departures such as transparent accounting or monthly sessions that are open to the entire company rather than their current centralized processes. Staying with the old way may obscure a deeper and more important concern related to core organization purposes.
New growth typically involves different disciplines within the company. However, cross-functional collaboration presents a number of challenges (Schein, 1984). Members of different functions may hold different mental models of innovation, which can lead to frictions and misunderstandings. Mental Models are people’s representations of the world based on experiences and assumptions. The concept originated from cognitive psychology (Craik, 1943; Johnson-Laird 1983). It was adapted and later used heavily in the field of Human Factors Engineering as conceptions about how systems work (Nielsen, 1990; Moray, 1999), which since the 1990s has largely been incorporated into the field of Human-Computer Interaction (HCI).
Use of mental models was popularized in the HCI and interaction design community by Donald Norman (1998) in his book The Design of Everyday Things. He provides several examples of how mental models became an explanatory device for making sense of usability problems. For example, if a system fails to match a user’s mental model of it then there will be a breakdown. When a system matches the mental model of the person using it there should be fewer if any problems. Therefore it is thought that in order to build computer programs, systems, and especially interfaces, system developers should aim to match the mental model of those using the system. The concept of mental models is a powerful one, bringing with it the baggage of cognitive psychology, but we do not import this wholesale; rather, we invoke it as a metaphor useful in explaining how people understand their work.
Mental Models are used in organizations to edit the world and facilitate operations by simplifying complex situations and permitting distributed decision making. They are, in essence, goal-driven images of the world that are built to understand the current and future states of a situation. As such, they are best characterized by incompleteness.
Like all crutches, both bias and mental models are useful because they can help filter information. However, they can also enable dependency, atrophy, and focus on maintaining the status quo. When faced with disruption (such as a crisis event, regular market competition, or finite resources) people generally favor the mental factors that are based on experience, expertise, knowledge, and learning; these become liabilities and make the system rigid (Senge, 1990; Leonard-Barton, 1998; 2007).
Mental models experience four common challenges. First, the oversimplification that made them useful ca n render them incorrect. Second, they can be improperly used. Third, they can lead to wrong answers if provided incorrect information. And fourth, their effectiveness is rarely assessed. Much like a company’s highly developed core capacity, mental models can often present the single most important barrier to change. Long-held mental models can make a company rigid.
The elements of the corporate architecture change as the corporation matures and the mental models change. It is the evolution of corporate architecture—with the mental models steering the direction—that determines the competitiveness of the corporation. Unmanaged, the evolution of the corporate architecture proceeds in a predictable way, which inevitably leads to cultural lock-in—a state in which the organization is effectively frozen in place by three fears: the fear of cannibalization of the existing product line, the fear of moving into businesses that will conflict with its customers’, and the fear of acquiring companies that will result in the short-term dilution of the company’s earnings and therefore a potential decline in stock price (Foster & Kaplan, 2001). Thus the process of building mental models—whether these processes are explicit and examined or implicit and unexamined—is the core managerial process of the corporation. If a mental model goes undefined, it will go unrecognized. A mental model unrecognized is a mental trap, a trap that prevents further learning.
Although mental models cannot and should not be avoided, they must be re-examined and adapted to reflect discontinuity and new opportunities (Senge 1990; Foster, 2001). An example of this is the myopia suffered by the railroad industry, and later the taxi industry. The railroads did not stop growing because the need for passenger and freight transportation declined. That grew. The railroads are in trouble today not because the need was filled by others (Cars, trucks, airplanes, etc.), but because it was not filled by the railroads themselves. They let others take customers away from them because they assumed themselves to be in the railroad business rather than in the transportation business. The same fate has befallen the taxi industry in the advent of rideshare programs like Uber and Lift.
Every industry has been a growth industry. However those that are riding a wave of growth enthusiasm are already in the shadow of decline (Levitt, 1960; Collins, 2011; West, 2011). Others which are thought of as seasoned growth industries have actually stopped growing. In every case, growth is threatened, slowed, or stopped not because the market is saturated but because of a failure of management. Shortsighted managers often fail to recognize that in fact there is no such thing as a growth industry (Levitt, 1960). This is an example of a restrictive “mental model,” an image that some industries have of themselves which keeps them from seeing their actual situation more objectively.
In a period of disruption (technical advancements, external threats, finite resources, quality issues, etc.) the very mental models that are at the heart of managerial strength are also at the heart of managerial weakness. Functions like sustainability, crisis management, and corporate responsibility have become increasingly relevant in organizations (Sterman, 2000; Kahane, 2004; Mitroff & Anagnos, 2001; 2011; Carroll & Shabana, 2010). Here again, leaders fall into technical leadership (doing what was required to address an issue or problem when there was a known resolution) instead of adopting these new functions. Such functions were not required on path to success, so incorporating them seems initially unnecessary. In trying to replicate the success of the past, however, leaders have missed that the world context is changing, requiring such functions to help them navigate, prepare, and innovate.
As globalization, finite resources, and other influences force companies and entire industries into greater interdependence with their stakeholders, companies are called upon to deal with an ever increasingly amount of complexity. Melanie Mitchell (2009) defines complexity as containing three primary characteristics: the situation is emergent; 2) as a result, there is a constant flow of information to negotiate; and 3) this means that actors in the system are constantly adapting their behavior. Complexity can result in positive or negative disruption. The problem is not an inability to take action but an inability to take appropriate action. The world is changing in complex ways. Companies need to respond to the changes, but because of the complexity, finding an appropriate response is a challenge. Companies can look at this challenge either through an innovation lens (seeking to respond via new products and systems) or a prevention lens (seeking to prevent loss or disruption of existing business).
A major concept in understanding how leaders respond to welcome and unwelcome change is understanding how they negotiate complexity, and how the identify problems. Mitroff & Alpaslan (2011) quote Russell Ackoff on the understanding of problems as symptoms of wider systemic messes:
[People] are not confronted with problems that are independent of each other, but the dynamic situations that consists of complex systems of changing problems that interact with each other…..I call such situations messes. Problems are abstractions extracted from messes by analysis…..
Therefore, when a mess, which is a system of problems, is taken apart [i.e., analyzed], it loses its essential properties and so does each of its parts. The behavior of a mess depends more on how the treatment of its parts interact than how they act independently of each other. A partial solution to a whole system of problems is better than whole solutions each of each of its parts taken separately [emphasis added]. (Mitroff & Alpaslan, 2011, p. 16)
Leaders are not just tasked with leading change but with being sensitive to the many reasons why change in programs or procedures is not only needed but becoming more urgent. The basic idea between First and Second-order change is simple. First-order change is doing more or less of something already being done. First-order changes are always reversible, require small adjustments to existing structures in order to maintain or restore balance, and are non-transformational (Bateson, 1979; Bergquist, 1993). With first order change, the old story remains the same. Second-order change is deciding (or being forced) to do something significantly or fundamentally different from what was done in the past. These changes are irreversible, enable a new way of seeing things, and requires new learning (Bateson, 1979; Bergquist, 1993). Second order change often begins through informal networks and results in a transformation to something new. A new story is born.
Related to the kinds of changes leaders need to make, are the kinds of errors they are likely to commit. A Type One error is the incorrect rejection of a true null hypothesis—or a false positive. An example of this would be measures indicating a tsunami where there is none. A Type Two error is the failure to reject a false null hypothesis. An example of this would be a tsunami coming, and measures remaining unconfirmed. Although Type I and Type II errors are taught in virtually all statistics courses, Type Three errors are almost never discussed (Mitroff & Silvers, 2010). Type III errors are the right answer to the wrong question (Raiffa, 1968). We commit Type III errors when we attempt to solve higher order problems with lower level solutions. Mitroff & Silvers (2010) credit Peter Drucker in framing the issue this way: “Managers and technicians do known things right; leaders ask what are the right things to do” (Mitroff & Silvers, 2010, p.4). Raiffa’s point was this: “What good does it do to minimize or control for Type I or II errors if the problem one is attempting to solve is wrong to begin with?” (Mitroff & Silvers, 2010, p.4).
When organizations manage they focus on existing offerings and existing users. They are focusing on the new version of something already successful. They forecast based on what is known, and attempt to control the predictability of the revenue stream—this turns part of the discussions of running the business into an exercise. Exercises are well-defined, canned scenarios, generally within a single discipline, where the information to answer the issue is provided. All confusion and extraneous information (noise) are removed. Once solved, exercises remain solved, turning the solver into a “certainty junky“ (Mitroff & Alpaslan, 2011, p. 19). The majority of the company’s effort is organized toward this type of growth because it provides the most comforting message to their shareholders. In many ways, management turns the business into an exercise. However, something unexpected always happens. Given the pace of technology, failure rate of companies, and general turnover, conditions can never be fully controlled. Mitroff & Alpaslan (2011) make a distinction between exercises and complex problems. However, complex problems cannot just be divided into a series of simple and independent exercises. They are not canned scenarios. They are ill-defined and multidisciplinary. They have more than one solution because they have the potential for more than one formulation. Complex problems are dynamic, always reacting to the solutions implemented, or their environment. Complex problems are messy. If the problem is sanitized to be simpler or more palatable, the solution becomes less effective and the problem becomes worse.
Consider some of the interconnectedness of systems we interact with on a daily basis, such as cloud services constantly under security attacks, or the amount of personal and financial data we share with various organizations on a daily basis. This complex web of relationships started with small and relatively simple transactions. Most people have an online email and bank account. Over time, personal information has become the currency in which many companies barter with us in order to begin a relationship —they require a login. Personal and financial information is now spread exponentially to news and information, entertainment, and online retail sites. The consumer is now faced with how to protect their identity, remember multiple logins, and secure their information. We have created systems that are now so big and so complicated that they have mutated into entirely new forms, highly complex and intertwined (Mitroff & Anagnos, 2001, p. 20). They have grown so complex that no one, including their designers, fully understands how they will act even under “known” operating conditions. In effect, we have created systems that are unmanageable precisely because they have unforeseen and, even worse, unknowable side effects (Mitroff & Anagnos, 2001, p. 22).
The inability of a leader to manage their own fear and complacency (as well as that of their organization) can not only hold the company back, but can hijack an entire industry. Since 2002, Google, Amazon, and Netflix have joined the S&P 500, Kodak, the New York Times, Palm and Compaq have all been forced off, essentially by changing technology. Richard N. Foster, a consultant who helped popularize of the idea of “creative destruction” suggests that big companies cannot ever out-innovate the market (Innosight, 2012). Instead, he thinks that to stay big, companies need to be willing to exit old businesses and enter new ones—and do it quite boldly. The taxi industry is too heavily regulated to innovate something like Uber. And HP could not decide whether to jettison its PC business. Foster’s data do tell us which company is America’s greatest corporate survivor. It is General Electric, the only company that has remained on the S&P Index since it started in 1926.
In the early 1990’s a problem that many early technology companies were trying to solve was the ideal of cross-platform compatibility. Technical approaches such as vendor interdependency, push-button code generation, and cross-compilation were attempted to solve this issue but were unsuccessful. Microsoft, Oracle and other corporate platform entities were blamed for being proprietary and creating a fractured landscape. But the real problem was not a technology issue: it was a usability issue, a culture issue, and a marketing issue. The value in these platforms lay in their differences; they each approached different knowledge areas in a unique way. At one point, Java managed to solve the technological problem for good, and that was the point where the industry realized with sadness that cross-platform compatibility was not as important as was previously thought.
Now that we have multiple devices such as tablets and smartphones, the issue on the table once again is the need for a common operating system. We want to use the same software across these environments. Windows 8 offers the same OS across all these devices. But people do not buy operating systems, they buy devices. A uniform OS will likely not solve the issue of convergence across devices since the devices are inherently different. All the subtle differences will start to add up, requiring unique approaches. Convergence is not the issue, it is interoperability—especially considering that the actual ways of using the devices are starting to diverge. The cell phone is becoming more voice-operated, which is not a feature relevant to the tablet or PC.
The decisions relating to convergence versus interoperability came from an organizational culture where there was twenty five years of legacy to protect (in the operating systems and related software). This resulted in products that had platform convergence as their number one feature. Innovation begins by acknowledging these biases and mental models early on so that the organization can be explicit in its decisions, and enable creativity in thinking beyond the predictable, iterative step.
The literature refers to small versus large changes using a variety of paired terms: incremental versus iterative (Christensen, 1993), first-order versus second-order (Bateson, 1979; Bergquist, 1993), or exploratory versus exploitative (Ahuja & Lampert, 2001), to name a few. First-order (iterative) change tends to focus on adjustments within existing structures, doing more or less of something; new learning is generally not required, and the old story about the organization can continue. First-order change helps organizations deal with rapid obsolescence of products and services. Examples of this are the iterations of the iPhone and the Windows 95 operating system since their initial launches. The first versions of these products were game changers for their respective companies. Subsequent iterations of the products contained updates, color changes, and platform enhancements, but the primary technologies did not change.
The danger of iterative change is that it provides an open window for competitors to imitate or evolve these same stories at lower cost. Google has done just that with Google Docs, providing a free, cloud-based solution to Microsoft Office’s shrink-wrapped software. This has forced Microsoft to create their own version of their own cloud-based version of MS Office.
Second-order change is about a new way of seeing things: it is irreversible, often begins through an informal system, requires new learning, and tells a new story. Before the iPhone was announced, the Android did not support touchscreen input, a feature that has now become standard throughout the smartphone industry. Google’s plans for Android in 2006 involved physical keys for control and no touchscreen input support. Revealed in court documents from the ensuing Apple-Samsung legal fray, the early specification says that “the product [Android] was designed with the presence of discrete physical buttons as an assumption. However, there is nothing fundamental in the product’s architecture that prevents the support of touchscreen in the future” (Smith, 2013, para. 1). Between the announcement of the iPhone and the finalizing of Android’s software requirements, not only did touchscreen input become supported — multi-input touch was required. Our phones have never been the same again.
Given all this potential for rigidity, there does not seem to be much room for the culture absorb, synthesize, and act on disruption. In his book, Culture’s Consequences, Geert Hofstede (2001) researched over 115,000 IBMers across 50 nations and analyzed differences in their “mental programs” (or what he referred to as “the software of the mind (p.2)”. His research indicated that national culture mostly stems from consistency in values and organizational culture stems mostly from consistency in practices. Hofstede (2001) highlighted five dimensions of culture, one of which was uncertainty avoidance (UA). His distinction between uncertainty avoidance and risk avoidance is significant in considering an organization’s ability to effectively manage for welcome (innovation) and unwelcome (crisis management) disruption.
Uncertainty is to risk as anxiety is to fear. Fear and risk are both focused on something specific: an object in the case of fear, an event in the case of risk. Risk is often expressed in a percentage of probability that a particular event may happen. Anxiety and uncertainty are both diffuse feelings. Anxiety has no object, and uncertainty has no probability attached to it. It is a situation in which anything can happen and one has no idea what. As soon as uncertainty is expressed as risk, it ceases to be a source of anxiety. It may then become a source of fear or accepted as a routine (Hofstede, 1984, 2001, p. 148).
Uncertainty avoiding cultures shun ambiguous situations. People in such cultures look for structure in their organizations, institutions, and relationships, which makes events clearly interpretable and predictable (Hofstede, 2001, p. 148). Paradoxically, they are often prepared to engage in risky behavior in order to reduce ambiguities—such as starting a fight (i.e., act out) with a potential opponent rather than sitting back and waiting (Hofstede, 2001). His Uncertainty Avoidance index (UAI) is comprised of three questions focused on rule orientation, employment stability, and stress. It suggests that ”in higher-UAI countries innovations are more difficult to bring about” (Hofstede, 2001, p. 167); cultures with lower UAI scores showed higher rates of innovation in terms of trademarks granted (p.169).
A number of companies have tried to build themselves up around creating something truly new, and many have struggled when that idea failed to produce anything that could eventually be commercialized. Being first to market has nothing to do with being first to profitability. And being first to profitability has little to do with how quickly, deeply, and ubiquitously an innovation spreads. What keeps organizations where they were at? What calcified their growth and in some cases enabled their decline? What catalytic factor(s) support(s) a small group of people who felt otherwise and created new enterprises?
Change—welcome or unwelcome—can be viewed through several lenses:
the type of innovation a company engages in;
their approach to management of business continuity;
leader’s degree of ability to manage both short and long term change (ambidexterity) and,
their perception of problems which have a significant impact on culture.
The type of Innovation an organization engages in (i.e., management, extension, adaptation, and/or creation) determines their growth outcomes. It also is reflective of where the organization is in their market strategy (i.e., pioneers, imitators, and late entrants) and their lifecycle (birth, adolescent, death, to name a few).
Business Continuity is the result of the level of preparation for unexpected disruption (i.e., crises) and serves to protect the company’s current assets. This function is generally staffed based upon the organization’s perception of its relevant markets and the risks within those markets. This paper is investigating the correlations between innovation and crisis management in organizations. Is how one grows one’s business related to how one protects it? While this may be true of all organizations, this paper and subsequent research will focus on high tech organizations.
In dealing with change, leaders need to be aware of the kinds of errors they are likely to commit. Two areas where leaders are likely to misinterpret potential problems are: incorrect interpretation of opportunity (and the organization’s capability to achieve growth or compete) and incorrect judgment of the probability of threats.
Cognitive bias—that systematic error in the way we process information—can warp decision making of any kind. Fear, complacency, and a desire to protect current assets are forces for maintaining the status quo.
High tech organizations confront dual demands of exploring new and exploiting existing products/processes. Ambidexterity is the ability to manage both innovation and