Digital Transformation, Change Management and Family Businesses

One of the inherent system risks for family-owned businesses is the lifecycle (May 2012). Schumpeter (1939) explained why doing business in capitalistic markets is a cycle of economic growth and recession. Especially for companies with the aspiration to sustain over many generations this is a huge challenge. May (2012) suggests family businesses to outwit the lifecycle by following a few simple rules: (1) operate in long-lasting markets, i.e. chose a product portfolio which is independent from short-term trends, (2) introduce a lifecycle radar, a combination of strategic tools and KPIs, (3) continuous adjustments to such an extent to constantly eliminate products which are at the end of the lifecycle and to invest into innovation, (4) make bold decisions, e.g. radical changes like cannibalizing the current revenue and jumping onto new technologies to overcome the innovators dilemma (Christensen 1997).

Bartels, von Hochberg and May (2017) interviewed 50 owners of large family businesses among others related to disruptive trends. They identified that companies that had already survived several generations and had been faced with the downfall of their original business areas have developed strategies to diversify their business and change the business models. Some do not operate in their original business area any more, but others had been able to adopt their business model from selling their product to offer their product-as-a-service (cf. Digital Transformation Process). The common challenge today is the increasing dynamic and speed of change. These changes are not only of technical nature, but especially a question of changing the culture. A possible success factor might be the opportunity of succession as the following generations are already digital natives (cf. Digital Transformation Context).

These considerations demand transformation capabilities in family-owned businesses. Cassia, Massis and Pizzurno (2012) researched “strategic innovation and new product development in family firms” due to the fact that little is known about leading and managing complex transformations in family businesses and with the aim to offer a better understanding of the influence of “familiness” (cf. Family Businesses) in particular the strength and weaknesses. They found out that the advantages are long-term orientation, human resources and dedication to “progression”, tendency to be close to their customers and being focused. Their disadvantages are being conservative and risk averse, a lack of openness, readiness to change, conflicts within the family and the economic rationality of decision-making processes.

Gouillart, Kelly and Gemini Consulting (1999) say that the business models originate from the industrial age and are influenced by mechanical engineering. In the digital age these business models come to a limit. Business transformation means a fundamental change, where a company needs to redefine all dimensions (cf. Digital Transformation Content). Gouillart et al. (1999) researched how companies in industries like chemistry, electronics, pharmacy, automotive etc. managed the change and synthesized these approaches into the “four R of transformation” that need to be achieved:

  • Reframing, i.e. change of attitude by achieving mobilization of the employees, creating a vision and setting the goals and KPIs;
  • Restructuring by constructing a value adding business model, aligning the necessary infrastructure and redesigning the business processes;
  • Revitalizing by becoming customer centric, inventing new business and changing the rules with the help of emerging technologies;
  • Renewing by creating a reward structure, encouraging individual learning and renewal of the organization.

This business transformation approach follows the basic principle of change management described by Lewin (1947, 34): “Unfreezing, Moving, and Freezing of Group Standards”.

The most prominent model underlying the research of Lewin are Kotter´s “8 step process for leading change” (Kotter 1995), summarized here only on headline level: (1) establish a sense of urgency, (2) form a powerful guiding coalition, (3) create a vision, (4) communicate the vision, (5) empower others to act on the vision, (6) plan for and create short-term wins, (7) consolidate improvements and produce more change, (8) institutionalize new approaches.

Kotter never claimed to have developed this model, he captured it by observing more than 100 companies going through transformational change (Farell 2017). One prominent example is the digital transformation of IBM after the company lost more than US$ 16bn and needed to change their business model from selling and running mainframe computers to an e-business company (Farrell 2017).

Although evidently successful for many large enterprises, Oxley (2017) claims that “Kotter’s change framework doesn’t work for large family businesses”. He argues that on the one hand, steps 1 to 5 of Kotter’s model are based on the assumption that no individual leader can enforce change and followers must be convinced to change. On the other hand, the underlying message of steps 5 to 8 is that those who do not comply with the change must leave the organization. Oxley (Oxley 2017) says that this is contradictory to the “familiness” and therefor special characteristics of a family business: (A) dominant ownership, often combined with the existence of a figure who is followed unquestioned by the organization and (B) individual loyalty, i.e. a very strong commitment to the employees and the sense of obligation to take care of them (cf. Family Businesses).

Figure 1: Success Factors of Digital Transformation, adopted and translated from (Müller-Seitz and Weiss 2019, 51)

An alternative approach for family business and hidden champions will be provided by Müller-Seitz and Weiss (2019) who describe five success factors for cultural and structural change to manage digital transformation, cf. Figure 1:

  • Self-organization:
    Change to agile ways of working as the central guiding principle to give space for innovative thinking due to interdisciplinary teams and flexible work environments. Self-organization demands a respectful understanding of people, in which employees are fully trusted.
  • Dealing with uncertainty:
    “Across many industries, a rising tide of volatility, uncertainty, and business complexity is roiling markets and changing the nature of competition” (Doheny, Nagali and Weig 2012). VUCA as an acronym referring to volatility, uncertainty, complexity, and ambiguity has recently found its way into business lexicons (Bennet and Lemoine 2014). To deal in a VUCA world demands curiosity and the attitude of “fail early and fail often”.
  • Work, organization and communication:
    A customer and innovation centric company culture as the basis for success and strengthen the strength of the people as a guiding principle for HR.
  • Add value with cooperation partners:
    Valuable partnerships create the basis for common success as well as building of intercompany networks and linking of work.
  • Organizational learning and knowledge management:
    Implicit knowledge is difficult to handle, but worthwhile to transfer within the organization. Knowledge platforms inside the intranet are possible solutions.

Work Cited

Bartels, Peter, Peter von Hochberg, and Peter May. Strategien erfolgreicher Familienunternehmen 2017. Report, PWC, 2017.

Bennet, Nathan, and G. James Lemoine. “What VUCA really means for you.” Harvard Business Review, Vol 92. (1/2), 01 15, 2014: 27-29.

Cassia, Lucio, Alfredo de Massis, and Emanuele Pizzurno. “Strategic innovation and new product development in family firms.” International Journal of Entrepreneural Behaviour & Research, Vol. 18 (2), 03 2012: 198-232.

Christensen, Clayton M. The Innovator’s Dilemma: When New Technologies Cause Great Firms to Fail. Boston: Harvard Business School Press, 1997.

Doheny, M., V. Nagali, and F. Weig. “Agile operations for volatile times.” McKinsey Quarterly. 05 2012. https://www.mckinsey.com/business-functions/operations/our-insights/agile-operations-for-volatile-times (accessed 09 20, 2019).

Farell, Adrian. John Kotter – Leading Change Guru. 04 28, 2017. http://candowisdom.com/change/change-management/john-kotter-leading-change-guru (accessed 09 01, 2019).

Farrell, Adrian. Lou Gerstner – IBM’s Digital Transformation Change Master. 05 21, 2017. https://candowisdom.com/change/change-management/lou-gerstner-ibm-digital-transformation (accessed 09 01, 2019).

Gouillart, Francis J., James N. Kelly, and Consulting Gemini. Transforming the organization <dt.>. Wien: Ueberreuter, 1999.

Kotter, John P. “Leading Change: Why Transformation Efforts Fail.” Harvard Business Review, May-June 1995: 59-67.

Lewin, Kurt. “Frontiers in Group Dynamics: .” Human Relations, Vol 1 (1), 1947: 5-41.

May, Peter. Erfolgsmodell Familienunternehmen. Das Strategie Buch. Hamburg: Murrmann, 2012.

Müller-Seitz, Gordon, and Werner Weiss. Strategien zum Umgang mit der digitalen Transformation … aus der Sicht eines mittelständigen “Hidden Champions”. München: Vahlen, 2019.

Oxley, David R. Why Kotter’s Change Framework Doesn’t Work for Large Family Businesses. 07 11, 2017. http://www.davidroxley.com/kotters-change-framework-doesnt-work-large-family-businesses/ (accessed 09 01, 2019).

Schumpeter, Joseph A. Business Cycles – A Theoretical, Historical and Statistical Analysis of the Capitalist Process . New York, Toronto, London: McGraw-Hill Book Company, 1939.

Why do companies digitally transform?

Around 70,000 years ago, during the first revolution homo sapiens went through the development of language, which distinguished us from all other species. This revolution helped us to cooperate, to share information and in the end to build complex social systems.

Since then several technological revolutions followed in the areas of agricultural development, weapons development, communication, transportation and industrialization, but mankind has gone through two fundamental civilization phases. While the first, the Neolithic Revolution, took place 20,000 to 15,000 years ago, where among others the wheel, agriculture, woven fabric and construction was invented, and people started to domesticate animals. This revolution led to the occurrence of first villages and small-scale societies. The second, the Industrial revolution, started a massive accumulation of knowledge. The invention of machine-supported, labor-saving work enhanced manual skills and capacities, led to a massive increase of productivity and had a huge social, economic and political impact on humanity (TWI2050 – The World in 2050 2019) (Gregersen n.d.) (Loendorf 2010).

Within the industrial revolution we went so far through three waves of modern technology enabled transformations. During the first industrial revolution it took three generations from 1780 to 1850 to completely change the face of England, who became a role model for industrialization worldwide (Fremdling 1996). The second industrial revolution started in the late 19th century and lasted into the early 20th century with the invention of electrical power generation and led to mass production and assembly automation. The third industrial revolution, also called the computer or digital revolution began in the 1960s with the introduction of mainframe computing, followed 1980 with the personal computing and in the 1990s the internet (Schwab 2016) (Gregersen n.d.).  

The transformations of the 1980s and 1990s was IT enabled and resulted in the digitalization of processes by the introduction of information systems. Information was recognized to give companies a strategic competitive advantage (Porter and Millar 1985).

Internally, in the micro economy, there are three main aspects of an organization: (1) internal, i.e. run production and operations, (2) external, i.e. analysis and reaction to the political, economic, social, technological, legal and environmental (PESTLE) situation, and (3) co-ordinating, i.e. to mediate between internal and external aspects and to process the related information for the organization. Here the benefits of computers started from data processing over “office automation” to information processing with huge impacts on the organization due to business process redesign or reengineering (Noble 1995). The focus was to increase the efficiency (Venkatraman 1994).

Externally, in the macro economy, the benefits come from the improved productivity, network effects like reduced transaction costs and accelerating innovation. “The network advantage does not depend on the operation of a given company and its business strategy” (Sasvari 2011, 77). As it is possible to show the benefits on the macro-economic level, it is unequally difficult on the micro-economic level. The secondary effects of changed processes, social interaction, decision making due to information access are hardly measurable. It even shows a “productivity paradox”, a discrepancy between IT investments and productivity outcome as the effects on productivity depend on longer or shorter learning curves (Sasvari 2011) (Bakis, Kagioglou and Aouad 2006) (MacDonald 2002). Moore´s law1 is one indicator for the rapid technological development which lead to a commoditization of IT: As a result, the later an investment will be done, the cheaper and more advanced the technology is. Carr (2003) argues that IT is essential to competition, but inconsequential to strategy. IT becomes an operational risk, when an IT outage “can paralyze a company´s ability to make its products, deliver its services, and connect with its customers, not to mention foul its reputation” (Carr 2003, 11).

1Moore´s law is the empirical observation that the number of transistors in an integrated circuit-close related computational performance – has for several decades doubled approximately every two years.

The three waves of industrial revolution changed the world from executing manual physical tasks to automation driven by machines providing the physical power with added value of information and human mind (Bilton, et al. 2017). The World in 2050 Initiative (2019) quotes a not yet published report from the German Advisory Council on Global Change (WBGU) that the Digital Age can be characterized by three major dynamics going from transformation to sustainability. All three dynamics are emerging in parallel with different intensities and with no strict chronological order. The first dynamic describes the IT enabled transformation, the digitalization of existing procedures and the automation of manual work. The second dynamic describes the transformation towards a digitalized society. Digital technologies like virtual reality (VR) and augmented reality (AR), additive manufacturing, artificial intelligence (AI), Internet of Things (IoT) can much faster than ever before enable a disruptive revolution by promoting circular or shared economies and the automation of cognitive work. The third dynamic describes the future of the homo sapiens as governance will be urgently needed. “The disruptive dynamics of digitalization are challenging the absorptive capacities of our societies, possibly multiplying the already alarming trends of eroding social cohesion” (TWI2050 – The World in 2050 2019, 9). The World in 2050 Initiative (2019) see four major challenges: (1) inequalities within society, (2) economic, and with it political, power concentration, (3) data sovereignty and civic rights (4) governance capacities as it is very difficult up to impossible to regulate big digital businesses within virtual environments.

To get to the stage of sustainability the minimum requirement of digitalization is to comply with corporate social responsibility initiatives and goes up to a “business strategy that serves to drive social and economic benefits for the organization and its consumers, employees, shareholders and the greater community” (Kaufmann und Horton 2015, 64).

Figure 1: Three possible dynamics of the Digital Age, (WBGU 2019 (forthcoming))

The difference between the actual digital transformation and the IT enabled transformation of the 1980s and 1990s is, that it is not about computer hardware, software and networks anymore. “Technology is growing exponentially, and since 1400 has doubled every 200 years (analogous to […] Moore’s law, applied across all technology)” (Lee 2013). Lee (2013) also says, that the technological change will accelerate with such a speed that “society will spend less and less time at any particular technological level”.

Figure 2: The accelerating growth of technology, (Rej 2017, 8) adopted from (Lee 2013)

Schwab (2016) argues these technologies becoming more sophisticated and integrated into existing physical, digital and biological domains and as a result are transforming societies and the global economy: New business models, disruption of established businesses, reshaped production, delivery, consumption and transportation, changed social behavior, new ways of working and communicating, reshaped government and institutions as well as education and healthcare. “In this [fourth] revolution, emerging technologies and broad-based innovations are diffusing much faster and more widely than in previous ones” (Schwab 2016, 12).

Another explanation for this massive appearance of innovations, which can be discussed as the starting point of the fourth industrial revolution, is the financial crisis from 2007 to 2009. This hypothesis is based on the theories of Nikolai Kondratieff. He observed long-term economic fluctuations in cycles of 40 to 60 years. These cycles begin with technological innovations, an extended period of economic upturn and end with a sudden or longer downturn of the economy. Since the industrial revolution five waves could be identified. (Allianz 2010)

Figure 3: Kondratieff cycles – long waves of prosperity, (Allianz 2010, 6)

Schumpeter (1939) investigated the first three Kondratieff cycles. His hypothesis of the existence of these business cycles is that innovation and technology influence economic growth. Innovations had not been distributed equally over time and clusters of major innovations create new opportunities that accelerate economic growth. Mensch (1982) added to Schumpeter’s observations that more innovations occur during recessions due to investment behavior. He argues that during times of economic prosperity investors do not take high risks. In times of recession are only a few low-risk opportunities available which leads to the rise of equity markets and venture capital. Costs of higher interest rates are not a problem at the beginning of each new cycle as entrepreneurs are able to increase their earning due to innovation. Later the commoditization of new technologies results in a high level of financial capital in comparison to physical capital, which leads to a financial bubble and then to a collapse (Allianz 2010).

At the same time as the financial crisis 2007 to 2009, a first generation of digital natives came to age. People of the Generation Y or also called Millennials were born between 1980 and 1994. They are “Technological Savvy” (Sa’aban, Ismail and Mansor 2013) as they are the first generation which has been growing up with digital technology and it has become part of their life, although the technology has been developed from the Baby Boomers and Generation X. Millennials are open-minded towards Industry 4.0 and the sharing economy (Brkljač and Sudarević 2018). Employees of all generations want to work for digital maturing companies and expect digital fluency from their leaders, which “requires the ability to articulate the value of digital technologies to the organization’s future” (Kane, et al. 2015, 4)
But while Baby Boomers prefer autonomy and hierarchies, the Generation Y challenges management and likes to collaborate and work in teams (Helyer and Lee 2012).

As Customers, the Millennials will be part of the “Third Wave” of the Internet (Abeyratne 2017), which Steve Case (2016) calls “The Internet of Everything” (Internet of Things), connecting the physical and the digital world driven by people, products, platforms, partnerships, policy and perseverance. The first two waves have been the static internet, which supports online consumer business, followed by the mobile internet, which allows business in real-time and anywhere. The fourth wave will be AI & Robotics (Fujitsu 2016), which makes perfectly sense as with the connection of everything data becomes available instantaneous, widespread and cheap. And “data is to the information economy like oil to the industrial economy” and became a critical enabler for automation and AI (Bilton, et al. 2017). Porter (2014) explained how “Smart Connected Products Are Transforming Competition”. He also made the statement, that “Competitive advantage grows fundamentally out of the value a firm is able to create for customers” (Porter 1985, xiv). Today Customers expect that companies not only respond to their expressed needs but want them proactively anticipating their evolving needs before they even have realized it by themselves. This proactive customer orientation is the most consistent driver of customer value (Blocker, et al. 2011). Innovative start-ups take advantage by creating and serving new customer demands and/or establishing new forms of customer engagement and relationships. By Exploitation of the competitive advantages and low barriers of the digital era they disrupt the business models of incumbent companies (Lucas, Jr., et al. 2013).

Disruption is possible when companies stop being customer-focused and become product focused. In a growing stage companies are focused on the customer as they are gaining for acceptance and still searching for the largest possible market. Sales and profit are growing due to the benefits from economies of scale. Once reaching a stage of maturity, further sales growth will be achieved by focusing on the product as profitability reaches the peak due to the production of higher volumes at lower costs, because of product standardization and a high level of efficiency (Luna 2019). Christensen (1992) defines the period of increasing product performance until maturity state the “technology S-curve” referring to Sahal (1981). Disruption happens when at the same time when a first technology is in the product-focused stage of maturity a second technology is in the growing phase offering similar customer value. To be able to avoid disruption, companies would need to innovate and enter a new technological cycle, while they are still profitable and before the stage of maturity. Christensen (1997) calls this strategic decision the “Innovator’s Dilemma”.

Figure 4: Technological S-Curve, adopted from (Christensen 1992, 340)

These had now been given the context of micro- and macro-economic drivers why companies digitally transform. They can be divided into internal motivation and external triggers.

Internal motivations: competitive advantages or with the commoditization vanishing advantages with the result of decreasing sales and financial pressure; cost savings due to the increase of productivity, efficiency or better decisions through information access; employees, especially younger generations, who like to collaborate and want to work in a digital enabled environment; strive for sustainability and corporate social responsibility.

External triggers: exponentially accelerating emerging technologies, especially IoT, AI, AR and VR; disrupting potential coming from the speed of new technology cycles and innovative start-ups who faster exploit these digital technologies; tech-savvy and pro-activeness demanding customers; pressure coming from the society and government regulations related to inequality, power concentrations, data sovereignty and civic rights.

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