6.1. An overview of management systems

Before discussing how innovative organizations can use the 7S framework for knowledge management, it is convenient to recall the basic definitions of management in general and innovation management in particular. A question that even advanced students sometimes struggle to thoroughly answer is, how can we define any type of management process – project management, knowledge management, innovation management etc.? While some of their answers capture some of the aspects of management, students rarely have a systemic view of the management process. Based on the classic PDCA cycle or “Deming Wheel”, Figure 6.1 illustrates the key elements of a simple management system.

The PDCA principles are nothing new. In fact, they can be traced back all the way to the creation of the Scientific Method by Francis Bacon in the 17th Century, whose “hypothesize–experiment–evaluate” process is very similar. What makes management a particular “science” is that it consists of planning, allocating and controlling a very particular set of resources (Platje and Wadman 1998; Singh 2013). These resources mainly consist of four essential components: human, informational, financial and material elements (Davenport 2013). Arguably, human and informational resources are the most important of these components. Indeed, if we have the right people, they will use the most relevant strategic sources of information to generate knowledge and intelligent decisions about financial and material resources required to deliver value to customers. Conversely, having a lot of money or materials but poor decision-makers will not get organizations very far.

Consider, for example, the case of Facebook. Mark Zuckerberg did not have a lot of money, infrastructure or personnel when he started his company in a Harvard dormitory. However, because he had the right vision and knowledge, and because he knew the right people (other developers, venture capitalists, experienced entrepreneurs), he could get all the other resources required to build the most successful social network in the history of the Internet.

Figure 6.1 summarizes what might be called the “DNA of every managerial problem”. As discussed above, management problems occur either because of poor planning, or due to implementation or controlling of people, information, money or materials. As simple as it is, this insight is a powerful way of identifying internal strengths and weaknesses in a managerial system, whether they deal with innovation management, HR management, IT management, logistics or finance. Like the DNA molecules that constitute all living things – microscopic or gigantic – these elements are the basis of every organizational process, whether we are talking about a one-person startup or a multi-billion-dollar business conglomerate.

Therefore, we can revisit our definition of innovation management as the process of planning, implementing and controlling knowledge (people + information) in order to create product and services that address certain unmet needs of the market. This definition introduces an external component, market needs and expectations, which is beyond the direct control of managers. Hence, good innovation managers are competent not only in dealing with the internal resources at their disposal, but also at understanding those poorly met market needs and expectations and to devise solutions for them (see Chapter 3 for a detailed discussion of internal and external variables in a management system).

Every basic system is composed of four basic elements: input, process, output and feedback (Ilgen et al. 2005). In a management system, as illustrated in Figure 6.2, inputs typically consist of the aforementioned resources (human, informational, financial and material). The process is defined by the stages of planning, allocating and controlling those resources in order to create outputs (products or services) that address customer needs. This approach is often called the “Resource-based View of the Firm” (Barney et al. 2001). Market feedback is the signal (in the form of product adoption rates, comments, criticisms) generated by customers who buy and/or use the product, as well as information concerning opportunities of doing a better job than competitors at solving current and future customer needs.

Great companies are very good at listening to market feedback and adapting their inputs and processes to bridge the gap between customer needs and the firm’s actual output. They behave like an open system, in which the conditions of the external environment directly influence how inputs and processes are managed – like an air conditioner that adjusts how much cold air it produces based on the readings of the thermostat and the desired temperature established by the user. Mediocre companies find it difficult to learn with the external environment and adapt its resources and processes accordingly, behaving like a closed system – like a ventilator that keeps the air flow steady at one level irrespective of the changes in external temperatures.

The examples of Nokia and Blackberry are very eloquent when it comes to illustrating the dangers of not listening to market needs/feedback and adapting its processes accordingly. By sticking to the idea that physical keyboards were a necessary element of smartphones, even after market feedback showed how the world craved tactile devices, these two companies basically signed their death sentences. Samsung, on the contrary, realized that this new market trend was irreversible very early on, and partnered with Google to develop tactile Android phones to compete directly with Apple.

6.2. The 7S framework for organizational analysis

Now that the basic elements of every managerial system are established, let us revisit the internal (thus controllable) elements of business environments. In Chapter 3, we used Porter’s Value Chain framework to look at primary activities (inbound logistics, process, outbound logistics, marketing, after sales) and secondary activities (technology, finance, human resources, infrastructure). These can be understood as systems for managing the four resources mentioned above. Porter’s framework is useful to distinguish between the primary and supporting systems, but it fails to portray other elements that affect organizational performance: strategy, structure and culture. As we also saw in Chapter 3, before the Resource-based View of the Firm was popularized by Barnes et al. (2001), the consulting firm McKinsey & Company created a framework that was very well adapted to that purpose, known as the “7S” framework (Waterman et al. 1980), shown in Figure 6.3.

The first thing to note in this approach is the fact that these variables are all interdependent and non-hierarchical (as suggested by the interconnected lines). A change in strategy will affect the way communication and control systems are used, for example, as well as the way people use the formal and informal structures to develop projects, the skills that will be prioritized, the people/staff who will play the most important role and, ultimately, how the organizational culture (shared values/style) will be affected. Conversely, recruiting new people (staff) or introducing new tools or systems will provoke changes in the organization’s DNA that will eventually cause all the other variables to adapt, and so on.

Another important aspect of this framework is the fact that certain variables are more easily controllable than others. Strategy, structure and systems are called “hard Ss” because, just like the “hard sciences” (physics, chemistry, mathematics), they can be quantifiable or at least explained by using explicit supports (diagrams, charts, slides, etc.). The “soft Ss”, however, belong to the sphere of the intangible, implicit domain of organizational culture (staff/people, management style, skills, shared values). It is much easier to design the strategy, the structure and the systems of an organization than to “develop” its “soft” aspects. When it comes to innovation, however, a close coordination between soft and hard elements is crucial for creating or developing a learning environment, as explained below.

6.3. Towards a framework for innovative knowledge management

In the early 2000s, an ex-McKinsey consultant called Claudio Terra created a model for innovation and knowledge management based on the classic 7S framework, which is shown in Figure 6.4.

Terra’s diagram has the merit of prioritizing the strategic, tactical and operational variables of the McKinsey model while adding a distinction between internal and external learning environments. The similarities and distinctions between the two models become clear at a glance: strategy (and vision, element number 1) becomes the most important layer. It is an “umbrella” overhanging all other variables; the rise or fall of organizations largely depends on how accurate and flexible their senior management vision and strategy are.

Culture (2) is the equivalent to style and shared values. Structure (3) remains a separate component, while staff and skills become HR Policies (4). Systems are subdivided into information systems (5) and performance measurement systems (6), emphasizing the importance of communication and control in learning organizations. Moreover, external learning (7) is added. We also see here how two of the input elements previously discussed in a management system are particularly prominent: people (4) and information (5), the basis of learning and knowledge creation (7). Furthermore, two of the management process variables are emphasized: planning (vision, strategy, number 1) and control (performance measurement, number 6).

It is worth mentioning the central role of culture (2) in Terra’s model: after vision and strategy, it is the second most important piece of his whole concept. All other elements in the organization converge to create and influence organizational culture, but as suggested by the double headed arrows, they are all equally influenced by those “shared values”. Without a culture of innovation that favors risk taking, initiative and iconoclastic thinking, companies are doomed to reproduce their success formulas from the past, ignoring the many learning opportunities presented by the evolving needs and expectations of customers.

Based on these elements, we can amplify our definition of innovation management: beyond planning, implementing and controlling knowledge in order to create product and services that address certain unmet needs of the market, innovation management can be defined as the ability of senior management to establish a guiding vision based on current and future unmet needs of customers, and to transform that vision into organizational structures, processes and systems that deliver superior value through a culture of constant learning.

In the following section, we will illustrate this definition by revisiting each one of the elements in Terra’s framework in the context of best practices by leading companies.

6.4. Applying Terra’s framework: best practices from leading companies

6.4.3. Information systems and performance measurement systems

Information technology (IT) as a tool to reduce costs and improve performance is at the heart of most innovations created by Amazon. At the world’s largest online retailer, IT algorithms are used, for instance, as follows:

• – to facilitate customer decision-making through search and recommendation engines at https://www.amazon.com/;
• – to improve logistics by tracking packages and determining optimum inventory levels according to demand;
• – to reduce travel costs by promoting videoconferencing and distant collaboration;
• – to create a dashboard of instant metrics, from the average time spent on the phone during customer service calls to sales forecasts.

Like Google, which is reputed for basing every product decision on data, Amazon has achieved their world dominance through a careful combination of technology and controlling systems. Jeff Bezos, Amazon’s CEO, created a culture of “decision by metrics” that permeates every meeting throughout the company. Those metrics take into account not just the financial aspects of the business, but also customer, process and learning performance indicators, as popularized by Kaplan and Norton’s (1996) Balanced Scorecard (BSC, shown in Figure 6.5).

The BSC was created with the notion that multiple dimensions are involved in business development. Making business decisions based only on financial data (past sales, growth trends, etc.) is like driving a car through the rear-view mirror. The BSC helps managers and entrepreneurs think in a multidimensional framework structured around the following sets of questions:

• – How should we appear to our shareholders/investors? Examples of key financial metrics include:
  • - return on investment;
  • - cash flow;
  • - return on capital employed;
  • - financial results (quarterly/yearly);
  • - internal business processes.
• – What activities should we excel at? Examples of key business process metrics include:
  • - rate of on-time delivery;
  • - order fulfillment time;
  • - rates of capacity utilization;
  • - yield measurements;
  • - percentage of project cost variance;
  • - employee productivity.
• – How will we sustain our ability to change and improve? Some key learning and growth metrics are:
  • - employee turnover;
  • - job satisfaction;
  • - training/learning opportunities;
  • - percentage of revenue from new products/services;
  • - engagement rate in innovation projects.
• – How should we appear to our targeted segments? Key customer metrics could include, for example:
  • - perceived brand attributes;
  • - customer satisfaction rate;
  • - customer percentage of market;
  • - customer retention rate.

Each company should create their own set of relevant indicators based on their industry best practices. The answers to each one of these questions should be inspired by the original vision and strategy of the firm, to make sure the used metrics are relevant and contributing to a move in the right direction. This reinforces the importance of the strategic element in Terra’s original model as the “starting point” and “overarching principle” that should guide every organizational dimension. It also reinforces the link between planning, allocation and controlling of resources as the basis of every management system.

It should be noted, however, that not everything can be measured and controlled. Personal judgment and “gut instincts” do play an important role in moving towards the vision. Einstein did not have any empirical data when he first formulated his theory of relativity – he famously stated that imagination is more important than knowledge. Therefore, it is appropriate that information and control systems remain at the operational level of Terra’s framework, entirely subordinate to the strategic and tactical levels. Even though the “hard Ss” (strategy, structure, systems) can and should be measured, the intangible “soft Ss” (skills, staff, shared values and style), which are part of the human side of organizations, are difficult to measure and yet remain essential for the innovation process to succeed.

6.5. Knowledge management in the ecosystem: Quintuple Helix and stakeholder maps

In order to scale up, businesses must learn from the external ecosystem in order to constantly adapt their strategies, structure and systems. Even their culture (style and shared values) must evolve if a company is to adapt their skills and staff profile to ever-changing competitive environments. Terra’s seventh dimension (learning with the external environment) offers a checklist of the key players that businesses must monitor to ensure they are constantly learning from customers, competitors, suppliers, partners, research centers and universities.

As mentioned in Chapter 1, Carayannis et al. (2012) offer an even more comprehensive framework for analyzing the collaboration opportunities in the innovation ecosystem. Figure 6.6 reproduces the adaptation of the concept of Quintuple Helix. In it, we see how sustainable development/growth can be achieved through innovation; in order to be innovative, companies need to learn from their own competitive environment (the economic system where the “entrepreneurial capital” stems from). They must also constantly interact and learn from universities and research centers (sources of human capital). The government can be a key player in this environment, offering financial support, data and networks. Thus, companies must not only keep informed of government policies concerning innovation and economic development, but also actively participate in government-sponsored activities in bodies such as embassies, chambers of commerce and public agencies.

In a digitally connected world, in which any private citizen can make or break a brand with a tweet or a Facebook post, it has become more necessary than ever to monitor the attitudes of the general public as a key stakeholder. An important subset of this group is, of course, the company’s direct customers. The way a company and its products are perceived are important not just in terms of reputation (social capital) but also as a source of learning about unmet needs and expectations.

The final dimension of Carayannis’ model is the natural environment. Ecological constraints are an increasingly important component in any company’s strategy. Learning how to reduce one’s impact on the environment (thus increasing one’s “natural capital”) could be a powerful source of innovation.

This multitude of stakeholders could easily lead a company to lose focus and to spread its scarce informational resources over too large a field of intelligence gathering. As usual, some sort of prioritization framework is necessary to help decision-makers focus on the key players in the external environment. Stakeholder mapping, shown in Figure 6.7, is a commonly used tool to prioritize sources of learning from the ecosystem. First introduced by Mendelow (1981), this four-by-four matrix creates four profiles of stakeholders in an ecosystem:

• – Static powerless: These are actors who are unlikely to be an interesting source of opportunities or threats. They should be mostly ignored.
• – Dynamic powerless: Even though these actors cannot affect the business directly due to their low power, they are highly dynamic and could be an important source of learning, benchmarking. Potential partnerships could emerge here.
• – Static powerful: These are well-established players who change little over time. Though highly strategic, their static nature justifies saving resources by monitoring them only periodically.
• – Dynamic powerful: These are the key players in your field. These are “movers and shakers”. It is essential to create partnerships with them and to constantly learn from their best practices.

6.6. Teaching and learning knowledge management

In this chapter, we tried to synthesize through a few key images and examples how the use of frameworks can make it easier to understand the role of strategy (and vision), structure and systems in innovation management. We tried to demonstrate that an innovation management system consists, like any other management process, of planning, allocating and controlling resources. The ability of an organization to learn and use knowledge (people + information) to address the unmet needs of customers is what distinguishes innovation from other processes.

Terra’s framework, based on McKinsey’s original 7S model, integrates these variables beautifully. It gives a prominent role to strategy and vision as the starting point of every innovation process. Vision and strategy are, as seen, supported by structures and systems in tactical and operational levels. Innovative organizations are designed to appropriately adapt each one of these components in order to maximize learning from the external environment. The Quintuple Helix and the stakeholder mapping tools can help identify all the stakeholders in the ecosystem and prioritize them.

For the sake of synthesis, some of the interesting relationships between the variables are simplified or omitted here. The best way to internalize the frameworks presented in this chapter is to practice them. After introducing Terra’s model, teachers may encourage students to work in small groups to interview startup founders and to diagnose their “knowledge management maturity” level using the conceptual lenses discussed here. The “checklists for thinking” in this chapter should make it easier to identify problems in the learning processes of those organizations and how to propose solutions on how to better manage resources to promote innovation and growth.

Here are a few questions that may help in this process:

• – Do they have a clear vision of their role in fulfilling unmet needs and a coherent strategy to deliver that value?
• – Do they have a culture that prioritizes constant learning and adaptation to the ever changing opportunities and threats of the external environment?
• – Do their organizational structures facilitate sharing and learning?
• – Do they recruit the right people, with the right competences to fulfill their vision?
• – Are these people incentivized to learn and grow?
• – Can these people rely on efficient information and communication systems to produce and share knowledge?
• – Are the performance metrics relevant and attuned to the vision and strategy?
• – Is this organization capable of constantly adapting its processes and outputs based on feedback from the actors in the external environment (above all customers, and also partners, suppliers and competitors)?

After interviewing one CEO or startup founder using this interview guide, each group should meet and debrief their findings. If they had permission to film the interviews, they could use online tools such as Microsoft Stream or YouTube Studio to automatically obtain a transcript of the interviews (as downloadable closed captions from the uploaded videos). A synthesis of these transcripts can then be parsed on a collaborative spreadsheet, as shown in Table 6.1.

A vertical analysis of each column would give a synthesis of the strengths and weaknesses of each startup on the last line of the table (“Vertical synthesis”). A horizontal analysis would allow students to compare differences between the several testimonials, giving an overview of typical difficulties faced by these startups in their knowledge management process. If done well, the horizontal analysis could become an eloquent portrayal of typical pitfalls and barriers that hinder startup innovation and growth.