DECISION INTELLIGENCE
- Intelligence comprises of all sorts of data, information, knowledge and insights.
- Decision Intelligence (DI) is the FIT between the Intelligence Requirements of an organization / individual and the Intelligence Processing Capacities of the same.
- In today's world driven by Uncertainty, Ambiguity, Industry Dynamics and Industry Convergence, the Intelligence Requirements of organizations / individuals are rising dramatically.
- To match the rising Intelligence Requirements, organizations / individuals need to adapt and often significantly change the way they are gathering and processing intelligence (i.e. their Intelligence Processing Capacities).
- The Decision Intelligence Navigator (DI-Navigator) supports organizations / individuals in achieving a FIT between their Intelligence Requirements and their Intelligence Processing Capacities. The DI-Navigator consists of four major elements:
- Contextual Mindset,
- Framework Proficiency,
- Intelligence Access &
- Decision Proficiency.
The Decision Intelligence Navigator
LOGIC
LOGIC
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The starting point of our Decision Intelligence Navigator is the the CHANGE in the CONTEXT of individuals/organizations. In today's world, especially companies and their executives are facing a dramatic increase of factors that are changing fast and significantly - finally affecting their business models and profits. The management literature often uses the term "VUCA" (Volatility, Uncertainty, Complexity, Ambiguity) to describe this challenge of companies and their executives.
In our work with executives we have realized that they have severe problems to apply the "VUCA" concept in reality as the four terms are - at least from our perspective - not mutually exclusive. This is why we have developed an adapted concept to address the CONTEXTUAL MINDSET of executives. It focuses on two major aspects:
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Decision Intelligence Navigator
Exhibit 1: Decision Model Navigator
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Only if executives have a specific CONTEXTUAL MINDSET regarding the uncertainty & ambiguity as well as industry dynamics & industry convergence they face, they are able to select the right analysis framework(s) as well as the required access to intelligence.
Some of the following passages are part of ongoing academic publication project.
Contextual Mindset
Exhibit 2: Insight Level Matrix
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The CONTEXTUAL MINDSET of executives facing a decision making challenge is the starting point of our Decision Intelligence Navigator. It helps executives to understand what kind of insight level (Exhibit 2) they are starting from and what kind of change level (Exhibit 3) they need to include into their choice of suitable frameworks and intelligence access.
Therefore, only if executives have a clear CONTEXTUAL MINDSET for a specific decision making challenge they can create DECISION INTELLIGENCE through FRAMEWORK PROFICIENCY & INTELLIGENCE ACCESS. |
Exhibit 3: Change Level Matrix
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In our interactions with various academics and practitioners, we developed the Insight and Change Level Matrices (Exhibit 2 & 3) helping executives to structure their VUCA environment. The Insight Level Matrix (Exhibit 2) structures the intelligence requirements faced by executives in the context of a specific decision-making challenge by mapping the level of uncertainty and the level of ambiguity. A decision-making challenge where both uncertainty and ambiguity are low represents an exploitation situation, while the opposite case with high uncertainty and ambiguity necessitates an exploration mindset to acquire the required intelligence to make a decision. On the other hand, practitioners voice a focus on experience to interpret available insights in cases of low uncertainty and high ambiguity, and a focus on expertise to reduce the level of uncertainty. The Change Level Matrix (Exhibit 3), on the other hand, helps executives to understand what degree of change their company is facing in the context of their decision-making challenge, with industry dynamics and convergence serving as proxies for the volatility and complexity the company faces in the business environment. The level of industry dynamics determines how quickly the intelligence is needed, which also influences how the intelligence can be collected. The level of industry convergence determines how much change the company experiences in the industry ranging from a simple shift of best practices on a functional level to the complete convergence of different industries. While cases of low industry dynamics and industry convergence represent gradual evolution, the contrary case represents a revolutionary development in the business environment.
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In the context of Decision Intelligence, a CONTEXTUAL MINDSET at the organizational level can be said to exist when senior executives understand the relevance of various forms of intelligence as well as the value of a multitude of ways to gather and process intelligence in different decision-making contexts. In other words, this is when the senior executives of a company understand the importance of the fit between the intelligence requirements driven by the different levels of VUCA that their company faces in its business environments and the variety of intelligence gathering and processing capacities it requires. Without an understanding of the intelligence requirements in their business environments, it is unlikely that senior executives will proactively make the necessary investments to master the subsequent steps (Exhibit 4).
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Exhibit 4: Contextual Mindset Implementation
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The importance of explicitly investing in intelligence acquisition and processing efforts as a precursor to strategy formulation has long been recognized by leading strategy scholars. For instance, Richard Makadok and Jay Barney wrote in 2001 that “It is, in many ways, ironic that research in the field of strategic management has proceeded for so many years without a theory of information acquisition strategy tied to the creation of competitive advantage. Most work in the field has focused on answering the question, ‘Given a firm's strategic situation, what actions should it take?’ while overlooking the logically prior question, ’What information should a firm collect to understand its strategic situation?’ If firms do not collect the information they need to accurately assess their strategic situation, it is very unlikely that they will be able to make profit-maximizing strategic choices”. While this was written in the context of strategic factor markets (i.e. resource-based view), the same authors suggested that it is equally applicable for product markets (i.e. market-based view). With the institution-based view gaining traction in strategy literature, the same arguments can be intuitively extended across the entire strategy tripod.
Consequently, companies and their senior executives must recognize and react to the implications of increased VUCA environments on their intelligence requirements. Companies that adopt a CONTEXTUAL MINDSET can enable executives to focus more on the ex-ante intelligence acquisition and processing to subsequently secure the most valuable resources (i.e. resource-based view), build their business upon the most powerful industry dynamics (i.e. market-based view), and prepare for the most significant changes in the industry environment (i.e. institution-based view). This is illustrated through the case of PharmaIntel (Exhibit 5).
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"A fresh strategic insight – something your company sees that no one else does – is one of the foundations of competitive advantage. It helps companies focus their resources on moves that separate them from the pack. In the same survey only 33% of more than 2000 global executives believed their strategies rested on unique and powerful insights. This figure is dramatically lower than the average of 62% of respondents for the nine other tests to measure their strategy against."
McKinsey Quarterly, McKinsey Global Survey Results, 2010 
Exhibit 5: Contextual Mindset Example
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A CONTEXTUAL MINDSET can be leveraged by using any of the following exemplary approaches:
- Making use of existing intelligence, such as big data, in a way that nobody else does – e.g. developing new algorithms;
- Making use of intelligence that nobody else has - e.g. applying new perspectives or frames to analyze the current or future business environment or the company;
- Innovating the way of intelligence gathering and processing - e.g. leveraging access to social capital or to new data transmission technologies such as low power wide area networks (LPWAN).
Framework Proficiency
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Companies that have developed a CONTEXTUAL MINDSET and understand the value of intelligence to drive competitive advantage invest into the FRAMEWORK PROFICIENCY of their executives. FRAMEWORK PROFICIENCY is the capability of executives to apply multiple perspectives and approaches to the major decision-making challenges that they face (Exhibit 6). The importance of FRAMEWORK PROFICIENCY might be best summarized by a statement of Peter Drucker in 1967 , “To know something, to really understand something important, one must look at it from 16 different angles.” In the same article, he further wrote: “The question we must ask is not, ‘How many figures can I get?’ but ‘What figures do I need? In what form? When and how?’ We must refuse to look at anything else." Today, senior executives must not only address the acquisition of intelligence through a multitude of sources, but also analyze their organizations and business environments through different lenses, or frameworks, to have a more comprehensive understanding of the status quo and relevant future developments.
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Exhibit 6: Framework Proficiency Implementation
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Prof. Michael G. Jacobides of the London Business School recently noted that “we may need new tools or frameworks. When the environment changes profoundly, the maps with which we navigate it may need to shift as well.” This translates into the need for senior executives to refocus efforts to developing customized decision-making models instead of simply trying to replicate existing frameworks with an insufficient appreciation of the contextual factors in which they succeeded in the past .
Senior executives with FRAMEWORK PROFICIENCY thus focus on the development of tailored decision-making models – be it to decide on a potential joint venture in the Indian aerospace industry or the establishment of a micro-brewery in Timor-Leste . Framework proficient executives can ask the right questions, actively seek only the intelligence they need, and adapt their information gathering and processing activities to fit their intelligence requirements (see Figure 7). In other words, senior executives select from existing frameworks or create their own frameworks to generate insights that matter most for a specific decision they must make. |
Exhibit 7: Framework Proficiency Example
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Intelligence Access
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In a VUCA world, senior executives can only leverage their FRAMEWORK PROFICIENCY if their companies can provide them with the INTELLIGENCE ACCESS they need to address their decision-making challenges. The best decision-making frameworks are useless without access to the required intelligence. Having such access, beyond what is available from conventional sources and traditional media, helps senior executives to address their insight deficits efficiently and effectively. While FRAMEWORK PROFICIENCY enables executives to identify and use ideas that nobody else has, INTELLIGENCE ACCESS allows them to make better use of existing data as well as to acquire data that isn’t available to competitors (Exhibit 8). In a VUCA world, this is a fundamental source of firm heterogeneity and, if leveraged effectively in a company’s strategic decision-making process, forms the basis of competitive advantages.
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Exhibit 8: Framework Proficiency Implementation
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In this context, we differentiate between ‘small data’ and ‘big data’ that companies should access. On the one hand, big data consists primarily of vast quantitative information and the correlations which they can reveal, where companies can leverage the almost unlimited possibilities of advanced (data) analytics. On the other hand, small data refers to the opinions of a relatively limited number of people and their qualitative views and assessments based on their experience and expertise to uncover causal relationships or disruptive future developments. This is especially significant when an understanding of past developments does not allow drawing conclusions regarding the future as in the case of most emerging geographical as well as product and service markets and their policy environments. For example, referring to specific domain experts ensures the richness of the intelligence at hand since they draw upon their extensive knowledge and understanding of local contexts. Taken together, big and small data provide executives with an effective way of dealing with a VUCA world.
Decision Proficiency
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As the final element of Decision Intelligence, framework proficient executives with the right contextual mindset and intelligence access still need to turn their insights into strategic decisions and implementation activities. Beyond understanding the current industry and institutional environments, and analyses of possible future changes, senior executives should evaluate the implications of the gathered intelligence for the company and derive consequences on a functional level. DECISION PROFICIENCY is about understanding how to improve decision-making, including the avoidance of biases and increasing the capacity to deal with dynamic business environments (Exhibit 9). It encourages the realization of the true value of decisions by translating them into concrete actions with implementation design and change management plans.
Improved decision-making starts with an understanding of how to avoid biases to effectively leverage the acquired intelligence. It is important for executives to protect themselves from being one-sided or predisposed to views. Therefore, knowledge about the cognitive and personal biases involved in decision-making processes is imperative. Nowadays, a lot of advice is available on this front and the numerous diversity programs in companies are a positive development to include a multitude of perspectives in analyses and decision processes. Extant literature has also documented the role of managerial social capital in mitigating biases. |
Exhibit 9: Decision Proficiency Implementation
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Exhibit 10: Decision Proficiency Example
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Finally, being aware of the implications of their decisions, senior executives need to know how to turn them into actions. They need to better understand how to design plans to implement the strategic initiatives resulting from their decisions. Executives need to make use of implementation frameworks that allow setting things up the right way. They need to break down targets into timely, digestible, and definable goals, and create a roadmap that aligns the day-to-day activities of the organization with the overarching mandates of their strategy. It is also crucial that these (sub-)targets can be communicated within the organization easily to ensure employee buy-in and commitment. To do so, executives need to pivot their plans around the organization, people, processes, and technologies. The case of PharmaIntel (Exhibit 10) provides a further illustration of how Decision Proficiency was implemented, based on the other Decision Intelligence elements.
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Decision Proficiency Tool: The Institutions-Resources Matrix
To advance Decision Proficiency in practice, we have developed and deployed a tool called the Institutions-Resources Matrix to support executives in systematically analyzing future institutional changes in the environment and breaking them down into consequences at the functional level (see Figure 11). In short, this involves the following iterative steps:
- Choose a specific future business environment scenario or single trend in the institutional environment, and derive the consequences for the focal company’s business unit strategies
- A) Choose a specific functional focus (e.g. after-sales, purchasing, human resources) of the business unit and identify those elements of the business unit strategy that have strategic implications for the chosen function.
B) Transform the identified strategic implications from the business unit strategy level to the chosen functional strategy level.
C) Finally, derive the consequences for the human, physical, and technological resources, organizational structures, as well as internal and external relationships of the chosen function from the identified strategic implications. - If required, assess the potential financial ramifications of any identified consequence for the resources of a function to provide an outlook on the required budget.
Decision Intelligence Navigator: CONCEPT SUMMARY
The explosive growth in information processing capabilities driven by technological innovations has thrown up the challenge for executives and organizations to manage a wealth of information and make the best use of it. Consequently, there is a need for executives to revisit extant attention and decision-making frameworks. At the same time, businesses are increasingly facing environments with varying VUCA levels. Taking an information processing perspective towards these developments, we experienced that this leads to two major challenges.
Decision Intelligence starts with companies understanding the value of intelligence, and rejigging the efforts of their executives to leverage it. As a first step, executives need to spend (more) time upfront to evaluate and structure the VUCA business environment they face. The Insight and Change Level Matrices help them capturing the actual VUCA challenges in terms of uncertainty, ambiguity, dynamics and convergence and the resulting challenges in achieving a fit between their intelligence requirements and the intelligence processing capacities at hand.
With a CONTEXTUAL MINDSET helping executives to gauge their business environment, they can contingently decide which intelligence processing capacities are best suited to generate the required strategic insights. This is why FRAMEWORK PROFICIENCY requires executives to develop (more) customized strategic analysis frameworks to address the challenges and requirements of a specific decision that they need to make. FRAMEWORK PROFICIENCY therefore highlights the need for them to master a multitude of management frameworks. The choice and combination of frameworks and analysis tools further has consequences for the required INTELLIGENCE ACCESS. As in the case of AutoIntel, a PESTEL-based framework was complemented with elements from value chain and ecosystem perspective, while an online, real-time Delphi study and scenario development workshops were used as methods to access expert opinions and develop scenario matrices. Thus, Decision Intelligence encourages companies to invest more strategically into their INTELLIGENCE ACCESS infrastructure to also leverage recent developments in gathering and analyzing big data. Simultaneously, they also need tailored approaches to collecting and using small data. Companies might also consider providing their executives with more resources to develop specific platforms to engage with a broad range of experts beyond the access that professional networking and social media platforms already provide. INTELLIGENCE ACCESS allows executives to identify information asymmetries earlier and develop the necessary means to fill the gaps FRAMEWORK PROFICIENCY and INTELLIGENCE ACCESS combined allow executives to better cope with their information overload and adapt their intelligence processing capacities.
Finally, DECISION PROFICIENCY supports executives in turning their strategic insights into consequences to support strategy implementation. The Institutions-Resources Matrix is an example for a tool to translate strategic decisions into actionable goals at a functional level. DECISION PROFICIENCY also requires executives to understand the dangers of mental biases in decision making and take proactive countermeasures. To some extent, companies have been pushing diversity as a necessity to generate multiple and diverse perspectives in the actual decision making. However, they have not sufficiently adapted how they leverage diverse perspectives inside and outside the company to address their ex-ante information acquisition challenges in dynamic business environments.
In sum, Decision Intelligence requires executives to achieve a fit between their VUCA-driven intelligence requirements and their capacities to gather and process intelligence despite information overloads.
- On the one hand, dynamic business environments trigger much higher intelligence requirements for executives.
- On the other hand, today’s information age implies that executives are routinely faced with information overloads while still being constrained by limited individual attention and information processing capabilities.
Decision Intelligence starts with companies understanding the value of intelligence, and rejigging the efforts of their executives to leverage it. As a first step, executives need to spend (more) time upfront to evaluate and structure the VUCA business environment they face. The Insight and Change Level Matrices help them capturing the actual VUCA challenges in terms of uncertainty, ambiguity, dynamics and convergence and the resulting challenges in achieving a fit between their intelligence requirements and the intelligence processing capacities at hand.
With a CONTEXTUAL MINDSET helping executives to gauge their business environment, they can contingently decide which intelligence processing capacities are best suited to generate the required strategic insights. This is why FRAMEWORK PROFICIENCY requires executives to develop (more) customized strategic analysis frameworks to address the challenges and requirements of a specific decision that they need to make. FRAMEWORK PROFICIENCY therefore highlights the need for them to master a multitude of management frameworks. The choice and combination of frameworks and analysis tools further has consequences for the required INTELLIGENCE ACCESS. As in the case of AutoIntel, a PESTEL-based framework was complemented with elements from value chain and ecosystem perspective, while an online, real-time Delphi study and scenario development workshops were used as methods to access expert opinions and develop scenario matrices. Thus, Decision Intelligence encourages companies to invest more strategically into their INTELLIGENCE ACCESS infrastructure to also leverage recent developments in gathering and analyzing big data. Simultaneously, they also need tailored approaches to collecting and using small data. Companies might also consider providing their executives with more resources to develop specific platforms to engage with a broad range of experts beyond the access that professional networking and social media platforms already provide. INTELLIGENCE ACCESS allows executives to identify information asymmetries earlier and develop the necessary means to fill the gaps FRAMEWORK PROFICIENCY and INTELLIGENCE ACCESS combined allow executives to better cope with their information overload and adapt their intelligence processing capacities.
Finally, DECISION PROFICIENCY supports executives in turning their strategic insights into consequences to support strategy implementation. The Institutions-Resources Matrix is an example for a tool to translate strategic decisions into actionable goals at a functional level. DECISION PROFICIENCY also requires executives to understand the dangers of mental biases in decision making and take proactive countermeasures. To some extent, companies have been pushing diversity as a necessity to generate multiple and diverse perspectives in the actual decision making. However, they have not sufficiently adapted how they leverage diverse perspectives inside and outside the company to address their ex-ante information acquisition challenges in dynamic business environments.
In sum, Decision Intelligence requires executives to achieve a fit between their VUCA-driven intelligence requirements and their capacities to gather and process intelligence despite information overloads.
