Strategic Intelligence: making more effective decisions

Every day, managers make decisions on the most varied topics, influencing a wide range of organizational results in the short and long term. It turns out that these decisions are very often made based on insufficient, outdated, limited, or biased information. What if we had more qualified information and knowledge to support each type of decision? What if the decision-making process itself were structured for greater effectiveness?

So-called Strategic Intelligence exists precisely to support decision-making processes, ensuring smarter – and more effective – decisions. It can be predominantly oriented towards monitoring competitors (competitive intelligence), market data and movements (market intelligence), technological trends (technological intelligence), or even the business’s own information (business intelligence). It is an organizational capability with immense potential to generate results if structured (pardon the redundancy) intelligently.

Note: This article is not about Artificial Intelligence, but rather about the processes and practices that feed decision-making with qualified information and knowledge – processes that can apply AI technologies, but are not limited to them.

Decision-making: the focus of intelligence

The act of “deciding” is one of the most complex and, at the same time, one of the most important actions in any organization. It happens at all hierarchical levels and in all processes and activities of the organization, determining its direction and results.

Even though it may happen in a more or less diluted way amidst our activities, a decision is the choice of a path to act upon.⁽¹⁾ A choice that selects a course of action and, consciously or not, discards several other possible ones. A choice that can have limited and short-term consequences, or it can have a broad impact on all organizational processes for a long time. A choice that leads to several other choices, all of them with direct and indirect consequences.

Every day, managers make dozens of decisions based on limited information, or information distorted by interpretation problems.

Everything we do and all the results we achieve are the consequence of previous decisions, and everything that lies ahead results from the decisions we make now. Given this, decision-making deserves attention and method. But this is not always what we see in our organizations.

The challenges of decision-making in the organizational context

Strategic decisions in any business involve a large number of variables with a high degree of uncertainty. They require broad knowledge of the market and specific knowledge of the industry, as well as constant monitoring. The macro-environmental factors that influence the organization and its scope of action – an industry, the market, or society – are many and are changing all the time.

Strategic decisions in specific processes – such as marketing, legal, or research & development, for example – also require specific technical information and knowledge. The uncertainty may be relatively lower, but there are still many influencing variables and the speed of environmental transformations is high.

And even when well-supported by information and knowledge, the decision-making process involves selecting and interpreting this information, which can be highly influenced by cognitive biases, limitations, and distortions related to mental models and pressures from the immediate context. The following table, without claiming to be exhaustive, shows some of the many interferences with the decision-making process in the different types of decisions within an organization.

Every day, managers make dozens of decisions based on limited information, or information distorted by interpretation problems. Some of these decisions have a high potential to impact the organization’s performance and results, yet they are still made with a high degree of subjectivity and without considering the knowledge already available and accessible internally or externally.

In a complex and dynamic market, dealing with multiple variables, a decision-making process that does not consider the information and knowledge already available and does not have a well-structured process can be called inefficient: it is taking unnecessary risks and ignoring elements capable of reducing uncertainty and increasing the probabilities of success.

By analyzing and interpreting relevant data and knowledge from the macro-environment, Strategic Intelligence enables organizations to reduce uncertainty and improve decision effectiveness

We imagine decision-making as an intuitive impulse or the exclusive fruit of the leader’s or decision-maker’s talent. And indeed, some executives adopt this behavior, making decisions in an unstructured, individualistic manner, without a peripheral vision.

But a decision actually begins much earlier, with obtaining information and forming a judgment on the subject to be decided. This process of “instructing” the decision until the moment of “striking the gavel” happens in every decision-making process, consciously or not, structured or not. When unconscious and unplanned, the process is subject to gaps and distortions that can compromise the quality and outcome of the decision. On the other hand, if the decision-making process is conducted consciously, supported, and structured, the conditions are created for a well-informed decision, which has analyzed possible scenarios and impacts, and has made a grounded consideration for a qualified choice.

Strategic Intelligence – Macro-environment, information, and decisions

We call Strategic Intelligence the processes and practices aimed at providing a comprehensive and continuous understanding of the key elements of the environment external to the organization. It involves monitoring and interpreting relevant macro-environmental variables, formulating scenarios, identifying trends, defining possible and desirable futures, anticipating opportunities and threats, and from there, generating qualified information and actionable insights to support specific decision-making processes across the organization’s various dimensions.⁽²⁾

But how does strategic intelligence happen in practice? The concept is simple: decision-makers responsible for key organizational decisions receive reports with data, analyses, and insights that help enrich their understanding of the context, enabling them to make more informed, intelligent, and effective decisions. These reports are the intelligence products, generated periodically or on demand by intelligence analysts, as part of the intelligence process.

By identifying, selecting, analyzing, and interpreting relevant data and knowledge about various dynamic environmental factors – such as market movements, new technologies, competition, social and demographic changes – Strategic Intelligence enables organizations to reduce uncertainty and improve the effectiveness of the most varied types of decisions:

• Defining business strategies: Providing selected information and future scenarios for short and long-term planning and adaptation to changes in society or a specific sector. Public or private organizations in the healthcare sector, for example, can adjust their strategies and priorities based on scenario analyses pointing out the implications of the aging Brazilian population in the coming decades (demographic trends).
• Optimizing operations: Monitoring the supply chain, the availability of inputs, and competitors’ movements to ensure efficiency and competitiveness. To illustrate: the procurement department of an industry can anticipate and seek substitute raw materials for an element that is on the verge of having its application restricted due to environmental issues in developed countries (as happened with asbestos).
• Guiding marketing decisions: Tracking changes in consumer behavior, the emergence of new direct and indirect competitors, or even typical expressions of a public segment that can be used in targeted communication actions. Intelligence reports in this context can indicate the growth trend in the adoption of a specific social network, creating opportunities to redirect a brand’s media strategy.
• Driving innovation: Identifying technological trends, emerging knowledge, and opportunities for developing new products, services, and business models. Another example: mapping promising technologies with experts in a certain sector can reveal the opportunity to invest in research and development of solutions that can quickly benefit – and ahead of competitors – from emerging technology once it matures.
• Managing risks and opportunities: Anticipating threats and identifying new areas for growth and investment. An illustrative case: a company producing electrical components for automobiles noticed, before its competitors, the opportunity to expand its offering to automakers by also providing components for data transmission, as trend reports indicated the rapid increase of digital technologies embedded in vehicles, in the form of cameras, sensors, connectivity, among others.
• Developing organizational skills and capabilities: Identifying emerging knowledge and skills needed for the future. Emerging knowledge maps can reveal strategically relevant themes for an organization (such as digital transformation or artificial intelligence applications, for example), encouraging the creation of training programs or scientific production focused on preparing teams and processes to adopt relevant new concepts, methodologies, or technologies.

Key elements of a Strategic Intelligence model

Whatever your organization’s priorities, it can benefit from a management model and a systematized intelligence process that supports key decisions. The key elements of a strategic intelligence model are represented in the following figure.

Based on the strategy and desired outcomes for the business or organization, the decisions to be supported by intelligence are selected. Objectives and scope, products to be generated, and support infrastructure for the process of planning, monitoring, analyzing, and reporting are defined.

Adopting Strategic Intelligence requires a systematic and continuous process. Structuring and executing the intelligence process involves the following steps:

1. Direction: based on the organizational strategy and desired outcomes, selecting the key decisions to be subsidized by intelligence and their impact on business indicators. Defining the scope and reach of the intelligence process: macro-environmental or sectorial focus, local or global reach, short or long-term horizon, among other criteria. Direction also involves defining the formats for intelligence services (continuous, periodic, on-demand, among others) and the degree of access or confidentiality for each type of information handled within the scope of intelligence.
2. Definition of intelligence products and infrastructure: establishing the format (or formats) of the intelligence products to be generated, considering the types of decisions to be supported and decision-makers’ preferences; defining support platforms for the intelligence process; and establishing the structure, roles, and responsibilities for intelligence services.
3. Planning: selecting primary and/or secondary sources to be monitored, planning the data, information, and insight collection or production process, aiming to achieve the defined objectives.
4. Monitoring: tracking, gathering (or producing), and selecting information and knowledge from the defined information sources.
5. Analysis: evaluation of the collected data and information, cross-referencing information, interpreting signals, identifying patterns, threats, and opportunities, and the subsequent generation of insights to support decisions.
6. Reporting: making intelligence products available to decision-makers, according to defined formats and criteria.
7. Evaluation of results: tracking the usage and measuring the results and impacts of intelligence products on decision-making and their effectiveness within the business context, feeding back into the intelligence process.

Challenges in generating results from Strategic Intelligence

Developing Strategic Intelligence as a systematic and sustainable organizational capability brings great benefits to the organization by providing qualified input for smarter and more effective decisions, whether strategic or technical. On the other hand, maximizing value generation from intelligence processes requires addressing non-trivial aspects of managing a private company or public agency.

• Scope of Intelligence: organizations unaccustomed to looking outward and monitoring macro-environmental elements may struggle to define a clear scope for intelligence. The risk lies in establishing an overly broad focus (in terms of time horizon or thematic reach, for example, generating excessive information with little utility for decision-making) or one that is too narrow (losing sight of relevant environmental movements and benefiting too few types of decisions).
• Governance of Decision-Making Processes: the adoption of Strategic Intelligence practices cannot be viewed as the only possible improvement in decision-making processes. Besides providing valuable knowledge, information, and insights to decision-makers, it is crucial to ensure a balance of responsibilities in organizational decisions. Decisions with long-term impact affecting many organizational processes and areas can benefit from a more participatory or consultative decision-making process. The same applies to complex technical decisions or in contexts of complexity.
• Data and Technology: many organizations seek to use artificial intelligence (AI) tools for data analysis or even insight generation, and some of them have their own databases as potential sources for intelligence extraction (business intelligence). These are initiatives that can positively influence intelligence quality, but over-reliance on data – proprietary or third-party – can mask weaknesses, and over-reliance on AI can lead to misguided decisions. It must be clear that there will always be a degree of uncertainty in any decision.
• Compliance: confidentiality and data protection policies are adopted to regulate the use of data and information in organizations worldwide. In Brazil, the LGPD (General Data Protection Law) has recently brought new references for handling sensitive information. Similarly, there are codes of ethics and conduct, drafted by representative entities of intelligence professionals, to guide the activities of professionals in the field. When adopting Strategic Intelligence in your organization, it may be beneficial to draft a specific policy and guiding codes, aligned with other active compliance mechanisms.
• Indicators and Continuity: every organizational capability needs to be developed from the strategic to the operational level, and goes through a learning curve. It is no different with Strategic Intelligence: it is necessary to establish a long-term vision, define contribution indicators, and develop an evolution plan, a “roadmap” outlining the steps to be taken until it reaches its full potential. By defining the vision of the future and the evolution stages with their respective indicators, it is possible to align expectations and ensure the continuity necessary for the process to consolidate and evolve.

Strategic Intelligence is not just a function or process, but an organizational capability that makes all the difference for companies and organizations aiming to generate more value in an environment of intense transformation and high uncertainty.

By generating useful insights for decision-makers, intelligence assists in interpreting the multiple movements of the external environment in order to reduce uncertainty, anticipate challenges and opportunities, develop greater readiness and adaptability to changes in the environment and the market, drive innovation, and achieve superior results. In short: Strategic Intelligence contributes to generating smarter decisions, and smarter decisions.

References:

⁽¹⁾ “Decisões Vencedoras”, J. E. Russo e P. J. H. Schoemaker, Campus 2002. “As melhores decisões são sempre difíceis”, T. Davenport e B. Manville, Campus 2012.

⁽²⁾ “O Milênio da Inteligência Competitiva”, J. P. Miller, Bookman 2002. “From Knowledge to Intelligence”, H. N. Rothberg e G. S. Erickson, Elsevier 2005.