Competitive intelligence: A precursor to a learning health system

Abstract

Unlike other developed countries, the US healthcare system is largely privatized and highly competitive. This dynamic stifles effective information sharing, while the need for prompt and accurate evidence-based decision making has become crucial. Crises, like the COVID-19 pandemic, elevate the importance of quality decision making and exacerbate issues associated with the lack of a cohesive system to share information. Competitive intelligence (CI) is a discipline that encourages gathering, analyzing, and sharing information throughout a firm in order to develop and sustain competitive advantage. CI could be considered a precursor in establishing a learning organization (LO). Although CI research has focused on its process and value, little is found in the literature on how to integrate CI into an organization; this is particularly true in healthcare. A conceptual model is proposed to build and integrate a CI function and culture within a healthcare organization to encourage effective information sharing and knowledge development. In turn, this can provide a mechanism to create a learning health system (LHS). Although the model was developed specifically for US healthcare, it offers application to healthcare in other countries as well as most any industry.

Keywords

competitive intelligence learning organizations learning health system decision making in healthcare management data analytics

Introduction

The cost of healthcare equates to almost 20% of the US economy with the industry having become the largest employer in the nation.¹ Unlike other developed countries, US healthcare is perceived as a commodity, resulting in an aggressive competitive environment similar to most other industries. As a result, the US healthcare industry struggles with information sharing for fear of losing competitive advantage. Further, healthcare organizations often operate in functional silos creating barriers to sharing information. While healthcare organizations collect and store enormous amounts of clinical and business information, these organizations often lack mechanisms to share knowledge hampering their ability to become a LHS. The failed US response to the COVID-19 pandemic has highlighted flaws in the business decision making process that led individual healthcare organizations to reduce capacity and limit inventory of personal protective equipment and other essential equipment and supplies. These efforts to create competitive advantage and cost reductions rendered healthcare systems incapable of effectively responding to the demands brought about by the pandemic.

Historically, healthcare providers have been compensated under a volume-based model. The goal is to provide as many services as possible in order to exploit economies of scale and maximize reimbursement for revenue. Currently, there is a movement toward value-based models of care, emphasizing the importance of collaboration between administrators and clinicians in order to provide the highest quality services, while controlling costs.³ This value approach has highlighted the negative impact traditional decision making has had on healthcare capacity and costs.

The discipline of Competitive Intelligence (CI) offers the capabilities to aid a firm in converting data and information into intelligence for improved decision making. According to Chevallier et al. (2016), “CI is the interface between an information economy and a knowledge economy…It is a process that produces and modifies information into intelligence” (p. 1193). Competitive intelligence offers a strategic management tool and a foremost technique for achieving competitive advantage.⁴ Integrating the CI function into the US healthcare industry provides a plausible solution to converting information to knowledge and knowledge to action in the process of becoming a LHS. A review of the literature denotes an absence of the application of CI in the healthcare industry. Festervand and Lumpkin⁵ were one of the first to propose the potential benefit of applying the CI process in healthcare management; yet, there is little evidence in the literature that their recommendations were adopted. This infers a lack of understanding of CI’s capabilities in knowledge generation and facilitating quality decision making.

Professional level literature has recognized the importance of establishing information sharing within a firm.⁶ However, little academic research addresses building a unified CI process for information sharing in healthcare. This gap lends opportunity to study CI as an aid in creating a value-based model and subsequently, encouraging a LO.

A theoretical model of CI as a continuous cycle of information sharing and knowledge generation is presented and applied to a US healthcare organization. This model emphasizes the importance of infrastructure and leadership in supporting a culture to build a LHS. The CI function along with the flow of information to knowledge generation will be discussed. Finally, implications, limitations, and future research are presented. Although the model is applied to US healthcare industry, it is adaptable to other industries and countries.

This model will address the research question of how can CI be integrated into a US healthcare firm to encourage a LHS?

The learning organization

The concept of LOs is well known and widely studied.^2,7 LOs are typically viewed as proactive and focused on developing processes that ultimately, lead to shared knowledge. This knowledge positively changes organizational behavior and results; whereas, non-learning organizations are simply reactive. LOs have the ability to more fully control the direction of the organization and are characterized as being more progressive resulting in improved knowledge and financial performance.⁸ High productivity is created in LOs as a result of the superior synergy among employees, departments, and divisions; this can improve quality and increase market share.⁹ LOs are able to develop distinctive competencies resulting in competitive advantages. The end result is that LOs outperform their competitors both in quality of outcomes and financial performance.¹⁰

Jones and Hendry¹¹ conveyed that, “… although it is not possible to identify specific circumstances in which to create learning organizations, their creation is triggered by such situations as the need to get greater participation from the work force…and need to produce better products and services” (p. 10). Although the current literature has established the benefits of becoming a LO, it is devoid of a roadmap to develop such an organization.

Learning health system and CI

The healthcare industry has been slow in adopting the principles of LO. However, in the last decade, there has been some movement in the form of LHS. A LHS is one in which science, informatics, incentives, and culture are aligned for continuous improvement and innovation.⁷ McGinnis et al. (2013) stated, “A learning health system is stewarded by leadership committed to a culture of teamwork, collaboration, and adaptability in support of continuous learning as a core aim” (p.138). The LHS can only be accomplished when strong support systems are in place that, “… constantly refines complex care operations and processes through ongoing team training and skill building, systems analysis and information development, and creation of the feedback loops for continuous learning and system improvement”¹² p.138). Research has also reinforced the economic and clinical value of creating LHS⁷). For example, Spetz et al.¹³ established that costs, mortality, and morbidity can be decreased through the open sharing of clinical data. The development of a LHS must begin with gathering and sharing of data to develop valuable knowledge for effective decision making.

The CI discipline can offer the intermediary step of generating intelligence from information to knowledge.¹⁴ For effective use of intelligence within a LO, Breckenridge¹⁵ argued that “knowledge must be shared collectively, ideas diffused rapidly throughout the organization and embedded in organizational memory; learning requires action” (p. 199). LO research compliments and supports the CI discipline based on the underlying theme of creating value through knowledge acquisition and sharing of market intelligence throughout the firm by the employees; little research has truly connected these concepts; a model will be presented to address this gap, but first a brief background of information challenges in the US healthcare industry.

The US healthcare industry

Miller and Tucker¹⁶ stressed the synergistic effects of information sharing in identifying cost reduction methods as well as improving quality of healthcare. Along with management and clinical data, there exists extensive information collected by regulatory and governmental agencies, vendors, and competitors. Festervand and Lumpkin's⁵ early work also recommended gathering data from other less biased sources such as surveys, observations and commercial reports. This wide availability of sources and growing volume of data further elevates the need for a well-structured systematic approach to data management.

Brief history of healthcare information

Healthcare professionals entered into computerized data collection and management through the finance function. The initial efforts to capture healthcare data were driven by Medicare and Medicaid reimbursement in the 1960’s. Financial managers quickly learned that computers were necessary in collecting and reporting data needed to generate bills efficiently. Much of this essential financial data was provided by clinical and support departments. These departments soon realized the potential value of automated collection of data for clinical and business purposes. Octo Barnett, Professor of Medicine at Harvard University, provided the clinical leadership in the development and application of electronic health records.¹⁷ Barnett argued that the practice of medicine depended on how healthcare organizations record, process, retrieve, and communicate information.

The federal government also recognized the potential of utilizing electronic health records for quality of care and cost reduction. This resulted in public policy measures to modernize the electronic health record infrastructure. The American Recovery and Reinvestment Act of 2009 (ARRA) authorized incentive payments through Medicare and Medicaid to providers that implemented certified electronic health records and demonstrated their “meaningful use.”¹⁸ Meaningful use focused on standardizing clinical data collection to facilitate sharing within and across healthcare organizations, but fell short of driving decision support capabilities. Proliferation of information in healthcare made it apparent that computer systems were necessary for the planning, collection, analysis, and dissemination of clinical and financial data. However, meaningful use lead to concerns regarding the structure by which this complicated process of data management could be accomplished and remains an ongoing debate.

Barriers to information sharing in US healthcare culture

The culture of open sharing of information and knowledge is a hallmark of LOs. However, like many traditional firms, healthcare organizations tend organize into segregated departments creating systemic and political barriers for sharing data. Further, there are often department specific computer systems referred to as “best of breed,” developed for a specific service (e.g., operating rooms or emergency departments). These best of breed systems are preferred by healthcare providers since they focus on the issues that are most important to their specialty or functional area, but often lack the capability to easily share data. Without appropriate integration, these stand-alone systems form significant barriers to information sharing.

At times, departments are required to share information between databases (e.g., basic patient demographics for admittance and laboratory results); this can actually exacerbate barriers. To accomplish data sharing, third parties are often hired to develop interfaces between systems resulting in a piecemealed approached creating yet another obstacle for systematic utilization of data. One promising development has been enterprise wide healthcare information technology (IT). Healthcare IT vendors have developed complex systems that can meet all the IT requirements of a firm. Although these systems are marketed for their interoperability, the data may or may not be shared in a meaningful way within the organization and is rarely shared outside the organization.

External environment

Wheelen et al.¹⁹ emphasized the importance of environment scanning in the decision making process of strategy formulation. “Environmental scanning is the monitoring, valuating and disseminating of information from the external and internal environments to key people within the corporation,¹⁹ p. 14). The large number of stakeholders in any healthcare system creates a diverse foundation from which external data can be obtained. Among these external sources are patients, employers, insurance companies, pharmaceutical firms, educational institutions where healthcare research occurs and governments as both a payer and regulator of healthcare services. There are also several not for profit organizations that collect and share health information including Dartmouth Atlas, Healthgrades and Leapfrog. Although each of these are potential sources, mining data can pose a significant challenge. First, not all potential sources are willing to openly share data. In the United States, this is due in part to the competitive nature of the industry. The data sources are spread across different electronic formats and may even be paper records. However, a well-established supported CI function may offer solutions to overcoming the barriers associated with external data sources. Unlike healthcare systems of other developed countries, the US healthcare system remains basically, capitalistic enterprise discouraging information sharing to maintain competitive advantage even though evidence supports that data sharing improves the quality of clinical services and reduces overall expense (Kraft, 2016). Fortunately, the outcomes of clinical research are widely reported in medical journals. However, details of clinical processes used by individual organizations are less likely to be openly shared in order to maintain an advantage.¹⁶ The challenge for healthcare administrators in adopting a process by which appropriate gathering and analyzing of data leads to information sharing with the goal to enhance the quality of administrative and clinical decision making while maintaining competitive advantage.

Competitive intelligence

As noted, minimal research has linked CI with healthcare.²⁰ Likely, a less formal and/or fragmented approach to CI may be occurring within the industry: “…islands of automation, providing only limited information…” ⁶ p.320). Empirical studies support a formal CI structure involving a dedicated CI manager or champion to coordinate the CIP process.²¹ For sake of parsimony, the CI function in this paper will focus on strategic initiatives and will be presented as its own unit reporting to executives.²²

The competitive intelligence process

Literature has debated the number of steps in the CI process.²³ This paper utilizes the seminal framework of Dishman and Calof²⁴ consisting of: planning and focus, collection, analysis, and communications. As the CI process is discussed, proposition will be established throughout the paper to create a conceptual model for a US healthcare organization.

Planning and focus

The intelligence process does not collect all information, but instead focuses on priority information needed by management. According to Saayman et al. (2008), this first step is used to “determine the necessary resources for the CI project in light of its purpose” (p. 385) and is typically, designated for senior management.²⁴ This is a structured planning procedure to identify needs, but also to support communication between CI professionals and decision makers.²⁵.

P1. The CI function plans with the C-suite to identify intelligence needs.

Collection

The collection phase uses a variety of sources and acquisition methods including environmental scanning.²⁴ Although CI has traditionally been regarded as externally focused, more recent literature supports reliance of both internal and external information.^22,25 This offers a more holistic approach to analysis and strategic decision making.

P2: The CI function collects both internal and external information.

Analysis

Amiri et al. (2017) stressed that the analysis phase is the most important stage of the CI process demanding great skills by the CI team. Saayman et al. (2008) defined the analysis phase as “converting information into usable intelligence on which strategic and tactical decisions may be made” (p. 385). CI analysis may utilize various analytic tools and software in this phase.^26,27.

P3. Analysis of internal and external information is conducted by the CI function to allow a holistic perspective for strategy.

Communication

This step reflects the end product: “packaging and communicating the results of the CI process”²⁸ p. 30). Results of the CI process should be communicated to those with authority and responsibility to act on the intelligence, typically executives.^29,30 Intelligence can be communicated through many venues including briefs, ad hoc reports, e-mails, presentations, and special memos.²⁶ Competitive intelligence continues to evolve with increasing data complexity and analyst must become more proficient with advancing technology for analysis and communication.³¹.

P4. The CI function communicates the end product of the CI process (intelligence) to the C-suite.

De Almeida et al. (2016) noted that executives must ensure a strong relationship with people providing information to CI, stressing support for collaborations and giving feedback for contributions. “Sustaining intrinsic motivation seems a fundamental aspect to the process’ success” (p. 1281). Saayman et al. (2008) stressed that “CI requires appropriate policies, procedures…. so that employees may contribute effectively to the CI system, as well as gain from the benefits of the CI process” (p. 386).

The value of employee involvement in the gathering and sharing of information is mentioned repeatedly in management literature specifically as it relates to the LO. Garvin et al. (2008) stated that “in a learning organization employees continually create, acquire, and transfer knowledge—helping their company adapt to the unpredictable faster than rivals can” (p. 109).

LO literature encourages intelligence be disseminated throughout the organization⁹ and supports an additional step in the CI process. C-suite dissemination of intelligence encourages both sharing and building of knowledge within the firm.

P5. The C-suite disseminates intelligence within the firm’s network to encourage growth of knowledge for the firm.

In summary, the CI process encompasses proper planning and collecting of data from an established strategic objective. After collection, CI ensures proper analysis to convert information into intelligence. Communication of intelligence serves as the antecedent to knowledge for the firm.³² Finally, executive dissemination of intelligence throughout the firm can encourage knowledge building for a LO.

To ensure successful CI integration, firm dynamics must also be addressed. Establishing a CI culture has been theoretically and empirically supported to be instrumental in impacting a CI function.

Establishing an effective “CI” culture

Literature emphasizes the importance of firm dynamics in generating knowledge and is key in establishing a strong CI culture.

…the knowledge-based view concerns itself extend beyond the traditional concerns of strategic management….notably the nature of coordination within the firm, organizational structure, the role of management and the allocation of decision making rights…,³³ p. 110).

Competitive intelligence research has identified two contextual variables that have been found to positively impact the CI process: formal infrastructure and culture of awareness.^23,24

Formal infrastructure

Dishman and Calof²⁴ stated infrastructure aids “the effectiveness as well as the efficacy of the intelligence effort within the firm” (p. 779). More current literature also supports formal infrastructure,^25,34 but also stresses the need for internal networks and designated positions within the firm (e.g., managers) specifically, in collection and dissemination.

Internal networks

To create an operational CI process at company-level, Ahearne et al. (2013) found the performance impact of CI quality is reliant on group-level factors, noting the importance of managers or “CI hubs.” Yin³⁵ noted “executives in organizations should support all members to improve information collecting through a team formation of competitive intelligence” (p. 544). CI research supports designated positions to develop a network overseeing the collection and dissemination of information to CI and executives.^22,36

Culture of awareness

Dishman and Calof²⁴ CI model proposed that awareness is twofold consisting of the actual awareness of intelligence in the firm and a culture of competitiveness to heighten this awareness. A culture of awareness is necessary in ensuring a firm is sensing and anticipating market changes. Awareness can be defined as “the organizational awareness of CI and a culture of competitiveness supported by leadership and utilized organization wide” ²³ p. 117). To build and maintain this culture, leadership support is essential.³⁷

Executive support for CI

The role of executive leadership in driving vision and strategy within an organization serves to set the expectations for the entire organization. Wheelen et al. (2018) noted that, “Top management responsibilities, especially those of the CEO, involve getting things accomplished through and with others in order to meet the corporate objectives” (p. 60). Leadership support is necessary to successfully deploy CI throughout the firm and hold the entire healthcare organization accountable for information sharing. In addition, dissemination of intelligence by executives along with the continual loop of employee contribution and feedback creates knowledge for the firm an essential process in establishing a HLS.⁹

While there are many barriers to effective cooperation across organizational departments, healthcare research has established that high performing hospitals work across traditional boundaries to improve quality.³⁸ Executive leadership can remove organizational barriers and establish the expectation of collaboration in support of strategic initiatives. CI can prove to be a central element of strategic planning and offer executives a powerful planning tool. Strategic planning provides a mechanism to evaluate the internal and external environment of the organization with a principle goal of creating sustainable competitive advantage by identifying competitive opportunity.¹⁹ A conceptual model is now proposed that provides a roadmap to link information management to effective decision making and the development of a LHS.

Conceptual model of CI process

The proposed model (Figure 1) reflects the propositions discussed throughout the paper. Competitive intelligence integration involves a designated function, a process and firm dynamics to share information for knowledge creation.³² As an established function, CI provides a destination for the process offering the capability to provide a comprehensive approach to planning, collection, analysis and communication. In turn, internal and external information feed into CI for analysis to create intelligence. CI can provide stronger intelligence to the C-suite, which can flow throughout the organization to create knowledge. Prescott¹⁴ identified CI as the meeting point of converting information into intelligence; thereby, creating knowledge for the firm. In terms of structure, this model encourages appropriate policies and procedures along with internal networks to assist in information sharing and thereby, elevate a culture of awareness. Finally, the model illustrates a continuous process of data and information generation to the formation of intelligence and finally knowledge dissemination. A culture disseminating information throughout the firm can create knowledge; a valuable resource and ultimately, precursor to a LHS resulting in competitive advantage.²⁸ Oubrich et al.²⁹ stressed that “where information is transformed into knowledge more efficiently and effectively, companies move ahead to the world class CI practice” (p. 31).

Figure 1.

CI process and developing a learning health system. Note: CI: competitive intelligence.

Although some concepts of CI are not new, recent research continues to validate the propositions. The gap in literature is the actual integration of establishing and nurturing a CI process within the firm. As discussed, leadership support is the antecedent to establishing an infrastructure, a designated CI function and culture of awareness.

Conclusion

Ghannay and Mamlouk⁴ argued that “the only competitive advantage that organizations will have in the 21st century is what they know and how they use it…the proper management and leveraging of knowledge can propel an organization to become more adaptive, innovative, intelligent and sustainable” (p. 24). This paper reinforces the value CI can provide in the growing challenge of data management in the healthcare industry along with establishing a plan to become a LHS.

Managerial implications

The proposed model offers a blueprint to develop an organizational CI function. Through executive leadership support and the dedication of necessary resources, information sharing can be encouraged supporting the evolution of a LHS. CI research has established the importance of culture and formal infrastructure in establishing an effective CI process.²⁴ While culture is more fluid, formal infrastructure is structured. Management can have an immediate impact in building a CI system. Integration of the CI process provides the necessary structure for managers and facilitates cooperation and synergy between departments, while also reinforcing the importance of access to external information. In turn, the intangible aspect of company culture and awareness must also be supported. Dedicating resources and networks along with educating the entire organization about CI encourages organizational sharing and growth of the firm’s knowledge. Saayman et al. (2008) emphasized that “top management support is an important element in guaranteeing legitimacy and importance” (p.403).

Theoretical implications, limitations, and future research

Healthcare organizations have been incentivized to adopt mechanisms for the electronic collection of data. However, few unified systems have been widely adopted. Theoretically, this model endorses executive support to nurture a CI environment and long term, a learning organization. That said, piecemealed outsourced systems in healthcare will likely come to the forefront and signify needs for streamlining and unification. This conceptual model provides a starting point and further research testing the propositions with healthcare professionals, executives, and mid-level managers is needed to provide the next step in CI integration.

Competitive intelligence is a newer discipline and definition consistency is still lacking in the research. A benefit of this model is that it provides standardization of definition and process. Additionally, information and data itself continue to evolve, changing the role of CI.³¹ Nuances of operationalizing the model are lacking, which allows for further exploration in research.

In summary, a conceptual model of CI integration within a firm was proposed and applied to a large U.S. healthcare firm. Propositions presented relationships of functions, processes and mechanisms to integrate CI into the firm. Although US healthcare was the topic of this paper, the overabundance of data and informational barriers exists within most organizations. This model serves as a starting point for CI integration into most any organization encouraging future research in many venues.

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

ORCID iD

H F Farley

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